by jacqueline patricia galica for the degree of …...1.1 fear of cancer recurrence (fcr) cancer...

Fear of Cancer Recurrence Among Survivors of Adult Cancers

by

Jacqueline Patricia Galica

A thesis submitted in conformity with the requirements

for the degree of Doctor of Philosophy

Faculty of Nursing

University of Toronto

© Copyright by Jacqueline Galica 2017

ii

Fear of Cancer Recurrence Among Survivors of Adult

Cancers

Jacqueline Galica

Doctor of Philosophy

Faculty of Nursing

University of Toronto

2017

Abstract

Purpose: Fear of Cancer Recurrence (FCR) is a common concern for which cancer survivors

want professional help to cope. Understanding the prevalence, predictors and mediators of FCR

is important to facilitate the identification of those at-risk for clinically-significant FCR in order

to expediently refer them into appropriate interventions. To clarify the empirical gaps which

would be useful in this regard, the objectives of this study were: 1) to assess the prevalence of

FCR; 2) to examine the relationships among predictors of FCR; and 3) examine the relationships

among mediators of FCR.

Methods: Survivors attending a cancer survivorship clinic were invited to participate in this

cross-sectional, mixed mode survey study. Participants completed standardized assessments of

FCR, Self-Esteem, Personality, Generalized Expectancies, Illness Representations, and Coping

Styles, in addition to a demographic form. Clinical and treatment information was extracted from

hospital charts. SPSS was used to conduct descriptive statistics to address objective 1, and Mplus

was used to conduct a structural equation modeling analysis to examine predictors and mediators

of FCR.

iii

Results: One-thousand two participants completed the survey. The mean age was 61.1 years and

most were female (85.2%). The mean time since diagnosis was 9.1 years (range 1-36 years) and

most were diagnosed with breast cancer (66.2%). Nearly fifty-nine percent of the sample had

clinically-significant levels of FCR. Age, sex, symptom burden, associations with cancer, self-

esteem and optimism had direct effects on FCR. The Timeline (acute/chronic) and Emotional

Representation components of an Illness Representation, and both Coping Styles, were found to

mediate some of these relationships.

Conclusions: This study found that a large percentage of survivors continued to experience

clinically-significant FCR, even years after diagnosis. The identified predictors of FCR may be

useful to identify those with higher FCR, while the identified mediators may have utility for

intervention development and refinement.

iv

Acknowledgements

To begin, I am deeply appreciative to the cancer survivors who participated in this project. Your

insights are, and continue to be, invaluable to advance the scientific understanding of important

issues in cancer survivorship care. It is my hope that the results of this project will have positive

implications in clinical, policy, and research contexts.

I am grateful to my supervisor, Dr. Kelly Metcalfe, who consistently provided me with prompt

and insightful feedback that brought enlightenment throughout my academic journey. Her

enthusiastic research acumen continues to be an inspiration.

I would like to sincerely thank Drs. Christine Maheu and Carol Townsley, my dissertation

committee members. Your research and clinical expertise were invaluable contributions to this

project and further solidified my appreciation for the importance of clinically-meaningful

research.

Many individuals collaborated with me to facilitate the completion of this work. Sophia Virani

provided tireless administrative support to this study. Wilma Pesongco, Nela Benea, and Angela

Duggen provided pivotal support to the collection of data described herein. Without the

enthusiastic collaboration of these individuals, this project would not have succinctly

materialized into the work that it is. Thank you so very, very much.

A special thank you to Drs. Eric Duku and Sarah Brennenstuhl who provided indefatigable

patience to my desire to learn and carry out the statistical analyses described in this dissertation.

Dr. Janet Rush was a source of valuable encouragement along the way; she was and is seminal to

my advancement as a nurse researcher.

This work was enabled by financial support from a number of agencies. Within the University

of Toronto community, thank you to the Nursing Alumni and Friends for a Helen Carpenter

Doctoral Award and Kathleen King Doctoral Fellowship, to the LS Bloomberg Faculty of

Nursing at the University of Toronto for a Doctoral Completion Award, and to the University of

Toronto School of Graduate Studies for a Norman Stuart Robertson Fellowship. Within the

nursing community, thank you to the deSouza Institute/Ministry of Health and Long Term Care

for a de Souza Scholarship, to the Registered Nurses Foundation of Ontario for twice supporting

this work with a Dr. Sheela Basrur and GE Oncology Nursing Education Scholarship, and to the

v

Canadian Association of Nurses in Oncology for supporting this work with a Research Grant and

an Education Scholarship. Thank you also to the Federation of Chinese Canadian Professionals

(Ontario) Education Foundation for supporting this work with a Zindart Graduate Award for

Nursing Care of Persons with Cancer. I am also appreciative for the opportunities that I have had

to present various aspects of this project, and the financial support from the University of

Toronto School of Graduate Studies Conference Grant and the Canadian Institutes of Health

Research/Institutes de recherché en santé du Canada Travel Award which permitted me to do so.

A sincere thanks must be given to my parents, Bea and Joe, who inspired me to have faith, work

hard, and strive to make a positive contribution in my corner of the world.

Most importantly, I am eternally thankful to my life companion, Kevin, and our children,

Willem, Gwenyth and Vivian. They each relentlessly supported to me to complete every

element of this project, and they did so with much grace. This work would not have been

possible if not for their repeated exoneration of my absence from our family life. I love you

more than I can express.

Jacqueline Patricia Galica

December, 2016

vi

Table of Contents List of Tables .................................................................................................................... viii

List of Figures .................................................................................................................... ix

List of Appendices ............................................................................................................... x

Chapter 1 ............................................................................................................................. 1

1 Background ................................................................................................................... 1

2 Statement of the problem ............................................................................................... 4

Chapter 2 ............................................................................................................................. 5

1 Purpose .................................................................................................................... 5

2 Fear of cancer recurrence ......................................................................................... 6

3 Prevalence of fear of cancer recurrence .................................................................... 8

4 Predictors of Fear of Cancer Recurrence ................................................................ 17

4.1 Demographic predictors of FCR ................................................................. 17

4.2 Clinical predictors of FCR .......................................................................... 22

4.3 Psychosocial predictors of FCR .................................................................. 30

5 Mediators of Fear of Cancer Recurrence ................................................................ 42

6 Statement of the Problem ....................................................................................... 44

6.1 Significance of the study ............................................................................ 45

Chapter 3 ........................................................................................................................... 47

1 Background ........................................................................................................... 47

2 The Predictors and Mediators of Fear of Cancer ..................................................... 49

3 Conceptualization of the Primary Outcome Variable .............................................. 51

4 Conceptualization of the Independent Variables ..................................................... 52

5 Conceptualization of the Mediating Variables ........................................................ 57

6 Strengths and Limitations of the Proposed Model .................................................. 58

vii

Chapter 4 ........................................................................................................................... 61

1 Purpose of the Study .............................................................................................. 61

2 Research Objectives ............................................................................................... 61

3 Overview of the Proposed Study ............................................................................ 63

4 Setting ................................................................................................................... 63

5 Sampling Frame and Target Population.................................................................. 64

6 Eligibility Criteria .................................................................................................. 65

7 Procedures for Data Collection .............................................................................. 66

8 Variable Definition and Measurement .................................................................... 69

9 Ethical Considerations ........................................................................................... 84

10 Data Analysis......................................................................................................... 85

Chapter 5 ........................................................................................................................... 91

1 Study Sample ......................................................................................................... 91

2 Objective 1 ............................................................................................................ 96

3 Objectives 2 and 3.................................................................................................. 97

4 Objective 2 .......................................................................................................... 110

6 Overall Summary of Results ................................................................................ 125

Chapter 6 ......................................................................................................................... 127

1 Prevalence of FCR ............................................................................................... 127

2 Direct and Indirect Effects of Variables on FCR .................................................. 128

3 Limitations .......................................................................................................... 140

Chapter 7 ......................................................................................................................... 145

viii

List of Tables

Table 1. A Summary of FCR Measures …………………………………………….…...…. 9

Table 2. Overview of Study Variables and Measures ………………………….……….….70

Table 3. Comparison of Responders to non-Responders ……………………….…………..92

Table 4. Demographic Characteristics of Participants ………………………….…….…….94

Table 5. Clinical Characteristics of Participants …………………………………….……...95

Table 6. Amounts of Missing Data by Measure…………………………………….……….96

Table 7. Exploratory Analysis of Demographic Characteristics with FCR …………….......98

Table 8. Exploratory Analysis of Clinical Characteristics with FCR ……………………..100

Table 9. Self-Identity Characteristics of Participants ……………………………………...102

Table 10. Illness Representation Characteristics of Participants …………………………..103

Table 11. Coping Style Characteristics of Participants ……………...…………….............104

Table 12. Analyses of the Measurement Models ………....……………………….............106

Table 13. An Overview of the Direct and Indirect Effects on FCR in Objective 3a ...........118

Table 14. An Overview of the Direct and Indirect Effects on FCR in Objective 3b………124

ix

List of Figures

Figure 1. The Predictors and Mediators of Fear of Cancer Recurrence Conceptual

Framework ……..……………………………………………………………....50

Figure 2. Study Recruitment Strategy …...…………………………………..……………68

Figure 3. Flow Diagram of Study Recruitment and Participation ………………………...92

Figure 4. Structural Model Results for Objective 2……………….……………………...112

Figure 5. Structural Model Results for Objective 3a…………………..…………...…….117

Figure 6. Structural Model Results for Objective 3b.………………………..………...…123

x

List of Appendices

Appendix A: Overview of cancer survivors attending the ACTT clinic and ........................ 177

Appendix B: Sample Size Estimations ................................................................................ 178

Appendix C: Information Letter ......................................................................................... 179

Appendix D: Consent Form ................................................................................................ 180

Appendix E: Fear of Cancer Recurrence Inventory (30) ...................................................... 182

Appendix F: Demographic Form ........................................................................................ 184

Appendix G: Data Extraction Form .................................................................................... 186

Appendix H: Rosenberg Self-Esteem Scale (174) ............................................................... 188

Appendix I: Big Five Inventory -10 (BFI-10) (180) ............................................................ 189

Appendix J: Revised Life Orientation Test (LOT-R) (115) ................................................ 190

Appendix K: Illness Perception Questionnaire – Revised (IPQ-R) (103) ............................. 191

Appendix L: Brief COPE (126) .......................................................................................... 194

Appendix M: Follow up Telephone Call Script ................................................................... 196

Appendix N: Detailed Sample Characteristics .................................................................... 198

Appendix O: Analyses of Missing Data .............................................................................. 202

Appendix P: Details of Measures Used ............................................................................... 211

Appendix Q: Exploratory Bivariate Analyses ..................................................................... 218

Appendix R: Analysis of Direct Effects .............................................................................. 221

Appendix S: Exploratory Mediation Analyses .................................................................... 222

Appendix T: Analyses of Indirect Effects ........................................................................... 227

1

Chapter 1 Introduction

1 Background

The incidence rates of cancer in Canada have increased or been stable over the past 30 years

whereas the overall mortality rates have declined (1). This translates into a higher number of

people living with cancer. In 2013, the Canadian Cancer Society estimated that there were over

840,000 cancer survivors in Canada (2), more than double the number surviving cancer 20 years

ago (3). This number continues to rise due to the introduction of earlier, highly sensitive

screening programs, improved effectiveness in cancer therapies, and better overall health and

behaviours within the general population (4,5).

Various definitions of ‘cancer survivor’ exist in the literature. The earliest description of

survivorship was recorded by Dr. Fitzhugh Mullan (6), who described survivorship in terms of

“seasons”: acute survival began at cancer diagnosis and spanned the duration of acute treatment,

extended survival began thereafter, followed by permanent survival, where the person is deemed

to be ‘cured’ of cancer but live with its physical and emotional consequences. The most widely

accepted definition of cancer survivorship was developed by the Office of Cancer Survivorship

at the National Cancer Institute (NCI). They define cancer survivorship as:

[the period] from the time of diagnosis, through the balance of his or her life. Family

members, friends, and caregivers are also impacted by the survivorship experience and are

therefore included in this definition (7).

Although this definition is broad to include persons in various phases of the treatment trajectory,

the Canadian Association of Psychosocial Oncology (CAPO) and the Canadian Partnership

Against Cancer (CPAC) indicate that the post-treatment phase of survivorship has often been

overlooked in advocacy, education, clinical practice and research (5). Therefore herein, a cancer

survivor was referred to as a person who had completed adjuvant treatment for a cancer

diagnosis.

2

1.1 Fear of Cancer Recurrence (FCR)

Cancer survivors have a unique subset of needs (4,5). Researchers have explored the

psychosocial needs of cancer survivors who rank fears about cancer returning as one of their

predominant concerns (8–10). Although different definitions of Fear of Cancer Recurrence

(FCR) exist (11,12), the one most commonly cited at the time of this writing was that of

Vickberg (11) as “the worry that the cancer will come back in the same place or in another part

of the body” (p.18). Research findings have identified a number of negative consequences of

FCR including lower quality of life (13–18), poorer mental wellbeing or mental health-related

quality of life (17–20), and poorer physical wellbeing or physical health-related quality of life

(18–20). Other negative outcomes found to be associated with FCR include higher levels of

emotional distress (21,22), uncertainty (21), fear of death (23), and a negative effect on

survivors’ ability to make plans for the future (24). Level of FCR has also been found to be

positively associated with outcomes that affect health care resources. Survivors with higher FCR

more frequently visited outpatient clinics and Emergency Departments (25) or made unscheduled

visits to physicians (24) than those with lower fears, conducted self-examinations more often

than recommended guidelines (26), and were less satisfied with their treatment and

communication with medical staff (26). These findings illustrate the numerous consequences of

FCR and its negative impact on both the cancer survivor and the health care system.

Collectively, these findings provide important implications for the early identification of patients

with or at high-risk of clinically-significant FCR in order to refer them to appropriate

interventions. Cancer survivors have indicated that they want help from professionals to cope

with their FCR (9,26–28), which has been recommended as a practice priority for cancer

professionals (4). Furthermore, FCR is an under-recognized concern by clinical cancer

professionals who have reported that they would like more training about how to identify and

manage FCR in cancer survivors (29). Collectively, these findings demonstrated the need for a

better understanding of the magnitude, predictors and mediators of FCR.

1.2 Prevalence of Fear of Cancer Recurrence

The prevalence rates of FCR are widely varied and may be explained by the various methods of

measurement, including the use of single-item, or multi-item, multi-dimensional tools. The

varied rates may also be due to the inconsistent psychometric properties of measures, particularly

3

in terms of their unstated validity. Furthermore, prevalence rates may be difficult to determine

since there is a lack of consensus about what constitutes a clinically significant FCR (30).

Therefore, further research was needed to clarify the prevalence of FCR to provide a clearer

indication of its magnitude among cancer survivors and provide clarity for clinical and research

resources.

1.3 Predictors of FCR

Three types of predictors of FCR have been identified in the literature: 1) demographic, 2)

clinical, and 3) psychosocial. Demographic variables such as age (24,31–37), socio-economic

status (38) and ethnicity or race (39,40) have been suggested as predictors of FCR, but have

largely been determined in samples of breast cancer survivors. The clinical and psychosocial

variables are diverse and been identified in a small number of studies. Clinical variables

included: physical wellbeing and co-morbidities (16,39,41), physical symptoms (15,31,35,38–

40,42), severity of cancer or cancer stage (19,31,34,43), and type of cancer treatment (31,32,39).

Psychosocial factors stemming from research findings can be grouped as: psychological and

emotional (10,22,31,36–38,44–46), survivor beliefs and perceptions (31,36,42,44,45,47,48),

stress and coping (34,35,38,42), relationships (31,49,50), existential considerations (33,35,49),

and healthcare resources (25,39). While all of the factors bear importance on FCR, the collective

literature inhibited the generalizability of findings since corroboration has mainly occurred in

samples of breast cancer survivors. Understanding the predictors of fear of recurrence was

necessary in order to identify survivors with, or at highest risk of developing, clinically

significant FCR.

1.4 Mediators of FCR

Mediating variables add clarity to the relationship between an independent and dependant

variable (51). It is important to examine the mediators of FCR when considering the

development of tailored interventions for survivors. Self-efficacy (36), methods of coping (35),

ease of understanding information, symptom management and care co-ordination (39), were the

only variables that were reported as mediators of FCR. However, these findings were

determined in breast cancer survivors and were therefore limited in their generalizability.

Further study about the mediators of FCR was needed since they have the potential to affect how

4

the individual manages their level of FCR. This information would be useful in the development

of relevant interventions for cancer survivors to cope with FCR.

2 Statement of the problem

The literature indicates that there is a high number of cancer survivors (3,52) who rank fears of

cancer recurrence as their most important unmet need (27). This high number may translate into

a high burden on the Canadian health care system, since the data indicated that higher FCR is

associated with a higher use of healthcare resources (24–26,39). Prior to this dissertation, the

literature was unclear about the prevalence and clinical significance of FCR among adult cancer

survivors (53–55) which may negatively affect the allocation and efficiency of healthcare

resources. Although predictors and mediators of FCR had been presented in the literature, these

findings were interpreted as preliminary due to issues with generalizability. Clearly, the

outcomes of and factors associated with FCR are debilitating for cancer survivors and warranted

further exploration.

To this end, a large sample of heterogeneous cancer survivors was sampled to address these

limitations. The need for this research was based upon the identified needs of cancer survivors

(9,26–28), the recommendations to address FCR in professional cancer care (4), and the requests

from clinical care providers to receive training to identify and care for FCR of cancer patients

(29). Therefore, the purpose of this research was to provide clarity about the prevalence,

predictors, and mediators of FCR among survivors of adult cancers.

5

Chapter 2 Review of the Literature

1 Purpose

The purpose of this literature review was to examine what was known about the prevalence,

predictors, and mediators of FCR among survivors of adult cancers. First, an overview of FCR

was conducted. The literature review then concentrated on three areas to determine what is

known about: 1) the prevalence of FCR, 2) the predictors of FCR, and 3) the mediators of FCR,

all among survivors of adult cancers.

1.1 Search strategy

A search was conducted to determine the known predictors of fear of cancer recurrence. The

literature search, initially conducted in December 2012, was intended to capture all original

articles published using the following stated criteria, however the literature was continually

monitored throughout the study and the review was updated as necessary. The CINAHL,

Medline, PsycINFO, Sociological Abstracts, Web of Science, and Proquest Dissertations and

Thesis databases were searched using the keywords cancer* or neoplasm* AND fear* AND

recur* or relaps*. Studies were included if: 1) Fear of Recurrence, or Fear of Cancer

Recurrence, or Fear of the Future, or Fear of Progression was a major outcome variable assessed

in the study; 2) of which the prevalence, predictors, or mediators were assessed; 3) in a sample of

patients or survivors of adult cancer, defined as those greater than or equal to 18 years of age.

All English-language qualitative and quantitative studies were included in the review and no

restrictions were placed on publication date. A hand search through the reference lists of each of

the reviewed articles was conducted in order to identify any additionally relevant articles that

may have been missed during the electronic search. The literature published by provincial,

national, and international organizations regarding Fear of Cancer Recurrence, or Fear of

Recurrence, were reviewed to provide additional context.

The initial search retrieved 266 original papers after duplicates were removed. All papers were

reviewed in light of the stated inclusion criteria, resulting in 53 original research reports. In

addition to these original research reports, 3 systematic reviews addressing an empirical

understanding of FCR were retrieved (53–55). Although, as identified in the search strategy

6

above, original research reports were sought, acquired and discussed in the current literature

review, these quality systematic reviews (53–55) were included herein as a means to triangulate

the findings of the following review.

2 Fear of cancer recurrence

At the time of this writing, the most widely cited definition of FCR was based upon the work of

Vickberg (11), who described it as “the worry that the cancer will come back in the same place

or in another part of the body” (p.18). Although Vickberg’s (11) definition was the most

commonly cited in the FCR literature, a consensual definition of FCR remained elusive (12).

With the intent to rectify this matter, an international group of clinicians and researchers

specializing in FCR convened in 2015. They used a Delphi process (12) which resulted in the

formation of a new definition of FCR: “Fear, Worry, or concern relating to the possibility that

cancer will come back or progress” (p.3266). Despite this more recent, consensual definition

(12), the FCR definition proposed by Vickberg (11) was the most commonly cited at the time of

the current study’s conceptualization and was therefore adopted for this study.

Despite the new consensual definition of FCR (12), the conceptual dimensionality of FCR has

been suggested to require further investigation (56,57). At the time of this study’s

conceptualization, the work of Lee-Jones et al. (58) was the most commonly cited

conceptualization of FCR (see Chapter 3 Section 1.0 for further details) who proposed that FCR

was comprised of cognitions, beliefs and emotions (58). According to Lee-Jones et al. (58),

cognitions included the person’s past experience with cancer and its treatment, their knowledge

base of cancer (i.e. cure and survival rates), and their beliefs about the eradication of cancer

(p.102). Lee-Jones et al. (58) went onto propose that a person’s beliefs about their personal risk

to a cancer recurrence as the second component of FCR (p.102), whereas a person’s emotions,

including worry about the cancer returning, anxiety about the cancer itself, and regret for not

selecting more aggressive treatment (p.102) to be the final component of FCR. This

conceptualization of FCR (58) regards the concept as comprised of a number of dimensions, or

in other words, a multi-dimensional construct.

Although FCR has been commonly accepted as a multidimensional construct (11,30,58,59), the

method of assessing FCR, either as a unidimensional or multi-dimensional measure, remained

widely varied (57). Recognizing that the formulation of FCR proposed by Lee-Jones et al. (58)

was the reference conceptualization for the current literature review, measures referred to as

7

“multi-dimensional” in the FCR literature were not necessarily referred to as such in the current

review. For example, Vickberg’s (11) Concerns About Recurrence Scale (CARS), although

theoretically founded (60) and comprised of a number of “domains” (p.17), questions remained

about the consistency of these “domains” (p.17) with the components of FCR as proposed by

Lee-Jones et al. (58). That said, it appeared that Lee-Jones et al.’s (58) emotional component of

FCR was represented in a number of CARS’ items that addressed worry, and therefore the CARS

was regarded as unidimensional in the current literature review. Authors of other FCR measures

were more explicit about the conceptualization of FCR used in the development of a particular

measure. For example, Simard et al. (30) overtly referred to the work of Lee-Jones et al. (58) as

foundational to their development of the Fear of Cancer Recurrence Inventory (FCRI), which

included triggers, severity, psychological distress, coping strategies, functioning impairments,

insight, and reassurance subscales. Because of the consistency of the FCRI (30) items with the

FCR formulation presented by Lee-Jones et al. (58), the FCRI was regarded as a multi-

dimensional measure in the current review. Still, developers of other FCR measures, claimed

that a conceptual framework to guide FCR research was not widely available (59), however the

items within their measure seemingly mapped onto each of Lee-Jones et al.’s (58) components of

FCR. For example, in their development of the Fear of Progression Questionnaire (FoP-Q),

Herschbach et al. (59) completed interviews with patients having cancer, inflammatory

rheumatic diseases and diabetes mellitus (ibid (59)) to generate statements about fear of

progression. Through a clearly articulated process (59), the FoP-Q was comprised of 5 subscales

(affective reactions, partnership/family, occupation, loss of autonomy, and coping [p.508]) that

seem to map onto each of Lee-Jones et al.’s (58) domains of FCR. In this way, the FoP-Q (59)

was regarded as a multi-dimensional measure for the current literature review. In summary, a

number of FCR measures have been developed (57), however their development has been

inconsistently based upon theory, and/or the selection of the foundational theory varied widely.

For the purpose of this literature review, measures were explored in regard to their consistency

with Lee-Jones et al.’s (58) components of FCR and regarded as unidimensional or multi-

dimensional depending upon the number of Lee-Jones et al.’s (58) components represented in

the measure. The dimensionality conclusions proposed herein should be considered as

speculative. As such, further examination and discussion beyond this review is suggested.

Notwithstanding the previously mentioned inconsistencies in FCR measurement, the correlates

of FCR have included a number of factors. Cancer survivors with higher fears reported lower

8

quality of life (13–16), poorer mental and physical wellbeing (18,19), and lower satisfaction with

treatment and communication with medical staff (26). Higher FCR was reported to influence

mood and ability to make plans for the future (24), and was correlated with higher use and

financial expenditures on Complementary and Alternative medicines (CAM) (24,61). Survivors

with higher FCR made more unscheduled visits with physicians (24), conducted self-

examinations more frequently than recommended guidelines, and more frequently attended

counselling and support groups (24) than those with lower fears. Furthermore, FCR was

reported as a predictor of overall quality of life (17), mental health-related quality of life (19,20),

physical health-related quality of life (19,20), emotional distress (21), uncertainty (21), fear of

death (23), as well as anxiety and depression (40). To summarize, the outcomes of and factors

associated with FCR are debilitating for cancer survivors and warranted further exploration.

3 Prevalence of fear of cancer recurrence

Fears about cancer recurrence have been identified as a concern for 10-85% of cancer survivors

(11,15,24,38,43,46,62), and qualitative studies have substantiated its significance (63–72). The

widely varied prevalence rates may have been explained by the various methods of measuring

the concept, either by a single-item, or by a multi-item, multi-dimensional tool. The varied rates

may also have been due to the inconsistent psychometric properties of measures. Furthermore,

prevalence rates may have been difficult to determine since there was a lack of consensus about

what constituted a clinically important level of FCR (30). Recently, the use of multi-item

measures to assess FCR has been the preference of psychosocial oncology researchers, who

acknowledge the multi-dimensionality of the construct (30,58). Table 1 presents measures used

among studies meeting the current literature review criteria, however, it is recognized that other

measures to assess FCR have been developed (57).

9

Table 1. A Summary of FCR Measures

Measure Number

of Items Validity Reliability

Concerns of

Recurrence Scale

(CARS) (includes

the Overall Fear

Index and 4

subscales) (11)

30

Convergent validity with

Intrusive Thoughts subscale of

IES* in breast cancer survivors

(r=.43-.64)(11)

Internal consistency in breast

cancer survivors (α=.87) (11)

Fear of Recurrence

Questionnaire

(FRQ) (73) 22

Content validity by 3 experts

(73); convergent validity with

POMS* in breast cancer

survivors (r=0.47) (50)

Internal consistency in breast

cancer survivors (α=.70-.89)

(73), and mixed cancer survivors

(α=.92) (49)

Fear of Cancer

Recurrence

Inventory (FCRI)

(30)

42


CARS (r=.77), FRQ (r=.71) in

mixed cancer survivors (30).

Divergent and discriminant

validity also explored (30)

Internal consistency in mixed

cancer survivors (α=.95), and 1-

month test-retest =.89 (30)

Fear of

Relapse/Recurrence

Scale (FRRS) (74) 5

Some evidence for convergent

and divergent validity (57)

Internal consistency in leukemia

survivors (α=.69) (75), and

prostate cancer survivors (α=.88)

(18)

Fear of Recurrence

questionnaire

(FoRq) (28) 7


anxiety (r=-.71), mood (r=-

.62), and social-emotional

function (r=-.59) subscales of

UWQOL* in head and neck

survivors (37)

Internal consistency (α=.90) in

head and neck survivors (28)

Cancer Worry

Scale (CWS)

(34,47,76) 4


depression (34)

Internal consistency (α=.87)(34)

and test-retest (r=.50-.62) (47)in

breast cancer survivors. Internal

consistency (α=0.7) in ovarian

cancer survivors (76).

Worry of Cancer

Scale (WOCS)

(22,77)

5

Unstated. Unstated.

Fear of

Progression

Questionnaire-

Short Form (FoP-

Q-SF) (78)

12

Convergent validity of full 43-

item scale with anxiety (r=.66)

and depression (r=.57)

subscales of HADS* in chronic

disease (59). Short form

validity is unknown.

Internal consistency of full scale

is α=.95 and test-retest (.94) in

chronic disease (59), α=.87 in

mixed cancers (43), and α=.89 in

breast cancer survivors (79).

* HADS= Hospital Anxiety and Depression Scale; IES=Impact of Events Scale; POMS=Profile

of Moods States; UWQOL = University of Washington Quality of Life version 4.

10

The prevalence of FCR has been explored in various cancer populations, each of which were

explored and are outlined in the following sections. Studies were critically appraised with

emphasis on the operational measurement of concepts and the psychometric properties of the

measures.

3.1 Prevalence of FCR in samples of breast cancer survivors

The largest group of cancer survivors represented in the fear of cancer recurrence literature were

survivors of breast cancer, where seven studies used various tools to assess FCR. Of these seven

studies, Vickberg et al. (11), van den Beuken-van Everdingen et al. (15), and Taylor et al. (17)

used the 30-item Concerns of Recurrence Scale (CARS), which seemingly reflected only Lee-

Jones et al.’s (58) emotional component of FCR, although it has established validity and

reliability in breast cancer survivors. Although only van den Beuken-van Everdingen (15)

overtly sought to determine the prevalence of FCR in this population, Taylor (17) sought to

“measure the extent” of FCR (17) and Vickberg (11) assessed the “frequency” and “intensity” of

FCR, and have been included in this review. The fore-mentioned authors used the Overall Fear

Index, which are the first 4-items of the CARS, to report the prevalence of FCR. This was

appropriate since the overall fear index is intended to assess frequency, potential for upset,

consistency and intensity of fears, whereas the remaining 26-items are to determine the nature of

fears (11). However, these studies lack consistency in their determination of FCR prevalence.

The interpretations of the overall fear in these samples ranged from “low to moderate” (17),

“moderate” (11), and “moderate to high”(15), which did not appear to be consistent with the

reported means of each study. Overtly expressing prevalence in their samples, van den Beuken-

van Everdingen et al. (15) described 56% of the sample had moderate to high overall fear,

whereas Taylor et al. (17) described 67% of the sample reported “some degree” of FCR.

Similarly, Vickberg (11) indicated that 10% of their sample reported high levels of FCR, defined

as results on the “higher third of the Likert scale” (p.21). Collectively, these studies illustrated

the varied prevalence rates of FCR among studies of breast cancer survivors, but also indicated

the inconsistencies in defining FCR prevalence using the CARS.

McGinty et al. (34) used the 4-item modified Cancer Worry Scale (mCWS), which was

developed to measure levels of worry and how it impacts daily functioning in a sample of

women with an abnormal screening mammogram (80). The only psychometric report about this

measure were by McGinty et al. (34) who reported its internal consistency in a sample of breast

11

cancer survivors (34). Although the determination of prevalence was not an objective of

McGinty et al.’s (34) study, they did report and interpret the mean total FCR score. The authors

reported that the overall mean corresponded to a result between the responses ‘not at all/rarely’

and ‘sometimes’ (p.206). This study failed to add clarity to understanding the prevalence of

FCR in breast cancer survivors since it used only 4-items, which appears to only include the

emotional component of Lee-Jones et al.’s (58), instead of a multi-dimensional construct as was

commonly accepted (30,58), and lacked clarity about its psychometric properties.

Koch et al. (79) used the 12-item Fear of Progression Questionnaire Short Form (FoP-Q-SF) to

determine the prevalence of FCR among long-term (≥ 5 years) breast cancer survivors. The

authors used the developer’s theoretical definition of moderate FCR (43) to report the prevalence

of FCR in their sample1. Eleven percent of the sample reported a moderate level of FCR, and

another 6% reported high levels of fear. Although this study used a short-form of a multi-

dimensional measure (59) aligned with Lee-Jones et al.’s (58) formulation of FCR, readers are

unclear about which (FoP-Q) (59) items were adopted and therefore cannot be certain about

which of Lee-Jones et al.’s (58) commonly accepted dimensions of FCR are included in this

short-form. Furthermore, concerns remain about the psychometric properties of the FoP-Q-SF

and the method by which the reportable level of FCR was determined, despite being determined

within a large sample (n=2641) that allows generalizability.

Gibson et al. (81) sought to determine the level of breast cancer fear by phase of cancer

survivorship. In a secondary analysis, they used 4 items adapted from the Quality of Life/Breast

cancer Psychological Well-Being (PWB) Subscale (82) to address 4 fears: fear of future

diagnostic tests, fear of a second cancer, fear of recurrence, and fear of metastasis, capturing only

the cognitive and emotional components of Lee-Jones et al.’s (58) formulation of FCR.

Although an acceptable Cronbach’s alpha was reported (α = 0.90) and content validity was

obtained, the authors provide no rationale for the determined “low”, “moderate”, and “high” fear

levels. The authors only reported the mean level of fear (x = 36.57, SD = 17.5) that they

described as “moderate”, which they claim did not statistically differ by survivorship phase.

This study seemingly sought to determine a prevalence-like value among breast cancer survivors,

however the reported statistic (x) and the method of conceptual measurement do not provide

clarity to the prevalence of FCR among breast cancer survivors.

1 Koch et al. (79) reported a Cronbach’s α = 0.89 for the Fear of Progression Questionnaire Short Form (FoPQ-SF)

in their study.

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The primary objective of Thewes et al.’s (24) study was to explore the prevalence and correlates

of FCR among breast cancer survivors. They used the 42-item Fear of Cancer Recurrence

Inventory (FCRI) (24), which is multi-dimensional in alignment with Lee-Jones et al.’s (58)

conceptualization, and has established reliability and validity in mixed cancer survivors (30).

Thewes et al. (24) reported the prevalence of FCR as 70% of the sample who scored a level of

FCR that was clinically significant. The definition of ‘clinically significant’ was defined as a

score of ≥13 (range 0-36) on the 9-item Severity subscale of the FCRI (24). Using the Severity

subscale to screen for FCR among survivors is appropriate due to its strong correlation with the

overall FCRI score (r(599)=0.84, p<.001) (30). Of all the studies that have reported the scores of

FCR among breast cancer survivors, the results presented by Thewes et al. (24) are the most

cogent based upon the use of a valid and reliable multi-dimensional measure with a clinically-

significant cut-off score. In summary, the prevalence of FCR in breast cancer survivors

remained unclear, due to the varied means of assessing the concept and varied methods of

defining and reporting prevalence.

3.2 Prevalence of FCR in samples of colorectal cancer survivors

There was one study that reported the prevalence of FCR among colorectal cancer survivors.

Mullens et al. (62) reported the prevalence of FCR among a sample of colorectal cancer

survivors to be 81.5%. However, the development of and rationale for the 6-items that were

used to assess FCR are not indicated, however the items appeared only to capture information

pertaining to Lee-Jones et al.’s (58) emotional component of FCR. Furthermore, the prevalence

rate was calculated by including a range of scores, including those who indicated even ‘a little bit

of worry’, which likely overestimates the clinically relevant prevalence of FCR in colorectal

cancer survivors. Additionally, the unstated validity of the items and the small sample size

(n=41) limited the generalizability of these findings to other samples of colorectal cancer

survivors and survivors of other cancers. Collectively, the findings of this literature review

indicated that the prevalence of FCR in colorectal cancer survivors may be overestimated, and

further study was needed to generalize multi-dimensional FCR in this population.

3.3 Prevalence of FCR in samples of prostate cancer survivors

There was one study (45) that explored the rates of FCR among a sample of prostate cancer

survivors, although it was not prevalence rates were reported. Mehta et al. (45) used the 5-item

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Fear of Recurrence/Relapse Scale (74), about which the conceptual foundation is unstated, to

explore the pattern of FCR between pre-treatment and 2-years thereafter. Results were presented

as mean scores (𝑋=60-78) at four time-points (45), where higher scores (range 0-100) indicated

less fear. Furthermore, the validity of the scale had not been reported in an original source, and

the internal consistency has suggested its reliability (α=0.69-0.75) (74,75). In conclusion, the

prevalence of FCR in prostate cancer survivors was not clear although modest levels of FCR

were suggested.

3.4 Prevalence of FCR in samples of testicular cancer survivors

There were two studies that reported the prevalence of FCR among testicular cancer survivors.

Skaali et al. (38) and Pedersen et al. (44) each developed a single question that seemingly

captured only the emotional element of Lee-Jones et al.’s (58) formulation of FCR to assess

FCR, whereby case-ness was determined by the top two responses (‘quite a bit’ and ‘very much’)

of a 4-point Likert scale. Neither of the reports indicated an assessment of the validity of this

item, and only Skaali et al. (38) reported its internal consistency. Results from these studies

were similar, where 28% (44) and 31% (38) of the samples reported ‘quite a bit’ or ‘very much’

fear about the cancer returning. Although the sample sizes (n≥450) contributed to their

generalizability, the prevalence of FCR among testicular cancer may have been under-estimated

since it was assessed using a single-item with unknown validity and seemingly addressed only

one element of Lee-Jones et al.’s (58) formulation of FCR.

3.5 Prevalence of FCR in samples of head and neck cancer

survivors

Three studies had assessed the levels of FCR in survivors of head and neck cancers (22,37,46).

Although none overtly aimed to determine prevalence, they provided an indication of FCR

prevalence in this population. Llewellyn et al. (46) sought to explore the “extent” (p.528) of

reported FCR, Hodges et al. (22) intended to “describe and compare levels” (p.842) of FCR, and

Ghazali et al. (37) sought to “explore the longitudinal trends” (p.808) of FCR.

A great limitation of the findings related to the levels of FCR in head and neck survivors was that

these studies used 1-item (46), 2-items (22) or 7-items (37) to assess FCR, which failed to

recognize the multi-dimensionality of the concept (30,58). Llewellyn et al. (46) used 1-item

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from the 5-item Worry of Cancer Scale (77) without an explanation for not using the other items,

however this item captured information about the emotional component of FCR as described by

Lee-Jones et al. (58) and therefore appeared to regard FCR as a unidimensional construct.

Hodges et al. (22) used 2 items from the 5-item Worry of Cancer Scale (77), claiming that the

other 3 items were “inappropriate” (p. 843) to be used with their sample. These 2 items (22)

both reflected “worry” (p.843) and therefore seemingly only the emotional dimension of Lee-

Jones et al.’s (58) formulation of FCR. Although the psychometric properties of the entire 5-

item Worry of Cancer scale has been established in breast cancer survivors (77), Llewellyn et al.

(46) neither reported the reliability nor validity of the items used, whereas Hodges et al. (22)

reported the internal consistency of the 2-items (α = 0.85-0.90), but did not discuss their validity

(22). Collectively, these indicated limitations in FCR measurement.

Similar discrepancies existed in the reporting of FCR levels in these studies of head and neck

cancer survivors. Llewellyn et al. (46) reported the percentages of responses within each of the

5-ordinal response categories, as well as the mean scores (𝑋=2.8 & 2.6, before and after

treatment respectively) for survivors who reported occasional worry about the cancer coming

back (range 1-5, where higher scores indicated more fear) (46). Hodges et al. (22) also reported

means of the 2 items for the two time points as 11.74 and 11.71 (range 0-20) (22). Although

these means were similar, the selection of data to present as means varied: Llewellyn et al. (46)

presented the data for only those responses that indicated occasional worry on the single-item,

where Hodges et al. (22) presented all data for the 2 items used. Therefore, the prevalence of

FCR among head and neck cancer survivors may not have been clear.

Ghazali (37) used the 7-item Fear of Recurrence questionnaire to explore the longitudinal

prevalence trends in “significant” (p.808) FCR. “Significant” (p.808) FCR was defined as the

selection of one item indicating ‘a lot’ or ‘all the time’ on any of the 6 ordinal items, or as a score

7-10 on the single-ratio item (range 0-10). The justification for this calculation was not

provided, and so the clinical significance of this score remained unknown. The justification for

selecting the 7 items from the original 16-item measure was not reported, however they reflected

each of the FCR dimensions outlined by Lee-Jones et al. (58). Furthermore, the development of

the original measure is not indicated and therefore the psychometric properties of the original

and revised measures aren’t clear. Ghazali (37) reported the prevalence of significant FCR in

this sample to be 35%, using the previously identified definition. However, due to the lack of

15

clear scale and item development, as well as the lack of psychometric testing, FCR levels in this

sample needed to be cautiously interpreted.

In summary, there were limitations in the psychometric properties of the measures used to assess

FCR in samples of head and neck cancer survivors. Furthermore, the definitions of FCR used to

determine reportable levels of FCR risked overestimating the true prevalence of FCR, since they

included few items representing variations in dimensionality to assess this multi-dimensional

concept (30,58). Collectively, the prevalence of FCR in samples of head and neck survivors was

unclear.

3.6 Prevalence of FCR in samples of melanoma cancer

survivors

One study has reported the prevalence of FCR among a sample of melanoma survivors (83),

although the authors’ original intent was to examine the fit of the FCRI according to Item

Response Theory (IRT). In using the valid and reliable FCRI, Costa et al. (83) determined that

72% of the sample had a FCRI Severity subscale score that reached a level of clinical

significance (30,84). Since other measures have indicated that melanoma survivors live with

psychological concerns after treatment is completed (85,86) and Costa et al. (83) used the valid

and reliable FCRI to assess FCR founded upon the formulation of FCR presented by Lee-Jones

et al. (58), the findings published by Costa et al. (83) are credible.

3.7 Prevalence of FCR in samples of mixed-cancer survivors

Three studies (25,30,43) had explored the level of FCR in samples of mixed cancer survivors.

Simard et al. (30) and Lebel et al. (25) both used the Fear of Cancer Recurrence Inventory

(FCRI) founded upon the formulation of multidimensional FCR presented by Lee-Jones et al.

(58), however neither sought to assess FCR prevalence as a primary outcome. The goal of

Simard et al. (30) was to report the initial psychometric properties of the new FCRI in a large

sample of heterogeneous cancer survivors (n=1,704). In their descriptive analysis, Simard et al.

(30) reported the mean score of the FCRI in the entire sample as 51.7 (range 0-168), with

significant differences noted by gender and cancer site (30). Similarly, Lebel et al. (25) reported

the mean FCRI score of the sample as 45.1 (range 0-138.6) (25). Although mean FCRI scores of

a sample may have given an indication to the levels of FCR among the subjects, a true

prevalence rate could not have been determined without identifying the level at which clinically-

16

significant FCR is captured. To fill this gap, Simard et al. (84) conducted a Receiver Operating

Curve (ROC) analysis of the Severity Subscale of the FCRI, which was used as a brief screening

measure since the 9-items are highly correlated with the entire FCRI (30). A score of 13 or

greater on the subscale indicates a clinically-significant FCR (84), which is useful in determining

accurate prevalence rates of FCR. Therefore, Lebel et al.’s (25) finding that 58.3% of the sample

scored above 13 on the Severity Subscale may present the most valid prevalence rate of FCR in a

mixed cancer sample when using the FCRI.

Mehnert et al. (43) sought to determine the prevalence of FCR in a sample of mixed-cancer

survivors using the short version (FoP-Q-SF) of the valid, reliable, multi-dimensional (58) Fear

of Progression Questionnaire (FoP-Q) (59), however, readers are unclear about which (FoP-Q)

(59) items were adopted and therefore cannot be certain about which of Lee-Jones et al.’s (58)

commonly accepted dimensions of FCR are included in this short-form. At the end of cancer

treatment, 84.7% of the sample reported moderate or high levels of FCR and this value remained

constant for one-year (43). Sampling bias may have been a major limitation of this study’s

findings since the sample was recruited from a cancer rehabilitation clinic targeted for cancer

survivors to regain physical and psychosocial functioning (43). It seems plausible that survivors

who attended this optional clinic may have had higher FCR for which they choose to attend the

clinic. Furthermore, the high prevalence rate may be explained by Mehnert et al.’s (43)

definition of low, moderate or high FCR as the mean sample FCR value ±1 SD. This mean value

may have been higher than other cancer samples due to the nature of the sampling frame.

Finally, although the validity and reliability of the full measure had been established (59), the

validity and reliability of the short form used in this prevalence study was not established.

3.8 Overall understanding about the prevalence of FCR

The levels of FCR in studies of adult cancers were widely varied, likely due to their methods of

FCR assessment and definition of case-ness. Among the results of their systematic review, Crist

et al. (54) concluded that the diversity of measures used to assess prevalence were not

appropriate to reliably determine clinically significant FCR, which may have increased the error

variance among the samples. In other words, factors not under investigation, and also not

accounted for in the study method, may have had a greater influence on the results than if a

longer more robust measure was used to assess FCR. This corroborates with the work by FCR

17

scholars who have suggested that FCR is a multi-dimensional concept (30,58) and therefore

using a single or few-items to assess the concept may underestimate its magnitude.

With so many measures used to assess FCR, comparing results between studies was challenging.

Authors did not always report on the development, validity, and reliability of the items or scales

which results in a lack of clarity about the concept being measured. The varied interpretations of

FCR case-ness also contributes to the lack of clarity about FCR prevalence, where some studies

included any indication of FCR in the prevalence score, whereas others included only the

frequencies of scores from the highest ordinal categories.

No studies had specifically set out to explore the prevalence of FCR in a large sample of

heterogeneous cancer survivors using a reliable, valid, multi-dimensional measure that uses a

reliable score indicating clinically significant FCR. Therefore, further study was needed to fill

this gap.

4 Predictors of Fear of Cancer Recurrence

In the following pages lies a description of the literature in reference to the known predictors of

FCR. Studies that found statistically significant predictors of FCR were included in this review

and grouped into three categories: 1) demographic, 2) clinical, and 3) psychosocial. The

individual predictors of FCR were explored as components of these categories, and each study

was critically appraised.

4.1 Demographic predictors of FCR

Age, socioeconomic status, and ethnicity or race, were found to be statistically significant

predictors of FCR. These articles were summarized and critically appraised in the following

pages. Correlational evidence that supports or refutes these relationships was incorporated as

available.

4.1.1 Age as a predictor of FCR

There were ten studies that found younger age to be a predictor of higher FCR, either measured

as age at diagnosis (24,36) or by age at the time of study assessment (15,31–35,37,39).

Conversely, Gibson et al. (81) determined that among the 47.5% of their sample with highest

fears, older women (65-85 years old) comprised the largest proportion, suggesting that older

18

women have highest FCR. All but one (37) of the above studies were conducted in samples of

breast cancer survivors, which limits the generalizability of this finding to non-breast cancer

samples. However, age was not correlated with FCR in survivors of testicular cancer (38),

thyroid cancer (16), as well as other samples of breast cancer patients (87,88) and survivors,

collectively suggesting a need for further study of age as a predictor of FCR in mixed-cancer

survivors.

In studies where age was found to be a significant predictor of FCR, FCR was assessed using a

variety of measures. Costanzo et al. (32), van den Beuken-van Everdingen et al. (15), Lydon

(35), Liu et al. (31), and Ziner et al. (36) used the CARS to measure FCR, whereas Thewes et al.

(24) used the FCRI. Both the CARS (11) and the FCRI (30) are multi-item measures of FCR

with established validity and reliability in cancer populations, however, as described above, only

the FCRI (30) was regarded as a multi-dimensional measure of FCR aligned with Lee-Jones et

al.’s (58) conceptualization of FCR. In the remaining 5 studies, McGinty et al. (34), Stanton et

al. (33), Ghazali et al. (37), Janz et al. (39), and Gibson et al. (81) used the 4-item modified

Cancer Worry Scale (47), 6 items from the Fear of Recurrence Questionnaire (73), a different 7-

item Fear of Recurrence questionnaire, a 3-item measure , and the Fear of Progression

Questionnaire Short Form (FoP-Q-SF), respectively. The small number of items generally used

to assess FCR by these measures may under-estimate FCR as a multi-dimensional concept

(30,58), however only the measures used by Stanton et al. (33) and Ghazali et al. (37) clearly

aligned with the conceptual formulation of FCR proposed by Lee-Jones et al. (58). Furthermore,

Ghazali et al. (37) failed to report any psychometric data of the FCR measure used in their

sample, whereas only the internal consistencies were reported by McGinty et al. (34), Stanton et

al. (33) and Janz et al. (39). According to Brennan (89), when information is collected at a single

time point, such as the case of internal consistencies reported for the measures used by McGinty

et al. (34) and Janz et al. (39), the reliability will likely be overestimated. In other words, the

reliabilities of these measures are likely to be lower than reported, raising concerns about the

interpretability of the findings.

In summary, four of the ten studies that found age as a significant predictor of FCR had great

limitations in the reliability and/or validity of the measure used to assess FCR, which in turn may

alter any observed relationships. These four studies used measures with few items, only 2 of

which aligned with the dimensions of FCR as proposed by Lee-Jones et al. (58). Furthermore,

generalizing age as a predictor of FCR to non-breast cancer samples may be erroneous, since

19

nine of the ten studies reporting this relationship have been conducted in samples of breast

cancer survivors. Breast cancer samples are dominated by women, and therefore generalizing

these findings to male survivors may not be appropriate. However, differences in FCR by sex

remain contradictory (49,90). Collectively, the relationship between age and FCR needed further

study using a valid, reliable, multi-dimensional measure to assess FCR in a sample of mixed-

cancer survivors.

4.1.2 Socio-economic status as predictors of FCR

According to the Canadian Institute for Health Information, factors related to socio-economic

status include income level, education, employment and housing (91). One study has found

socio-economic factors to be a significant predictor of FCR (38). Skaali et al. (38) developed a

single question to assess FCR, which appeared to reflect only the emotional element of Lee-

Jones et al.’s (58) formulation of FCR, in a sample of 1,336 testicular cancer survivors, but did

not report the validity, reliability, nor process of question development. They found that

economic problems, defined as “having trouble to pay for regular expenses sometimes or often

during the last year” (p. 581), as well as unemployment, predicted FCR (38). Although Skaali et

al. (38) determined these results within a large sample (n=1,336) rendering them generalizable,

studies conducted in samples of breast cancer survivors have found opposing results (21,35,42).

While Janz and colleagues (2011) found that being employed predicted higher FCR, a limitation

of this finding is that FCR was assessed by 3 items developed by the researchers that also

seemingly reflected only the emotional element of Lee-Jones et al.’s (58) formulation of FCR,

with only the internal consistency reported (α = .88). Furthermore, information about the

validity and process of item development was not reported, resulting in an overall limitation of

the psychometric properties for the measure. In other samples of breast cancer survivors,

Freeman-Gibb (42), Lydon (35), and Mast (21) found that FCR was not associated with income

when using valid, reliable, multi-item measures of FCR, however only the measures used by

Freeman-Gibb (42) and Mast (21) appeared to align with Lee-Jones et al.’s (58) formulation of

FCR. In summary, the studies exploring the relationship between employment and/or economic

status had various strengths in terms of their sample size or method of measurement, upon which

their varied results may be dependent.

Skaali et al. (38) found that level of education predicted FCR in testicular cancer survivors.

Similarly, Costanzo (32) found that level of education predicted FCR in breast cancer survivors

20

when using the multi-item, valid and reliable CARS, however van den Beuken-van Everdingen

et al. (15) found no association between these variables when using the same measure.

Similarly, Freeman-Gibb et al. (42), Mast (21), and Thewes et al. (24) did not find an association

between these variables in their samples of breast cancer survivors, however these authors used

various multi-item, valid and reliable measures of FCR that seemingly reflected the

dimensionality of FCR as proposed by Lee-Jones et al. (58).

Mehnert et al. (43) found that lower ‘social class’, defined as level of education, household net

income, and occupational position, was a predictor of FCR as assessed by the FoP-Q-SF.

Although this finding was determined in a sample of mixed-cancer survivors enabling

generalizability, and used the FoP-Q-SF that seemingly reflected the of dimensionality of Lee-

Jones et al.’s (58) conceptualization of FCR, the validity and reliability of the FoP-Q-SF were

not clear, and therefore the conclusions of this study (43) was interpreted with caution.

Collectively, the findings about the associations between employment status, economic status, or

level of education with FCR were contradictory. The varying results may be explained by

different cancer populations, method of FCR measurement, or sample size. These differences

may also be explained by sex, such as the studies exploring testicular and breast cancer survivors

above, although differences in FCR by sex has been disproved (49). In summary, these findings

indicated the need for further assessment of the relationship between economic/employment

status and level of education with FCR in a heterogeneous cancer sample using a valid and

reliable multi-dimensional method of measuring FCR.

4.1.3 Ethnicity or race as predictors of FCR

Cultural socialization may determine health-seeking behaviours, the expression of symptoms,

self-care practices, and the availability of familial supports (92), all of which may be excessive

when a cancer survivor fears a cancer recurrence. In their review of the literature, Meyerowitz et

al. (93) found that ethnicity had a direct impact on socioeconomic status, health and cancer

related cognitions, and had an indirect effect upon adherence behaviours, and cancer outcomes

such as survival and quality of life. Furthermore, cancer patients identified as ethnic minorities

have been found to have higher levels of distress (94). Collectively, these suggest that ethnicity

has an influence upon aspects of living with cancer. Therefore, the relationship between

ethnicity and/or race with FCR was deemed as important to explore.

21

Two studies have specifically set out to explore the relationship between ethnicity or race and

concepts similar to FCR (39,40). Janz et al. (39) explored socio-demographic variables and their

correlation with worry about breast cancer recurrence. The dependent variable, worry about

recurrence, was assessed by 3-items that were developed by the researchers, with only the

internal consistency reported (α = .88) and which seemingly reflected only the emotional

component of Jones et al.’s (58) conceptualization of FCR. Furthermore, information about the

validity and process of item development was not reported, resulting in an overall limitation of

the psychometric properties for the measure. Regression analysis of the data collected from

2,268 breast cancer survivors indicated that ethnicity/race remained a significant predictor of

worry about recurrence, with lowly acculturated Latinas having had the highest levels of worry

about recurrence (39). Although a valid and reliable measure was used to define acculturation in

this large sample, all women who participated in the study were either English or Spanish-

speaking, which limits the generalizability of findings to other ethnic groups.

Similarly, Deimling et al. (40) explored the influence of personal characteristics, such as race, on

cancer-related health worries of long-term cancer survivors. Although race was found to be a

significant predictor using regression analysis, the method of assessing the dependent variable,

cancer-related health worries, was assessed by 4 items that seemingly reflected only the

cognitive and emotional elements of Lee-Jones et al.’s (58) formulation of FCR. However, the

development and psychometric properties of these items (40) are not publically available and

therefore greatly limited the validity of findings.

Although race and ethnicity were found to predict concepts similar to FCR, ethnicity and race

have not been correlated with FCR. Liu et al. (31) and Mellon et al. (49) collected dichotomous

data about race, finding that these variables are not correlated to FCR in cancer survivors when

using the valid, reliable CARS that seemingly reflected only the emotional component of Lee-

Jones et al.’s formulation of FCR (58). Similarly, Llewellyn et al. (46,95) found that FCR was

not related to ethnicity in their sample of head and neck cancer survivors, however FCR was

assessed using a single-item for which the psychometric properties were not stated and which

also appeared to reflect only the emotional component of Lee-Jones et al.’s (58) formulation of

FCR. Another limitation of this finding was that the ethnicity variable was collected as a

dichotomous variable, in which 92% of the subjects were Caucasian (46,95). Collectively, these

findings suggest that ethnicity and race were not correlated with FCR however, data about

ethnicity or race has been limited as a dichotomous variable captured as Caucasian or Other

22

(31,42,46,49), dominated (92-95%) by Caucasian subjects (42,46), and assessed by measures

that appear to regard FCR as a unidimensional construct. This method of data collection and

these sample compositions reduce the generalizability of findings to non-Caucasian populations,

although a single-study found that African Americans had low to moderate levels of FCR (17).

Although FCR researchers may collect data about the ethnicity of their sample, this data is not

always used in multivariate analyses. For example, Meta et al. (45) only used ethnic data to

describe their sample composition, and Bellizzi et al. (20) used ethnicity as a component of their

regression analysis, but did not report the relationship between ethnicity and other data. Both of

these studies had large sample sizes (n=519 and n=730), which would have offered generalizable

findings, had ethnicity been analyzed as a study variable.

In summary, race and ethnicity were deemed as inconsistent predictors of FCR. However, as

suggested by Janz et al. (39), an individual’s level of acculturation has an impact on their level of

worry about recurrence, suggesting that ethnocultural variables do influence FCR. Level of

acculturation has been negatively associated with a number of negative health outcomes (96,97)

and risky health practices (96,98) including reductions in cancer screening (96,98). Collectively,

these findings suggested that further exploration of ethnocultural variables needed to be explored

as predictors of FCR in a heterogeneous group of cancer survivors recruited from a multi-cultural

community.

4.2 Clinical predictors of FCR

Various clinical predictors of FCR had been reported including: 1) physical wellbeing and co-

morbidities; 2) physical symptoms including pain and fatigue; 3) cancer stage or severity of

cancer; 4) type of cancer treatment; and 5) time from diagnosis and cancer treatment. This

research was summarized and critically appraised in the following pages. Correlational evidence

that supported or refuted these relationships were incorporated as available.

4.2.1 Physical wellbeing and co-morbidities as predictors of FCR

A cancer diagnosis and treatment have physiological impacts such as fatigue and pain, but may

also negatively affect a person’s functional ability and physical health (4). Alterations in these

physical states have been found to contribute to poorer psychosocial adaptation (92) and higher

reports of distress (99).

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One study (16) found physical well-being to be a predictor of FCR. Physical well-being has

been defined as “the control or relief of symptoms and the maintenance of function and

independence” (100). In a small sample of thyroid cancer survivors (n=57), Rasmussen (16)

found that physical wellbeing, as assessed by the valid and reliable Functional Assessment of

Cancer Therapy (FACT) scale, significantly predicted FCR. However, FCR was assessed using

a 6-item modified version of the Fear of Recurrence Questionnaire (73) for which the reliability,

validity, nor rationale for item reduction were stated. Furthermore, the included FRQ items are

not clear and therefore the dimensionality of FCR assessment is uncertain. However, Urbaniec

et al. (10) also used the FACT scale to assess physical wellbeing in a sample of gynecological

cancer survivors (n=45), and found that it was not correlated with FCR as measured as a single-

item that appears to capture the cognitive component of Lee-Jones et al.’s (58) formulation of

FCR. Collectively, the findings about overall physical wellbeing as a predictor of FCR were

deemed as inconclusive, based upon small sample sizes and weak methods of assessing FCR.

Two studies have found that the number of co-morbidities that a cancer survivor has predicts

their level of FCR (39,41). Janz et al. (39) and Bergman et al (41) both found that a higher

number of comorbidities predicted a higher level of FCR in a sample of breast cancer survivors

and prostate cancer patients, respectively. Both studies appropriately used multivariate

regression models to assess these relationships, however, the measures used to assess FCR were

not validated to specifically assess FCR. Janz et al. (39) failed to report the validity and process

of item development for the measure that appeared to map onto only the emotional component of

Lee-Jones et al.’s (58) formulation, and Bergman et al (41) used a measure that assessed anxiety

from FCR in which items were seemingly consistent with the cognitive and emotional

components of Lee-Jones et al.’s (58) formulation. Although both of these studies suggest the

importance of the number of co-morbidities on levels of FCR, they both have limitations in their

validity and conceptual assessment of FCR.

4.2.2 Physical symptoms as predictors of FCR

Six studies have found that physical symptoms predict FCR (31,35,38,40,42,43), each having

limitations about the methods used to assess the presence or influence of the symptoms. Liu et

al. (31) assessed the severity of surgical side effects in a sample of breast cancer survivors

finding that more severe surgical side effects at 6- and 24-months post-operatively, predicted

higher levels of FCR at 24-months post-surgery. The researchers (31) developed an 8-item

24

measure to assess surgical side-effects based upon a review of the literature and expert opinion

which suggested the validity of its content, however the validity of the item was not reported. To

assess FCR, 5-items were used: 4-items from the FRI of the CARS, plus an additional item

developed by the researchers to assess perceived risk of recurrence, which collectively seemed to

map onto the emotional and beliefs components of Lee-Jones et al.’s (58) formulation of FCR.

Neither the development nor psychometric properties of this one-item are indicated. Due to the

multi-dimensional nature of FCR, assessing the concept with so few items seeming to not

capture the multi-dimensionality of FCR (58), is a limitation of the findings, as are the

psychometric limitations assessing both concepts.

Lydon (35) also found that physical symptoms predicted FCR among breast cancer survivors.

The researcher originally intended to both capture both the presence of a symptom and the

degree to which the women were distressed by each symptom. However, due to missing data,

the researcher revised the method of assessing physical symptoms to a dichotomous variable

(yes/no) acknowledging the “suboptimal” reliability that resulted (α = .57). Despite the

limitations in the collection of this independent variable, FCR was assessed using the CARS

which had high internal consistency (35), but seemingly only addresses the emotional component

of Lee-Jones et al.’s (58) formulation of FCR.

Among samples of mixed cancer survivors, Deimling et al. (40) and Mehnert et al. (43)

respectfully reported that the number of physical symptoms predicted cancer-related health

worries and fear of progression, concepts similar to FCR. Deimling et al. (40) developed the

measure that was used to capture the number of symptoms that survivors experienced, however,

only the content validity of the measure was alluded to while the psychometric properties of the

measure were not indicated. Furthermore, the development and psychometric properties of the 4

items used to assess FCR are not publically available which collectively weaken the validity of

the findings and pose limitations to the multi-dimensionality of FCR. Mehnert et al. (43) used

the valid and reliable NCCN Distress Thermometer to assess the number of physical symptoms

that the subjects experienced (101,102), however there are limitations to the validity of their

results based upon the unavailable psychometric properties of the short form tool that they used

to assess FCR about which Lee-Jones et al.’s (58) dimensionality of FCR cannot be certain.

Although the above-mentioned studies assessed the presence of physical symptoms, the presence

and interpretation of symptoms by the cancer survivor may be of greater significance to FCR.

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Skaali et al. (38) assessed the impact of ‘severe somatic symptoms’, defined as being ‘a lot

bothered’ by at least one symptom in the past year, upon FCR. Respondents reviewed a list of

symptoms that are commonly reported by cancer patients, summarizing their experience on an

ordinal scale for each symptom. It is unclear about the number of symptoms that respondents

were asked about, the validity of these items, or whether respondents had the opportunity to add

free text about other unlisted physical symptoms. As previously stated, Skaali et al. (38)

assessed FCR by a single-item reflecting unidimensional measurement without its validity

reported, causing a limitation in the multi-dimensional assessment of the concept. Despite these

limitations, the study findings indicated that neurotoxic side effects of treatment and severe

somatic symptoms both significantly predict FCR (38), which contradicts the findings presented

by Llewellyn et al. (46) who failed to find a correlation between the number of symptoms that

survivors related to their cancer and their level of FCR, as also assessed by a single-item and

therefore unidimensional assessment of FCR. The differences in these results may be explained

by the populations from which the samples were derived (testicular versus head and neck cancer

survivors) or by the time period from which subjects were to reflect upon their thoughts of

recurrence. Skaali et al. (38) asked respondents to reflect upon their FCR during the past week,

resulting in a smaller chance of recall bias, and thus more likely to represent an accurate

relationship between the variables.

Although the item that Skaali et al. (38) used to assess symptoms sought the amount of bother

that each provided to a cancer survivor, the cancer survivor’s interpretation of symptoms as a

predictor of FCR has been established in two studies of breast cancer survivors. Freeman-Gibb

(42) assessed symptom attribution, defined as the beliefs that cancer survivors have about a

symptom and its relation to their cancer using the Illness Perception Questionnaire-Revised

(IPQ-R) (103). The IPQ-R has established validity and reliability (103). Freeman-Gibb (42)

found that breast cancer survivors’ symptom attribution predicted FCR where the highest levels

of attribution were correlated with higher levels of FCR as assessed by the multi-dimensional

(58) Fear of Recurrence Questionnaire (73). Similarly, Phillips et al. (104) found that symptom

burden, together with fatigue and risk perception accounted for 33% of the variance in FCR.

However, although the measurement of FCR seemingly captured all elements of Lee-Jones et

al.’s (58) formulation of FCR, FCR was assessed by an adapted cancer worry scale, for which

the psychometric properties are unclear. Collectively, these findings highlight the importance of

26

survivors’ interpretations of a symptom rather than the presence of a symptom, especially since

survivors’ knowledge of recurrence signs and symptoms has not been correlated with FCR (105).

Collectively, there was evidence for a relationship between the survivor’s interpretation of

physical symptoms and their level of FCR. However, this finding may have been limited by

poor or unstated psychometric properties of the items used to assess symptom bother and the few

studies that presented this relationship.

Regarding specific physical symptoms that cancer survivors report, a single study, authored by

Janz et al. (39), found fatigue to be a predictor of worry about recurrence among breast cancer

survivors. A limitation of this finding is that Janz et al. (39) failed to include details about the

development and psychometric properties of the measures developed to assess the concepts, and

that the assessment of FCR appeared to be unidimensional. Although the findings from a single

sample of testicular cancer survivors affirm a positive correlation between fatigue and worry

about recurrence (106), further research relating these concepts was deemed necessary. Further

exploration into this relationship would be of particular interest since both fatigue (107,108) and

FCR (9,10) are paramount concerns for cancer patients and survivors.

Three studies (15,39,43) found pain to be a predictor of FCR. van den Beuken-van Everdingen

et al. (15) and Janz et al. (39) determined this relationship in a sample of breast cancer survivors,

however each study used different methods of assessing the concepts. van den Beuken-van

Everdingen et al. (15) used the valid, reliable, and seemingly unidimensional CARS to assess

FCR whereas pain was assessed using 4-items from the Brief Pain Inventory (BPI). The

rationale for using only 4 of the BPI’s 15-items is not clear, nor are the reliability and validity for

using this measure to assess pain in this population. Although Janz et al. (39) reported the same

predictive relationship between these concepts, neither the development nor validity of the tools

used to assess these variables were reported, and the assessment of FCR appeared to be

unidimensional, resulting in an overall limitation of the psychometric properties for the

measures. In a sample of heterogeneous cancer survivors, Mehnert et al. (43) also used the BPI

to find pain as a predictor of FCR, however the number of items used from the BPI was unclear,

as was the validity, reliability, and dimensionality of the FoP-Q-SF used to assess FCR.

Collectively, there was suggestion that pain was a predictor of FCR, although limitations exist in

the means of measuring these concepts. In studies that have explored concepts similar to FCR,

27

pain also predicted clinically-significant levels of distress (99), uncertainty about cancer

recurrence (106), and was associated with more cancer concerns (109).

The above-mentioned studies have explored a variety of physical symptoms experienced by

cancer survivors and their relationship with FCR. However, due to the heterogeneity of results

and the identified limitations of the literature, further study was deemed as necessary to explore

the influence of physical symptoms upon FCR.

4.2.3 Severity of cancer or cancer stage as predictors of FCR

Three studies found that severity of cancer or cancer stage was a significant predictor of FCR

(19,31,34). In a sample of heterogeneous cancer survivors, Kim et al. (19) found that cancer

severity predicted higher levels of FCR. Although the large sample (n=455) size allows for

generalizability, the methods of measuring each of these concepts have great limitations. FCR

was assessed by a single-item reflecting FCR as a unidimensional concept, for which neither the

validity nor reliability were indicated. The ‘cancer severity index’ that was used to determine

cancer severity, was developed and calculated by the researchers (19) based upon the mortality

rate for the specific type of cancer, the cancer stage, and time since diagnosis. Neither the

validity nor reliability for the cancer severity index were reported. Collectively, the lack of

validity and reliability for the measures in this study cloud the influence of cancer severity upon

FCR, particularly when Mellon et al. (49) reported that cancer stage, a component of cancer

severity index calculation (19), has been found to be not correlated to FCR as measured by the

multi-dimensional (58), valid and reliable Fear of Recurrence Questionnaire (73). These

opposing results, both arising from samples of mixed cancer survivors, may be explained by the

various methods of measuring these concepts that suggested a need for further study.

Among breast cancer survivors, Liu et al. (31) and McGinty et al. (34) found that cancer stage

predicted FCR as measured by, respectively, the 4-item Fear of Recurrence Inventory and an

additional item collectively reflecting the emotional and beliefs components of Lee-Jones et al.’s

(58) formulation of FCR, and the modified Cancer Worry Scale (mCWS) (76) that appeared to

only include the emotional component of Lee-Jones et al.’s (58) formulation of FCR. Other

studies (11,17,24,32) have failed to show any correlation of breast cancer stage with FCR as

assessed by multi-item, valid and reliable, unidimensional (11) or multi-dimensional (30)

measures. Similarly, Bergman et al. (41) found that although PSA levels greater than or equal to

28

10ng/ml significantly predicted higher levels of bi-dimensional FCR, the stage and grade of

prostate cancer did not predict levels of FCR among prostate cancer patients.

Collectively, the literature associating cancer severity or stage with FCR was deemed as

inconclusive, largely due to opposing results and limitations in the psychometric properties and

varying dimensionality of the measures used to assess the concepts. Furthermore, evidence

suggested that FCR was predicted by the type of cancer diagnosis a survivor had (43), although

this finding was limited to a single study. Mehnert et al. (43) explored the FCR, about which the

dimensionality was unclear, of a large sample (n=883) of heterogeneous cancer survivors finding

that a diagnosis of skin, colorectal or hematological cancer predicted the highest levels of FCR.

Due to these inconsistent findings and limitations, further exploration of this relationship was

necessary.

4.2.4 Type of cancer treatment as a predictor of FCR

The three main cancer treatment modalities, surgery, chemotherapy and radiation, had each

received attention as they relate to FCR. Three studies explored the FCR levels of breast cancer

survivors and the type of surgery that the survivors received. Costanzo et al. (32) found that

mastectomy (versus lumpectomy) significantly predicted unidimensional FCR, whereas Liu et al.

(31) found that those who had breast-conserving surgery had higher levels of bidimensional

FCR. Still, Freeman-Gibb (42) found no association between type of surgery and multi-

dimensional FCR.

Similar differences were found among studies exploring the relationships of chemotherapy or

radiation therapy with FCR. Although Liu et al. (31) found that having received chemotherapy

was significantly correlated with FCR that was seemingly cogent with only the emotional

component of Lee-Jones et al.’s (58) formulation, no studies found chemotherapy to be a

significant predictor of unidimensional (31,32) nor multidimensional (42) FCR. In regard to

radiation therapy, a single study (39) found that having received radiation therapy, predicted

higher FCR reflecting only the emotional element of Lee-Jones et al.’s (58) formulation of FCR

in a sample of breast cancer survivors. Of studies that have reported correlations between

radiation therapy and FCR, one (42) had reported a positive correlation between multi-

dimensional (58) FCR and radiation therapy, while others have reported no correlation between

29

radiation therapy and FCR comprised of only an emotional element (31), or as comprised of

cognitive and emotional components (40) of Lee-Jones et al.’s (58) formulation.

Although each of these studies used a valid and reliable instrument to assess FCR, the

inconsistencies of the results and dimensionality of measures used to assess FCR suggested that

further study was needed. Furthermore, the above-mentioned studies were conducted in samples

of breast cancer survivors which may have not been applicable to other cancer populations in

which preliminary evidence exists for a lack of association between type of treatment received

and FCR (38,49).

4.2.5 Time from diagnosis and cancer treatment as a predictor of FCR

The Canadian Association of Psychosocial Oncology (CAPO, 2009) suggests that the diagnosis

and post-treatment phases of cancer are times when survivors are vulnerable to emotional

distress and unmet psychosocial needs (110), such as FCR. Stephens et al. (70) conducted

telephone interviews with a convenience sample of 225 newly diagnosed breast cancer patients

to assess their needs and concerns during the first week after surgery (breast-conserving surgery

vs mastectomy). They found that 39% of the sample identified FCR is a dominant concern,

which represented the most common concern reported in the semi-structured interviews (70).

The stages of cancer were not indicated, and therefore it was unclear if these patients went on to

receive further treatment (e.g. chemotherapy or radiotherapy) which would have clarified how

FCR fits into the overall cancer trajectory. Nevertheless, these findings, as well as the

suggestion by CAPO, highlight the importance of reviewing time from diagnosis and/or

treatment as a predictor of FCR. However, none of the studies that have explored the

relationship between time since diagnosis, treatment, and FCR found time to be a significant

predictor of FCR. Time since diagnosis (11,21,105) and time since treatment have not been

correlated (24,38), or have been negatively correlated (42) with FCR that was assessed as either

a unidimensional (emotional) or multidimensional (58) construct, suggesting that FCR remains

stable or decreases over time. This suggestion corroborates with the findings of Costanzo et al.

(32) and Ghazali (37) who reported that FCR, either as a unidimensional (emotional) or

multidimensional (58) construct, is stable longitudinally. However, all but one (38) of the

above-mentioned studies had been conducted in samples of breast cancer patients/survivors,

limiting the understanding of time since diagnosis and treatment to FCR in survivors of other

types of cancers. To better understand the relationship between time since diagnosis and

30

treatment with FCR, a large study to explore these relationships in a sample of heterogeneous

cancer survivors was needed.

4.3 Psychosocial predictors of FCR

Variables that were found to be significant psychosocial predictors of FCR included: 1)

psychological and emotional; 2) cancer survivor beliefs or perceptions; 3) stress and coping; 4)

relationships; and 5) existential. The articles citing these results have been summarized and

critically appraised in the following pages. Correlational evidence to support or refute these

relationships have been incorporated as available.

4.3.1 Psychological and emotional predictors

Depression and anxiety were the most common psychological variables that were explored in

relation to FCR. Although psychiatric history, defined as a history of depression or anxiety and

current antidepressant use (p.1627), was not a predictor of FCR (32) that seemed to reflect only

the emotional component of Lee-Jones et al.’s (58) formulation of FCR, there was some

evidence for the relationship of various psychological and emotional variables as predictors of

FCR. These will be described below.

Depression was found to be a significant predictor of FCR in four studies (22,31,43,44). Liu et

al. (31) assessed this relationship in a sample of breast cancer survivors, whereas Hodges et al.

(22) assessed head and neck cancer survivors, Pedersen et al. (44) assessed testicular cancer

survivors, and Mehnert et al. (43) assessed mixed cancer survivors. Although the association

between depression and FCR was determined in a variety of cancer survivor populations

permitting generalizability, these studies used FCR measures that seemed to reflect only the

emotional (22,44) or emotional and beliefs components (31) of Lee-Jones et al.’s (58) FCR

conceptualization, or readers are uncertain about which (43) of Lee-Jones’s (58) components of

FCR were assessed. Depression had also shown a lack of correlation with FCR, where readers

aren’t clear of the dimensionality of FCR assessment in a sample of thyroid cancer survivors

(16), or where FCR was seemingly assessed with only the emotional component of Lee-Jones et

al.’s (58) FCR formulation in a sample of breast cancer survivors (15). Also of great concern to

the generalizability of these findings, was that these studies used a number of different measures

to assess these concepts, and the psychometric properties of the depression measures were not

always reported (22,31). FCR, which was seemingly assessed as a composition of Lee-Jones et

31

al.’s (58) cognitive and emotional aspects, had been found to be a predictor of depression (40)

which may have suggested a reciprocal relationship between the concepts.

Lazarus (111) cited anxiety as an emotion resulting from ambiguity, when information about a

situation is lacking. Overall anxiety had been found to predict FCR in three studies (22,31,37),

whereas trait anxiety, referred to as a stable personality trait consisting of feelings of

apprehension, tension and increased autonomic nervous system activity (112), predicted higher

FCR in a single study (105). Of great concern to the generalizability of findings, was that each

study used a different measure to assess anxiety, and the psychometric properties of the measures

were not reported in some articles (31,37). However, since measures that seemingly captured all,

or both the emotional and beliefs components, of Lee-Jones et al.’s (58) formulation of FCR

were included among those relating anxiety and FCR, strengthen the understanding between

these concepts.

General measures were also used to assess psychological and emotional predictors of FCR.

Mehta et al. (45) used the RAND 36-item Health Survey (SF-36) to find that mental health

subscale scores, which assessed anxiety, depression, loss of behavioural or emotional control,

and psychological well-being (113), predicted FCR in a sample of prostate cancer survivors.

Similarly, Urbaniec et al. (10) used the Functional Assessment of Cancer Therapy – General

measure (FACT-G) to find that the emotional and functional wellbeing subscales scores

significantly predicted FCR in a small sample (n=45) of gynecological cancer survivors.

Although the findings published by Mehta et al. (45) and Urbaniec et al. (10) add strength to the

suggested relationship between psychological and emotional characteristics and FCR, limitations

existed in the reporting of the psychometric properties of the tools used to assess the variables.

For example, Urbaniec et al. (10) used a single-item from the Cancer Survivors Unmet Needs

Measure (CaSUN) to assess FCR that seemingly mapped onto the cognitive component of Lee-

Jones et al.’s (58) formulation of FCR, but the validity of this item as a measure for FCR was

unstated. Similarly, Mehta et al. (45) did not report the psychometric properties for either the

SF-36 nor the measure of FCR, but instead relied on other sources for this information (45)

which leaves readers unclear about which of Lee-Jones et al.’s (58) components of FCR were

assessed. According to Barnes et al. (114), the belief that reliability is a property of a specific

measure is erroneous, so researchers should assess and report reliability for their own data.

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Optimism, defined as a general expectancy for a positive outcome (115), was found to predict

FCR in two studies (40,46). Llewellyn et al. (46) found that head and neck cancer survivors who

had lower optimism prior to their treatment predicted higher FCR 6-8 months after treatment was

complete. A great limitation of this study was that FCR, which had previously been described as

a multi-dimensional concept (11,30,58,59), was measured using one-item from the Worry of

Cancer scale (77) that appeared to address the emotional component of Jones et al.’s (58)

formulation of FCR, without the validity, reliability, nor rationale for using this item stated.

Although the longitudinal nature of Llewellyn et al.’s (46) study adds rigor to its design, the

trajectory of a cancer diagnosis and treatment has been recognized as a period of adjustment that

causes changes in the person’s ability to manage, learn and adapt to life circumstances (116).

Therefore, assessing optimism prior to treatment, without a corresponding assessment post-

treatment, may not have provided comprehensive insight about its influence on FCR. Deimling

et al. (40) provided insight into this relationship after cancer treatment was completed, finding

that optimism was a significant predictor of FCR among a sample of heterogeneous long-term

cancer survivors. However, as previously indicated, a great limitation of Deimling et al.’s (40)

study is that the development and psychometric properties of the 4-items used to assess FCR are

not publically available, although results suggest that the measure may capture the cognitive and

emotional components of Lee-Jones et al.’s (58) formulation. Therefore, the validity of the

evidence to support optimism as a predictor of FCR was limited by the methods used to assess

FCR although the construct validity of valid and reliable measures of the concepts has been

established (15). In sum, further exploration of optimism as a predictor of FCR in cancer

survivors was warranted.

While optimists hold positive expectancies for their future, pessimists have a more negative

outlook. Pessimism has been identified as a characteristic of neuroticism (115), which was been

found to predict FCR in a single study (38). Skaali et al. (38) used 6-items from the Eysenck

Personality Questionnaire (EPQ) to assess neuroticism in a sample of testicular cancer survivors.

The rationale for only using these 6 items was not stated, nor was their validity for assessing

neuroticism. The alpha for the neuroticism measure used in the study was .72, which may be

acceptable, but may be less than acceptable in such a large sample size (117). Furthermore, FCR

was assessed using a single-item addressing only the emotional element of Lee-Jones et al.’s (58)

formulation, without its development, validity, nor reliability stated. Therefore, the existent

33

literature had major limitations in the conceptualization and psychometric properties of the

instruments used to assess the relationship between neuroticism and FCR.

4.3.2 Cancer survivor beliefs or perceptions

Seven studies found nine different general or cancer-related beliefs or perceptions of cancer

survivors predicted their level of FCR. The beliefs or perceptions that had been explored vary

widely, as did their means of assessing these beliefs or perceptions and FCR.

Two studies assessed breast cancer survivors’ perceptions about their risk of recurrence (31,36).

In addition to assessing an emotional component (58) of FCR, both Ziner et al. (36) and Liu et al.

(31) assessed ‘perceived risk of recurrence’ using a single question about the likelihood that the

person would have cancer again in the future, where responses were collected on either a

categorical or continuous scale. In this way, both studies captured FCR as comprised of

emotions and beliefs, although the cognitive component of Lee-Jones et al.’s (58) formulation

did not appear to be addressed. In Ziner et al.’s (36) cross-sectional study, higher perceived risk

of recurrence resulted in higher fears of recurrence when using the valid and reliable CARS to

assess FCR. Although Liu et al. (31) also assessed perceived risk of recurrence, the researchers

went onto compare this perceived risk with 10-year risk of recurrence data from clinical trials, as

well as the widely available web-based resource, Adjuvant! Online (31,118). Liu et al. (31)

found that those who overestimated their risk of recurrence at 24- months post diagnosis had

higher FCR at that time than those who underestimated their risk of recurrence. As previously

mentioned, a limitation of Liu et al.’s (31) study is the use of the 4-item FRI, which is the first

section of the CARS that evaluates the magnitude of FCR (57), which on its own may reduce the

complexity of the concept. Regardless, these studies suggest the significant impact that patient

perceptions about their risk of recurrence have upon their FCR. This, in addition to the few

number of breast cancer survivors who accurately perceive their risk of recurrence (118),

suggested that a better understanding was needed about the FCR that survivors experience.

Six other various beliefs or perceptions were found to predict FCR, and the methods of assessing

FCR were widely varied among studies. Four of these six studies used assessments of FCR with

major limitations (44,45,47). Pedersen et al. (44) found that testicular cancer survivors’ belief

that their own psychological stress caused their cancer predicted higher levels of FCR, however

FCR was assessed by a single-item which regarded FCR as a unidimensional construct. Rabin et

34

al. (47) found that breast cancer survivors who interpreted their disease trajectory as either

chronic or cyclic, had significantly higher FCR than survivors who viewed the disease as acute,

however the method of assessing FCR seemed to capture only the emotional and cognitive

components of Lee-Jones et al.’s (58) formulation of FCR. Mehta et al. (45) found that the

general health perceptions, or the belief in one’s current and/or future state of health, predicted

the FCR of prostate cancer survivors. FCR was measured by 5-items for which the validity and

reliability in the sample are unstated, and for which readers are unclear about the conceptual

development of the items. Finally, Corter et al. (88) found that breast cancer survivors who more

strongly believed in the necessity of taking their prescribed Aromatase Inhibitors had higher

FCR as assessed by 4 of the 5-items on the Worry of Cancer Scale (88) which seemingly

represent the cognitive and emotional elements of Lee-Jones et al.’s (58) FCR formulation,

however the validity of the items were not stated.

The remaining three studies that found a variety of survivor beliefs or perceptions to be

predictors of FCR used a valid and reliable measure of FCR. Freeman-Gibb (42) and Ziner et al.

(36), respectfully, found that breast cancer survivors who attributed any symptom as a cancer

recurrence, and those who were reminded of the cancer experience, had significantly higher

FCR. The measures used to assess these independent variables had established validity and

reliability (36,42), however, only the Fear of Recurrence Questionnaire (FRQ) used by Freeman-

Gibb (42) appeared to be largely cogent with Lee-Jones et al.’s (58) formulation of FCR,

whereas the CARS used by Ziner et al. (36) seemingly only reflected the emotional component.

Although the independent variables addressed the negative outlooks of the cancer survivor,

beliefs or perceptions with positive attributes had also been found to predict FCR. Ziner et al.

(36) found that breast cancer survivor self-efficacy significantly predicted FCR, indicating that

those with the highest levels of confidence to deal with concerns related to cancer and its

treatment had the lowest levels of fear. Similarly among hematological cancer survivors, Black

et al. (48) found that those with a higher sense of coherence, briefly defined as “a global

orientation that expresses the extent to which one has a feeling of confidence” (119), predicted

lower FCR. Collectively, these findings suggested the negative influence of negative type

beliefs or perceptions, and alternatively the positive influence of positive-type beliefs or

perceptions upon cancer survivors’ FCR, although the dimensionality of FCR measurement used

in these studies were varied.

35

The concepts of beliefs and perceptions of cancer survivors may be equated with what

Leventhal’s Common-sense Model (120) refers to as “Illness Representations”, or making sense

of an illness experience (p.142). Freeman-Gibb (42) and Corter et al. (88) explored the

relationship between illness representations and FCR, respectfully finding that the emotional

representations and illness representations of breast cancer survivors significantly predicted their

level of FCR. The independent variables were assessed using the Illness Perception

Questionnaire-Revised (IPQ-R) (42,103) and the Brief Illness Perception Questionnaire (BIPQ)

(88,121), which are both appropriate to assess these variables. Furthermore, the IPQ-R and the

BIPQ had both demonstrated reliability and concurrent validity, allowing the findings of these

studies to be easily compared. However, variation lies in the assessment of the dependent

variable. Freeman-Gibb (42) assessed FCR by the valid and reliable multi-dimensional (58)

FRQ, whereas Corter et al. (88) assessed FCR using 4 items from the Worry of Cancer scale

(77), which as previously indicated, seemingly only captured the cognitive and emotional

elements of Lee-Jones et al.’s (58) formulation of FCR. Although the selected items from the

Worry of Cancer scale (77) were identified and their alpha reliabilities were appropriate (α=.81),

the rationale for their selection and validity were not stated. Furthermore, concerns about the

multi-dimensional assessment of FCR continued to exist.

Although these studies added strength to the collective evidence relating the beliefs or

perceptions of survivors and their level of FCR, the research linking survivor beliefs and

perceptions to FCR had largely been conducted in breast cancer samples, limiting the

generalizability of findings. Furthermore, the number of beliefs and perceptions that had been

explored were many, and the tools that were used to assess the concepts varied accordingly.

Therefore, further research about the influence of cancer survivors’ beliefs and perceptions on

their level of FCR was needed in order to generalize the findings.

4.3.3 Stress and coping

Stress and coping had variably been explored in relation to health. In the theoretical literature,

stress had been reviewed as a response to a stimuli, as the stimuli to which the person responds,

or as a transaction between the person and their environment (122). Stress had been

demonstrated as a major contributor of 30-60% visits to health care practitioners in the absence

of disease (122), suggesting the significance of its negative impact upon the individual. Coping,

as viewed by Lazarus et al. (123), involves managing a stressful situation that can be achieved

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using a variety of methods. Both stress, and to a greater degree coping, have been explored as

predictors of FCR the oncology literature.

Among testicular cancer survivors, Skaali et al. (38) found that cancer-related stress, defined as a

person’s psychological response to the cancer experience, predicted FCR as assessed by a single

item with unstated validity and reliability and appeared to capture only the element of Lee-Jones

et al.’s (58) formulation of FCR. Cancer-related stress was assessed using the Impact of Events

Scale (IES), which has demonstrated validity and reliability in a variety of conditions (124),

however its use in cancer research is limited and its psychometric properties have been

inconsistently reported. Furthermore, the IES had been accused of being an obsolete measure

(124,125) of Post-Traumatic Stress Disorder (PTSD) containing only the subscales of Intrusion

and Avoidance, since evidence exists for the addition of hyper-arousal as symptom cluster in

PTSD (125). Therefore, the Impact of Events Scale – Revised (IES-R), which includes the 3

subscales of Intrusion, Avoidance and Hyper-arousal, may more comprehensively capture the

assessment of stress of cancer survivors and its relationship with FCR. Recognizing this,

Urbaniec et al. (10) used the 22-item IES-R to assess post-traumatic stress in a sample of

gynecological cancer survivors. PTSD had a significant positive correlation with FCR, but this

significance did not persist into regression analysis (10). A limitation of the study published by

Urbaniec et al. (10) was that FCR was assessed by a single-item derived from the Cancer

Survivors Unmet Needs measure (CaSUN) without the validity of the item reported and which

appeared to capture only the cognitive component of Lee-Jones et al.’s (58) formulation of FCR.

In summary, there was suggestion for the significance of stress symptoms upon FCR, although

the evidence was deemed as preliminary.

Two studies (35,42) found that various methods of coping, using the Brief COPE (126),

predicted FCR as measured by a valid and reliable tool, although the means of assessing FCR

differed. Lydon (35) used the CARS which seemingly addressed only the emotional component

of Lee-Jones et al.’s (58) formulation where Freeman-Gibb (42) used the Fear of Recurrence

Questionnaire (FRQ) which appeared to be largely cogent with Lee-Jones et al.’s (58)

formulation of FCR. An obvious limitation of these findings was that they had been found only

in samples of breast cancer survivors, leaving a gap in the generalizability of understanding

coping and FCR in non-breast cancer survivors. However, the findings of the studies can be

easily compared since both have been conducted in the same population, and both used the 28-

item Brief COPE to assess coping behaviours. The Brief COPE (126) assesses 14 different

37

coping behaviours that are comprehensive and brief. The validity of the Brief COPE has been

established (126) but the reliability of some of the subscales in breast cancer samples had been

low, ranging from α=.48-.98 (42). Due to this low Cronbach alpha, Freeman-Gibb (42)

conducted a factor analysis uncovering four-factors comprised of 24-items from the Brief COPE.

The result was “improved” (p.68) reliabilities (α=.53-.82) that were used in the regression

analysis (42). However, readers are unclear about which 24-items were retained from the 28-

item Brief COPE measure, and therefore cannot be sure of its continued validity. Freeman-Gibb

(42) indicated that cognitive coping, which includes “seeking emotional support and comfort

from others” (p.68), predicted FCR through a positive correlation. These results suggested that

the more these behaviours are carried out by cancer survivors, the higher their FCR would be.

Lydon (35) also divided the Brief COPE into two factors, Active Coping and Escapist Coping,

based upon the factor analysis conducted by Bellizzi et al. (127). Lydon (35) clearly indicated

which of the Brief COPE’s subscales were used in each factor, concurring with Bellizzi et al.

(127) that the humor subscale did not appropriately fit into either factor (35). Lydon’s (35)

results indicated that active coping strategies (self-distraction, active coping, seeking emotional

and instrumental support, venting, positive reframing, planning, acceptance, and religion) and

escapist coping strategies (self-blame, denial, behavioural disengagement, and using drugs and

alcohol) predicted FCR. Positive correlations were found between these styles of coping and

FCR, although the escapist strategies achieved a higher correlation of greater statistical

significance. Collectively, the results presented by Freeman-Gibb (42) and Lydon (35) clearly

indicated the significance of coping strategies upon a survivors’ FCR where the unhealthy

strategies were more likely to result in higher fears. However, limitations about the methods of

measuring the variables and the generalizability of findings beyond breast cancer samples needed

to be acknowledged.

Another 2 studies (34,78) determined that coping predicted FCR, however the Brief COPE (126)

was not used to assess coping in these studies. McGinty et al. (34) explored the interactions of

coping, operationalized by measures of self- and response-efficacy (34), with other variables and

their collective influence on the levels of FCR among a sample of breast cancer survivors

(n=157). High threat appraisal, defined by scores of perceived vulnerability and perceived

severity of a cancer recurrence, combined with low coping appraisal, defined by scores of diet

self-efficacy, exercise self-efficacy, diet response efficacy, and exercise response efficacy,

predicted the highest levels of FCR (34). In other words, the breast cancer survivors who

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anticipated a health threat and also perceived that there were few protective factors to help them

reduce their risk of the threat had the highest levels of FCR. Although these findings are

consistent with Leventhal’s Common-Sense Model upon which the relationships of the study

variables were explored, the researchers used 4-items from the Cancer Worry Scale (CWS) to

assess FCR, which seems to regard only the emotional component of Lee-Jones et al.’s (58)

formulation of FCR. The rationale for selecting these 4-items was not stated, nor the validity of

the items in measuring FCR stated, both limiting the interpretability of the findings.

Conceptually similar to FCR is the Fear of Progression (FoP) defined as (59) the “fear that the

disease will progress with all its consequences” (p.506). The Fear of Progression Questionnaire

(FoP-Q) was developed in a sample comprised of patients with cancer, inflammatory rheumatic

diseases, or diabetes mellitus (59), and although a conceptual framework was not used to develop

the tool’s items, they seemed to align with each component in Lee-Jones et al.’s (58) formulation

of FCR. Mehnert et al. (78) used the short form of the FoP-Q in a sample of breast cancer

survivors finding that depressive coping, active problem-oriented coping, intrusion, avoidance

and hyper-arousal each significantly predicted FoP. The Dealing with Illness Inventory (128)

was used to assess coping in this study. Although the entire sample of breast cancer survivors

were greater than 2 years post-diagnosis, it was unclear how many were currently receiving any

cancer-related treatment, leaving readers to question the appropriateness of measuring fear of

progression versus fear of cancer recurrence. Furthermore, readers are unclear about which

(FoP-Q) (59) items were adopted in this short form and therefore cannot be certain about which

of Lee-Jones et al.’s (58) commonly accepted dimensions of FCR were included. However,

these findings add to the suggestion that types of coping predict higher FCR although findings

were cautiously interpreted due to limitations in the methods of measuring the concepts.

4.3.4 Relationships

Some of the suggested predictors of FCR were grouped into a category that encompassed the

relationships within which cancer survivors engage. Oncology-based practice guidelines suggest

that clinicians assess the relationships of their patients and offer appropriate resources as

interventions to support relationships (5,101,110). Offering such interventions may also affect

the patient’s perception of the quality and amount of health care provider communication, which

was found to positively and directly affect breast cancer patients’ thoughts about recurrence

(129). However, research had also indicated that neither the degree of familial social support nor

39

family hardiness were correlated with FCR (49), suggesting that FCR was influenced by the

survivors’ perception of their social network, rather than the presence of the network. Adding to

this suggestion was the results of another study that used an FCR measure aligned with Lee-

Jones et al.’s (58) FCR conceptualization, whereby FCR was predicted survivors’ perceptions of

spousal communication about cancer (50). Similar findings, albeit using FCR measures that did

not fully map onto Lee-Jones et al.’s (58) FCR conceptualization, found no association between

FCR with marital status (31) or living alone or with a partner (15), but instead that FCR was

predicted by the survivors’ perceptions of their social support (31). As such, it was important to

review the results of the studies that have explored the relationships of cancer survivors and their

influence on the survivor’s level of FCR.

Three studies (41,43,49) found various relational characteristics of cancer survivors predicted

their level of FCR. Mellon et al. (49) explored the factors associated with FCR and whether

survivors and their family caregivers influenced each other’s FCR as measured by the valid and

reliable Fear of Recurrence Questionnaire (FRQ) which appeared to be largely cogent with Lee-

Jones et al.’s (58) formulation of FCR. Within a mixed-cancer sample, results demonstrated that

survivors’ FCR was predicted by the family member’s FCR, as well as the amount of concurrent

family stress (49). These findings suggest that a high level of emotional involvement in

relationships has a great impact on the survivors’ FCR. Bergman et al. (41) found similar results

whereby the partnership status of men undergoing treatment for prostate cancer predicted their

level of FCR, as determined by the FCR subscale of the valid and reliable Memorial Anxiety

Scale for Prostate Cancer (MAX-PC) (130) which was seemingly consistent with the cognitive

and emotional components of Lee-Jones et al.’s (58) FCR formulation. In this study, men who

were living with a spouse/partner or who were in a significant relationship but not living

together, had significantly lower FCR than men who were not in a significant relationship (41).

These results suggested a protective effect in the patient’s determination of a significant

relationship.

The third study that explored the influence of relationships upon survivors’ FCR was conducted

by Mehnert et al. (43) in a mixed-cancer sample. Lower levels of social support and higher

amounts of detrimental social interactions, characterized by over-protective behaviour,

dismissive, conflictual behaviour patterns and pessimism (43), predicted higher levels of FCR

(43). The social support and detrimental social interaction variables were collected using the

Illness-Specific Social Support Scale (ISSS) (131) which has demonstrated reliability and

40

validity in samples of hematological cancer patients (132,133). Although the literature failed to

detail how social support was captured, studies using the tool indicate that it was the patient’s

perceptions of support that was collected (132,133). This finding corroborated with those

previously discussed in that the patient’s perceptions of their social support was likely of greater

influence on FCR rather than the number of supports. Similarly, detrimental social interactions,

were understood to be destructive to relationships and therefore negatively affected patient’s

perceptions of their relationships. Of great concern is Mehnert et al.’s (43) use of the short-form

Fear of Progression Questionnaire (FoP-Q) (59) about which readers are unclear about which

(FoP-Q) (59) items were adopted and therefore cannot be certain about which of Lee-Jones et

al.’s (58) commonly accepted dimensions of FCR are included.

Collectively, these findings indicated the influence that significant supportive relationships can

have upon a survivor’s FCR, particularly survivors’ perceptions of the quality and quantity of

their relationships. However, the methods of assessing social support varied greatly and did not

necessarily seek the patient perceptions of their social support.

4.3.5 Existential considerations

Cancer survivors have expressed their cancer experience as spiritually transformative (134) and

many have used spiritual and religious strategies to cope with cancer (135). Spirituality, which

should not be equated with an outward expression of religion, does not have a universally

accepted definition (134). However, commonalities exist among the definitions, such as finding

connection, direction, transcendence, meaning and purpose (134). Three studies found various

existential aspects to be predictors of FCR.

In her doctoral dissertation, Lydon (35) examined the influence of spirituality on the

psychological distress, including FCR, among breast cancer survivors. Using valid and reliable

measures to assess the outcome variables, where the FCR seemingly only addressed Lee-Jones et

al.’s (58) emotional component of FCR, results indicated that spirituality was a predictor of FCR.

Lydon (35) went onto suggest that spirituality may form a type of framework from which

survivors can establish meaning from their cancer experience (35). Similarly, Mellon et al. (49)

found that cancer survivors who reported a more positive meaning in their cancer experience had

significantly less FCR as determined by a measure consistent with Lee-Jones et al.’s (58)

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formulation of FCR. Collectively, these studies suggest the importance of spiritual resources in

reducing the FCR that cancer survivors experience.

Stanton et al. (33) conducted a longitudinal study assessing the predictors of psychological

adjustment, including FCR, to breast cancer at 3- and 12-months post-surgery. Prior to the

participant’s surgery, the researchers (33) assessed the various coping processes used by the

patients, one of which was turning to religion, which as outlined above, may represent an

outward expression of spirituality (134). Collecting the independent variable data prior to

diagnostic surgery may be a limitation of this study, since coping mechanisms may have changed

over the course of post-operative cancer treatment. It may have been useful to know if baseline

data remained accurate at the time when the dependent variable data was collected. Results of

this study (33) indicated that the interaction of turning to religion and hope predicted FCR at 12-

months post-surgery. In other words, turning to religion was most useful for women with the

lowest levels of hope, and turning to religion was the least useful for women with the highest

levels of hope. Other limitations of this study include the use of a “shortened” 6-item Fear of

Recurrence Questionnaire, for which the validity, dimensionality, nor rationale for using a

shortened version of the original valid, reliable and multi-dimensional 22-item FRQ are stated.

Acceptable reliability was reported (α= .76 and .87). Despite the identified limitations, the

existing research collectively suggested the importance of spirituality and spiritual practices in

predicting cancer survivors’ FCR.

4.3.6 Healthcare resources

One study found that ease of understanding information, better management of symptoms, and

more coordinated care were each significant predictors of FCR (39). However, Janz et al. (39)

developed and used a 3-item scale to assess FCR without stating the validity of these items

which raises questions about the multidimensionality of the outcome measured. No other studies

explored healthcare factors as predictors of FCR. However, one study explored FCR as a

predictor of the quantity of health care resources used by cancer survivors. Lebel et al. (25) used

the multi-item, multi-dimensional (58), valid and reliable FCRI to assess FCR among a sample

of mixed-cancer survivors. They found that higher FCR significantly predicted the number of

outpatient clinic visits made by cancer survivors, as well as the number of ER visits when

controlling for relationship status and education level (25). A limitation of the study is that

information about the participants’ co-morbid conditions was not collected, which may have

42

accounted for their increased healthcare utilization. However, these findings corroborate with

the results of Thewes et al. (24) which found a positive association between FCR, as assessed by

the FCRI founded upon Lee-Jones et al.’s (58) formulation, and unscheduled visits to General

Practitioners, conducting self-examinations, and the amount of complementary therapy used

(24), and add clarity to the influence of treatment satisfaction upon FCR (18). Collectively, these

findings suggested that those with higher FCR use more health care resources, strengthening the

implications for early identification of patients at risk for clinically-significant FCR.

5 Mediators of Fear of Cancer Recurrence

In distinguishing the characteristics of mediating variables, Baron et al. (51) indicate that a

mediating variable must have an established relationship between itself and the predictor

variable, as well as itself and the outcome variable. Mediators may be either full or partial,

which is determined by exploring the significance of correlations between the variables (51). In

the case of full mediation, the dependent variable is significantly correlated with the independent

variable, but then loses this statistical significance when the mediator is introduced (51).

However, partial mediation occurs when both the relationship between the independent and

dependent variable is significant as well as among the mediating relationship (136). Three

studies have found six statistically significant mediators of FCR assessed in breast cancer

samples. These studies are summarized and critically appraised in the following pages.

Correlational evidence for the support or refute of these relationships has been incorporated as

available.

Self-efficacy, defined as the belief in one’s own ability to control challenging demands from

their surroundings by taking action enabling adaptation (137), has been found predict FCR as

determined by the CARS. Ziner et al. (36) reported that breast cancer survivor self-efficacy was

a significant partial mediator of the relationships between FCR and age, perceived risk of

recurrence, trait anxiety and breast cancer reminders. These results were determined in a sub-

sample of a larger study in which the Breast Cancer Self-Efficacy scale was developed and

construct validity confirmed using structural equation modeling (36). No details are provided

about this larger study nor is the convergent validity of the measure with other self-efficacy

measures stated. Furthermore, readers are unclear about the rationale for this new scale

development, adding to the criticism of the measure used. Although the relationship between

breast cancer self-efficacy and FCR was significant, breast cancer self-efficacy only explained

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3% of the unique variance of FCR (36) which was assessed using measures and items consistent

with Lee-Jones et al.’s (58) emotional and belief components of FCR. This contribution may be

more indicative of the small magnitude of the relationship, particularly since McGinty et al. (34)

found that diet self-efficacy and exercise self-efficacy each failed to find an association with

FCR, that appeared to address only the emotional component of Lee-Jones et al.’s (58)

formulation, in breast cancer survivors.

As previously discussed, Lydon (35) reported that active coping and escapist coping are

predictors of higher FCR, which were also found to be mediators between physical health and

FCR. More specifically, active coping strategies, comprised of the Brief COPE’s self-

distraction, active coping, using emotional and instrumental support, venting, positive reframing,

planning, acceptance, and religion subscales, was found to be a partial mediator between

physical health and FCR. In other words, the impact of health upon FCR was equivalent with

and without active coping strategies as a mediator. On the other hand, escapist coping strategies,

comprised of the Brief COPE’s denial, behavioural disengagement, self-blame, and substance

use subscales, was found to be a full mediator between physical health and FCR (35). In other

words, the statistically significant correlation between physical health and FCR failed to

maintain this statistical significance when the escapist coping variable was introduced. This full

mediation suggests that poorer physical health influences the escapist coping strategies used by

breast cancer survivors that resulted in higher FCR, whereby the FCR measure seemingly

mapped only the emotional component of Lee-Jones et al.’s (58) formulation. Although the

utility and psychometric properties of the Brief COPE were adequately explained, the

measurement of the physical health variable may have several limitations. Lydon (35) defined

the physical health variable as a composite variable comprised of 4 measures: the Symptom

Checklist that assessed breast symptoms, the Performance 10 subscale of Medical Outcomes

Study SF-36 that assessed physical functioning, the Functional Assessment of Cancer Therapy

Fatigue subscale that assessed fatigue, and the Menstrual and Gynecological History

questionnaire that assessed hot flashes (35). Limitations of this composite measure exist in the

poor reliability (α=.57) of the measure used to assess breast symptoms, as well as the unstated

validity and reliability of the measure used to assess hot flashes. As a result of these limitations

of the stated measures, these mediating results were interpreted cautiously.

Janz et al. (39) found that low acculturation, younger age, employment, more pain and fatigue

and radiation therapy were partial mediators of the relationship between socio-demographic,

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clinical, and treatment factors and level of FCR, whereas the number of comorbidities fully

mediated this relationship. However, this interpretation requires further validation based on the

limitations of the measures used to assess the variables. Specifically, the measures used to assess

the mediating variables had moderate levels of alpha reliability (α=.65-.697), with only the face

validity of some of the items discussed. Furthermore, FCR was assessed in a 3-item scale

reflecting only the emotional component of Lee-Jones et al.’s (58) formulation, without the

validity of the items considered. Therefore, the results of this study proposed interesting

relationships among the variables, however further study among the concepts was warranted.

Although the studies exploring the mediators of FCR have explored the concept using multi-

dimensional (58) measures of FCR, the literature is limited to three studies exploring mediation

as related to FCR. All of these studies were conducted in samples of breast cancer survivors,

which may be erroneously transferred to other samples of cancer survivors. Of greater concern,

is that the measures used to assess FCR did not clearly map onto the multi-dimensional

conceptualization of FCR proposed by Lee-Jones et al. (58). Furthermore, limitations exist with

the measures used to assess the independent variables which suggest that further research was

needed to explore the mediators of FCR.

6 Statement of the Problem

Similar to the findings reported in systematic reviews (53–55), the current review found that

FCR is a major concern for cancer survivors however prevalence rates among studies remain

widely varied. The diverse prevalence rates of FCR may be explained by the use of single-item

or multi-dimensional (58) measures to assess this complex psychosocial issue suggested to be

comprised of a number of dimensions (11,30,58,59) (see Chapter 3 Section 1.0 for additional

details). Also contributing to the varied prevalence rates could be the lack of consensus about

how to define and therefore report what level of FCR on any given measure should be counted

toward prevalence. Clarifying the magnitude of this issue is important for clinicians to be able to

identify patients at highest risk of FCR in order to provide them with appropriate educational

resources or referrals to interventions to help cope with or reduce their FCR.

The negative impact of the outcomes associated with FCR support the importance of early

identification of cancer patients and survivors at highest risk of developing clinically-significant

FCR. Although a preliminary understanding about the predictors and mediators of FCR is

available from the reviewed empirical literature herein and supported by systematic reviews (53–

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55), a number of limitations have been identified. As described in the previous sections, the

overall literature about FCR is dominated by samples of breast cancer survivors, limiting the

generalizability of these findings to survivors of other cancers. Of greater concern, is the lack of

clarity about how the FCR measures identified herein map onto Lee-Jones et al.’s (58)

formulation of FCR. Although the dimensionality of various measures have been suggested by

this reviewer of the literature, these conclusions should be deemed as speculative. As such, these

conclusions require further examination and discussion beyond this paper.

Most of the research exploring the predictors and mediators of FCR has focussed on the

modifiable state-like factors of the cancer survivor and overlooked the stable demographic,

clinical, and individual traits. The results of recent systematic reviews (54,55) concurred with

this finding, indicating that weak or inconclusive evidence exists for the association between

FCR and socio-demographic and cancer-related factors. The influence of these stable factors

upon the FCR of cancer survivors is important to understand, since they could identify groups at

high-risk for clinically-significant FCR. This information is useful for clinicians to identify

cancer survivors who would benefit from preventative interventions to cope with or reduce their

level of FCR as they transition into post-treatment survivorship.

6.1 Significance of the study

Cancer survivors have indicated that they want help to cope with their fears of the cancer

returning (8,9). The current literature review identified that there were empirical inconsistencies

among the reported prevalence, predictors and mediators of FCR, which was similarly reported

in systematic reviews (53–55). Clarifying such inconsistencies was an overarching goal of the

current study, findings of which can support care improvements for this population. In

alignment with this goal, an accurate understanding about the magnitude of FCR in cancer

survivors was initially sought. Only recently had a multi-dimensional (58) measure with a valid

and reliable cut-off to detect clinically significant FCR been established (30,138) and therefore

available and appropriate to use. This was the first study in the oncology literature to use a

multi-dimensional (58) tool that has a valid and reliable clinical cut-off score to specifically

determine the prevalence of FCR in a large Canadian sample of mixed cancer survivors.

Furthermore, this study was the first to be conducted in a multi-cultural Canadian context, with

access to a large repository of cancer survivors.

46

The findings of this study was intended to differ from previous research in that it used valid and

reliable instruments to assess theoretically and empirically-derived predictors and mediators of

FCR. It was anticipated that the findings generated from this study would uniquely contribute to

the scientific literature by clarifying the inconsistently reported relationships of stable, trait-like

characteristics upon the cancer survivor’s FCR. It was anticipated that these findings would

enable clinicians to identify cancer survivors having characteristics (referred to as predictors

herein) that predispose them to the greatest risk of clinically-significant FCR. Early

identification of such high-risk survivors would allow for earlier education and/or referral to

appropriate interventions to help cope with FCR. A more novel intent of this study was that it

was expected to fulfill an unstudied area of FCR literature: theoretically-based modifiable

characteristics that mediate FCR (see Chapter 3 Section 5.0 for additional details).

Theoretically-based and empirically-supported mediators of FCR could be particularly useful to

develop interventions that effectively support survivors to cope with their FCR. Collectively,

these findings were expected to be of great use to policy-makers to direct the allocation of

healthcare resources, such as additional educational resources for clinicians and survivors to

cope with or reduce their level of FCR.

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Chapter 3 Conceptual Framework

1 Background

Although, as outlined in Chapter 2, FCR has received a great deal of empirical attention, there

are only 2 published papers that have attempted to describe FCR conceptually (58,139). The

most commonly cited is that of Lee-Jones et al. (58) who in 1997 reviewed the existent empirical

literature, available FCR measures, and theoretical perspectives that were useful to describe

FCR. Largely borrowing from Leventhal’s Common-Sense Model of Self-Regulation (CSM)

(140–143), Lee-Jones et al. (58) claimed that FCR was dependent upon one’s illness

representation, which Leventhal describes as how one ‘makes sense of’ their condition (120).

Based upon their analyses of the components in FCR measures and empirical understanding of

FCR, and incorporating elements of other relevant theories, Lee-Jones et al. (58) went onto

propose that FCR was comprised of a number of cognitions, beliefs and emotions, and that a

number of possible consequences of FCR existed. Recognizing the continued elusiveness of a

theoretical formulation of FCR, in 2016 Fardell et al. (139) conducted an updated review of

theories used to understand FCR, and presented a novel theoretical framework of FCR which

synthesized some of these theories. Being that Fardell et al.’s (139) framework was published

after the current study was conceptualized, the current study’s conceptual review of FCR

involved only that of Lee-Jones et al (58).

Lee-Jones et al.’s (58) formulation of FCR is widely acknowledged as a seminal paper to

describe FCR (25,30,55,71,84,88,139,144–146). In considering the overarching goal of the

current study (see Chapter 2 Section 6.1), Lee-Jones et al.’s (58) formulation of FCR was useful

to consider which variables and constructs were important to include. However, being that Lee-

Jones et al.’s (58) formulation of FCR remained untested (55,90,147) and did not include

mediators of FCR about which the current study intended to examine, alternative theories useful

to conceptually understand FCR were sought. One notable theory is that developed by Leventhal

et al. (148) that has become more widely understood at the Common-Sense Model of Self-

Regulation (CSM) (140–143).

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1.1 The Common-Sense Model of Self-Regulation

The Common-Sense Model of Self-Regulation (CSM) is used to explain how individuals process

information in order to generate responses to control health threats (140). The CSM is useful to

explore illness-related events from the perspective of the patient with chronic illness (140), such

as cancer. Various aspects of the self-regulation framework have been used to explore FCR in

breast (34,42,47,88), head and neck (46,149,150), colorectal (62) and testicular (44) cancer

survivors.

The central tenet of the CSM is the illness representation, which can be otherwise described as

how an individual ‘makes sense of’ their condition (120). The illness representation is

developed by the individual through two distinct but interacting processing streams: the

cognitive and emotional (151,152). The cognitive processing pathway generates a concrete

mental representation of the illness threat (151) and develops a deliberate plan to cope with it

(151,152), whereas the emotional processing pathway generates and regulates an emotional

reaction to the illness threat (151). Leventhal et al. (140,143,151) postulate that the resulting

illness representation is characterized by 5 cognitive domains: identity, timeline, consequences,

cause and control. Since the original theoretical construction, Lau et al. (153) further suggested

that the individual’s ability to coherently understand their illness also contributes to their illness

representation. The presence of the cognitive domains and the emotional representation have

been empirically supported (103,143).

The cognitive and emotional representations influence the selection of coping procedures or

specific health behaviours, which are both appraised by the individual for effectiveness, and

provide feedback to alter the representation (141–143,151). Leventhal et al. (140) suggest that

one’s progression through these processes is set in a context influenced by characteristics of 1)

the self-system; and of 2) the social-cultural context.

The self-system is comprised of a hierarchy of self-identities, of which self-esteem is at the top,

and narrow beliefs such as self-efficacy, are at the base (140). Although a summary of self-

identities is not provided, cited examples, in addition to those previously cited, include perceived

level of health (140), sense of meaning and purpose, self-concept, the physical self, self-motives,

self-definitions (151), and biological or psychological traits (143). Leventhal et al. (141)

characterize self-identities as a series of “generic, trait-like features of the self” (p.59).

49

Membership and roles in the social-cultural context impact all aspects of the CSM (143,154).

Leventhal et al. (141) suggest that these factors influence illness perceptions by: 1) providing

labels and differentiation of events that constitute illness; and 2) that social contacts guide the

interpretation of somatic information and the skills necessary to manage the symptoms.

Examples of the social-cultural context include observing sickness in others, comparing one’s

illness with another (143), cultural beliefs and values (154), and the social categories in which a

person is perceived by others (151).

2 The Predictors and Mediators of Fear of Cancer

Recurrence Conceptual Framework

Being that the existing conceptualization of FCR (58) did not address mediators of FCR about

which the current study intended to explore, and that the full Common-Sense Model of Self-

Regulation (140–143), albeit useful to guide an overall understanding of FCR (46,55,58), was

complex and comprised of a number of concepts and relationships, a new conceptual framework

was developed for this study. Specifically, this new conceptual framework merged the

predictors of FCR that were empirically discordant in the literature (see Chapter 2 Sections 6.0-

6.1 for details) with mediators of FCR derived from an established theory (140–143) useful to

understand overall FCR (46,55,58). The benefits of this new conceptual framework were: its

foundation upon a theory with a diversity of available resources outlining its empirical testing

(140–143), and; that it would be useful to fill gaps in the empirical understanding of FCR. After

assessing the prevalence of FCR, the current study used this new framework, referred to as The

Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework (Figure 1), to

explore the predictors and mediators of FCR in survivors of adult cancers.

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework proposed

that a cancer survivor’s FCR is influenced by their Illness Representations that they form about

their cancer experiences, their Coping Styles, as well as their demographic characteristics,

clinical characteristics, and self-identities. The Illness Representations and Coping Styles are

directly influenced by the demographic characteristics, clinical characteristics, and self-identities

of the survivor, which are comprised of characteristics that can be equated with the self and

social-cultural context of the CSM. Demographic characteristics, clinical characteristics, and

self-identities were also proposed to have a direct influence on FCR.

50

It is recognized that the CSM, upon which the Predictors and Mediators of Fear of Cancer

Recurrence Conceptual Framework was founded, regarded Coping Style as a mediator between

an Illness Representation and an Appraisal (141–143,151), such as FCR in the case of the current

study. However, this theorized relationship has been empirically rejected in breast cancer

survivorship research (42,155) and a meta-analysis concluded that evidence for such a causal

relationship was not supported (120). For these reasons, Illness Representation and Coping Style

were each regarded as a mediator within distinct relationships of the Predictors and Mediators of

Fear of Cancer Recurrence Conceptual Framework that guided this study.

Figure 1: Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework

Independent Variables Mediating Variables

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework was utilized

to plan data collection and analysis. The framework depicted relationships between various

predictors and mediators of FCR. There were four main aspects to the framework: 1) FCR; 2)

Illness Representations; 3) Coping Style; and 4) demographic characteristics, clinical

characteristics, and self-identities. The first feature detailed the level of FCR of the survivor of

adult cancer. The second feature described the interpretation of the cancer experience held by

the cancer survivor, otherwise known as Illness Representations. These Illness Representations

were postulated to be directly influenced by the characteristics and identities of the survivor, and

mediate the cancer survivor’s FCR. Thirdly, the Coping Styles of the cancer survivor, which

Illness Representation

1. Cognitive Representation Label

Cause

Consequence

Timeline

Controllability

Coherence

2. Emotional

Representation

Demographic Characteristics 1. Socio-demographic variables 2. Ethnocultural background 3. Generalized Expectancies

Clinical Characteristics 1. Cancer pathology & time since

diagnosis 2. Any cancer treatment 3. Number of Co-morbidities 4. Symptom burden 5. Associations with cancer

Self-Identities 1. Self-Esteem 2. Personality 3. Generalized Expectancies

Coping Styles

Fear of Cancer

Recurrence

51

was suggested to be influenced by the characteristics and self-identities of the survivor, mediated

the relationship between these characteristics and level of FCR. The fourth feature detailed the

predictors of FCR (demographic characteristics, clinical characteristics, and self-identities),

which directly influenced the Illness Representations and Coping Styles of the cancer survivor,

as well as their level of FCR.

3 Conceptualization of the Primary Outcome Variable

3.1 Fear of cancer recurrence

The main outcome variable of this study was Fear of Cancer Recurrence (11), defined as “the

worry that the cancer will come back in the same place or in another part of the body” (p.18).

Although Vickberg’s (11) definition was the most commonly cited in the FCR literature at the

time of the current study’s conceptualization, an updated definition of FCR was established in

2015. Using a Delphi process, a new consensual definition of FCR was developed (12): “Fear,

Worry, or concern relating to the possibility that cancer will come back or progress” (p.3266).

However, for the reasons stated above, the definition proposed by Vickberg (11) was adopted for

the current study.

At the time of this study’s conceptualization, the work of Lee-Jones et al. (58) was the most

commonly cited conceptualization of FCR who proposed that FCR was comprised of cognitions,

beliefs and emotions (58). According to Lee-Jones et al. (58), cognitions included the person’s

past experience with cancer and its treatment, their knowledge base of cancer (i.e. cure and

survival rates), and their beliefs about the eradication of cancer (p.102). Lee-Jones et al. (58)

went onto propose that a person’s beliefs about their personal risk to a cancer recurrence as the

second component of FCR (p.102), whereas a person’s emotions, including worry about the

cancer returning, anxiety about the cancer itself, and regret for not selecting more aggressive

treatment (p.102) to be the final component of FCR. This conceptualization of FCR (58) regards

the construct as comprised of a number of dimensions, or in other words, a multi-dimensional

concept. In alignment with this perspective, the current study objectively assessed FCR using the

valid, reliable, Fear of Cancer Recurrent Inventory (FCRI) (30) founded upon Lee-Jones et al.’s

(58) conceptualization. The FCRI was completed by the cancer survivor.

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4 Conceptualization of the Independent Variables

4.1 Demographic characteristics

4.1.1 Socio-demographic variables

In their systematic review, Crist et al. (54) determined that the evidence relating FCR and socio-

demographic characteristics is inconclusive. Specifically outlined, were the contradictory results

relating age, gender, marital status, and level of education with FCR, although age was more

consistently identified as a predictor of FCR than not (54). Similar inconsistencies were found

relating FCR with gender (25,43,49) and with income or employment-related variables

(21,35,38,39,42), suggesting that these socio-demographic characteristics needed further

exploration.

The social aspect of socio-demographic characteristics could include with whom one lives and

their level of dependence, which have received little empirical exploration in relation to FCR.

There was some empirical support for having children, versus not having children, and higher

associated FCR (38,78,156,157). However, the ages or dependency of the children upon the

survivor and their level of FCR remained contradictory (35,158).

Collectively, further empirical exploration was warranted to examine the relationship between

socio-demographic characteristics and FCR. The Predictors and Mediators of Fear of Cancer

Recurrence Conceptual Framework conceptualized socio-demographic variables as: age, sex,

marital status, parental status, level of education, and employment status. Additionally, the first

3 characters of the participant’s postal code was collected to explore urban-rural differences in

levels of FCR, which had been suggested to significantly differ (159). Information about these

characteristics were collected on a demographic form that was completed by the participant and

by data extraction from their medical chart.

4.1.2 Ethnocultural Background

The literature was inconsistent about the relationship between ethnocultural variables and FCR

(31,40,42,49). However, a similar concept, level of recurrence worry, was predicted by level of

acculturation (39) which refers to how individuals are adapting to a new cultural context (160).

Level of acculturation was also a predictor of self-rated health (161) and underutilization of

53

routine screening practices such as mammography (162,163), which further highlighted its

importance within the healthcare context. Specific to cancer care, ethnocultural factors were

suggested as important areas of focus in the cancer-related experience (164), and ethnic

minorities and immigrants were identified as vulnerable populations to which cancer resources

needed to be improved (165). These findings, coupled with the impact of social and cultural

factors upon illness representations in the CSM (141,154) upon which this study’s conceptual

model was founded, highlight the importance of exploring the influence of ethnocultural

variables upon FCR.

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework’s

conceptualization of ethnocultural background was derived from Ashing-Giwa’s (166)

Contextual Model of Health-Related Quality of Life, which was developed from and frequently

used in culturally-based psychosocial oncology research. In her model, Ashing-Giwa (166)

describes ethnic identity, defined as one’s sense of belonging to a group of ancestral origin that

influences how they view and behave in the world, as the foundation of one’s cultural context.

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework

conceptualized ethnocultural background as: ethnicity (or region of ancestral origin (166)); and

immigration status (1st, 2nd, ≥3rd generation in Canada, or not born in Canada). Collectively, this

information was expected to provide data comparable to results about ethnic identity, since many

of the complex details of ethnic identity (166) were beyond the objectives of this study. The

information about ethnocultural background was collected on the demographic form that was

completed by the participants.

4.2 Clinical Characteristics

As previously discussed, the results of the systematic review by Crist et al. (54) indicated that the

evidence for the association between FCR and cancer-related characteristics was inconclusive.

Specifically outlined, were the contradictory results relating cancer type, cancer stage, treatment

type (chemotherapy versus radiation therapy), type of surgery (conservative versus radical), and

how these variables affected the severity FCR (54). Related to time since diagnosis, Crist et al.’s

(54) systematic review identified that no studies had found an association with FCR. However in

their review, most of the studies focussed on breast cancer patients or survivors, and therefore

issues of limited generalizability suggested the need for further study.

54

Other clinically-based characteristics, such as number of comorbidities (39,41) and symptom

burden (38,42,104), had been explored in relation to FCR, however concerns about the

psychometrics of FCR measurement (38,39,41,104) remained. The CSM (141,154), upon which

the current study was conceptualized, describes the importance of somatic experiences upon the

interpretation of a current illness (143), and was therefore important to clarify in relation to FCR.

The CSM also cited the individual’s social observations and comparisons (140), as well as their

interpretations of concrete, perceptual experiences (167), as contributing factors to an illness

representation. This suggested that the cancer survivor’s associations with cancer, such as

knowing someone with a cancer recurrence, would contribute to their illness representation and

FCR. However, family history of cancer was not found to be a predictor of FCR (31) nor

recurrence worries (39). Based upon this theoretical and empirical inconsistency, further

empirical exploration about the relationship between associations with cancer and FCR was

needed.

Collectively, the state of the current empirical literature suggested that further exploration of

clinical characteristics and FCR be undertaken, which is substantiated by theoretical foundation.

In the current study, the variables conceptualized as clinical characteristics were developed from

the inconsistencies reported in the aforementioned systematic review (54), gaps in the empirical

literature (see Chapter 2), and theoretical explanation (140,143,167). The Predictors and

Mediators of Fear of Cancer Recurrence Conceptual Framework conceptualized clinical

characteristics as: type (pathology) of cancer diagnosis and time since diagnosis; type of cancer

treatment; number of comorbidities; symptom burden; and associations with cancer. The data

about cancer pathology and treatment were extracted from the medical chart. The study

participants provided information about their number of comorbidities and associations with

cancer on the Demographic Form, and provided information about their symptom burden on a

valid and reliable instrument (103).

4.3 Self-Identities

4.3.1 Self-esteem

Global self-esteem refers to the overall positive or negative attitude that an individual holds

about them self (168). Self-esteem has been positively correlated with well-being (169,170) and

negatively associated with depression (168), and distress (171). Although self-esteem has been

55

studied in a variety of populations, there is very little research conducted to explore the

predictive qualities of self-esteem in adult psychosocial oncology (172). Specific to FCR, a

single study (38) reported an inverse correlation between self-esteem and FCR however the

significance of this correlation did not persist into regression analyses. Additionally, a limitation

of the study was that FCR was assessed using a single-item developed by the researchers, about

which the validity nor reliability were stated. Theoretically, Leventhal et al. (140) cite that self-

esteem has paramount importance in the development of an illness representation, therefore

clarification about the relationship between FCR and global self-esteem was needed.


conceptualized self-esteem as a stable, trait-like construct (173) of the cancer survivor that

directly influenced their level of FCR, but also had an indirect influence on FCR via Illness

Representations and/or Coping Styles. It was conceptualized as the level of respect and worth

that an individual has about the self (174). It was determined through the use of a standardized

assessment tool (174) that was completed by the participant.

4.3.2 Personality

The Big Five Trait Taxonomy, sometimes referred to as the Five Factor Model (FFM), is a useful

representation of the dimensions of personality (175). The taxonomy is not intended to reduce

the complexity of personality into 5 traits, however each dimension (Extraversion,

Agreeableness, Conscientiousness, Neuroticism, and Openness) is meant to summarize a large

number of specific personality characteristics (175). Personality traits are important to study

because they influence how individuals interact with the environment and construe meaning

from it, and directs the individual to which aspects of the environment they will attend (175). In

this regard, it was postulated that personality influences the development of an illness

representation and affects level of FCR.

Various dimensions of personality have been found to predict good health habits (176),

adherence to treatment regimens (177), and successful coping (178,179). Therefore, the

dimensions of personality would be useful to explore in a sample of cancer survivors, among

whom only neuroticism (38) was found to be a predictor of FCR. The Predictors and Mediators

of Fear of Cancer Recurrence Conceptual Framework adopted the Five Factor Model (175) to

conceptualize personalities as a self-identity that directly influenced the cancer survivor’s FCR,

56

and indirectly influenced their FCR via Illness Representations, and/or Coping Styles.

Personalities were assessed using a valid and reliable assessment tool (180) that was completed

by the participant.

4.3.3 Generalized expectancies

The CSM (141,154), upon which the current study was conceptualized, described the importance

of a person’s attributes in creating their sense of vulnerability to, or likely success in preventing,

negative health effects (140). One such attribute may be the general expectations that a person

has toward an outcome (181), more specifically dichotomized as optimism–pessimism (182).

Optimists, referred to as those holding positive expectancies for their future (115), have been

reported as having higher quality of life (183) and less distress (178) than pessimists, referred to

as those with negative expectations for their future (115). Often referred to simply as

“optimism” (182), the trait, similar to that of personality traits, is viewed as such because of its

stability over time (115,181). In the psychosocial oncology literature, only two studies have

explored the relationship between optimism and FCR finding that optimism was a significant

predictor of FCR after the completion of cancer treatment (40,46). However, the support of

optimism as a predictor of FCR was limited by the measures used to assess FCR as 1-item (46)

and 4-items (40) about which the validity, development, and multi-dimensionality of the

measures are unclear. Therefore, further assessment of the relationship between generalized

expectancies and FCR in a heterogeneous cancer survivors was necessary.


conceptualized generalized expectancies as a stable, trait-like (182) self-identity of the cancer

survivor that directly predicted FCR. However, optimism had also been suggested to have an

indirect impact on psychological distress of women with breast cancer that was mediated by

coping (184). As such, the Predictors and Mediators of Fear of Cancer Recurrence Conceptual

Framework also conceptualized Generalized Expectancies as an indirect predictor of FCR

through Coping Styles and/or Illness Representations. Generalized Expectancies were more

specifically described on an optimistic-pessimistic dimension (182) and were assessed from the

participant perspective using a valid and reliable measure (115).

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5 Conceptualization of the Mediating Variables

5.1 Illness representations

Leventhal et al. (140) define an Illness Representation as an “elaborate set of meanings” (p.210)

enabling a person to understand the situation that they are experiencing. The Illness

Representation has both cognitive and emotional components from which the person plans their

methods to cope with a health threat (140,142,143).

Various aspects of an Illness Representation have predicted FCR among breast cancer survivors

(42,88). Similarly, aspects of Illness Representations have been correlated with FCR in a sample

of head and neck cancer survivors (46), however this relationship did not persist into regression

analysis. Therefore, the relationship between the Illness Representations of cancer survivors and

FCR was not clear suggesting further empirical study.

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework adopted

Leventhal et al.’s (140,143,151) conceptualization of Illness Representations, and depicted it as a

mediator in the relationship between the demographic, clinical, and self-identities and FCR. It

was determined through the use of a valid and reliable measurement tool (103) that was

completed by the study participant.

5.2 Coping Styles

Lazarus et al. (123) describe coping as an application of strategies toward the demands of a

stressor. This view is similar to that of the CSM in that methods of coping are viewed as

procedures to control or eliminate illness threats (141). According to the CSM (143), coping is

referred to as the “selection, performance, and maintenance of procedures that the individual

uses to prevent, cure, or halt the progression of an illness threat” (p.23). A wide variety of coping

procedures exist, ranging from short term to repetitive long-term actions (143). The selection of

a coping procedure is based upon the objective that that particular procedure is intended to meet

(143).

In a meta-analysis, active approaches to coping were found to significantly benefit the

psychological and physical well-being of cancer survivors and facilitate their return to their pre-

cancer activities (185). Related to FCR, methods of coping were found to be a mediator (35) and

58

predictor (42) of FCR in samples of breast cancer survivors. However, the positive or negative

association of coping with FCR in a sample of head and neck cancer survivors did not persist

into regression analysis (46). Due to these inconsistent results, further study of the relationship

between the concepts was needed.

This study’s conceptualization of Coping Styles is aligned with Leventhal et al.’s (141,143)

CSM, as outlined above. However, as described in Chapter 3 section 2.0, the current study

conceptualized Coping Styles in a distinct relationship apart from an illness representation and

instead regarded it as a mediator between demographic characteristics, clinical characteristics,

and self-identities of the individual and their level of FCR. Although Coping Styles was

assessed from the participant’s perspective using a valid and reliable measure (126), utilizing this

measure in its original form would have regarded Coping Styles as 14 distinct mediators in the

Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework. To overcome

this conceptual complexity, alternative conceptualizations of coping using the intended measure

(126) were sought (see Chapter 4 section 8.5.2 and Chapter 5 section 3.7.5 for additional details).

As a result, Coping Styles was regarded as 2 types: Active Coping and Escapist Coping2 (35).

This perspective of coping was believed to remain consistent with Leventhal et al.’s (141,143)

CSM described above, in that Coping Style represented a wide variety (143) of “procedures”

(p.24) used to control or eliminate illness threats (141).

6 Strengths and Limitations of the Proposed Model

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework was an

adaptation of the Common-Sense Model of Self-Regulation (140,143,167), which has been

theoretically used to explain how cancer survivors come to understand and make sense of their

illness experiences (34,42,44,46,47,62,88,149,150). In this regard, the model was especially

relevant for research to explore the factors that contribute to the recurrence fears of cancer

survivors.

Moreover, the Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework

identified a relationship between ethnocultural factors and FCR where earlier explorations of the

predictors of FCR have predominantly used this data for descriptive purposes. However, there

2 An Active Coping Style was comprised of self-distraction, active coping, emotional support, instrumental support,

venting, positive reframing, planning, acceptance, and religion coping procedures. An Escapist Coping Style was

comprised of denial, behavioural disengagement, substance use, and self-blame coping procedures.

59

was some evidence to suggest that ethnocultural factors play a larger role in predicting FCR

(39,40) and were considered here as such.

The Predictors and Mediators of Fear of Cancer Recurrence Conceptual Framework may be

useful in clinical oncology contexts since it explored both non-modifiable and modifiable factors

of the cancer survivor. Non-modifiable characteristics were identified as independent variables,

whereas characteristics that are modifiable are identified as mediators. The independent variables

that were determined to be significant in the findings will aid clinicians/researchers in knowing

which survivors are likely to have the highest FCR and should therefore be referred to receive

additional supportive care (e.g. interventions for FCR). The mediators in the framework were

characteristics that could provide support for researchers to develop interventions tailored to

modifiable patient characteristics that could help patients cope with or reduce their level of FCR.

In these ways, the Predictors and Mediators of Fear of Cancer Recurrence Conceptual

Framework has both clinical and research utility.

In regards to its limitations, the Predictors and Mediators of Fear of Cancer Recurrence

Conceptual Framework conceptualized the self-identities of the cancer survivor as comprised as

three distinct constructs (self-esteem, personality, and generalized expectancies). This view

failed to appreciate the cancer survivor as a multi-dimensional being. Howell et al. (110)

describe the psychosocial dimensions of cancer care as physical, informational, emotional,

psychological, social, spiritual and practical, reflecting the types of care directed to the many

dimensions of a person. The intention of cancer care strategies to view the survivor as a multi-

dimensional being (4) further highlighted the limitation of conceptualizing the cancer survivor’s

self-identities as three constructs. However, the overall intent of this model was to develop new

knowledge about the predictors of FCR, and therefore focusing on these few sound concepts

maintained its robustness.

Another limitation of the model was its omission of addressing anxiety and depression as

predictors of FCR. The rationale for these omissions were twofold. First, empirical results

consistently report positive associations of FCR with depression (22,31,43,44) and anxiety

(22,31,37,105). Since the intention of this study was to add new knowledge and empirical clarity

to the literature, only predictors and mediators that remain unexplored or ambiguous in the

literature were included. Second, this model incorporated theoretically and empirically based

60

stable, or trait-like characteristics as independent variables to predict FCR. These concepts were

included based upon gaps in the literature, criteria for which neither depression nor anxiety met.

7 Summary

This study used the Predictors and Mediators of Fear of Cancer Recurrence Conceptual

Framework, based upon the Common-Sense Model of Self-Regulation (CSM) (143), to explore

the predictors and mediators of FCR. The use of this model strengthened the knowledge about

the predictors and mediators of FCR, and aimed to add new knowledge about factors that have

been largely overlooked in the FCR literature. Specifically, new knowledge was hoped to be

generated about ethnocultural factors and self-identities as predictors of FCR. These were

included in the current framework based upon recent evidence that suggested their importance

upon concepts similar to FCR, such as Worry of Recurrence (39). Additionally, the model

provided clarity to the existing literature about demographic and clinical predictors, as well as

mediators of FCR.

The existing literature about the predictors and mediators of FCR largely focused on modifiable

characteristics that were amenable to intervention. This model adds to this literature in that

modifiable mediating characteristics of the cancer survivor sought clarification. Of greater

significance, this model intended to add clarity about the stable characteristics of the individual

that would be useful for clinicians and researchers to understand who will most likely develop

clinically-significant FCR and therefore benefit from additional care and referral to interventions

to cope with FCR. Since there was not an accepted, empirically-validated model of FCR

available in the literature (55), the Predictors and Mediators of Fear of Cancer Recurrence

Conceptual Framework provided a useful context to investigate these relationships as the

foundation for high-risk identification and future interventions.

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Chapter 4 Methods

1 Purpose of the Study

The purpose of this research was to assess the prevalence of FCR, and to examine theoretically-

and empirically-based predictors and mediators of FCR in a sample of survivors of adult cancers

attending a cancer survivorship clinic.

2 Research Objectives

The primary and secondary objectives of this study were:

Primary objective:

1) To assess the prevalence of Fear of Cancer Recurrence among survivors of adult cancers.

Secondary objectives:

2) To determine if demographic characteristics (socio-demographic variables and ethnocultural

background), clinical characteristics (cancer pathology and time since diagnosis; receipt of any

cancer treatment; number of co-morbidities; symptom burden; and associations with cancer), and

self-identities (self-esteem; personalities; and generalized expectancies) predict fear of cancer

recurrence among survivors of adult cancers. More specifically, Objective 2 explored the direct

effects of demographic variables (age, sex, marital status, parental status, level of education,

employment status, ethnicity, immigration status, and urban/rural location), clinical variables

(diagnosis [type and stage], time since diagnosis, receipt of any cancer treatment, number of

comorbidities, knowing someone with a cancer recurrence, belief that knowing someone with a

cancer recurrence affects FCR, having had metastatic disease/cancer recurrence/another primary

cancer, ACTT clinic status, and symptom burden), and self-identities (self-esteem, personalities,

and generalized expectancies) on level of FCR.

62

3) To determine if a) illness representations and b) coping styles are mediators of FCR among

survivors of adult cancers.

In keeping with Objective 3, Objective 3a explored the indirect effects of demographic

characteristics (socio-demographic variables and ethnocultural background), clinical

characteristics (cancer pathology and time since diagnosis; receipt of any cancer treatment;

number of co-morbidities; symptom burden; and associations with cancer), and self-identities

(self-esteem; personalities; and generalized expectancies) on level of FCR as mediated by illness

representations. More specifically, Objective 3a explored the indirect effects of demographic

variables (age, sex, marital status, parental status, level of education, employment status,

ethnicity, immigration status, and urban/rural location), clinical variables (diagnosis [type and

stage], time since diagnosis, receipt of any cancer treatment, number of comorbidities, knowing

someone with a cancer recurrence, belief that knowing someone with a cancer recurrence affects

FCR, having had metastatic disease/cancer recurrence/another primary cancer, ACTT clinic

status, and symptom burden), and self-identities (self-esteem, personalities, and generalized

expectancies) on level of FCR through illness representations.

In keeping with Objective 3, Objective 3b explored the indirect effects of demographic

characteristics (socio-demographic variables and ethnocultural background), clinical

characteristics (cancer pathology and time since diagnosis; receipt of any cancer treatment;

number of co-morbidities; symptom burden; and associations with cancer), and self-identities

(self-esteem; personalities; and generalized expectancies) on level of FCR as mediated by coping

styles. More specifically, Objective 3b explored the indirect effects of demographic variables

(age, sex, marital status, parental status, level of education, employment status, ethnicity,

immigration status, and urban/rural location), clinical variables (diagnosis [type and stage], time

since diagnosis, receipt of any cancer treatment, number of comorbidities, knowing someone

with a cancer recurrence, belief that knowing someone with a cancer recurrence affects FCR,

having had metastatic disease/cancer recurrence/another primary cancer, ACTT clinic status, and

symptom burden), and self-identities (self-esteem, personalities, and generalized expectancies)

on level of FCR through coping styles.

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3 Overview of the Proposed Study

To meet these objectives, an observational, cross-sectional design was employed. Cross-

sectional designs are useful to determine prevalence of phenomena (186) and assess the strength

of associations among variables (187), thus appropriate to meet the objectives of this research.

The study sample was recruited from a target population of survivors of adult cancers attending

the After Cancer Treatment Transition (ACTT) clinic in Toronto. Data were collected from each

participant by way of a survey that was completed either electronically or in paper form mailed

out in a package containing a returned-addressed postage-paid envelope. Study participants

completed the survey at a single point in time. The survey assessed the adult cancer survivor’s

FCR, Illness Representations, Coping Styles, Self-Esteem, Personalities, and Generalized

Expectancies, and collected information about the participant’s demographic and clinical

characteristics. Clinical characteristics related to cancer diagnosis and treatment were extracted

from the participant’s hospital chart.

4 Setting

The research took place at the ACTT clinic, which offers specialized cancer survivorship care for

patients who have completed active cancer treatment. The clinic, housed at Women’s College

Hospital (WCH), provides care for cancer survivors in full partnership with the Princess

Margaret Cancer Centre. The ACTT clinic was established in 2008 as an initiative to provide

care to cancer patients who had completed cancer treatment at Princess Margaret Cancer Centre.

The clinic was established as a place where these patients would continue to receive cancer

survivorship specific care as they transitioned back into the primary care of their general

practitioner. The pilot phase of the clinic provided care to breast cancer patients, and has since

provided care to patients with cancer at other disease sites. At the time of this study, only

patients completing treatment for breast, testicular, melanoma, gastro-intestinal, gynecological,

thyroid, or lung cancer at Princess Margaret Cancer Centre were able to receive transitional care

from the ACTT (188).

Patients were referred to the ACTT by their medical oncologist after they completed and

recovered from the immediate sequelae of active cancer treatment at the Princess Margaret

Cancer Centre. On initial consultation, patients met both the physician and advanced practice

nurse at the ACTT. During this appointment, the patient’s past medical history was

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collected/clarified, and patients were introduced to the background and purpose of the ACTT

clinic. Patients were introduced to the generic care plan of cancer survivorship and made aware

of the transitional nature of the clinic. Diagnostic and clinical examinations were arranged per

the care plan. Patients were seen and assessed in the clinic every 6-12 months per the practice

guidelines of the ACTT clinic. The mandate of the ACTT clinic was to follow patients for

approximately 5 years after their cancer diagnosis (S. Maura, personal communication, 2014).

As of January 2014, over 1900 cancer survivors had been referred to the clinic (personal

communication S. Maura, 2014). Of these, approximately 25% had completed their transition

through the program and been referred back to their primary care provider (S. Maura, personal

communication, 2014). For further details about the composition of patients followed at the

ACTT clinic, see Appendix A.

5 Sampling Frame and Target Population

The sampling frame for this study comprised all of the patients receiving cancer survivorship

care at the After Cancer Treatment Transition Clinic (ACTT) during the study period, from

January to August, 2015. Although only referrals from the Princess Margaret Cancer Centre

were accepted at the ACTT during the study timeframe, patients from across Central Ontario

may have received cancer treatment at Princess Margaret Cancer Centre and may have therefore

been referred and followed at the ACTT clinic. However, the majority of the patients were from

the Greater Toronto area. Per the ACTT clinic admission guidelines (Chapter 4, Section 4.0),

only patients completing treatment for breast, testicular, melanoma, gastro-intestinal,

gynecological, thyroid, or lung cancer were included in this study. The target population of

interest in this study were Canadian cancer survivors, who had completed primary adjuvant

treatment for any of the previously stated cancers that were diagnosed in adulthood.

5.1 Sample Size Considerations

Although all of the patients being followed at the ACTT were invited to participate in this study

(n=2,143), sample size calculations were estimated to ensure that adequate numbers were

available to meet the objectives of this study. The primary objective of this study was

descriptive, and was presented as proportions. In order to calculate the sample size needed to

adequately address the descriptive objective (189), an estimated population proportion of cancer

survivors who have clinically significant levels of FCR was needed. At the time of this study’s

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conceptualization, the proportions of clinically significant levels of FCR were published in 2

studies (24,25) that used the valid and reliable FCRI (30). These results widely varied, therefore

the more conservative published proportion (25) was used for the sample size calculation for this

study (58.3%). Using this value in the formula presented in Appendix B, with an alpha of .05

(α=0.05) and a 95% confidence interval (95%CI), a sufficient sample size to address the

descriptive objective was 374 participants (see Appendix B).

The sample size calculation to address the secondary objectives of this study, which were

inferential in nature, followed a different process. When considering the objectives of this study

(see Chapter 4, Section 10.4.) structural equation modeling (SEM) techniques were most

appropriate. SEM is described as a large sample technique (190,191) for which there are no

absolute guidelines to determine sample size (191). Although the N:q rule3 is commonly used to

determine sample size for SEM analyses, application of this rule in this study’s circumstance

would have needed in a sample size of 4,620, much larger than the number of available cancer

survivors at the ACTT clinic. Inviting all of the patients within the ACTT clinic database to

participate would result in a sample size of 2,143, which surpasses the “typical” sample size of

200 cases for SEM analyses (191). Assuming a 60% response rate, based on a 2013 survey

study conducted at the ACTT clinic (personal communication, C. Townsley, 2014), it was

anticipated that 1,285 ACTT patients would participate in the current study. This sample size

meets the definition for a large sample (191) and provides enough variation in the data for SEM

to be conducted (190,191).

6 Eligibility Criteria

Men and women were eligible for this study if they: 1) were older than 18 years of age; 2) were

currently receiving or had ever received survivorship follow-up care at the ACTT clinic; 3) were

currently free of cancer; 4) had no obvious cognitive impairment noted in their medical chart; 5)

were able to read, write and understand English; 6) were willing and able to provide informed

consent; and 7) were accessible by letter mail. Individuals were excluded from this study if they:

1) had a diagnosis of childhood cancer; or 2) were unwilling or unable to provide informed

consent.

3 The N:q rule requires that the commonly used maximum-likelihood (ML) estimation method be used in the SEM

analysis, and suggests that the ideal number of cases (N) to the number of model parameters that require statistical

estimation (q) be 20:1 (191,278).

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The rationale for these criteria stemmed from what was known from the existent literature. The

intention to generalize resulted in the inclusion of both men and women, and a broad range of

cancer diagnoses. Since fear of recurrence was been found to correlate with younger age at

diagnosis (11,34,36,49,105,192) and has often been explored in non-metastatic settings, these

criteria intended to include a broad range of adults, particularly younger adults, without

metastatic disease. The rationale for selecting English-speaking subjects was based on the

availability of English measures that were both valid and reliable.

It was anticipated that the number of ACTT patients who would meet the eligibility requirements

of this study would greatly outnumber those who do not. Therefore, all ACTT patients were

contacted to participate in this study, and respondents who returned the study documents

(described in Chapter 4, Section 7.1) were screened for eligibility using the information provided

in the study documents, as well as the data extracted from a medical chart review.

7 Procedures for Data Collection

7.1 Recruitment and Data Collection Procedures

Once Research Ethics Board approval was granted, all patients of the ACTT clinic were mailed

an Information Letter describing the study objectives and requirements (Appendix C). This one-

page Information Letter specified that the patient’s care at the ACTT would not be affected by

their decision to participate or not in the study, and a voicemail number was provided for those

wishing to opt-out from further contact about the study. The letter alerted patients that ten days

thereafter, they would be mailed a study package containing the study Consent Form (Appendix

D), the study questionnaires (Appendices E,F,H-L), and a return-addressed, postage-paid

envelope to return the study documents to the researcher. The Information Letter also indicated

that should patients wish to participate and complete questionnaires online, they could review

and complete the consent form and questionnaires using FluidSurveys™, an online questionnaire

tool, compliant with Canadian privacy laws and accessibility standards (193). The web address

for the survey was included on each Information Letter. In this way, this study employed a

mixed-mode survey design (194) whereby potential subjects were informed of the study via an

initial postal Information Letter (Appendix C), but then had the option to review and complete

the consent form and questionnaires in hard copy or electronically. Mixed-mode survey designs

had become increasingly common due to readily available online survey software that are easy to

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use. Mixed-mode survey designs have the ability to lower researcher costs, improve the

timeliness and accuracy of results, as well as reduce the likelihood of errors with data entry

(194). Although careful consideration must be given to consistent formatting and wording in all

modes of the surveys, postal-surveys and electronic-surveys have demonstrated equivalent

response rates (195,196).

In attempt to increase the uptake and response rates of the study, a modified Dillman’s tailored

design method (194) was followed. The Information Letter was congruent with Dillman’s

method of introducing potential participants to the study before the study packages are mailed.

Two weeks after the study packages were mailed, the researcher (JG) made a scripted telephone

call (Appendix M) to those ACTT patients who had not completed and returned a mail nor

electronic study package. This scripted telephone call reiterated the value of potential

participants’ perspectives relevant to the research objectives. If the patient requested a survey

package or web address to the electronic questionnaires, a study package and/or Information

Letter was sent for a second time.

To further facilitate the completion of study documents, the consent form encouraged

respondents that had difficulty completing the study documents (i.e. due to visual impairment) to

contact the study staff to aid in this process. Any patients who had not returned a survey 8 weeks

after the second package mail-out, were called a second time (see Appendix M for script of this

telephone call). Any patients that had not returned a survey after this second study package

mail-out were deemed to have not provided consent into the study. The study recruitment

strategy is presented in Figure 2.

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Figure 2. Study Recruitment Strategy

Aligned with Social Exchange Theory (194), the text within the study documents indicated the

valued perspectives of potential participants, who were thanked for their time in considering and

participating in the study. As an additional gesture of appreciation, all respondents who

completed and returned the study documents to the researcher were entered into a draw for the

chance to win an IPAD mini at the end of data collection. The Data Extraction Form (Appendix

G) was completed by the researcher as study packages containing completed surveys were

returned. Permission to access medical charts as indicated on the consent form by virtue of

survey completion, enabled the researcher to review the WCH charts to extract relevant data. As

such, Data Extraction Forms were completed in batches.

7.2 Data Storage

A log was kept of the number of Information Letters sent, study packages sent via mail, the

number of study packages returned (both post and electronic), the number calls made, and the

number of subsequent packages sent. In keeping with the WCH policies (A. Chappell, personal

communication, 2014), original source documents (e.g. completed surveys) were filed and

double-locked. These hard copies will be/were stored for 5 years and destroyed thereafter.

Anonymous study data were entered into a Microsoft Excel 2013 database where the data of

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each subject were identified by a unique study identifier. Identifying information was stored

separately from study data. Electronic data were stored on an encrypted device for 5 years.

8 Variable Definition and Measurement

Based upon the conceptualizations presented in Chapter 3, the selected measures that

operationalized the study variables are displayed in Table 2. The primary objective was

determined using a self-report questionnaire. The secondary objectives were determined by

chart audit and self-report questionnaires. It was recognized that research subjects were

participating in this study at various time points along the cancer survivorship trajectory and

therefore may be subject to recall bias. As such, measures that assessed stable, or trait-like

characteristics were used.

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Table 2. Overview of Study Variables and Measures

Concept Variable Measure Scale of

Measurement

Dependent Variable

Fear of Cancer

Recurrence

Fear of Cancer

Recurrence

Fear of Cancer

Recurrence Inventory

(FCRI) (30)

Continuous

42-items

Independent Variables

Demographic

Characteristics

Socio-demographic

Variables

Demographic Form &

Medical Chart Review

Categorical &

Continuous

7-items

Demographic

Characteristics

Ethnocultural Background Demographic Form

Categorical

2-items

Clinical

Characteristics

Type (pathology) & time

since cancer diagnosis Medical Chart Review

Categorical

3-items

Clinical

Characteristics Type of cancer treatment Medical Chart Review

Categorical &

Continuous

3-items

Clinical

Characteristics Number of co-morbidities Demographic Form

Continuous

1-item

Clinical

Characteristics Symptom Burden

IPQ-Identity Subscale

ONLY (see below)

Continuous

Clinical

Characteristics Associations with Cancer

Demographic Form &

Medical Chart Review

Categorical &

Continuous

4-items

Self-Identities Self-Esteem

Rosenberg Self-Esteem

Scale (RSES) (174)

Continuous

10-items

Self-Identities Personality

Big Five Inventory-10

(BFI-10) (180)

Continuous

10-items

Self-Identities Generalized Expectancies Revised Life Orientation

Test (LOT-R) (115)

Continuous 6-

items

Mediating Variables

Illness Representations Illness Perception

Questionnaire – Revised

(IPQ-R) (103)

Continuous

70-items

Coping Styles Brief COPE (126) Continuous

28-items

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8.1 Fear of Cancer Recurrence

Fear of cancer recurrence was assessed by the Fear of Cancer Recurrence Inventory (FCRI) (30).

The FCRI is a multi-dimensional self-report measure developed for use in mixed-cancer

samples. It comprises 42 items on seven subscales, which have demonstrated a consistent

factorial structure across cancer types representing 64% of the variance in FCR (30). The

subscales are: Triggers (8 items that address situations that make one think about the possibility

of a recurrence); Severity (9 items that assess the presence, frequency, intensity, and duration of

thoughts about a recurrence, as well as one’s perceived risk of recurrence); Psychological

Distress (4 items that address the emotions commonly experienced by thoughts of recurrence);

Coping Strategies (9 items that address nine strategies that may be used to cope with FCR);

Functioning Impairments (6 items that assess 6 types of functioning that may be disrupted by

thoughts of recurrence); Insight (3 items that address the perception that one’s fear is excessive);

and Reassurance (3 items that address 3 reassuring behaviours that may affect FCR) (30).

Responses to items are based on a 5-point Likert-like scale, where 0 indicates ‘not at all or

never’, and 4 indicates ‘a great deal or all the time’ (30). An overall higher FCRI score indicates

higher FCR (30).

As described in the review of the existing literature (Chapter 2), the prevalence of FCR has been

hard to pinpoint largely due to the various means of defining what level of FCR on any given

measure should be counted toward prevalence. The FCRI, developed for use in mixed-cancer

samples such as the sample used in the current study, has been explored using a Receiver

Operating Curve analysis (sensitivity 87.5%, specificity 75%) that determined a score greater

than or equal to 13 on the Severity subscale indicates a clinically significant level of FCR

(57,138). This cut-off was used in the current study to calculate the prevalence of FCR.

The FCRI has been found to be highly reliable (Cronbach’s alpha = 0.95, test-retest reliability =

0.89) (30), and its validity (convergent, concurrent, and divergent) has also been supported in

mixed cancer survivors (30,138). The internal consistency of the FCRI as determined within this

study’s sample was α=.953, and for the FCRI-Severity subscale was α=.881. Using Ponterotto et

al.’s (197) reliability matrix to estimate the adequacy of internal consistency coefficients (197),

the FCRI and its subscales had excellent internal consistency reliability.

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Although the total FCRI scores revealed a normal distribution (skewness = .208, and kurtosis = -

.302), an exploration of the means and standard deviations indicated the presence of outliers

(defined as a score more than 3 SDs (198). The presence of these outliers did not affect the

primary objective of the study (e.g. prevalence of FCR) and were therefore reported for

transparency. These descriptive statistics are detailed in Appendix P. The FCRI is found in

Appendix E.

8.2 Demographic Characteristics

The operationalization of demographic characteristics were based upon the conceptualizations

presented in Chapter 3. Demographic characteristics included socio-demographic characteristics

(9 items) and ethno-cultural background (2 items) of the study participants. Additionally,

participants were asked to provide the first 3 letters of their postal code which was collected as

an exploratory variable. The information was collected on the self-report Demographic Form

(Appendix F) and Data Extraction Form (Appendix G). After data collection was complete, the

frequency distributions for each categorical demographic variable were examined and, where

theoretically cogent, categories with low frequencies were combined while attempting to

maintain the variability within the sample.

8.2.1 Socio-demographic characteristics

The socio-demographic characteristics comprised the variables age, sex, marital status, parental

status, level of education, employment status, and the first 3 digits of the postal-code.

a) Age was measured as a continuous variable from a single self-report item.

b) Sex was measured as a categorical variable, male or female, and was extracted from the

participant’s chart.

c) Marital status was measured using a categorical question of their relationship as: common-

law; married; widowed; divorced; separated; single (never married); other. These categories were

modelled after the General Social Survey developed and conducted by Statistics Canada (199).

The majority of the sample were married or common-law, and as such, the marital status variable

was dichotomized into “Married or Common-Law” and “All other Groups” for all analyses.

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d) Parental status was measured as a continuous variable by the question “How many children do

you have?”. This value was dichotomized to represent the parental status as “parent” or “non-

parent”. Additionally, the ages of children among those who were parents was collected for

secondary analyses.

e) Level of education was measured as a categorical question indicating the highest level of

education that was completed: no formal education; some elementary school; some high school;

high school graduate; some community college or trade/technical school; community college or

trade/technical school graduate; some university; university graduate (Undergraduate Level);

some university (Graduate-Level); university graduate (Graduate-Level); other (specify). These

categories were modelled after the General Social Survey developed and conducted by Statistics

Canada (199). The majority of the sample had graduated with an undergraduate degree or

higher, and as such, the level of education variable was dichotomized into “Up to some

university” and “Undergraduate university graduate and higher and other” for all analyses.

f) Employment status was measured as a categorical question indicating their current work status

as: working at a job/business; with a job/business but not at work; not working with a

job/business; looking for work; and other (specify). These categories were broadly modeled

after the General Social Survey developed and conducted by Statistics Canada (199). The

majority of the sample indicated that they were working at a job/business, and as such, the

employment status variable was dichotomized into “Actively employed” and “Not actively

employed” for all analyses.

g) Using the Canada Post Corporation’s (CPC) definitions, the first 3 characters of the

participant’s postal code was used to determine their place of residence as rural or urban. The

CPC defines a rural postal code as a geographical location serviced by rural route drivers and/or

postal outlets, and is indicated by the number 0 as the second character in the code (200).

Similarly, the CPC defines an urban postal code as one that is generally serviced by a letter

carrier or community mailbox, and is denoted by the number 1-9 as the second character in the

code (200). The first character of the postal code (a letter K through P in Ontario) denotes the

broad geographical location in the province, where K indicates Eastern Ontario, L indicates

Central Ontario, M indicates Metropolitan Toronto, N indicates Western Ontario, and P indicates

Northern Ontario (200). The participants indicated the first 3 characters of their postal code on

the Demographic Form (Appendix F).

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8.2.2 Ethno-cultural background

The operationalization of ethno-cultural background was based upon the previously described

conceptualization in Chapter 3. It was composed of two distinct variables: ethnicity and

immigration status.

a) Ethnicity was measured as a single categorical question identifying the location of one’s

ancestral origin (166). The question was been adapted from the General Social Survey

developed and conducted by Statistics Canada (199), whereby participants selected one of the

following responses on the demographic form: White, Caucasian, or European descent; Chinese,

Southeast Asian, Korean, Japanese; Filipino; South Asian (East Indian, Pakistani, Sri Lankan,

etc.); Black or African American/African Canadian; Hispanic, Latino, Mexican American, or

Central American; Arab, or West Asian; Native Canadian (Inuit, Indigenous, etc.); Mixed

(parents are from 2 different groups); and other (specify). The majority of the sample indicated

that they were White, Caucasian or European descent, and as such, the ethnicity variable was

dichotomized into “White, Caucasian or European descent” and “All other ethnicities” for all

analyses.

b) Immigration status was captured as a categorical question indicating the participant’s status as

first, second, or third or higher generation in Canada. These categories were adopted from

Chakraborty’s (201) Composite Migration History Score, which was developed as a quick

measure of migration history for research about chronic disease risk factors. This validated

measure is composed of 9 items loaded onto a single factor, of which the question about

immigration status contained the highest component score coefficient (r =0.932) (201). Due to

the complex conceptualization and operationalization of cultural and ethnic related variables that

were beyond the scope of this study, this single item was used to assess immigration status. A

large proportion of the sample indicated that they were not born in Canada, and as such, the

immigration status variable was dichotomized into “Not born in Canada” and “Born in Canada”

for all analyses.

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8.3 Clinical characteristics

Clinical characteristics encompassed the type of cancer and time since diagnosis (3 items), type

of cancer treatment (3 items), number of co-morbidities (1 item), symptom burden (14 items),

and association with cancer (4 items). The cancer diagnostic and treatment related information

were extracted from the participant’s medical chart and recorded on the Data Extraction Form

(Appendix G). The information about number of comorbidities and symptom burden were

collected on the self-report Demographic Form (Appendix F) and IPQ-R questionnaire

(Appendix K), respectively. Data about the participant’s association with cancer were collected

on the Demographic and Data Extraction Forms. Additionally, 3 items related to time since

cancer treatment (chemotherapy, radiation therapy, and other cancer treatment) were collected

for secondary analysis. After data collection was complete, the frequency distributions for each

categorical clinical variable were examined and, where theoretically cogent, categories with low

frequencies were combined while attempting to maintain the variability within the sample.

8.3 Type (pathology) & time since cancer diagnosis

The type and time since cancer diagnosis was captured using 3 items to capture categorical and

continuous data about: year of diagnostic surgery, cancer type, and staging. This

operationalization was based upon the conceptualization presented in Chapter 3.

a) Time since cancer diagnosis was recorded and analyzed as a continuous variable that

subtracted the year of the most recent surgery to diagnose cancer from the year of survey

completion. This calculation indicated the number of years that had passed since diagnosis using

data extracted from the participant’s medical chart.

b) The data about cancer type were extracted from the participant’s medical chart, and recorded

as a categorical variable: breast, GI (colorectal, gastric, esophageal), testicular, gynecological

(cervix, uterus, ovary), melanoma, thyroid, and other (specified). These diseases were selected

based upon the cancer diagnoses followed at the ACTT clinic. The majority of the sample had

been diagnosed with breast cancer, and as such, the diagnosis (type) variable was dichotomized

into “Breast Cancer” and “All other cancers” for all analyses.

c) The data about cancer staging were extracted from the participant’s medical chart, and

recorded as a categorical variable using the American Joint Committee on Cancer (AJCC)

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staging system for the cancer type (202). A large proportion of the sample had been diagnosed

with stage 0 or 1 cancer, and as such, the AJCC stage variable was dichotomized into “Stages 0-

1” and “Stages 2-4 and missing” for all analyses.

8.3.2 Any cancer treatment

The receipt of any cancer treatment was represented as a single item for data analysis, but was

collected as 3 categorical items about whether chemotherapy, radiation therapy, and other

therapy were received (yes/no). An additional 3 items were captured as continuous data to

indicate the time since last cancer treatment. The continuous data were collected for secondary

analyses.

a) Binary data (yes/no) was captured to indicate whether chemotherapy was received and

whether the regimen was completed, whereas the date of last treatment was captured as a

continuous variable (yyyy). The date of last treatment was subtracted from the date of survey

completion to determine the time in years since last treatment.

b) Binary data (yes/no) was captured to indicate whether radiation therapy was received and

whether the regimen was completed, whereas the date of last treatment was captured as

continuous variable (yyyy). The date of last treatment was subtracted from the date of survey

completion to determine the time in years since last treatment.

c) Binary data (yes/no) was captured to indicate whether any other therapy was received and

whether the regimen was ongoing or was completed, whereas the date of last treatment was

captured as continuous variable (yyyy). The date of last treatment was subtracted from the date

of survey completion to determine the time in years since last treatment.

8.3.3 Number of co-morbidities

One item derived from the Self-Report Generated Charlson Comorbidity Index (203) and

founded upon the valid and reliable Charlson Comorbidity Index (204) was used to determine the

number of co-morbidities that a participant has. Participants were asked “As far as you know, do

you have any of the following health conditions at the present time?” to which they indicated the

presence (yes/no) on a list of co-morbidities: 1) asthma, emphysema, chronic bronchitis; 2)

arthritis or rheumatism; 3) diabetes; 4) digestive problems (such as ulcer, colitis, or gallbladder

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disease); 5) heart trouble (such as angina, congestive heart failure, or coronary artery disease); 6)

HIV illness or AIDS; 7) kidney disease; 8) liver problems (such as cirrhosis); 9) stroke; and 10)

other (specify). This adopted list contains all but the question about a cancer diagnosis from the

Self-Report Generated Charlson Comorbidity Index (203), which was not collected due to its

redundancy of the study objectives. The Number of Co-Morbidities variable was captured as a

continuous variable on the Demographic Form indicating the number of co-morbidities that the

participant was currently experiencing.

8.3.4 Symptom burden

The first section of the Illness Perceptions Questionnaire – Revised (IPQ-R) comprises the

Identity subscale, on which participants indicate (yes/no) to each of the listed 14 symptoms they

have experienced, and whether the participant believes (yes/no) the symptom is related to their

illness (103). The sum of the items to which participants reported “yes” on this second set of

questions forms the Identity-subscale of the IPQ-R (103). Higher scores represent stronger

beliefs about the number of symptoms attributed to the illness (103). The symptom burden

variable was captured as a continuous variable reflecting the number of symptoms participants

have experienced and believed to be related to their cancer diagnosis. Acceptable Cronbach’s

alpha’s of the entire IPQ-R has been demonstrated in samples of cancer survivors (42,46).

8.3.5 Associations with cancer

The operationalization of associations with cancer were based upon the conceptualizations

presented in Chapter 3. The associations with cancer variable encompassed items that addressed

the survivor’s personal experience with cancer recurrence, the previous receipt of a metastatic,

recurrence or another primary cancer diagnosis, and the participants current care status with the

ACTT. The information was collected on the self-report Demographic Form (Appendix F) and

Data Extraction Form (Appendix G).

a) The survivor’s personal experience with cancer recurrence was assessed by 2 categorical

items: 1) “In your personal life, is/was there someone close to you who had a diagnosis and

treatment for cancer, and then the cancer came back (cancer recurrence)?”; 2) “Has that person’s

cancer returning affected your fear that your cancer may come back?”. The responses to these

questions are “yes”, “no”, and “don’t know”.

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b) Data were extracted from the patient’s medical chart about whether they previously had

metastatic disease, a cancer recurrence, or another primary cancer (1 item). This information

was recorded on the Data Extraction Form (Appendix G).

c) The participant’s status with the ACTT clinic was assessed by a single question: “What is your

relationship with the ACTT clinic?” to which they responded by either “I am currently being

followed by the ACTT clinic staff” or “I have been discharged from the ACTT clinic and am no

longer followed by the ACTT clinic staff”. This data were completed by the participants on the

Demographic Form.

8.4 Self-Identities

Self-Identities encompassed the conceptual variables of self-esteem, personality and generalized

expectancies. Data were collected using standardized measures that were completed by study

participants (Appendix H –J).

8.4.1 Self-Esteem

The Rosenberg Self-Esteem Scale (RSES) (174) is a widely used assessment of self-esteem

among psychosocial oncology researchers (205). Participants are asked to rate the 10 items on

the RSES on a Likert-type scale varying from “Strongly agree” to “Strongly Disagree”. Five of

the items on the scale are worded and scored positively, and the other 5-items are worded and

scored negatively (174). The overall score (minimum to maximum: 0 to 30) is calculated to

reflect an overall global self-evaluation (172), where higher scores indicate higher self-esteem

(174), and scores greater than 20 suggest extremely high self-esteem (172).

Among cancer samples, the RSES has demonstrated Cronbach’s alphas varying from .76 to .87

(38,206,207), and acceptable test-retest reliabilities have been established (208,209). The

validity of the scale has been documented (210). The internal consistency of the RSES within

this study’s sample was α=.897. Using Ponterotto et al.’s (197) reliability matrix to estimate the

adequacy of internal consistency coefficients, the RSES had excellent internal consistency

reliability.

The total scores of the RSES revealed a non-normal distribution (skewness = 3.625, and kurtosis

= 13.070), and an exploration of the means and standard deviations indicated the presence of

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outliers (defined as a score more than 3 SDs (198). The presence of these outliers did not affect

the objectives of the study (e.g. prevalence of the outcome variable) and were therefore reported

for transparency. Similarly, the presence of outliers did not affect the second and third

objectives of this study since this analysis used the robust maximum likelihood method (MLR),

which can handle non-normal data distributions (211). These descriptive statistics are detailed in

Appendix P. The RSES is found in Appendix H.

8.4.2 Personality

The 44-item Big Five Inventory (BFI) was developed in order to provide a brief, reliable, and

valid instrument to assess the most central trait adjectives (extraversion, agreeableness,

conscientiousness, neuroticism, and openness) commonly referred to as the “Big Five

Personality Traits” (175). However, in an effort to further reduce response burden and to

improve the timeliness of assessing the Big Five Personality Traits, the 10-item Big Five

Inventory (BFI-10) was developed while maintaining acceptable reliability and validity (180).

Two items representing each of the Big Five dimensions were selected from the original BFI-44

based upon a set of clearly set criteria (180). One item from each dimension is reverse scored.

Participants are asked to rate how well each of the 10 items describe their personality on a 5-

point scale ranging from strongly agree (5) to strongly disagree (1). The scores for each of the

dimensions are presented out of 10, where higher scores indicate more frequent presentation of

that particular personality trait.

Part-whole correlations varying from .74 to .88 indicate that the results of the BFI-10 are

generalizable to the full BFI-44, and 8-week test-retest reliabilities have varied from .65 to .79

(180). Structural and convergent validity of the BFI-10 as also been established (180). The

internal consistency of the BFI-10 subscales within this study’s sample ranged from α=.008-

.635. Using Ponterotto et al.’s (197) reliability matrix to estimate the adequacy of internal

consistency coefficients`, the reliabilities of the BFI-10 subscales were all deemed to be

unsatisfactory, and raised initial concerns about whether the measure was capturing the construct

it was intended to.

The scores of the BFI-10 subscales revealed normal distributions (skewness ranged from -.928- -

.012, and kurtosis ranged from -.850 - .090). An exploration of the means and standard

deviations of the subscale scores indicated the absence of outliers (defined as a score more than 3

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SDs (198). These descriptive statistics are detailed in Appendix P. The items of the BFI-10 are

found in Appendix I.

8.4.3 Generalized Expectancies

Based upon the lack of measures to assess generalized (versus outcome) expectancies, Scheier et

al. (181) developed the Life Orientation Test (LOT). A decade thereafter, two-items assessing

coping were removed from the LOT to make a more focused measure of expectations (115). The

Revised Life Orientation Test (LOT-R) was highly correlated with the original LOT (r=.95,

p<.001) (115) suggesting the continued relevance of the revised measure. Both of these

measures fit the conceptualization presented in Chapter 3, in that they were developed upon

Scheier et al. (181) and Scheier et al. (115) conceptualizations of the generalized expectancies

spectrum of optimism-pessimism. For each of the 10-items of the LOT-R, participants indicate

their level of agreement (‘strongly agree’ to ‘strongly disagree’). Apart from the 4 filler items,

responses are summed to obtain an overall optimism score (minimum to maximum: 0 to 24)

(115).

The LOT-R has demonstrated appropriate convergent and divergent validity, and test-retest

reliability (115). Among cancer patients and survivors, the LOT-R has established acceptable

Cronbach’s reliability (40,127). The internal consistency of the LOT-R within this study’s

sample was α=.804. Using Ponterotto et al.’s (197) reliability matrix to estimate the adequacy

of internal consistency coefficients, the LOT-R had excellent internal consistency reliability.

The LOTR scores revealed a normal distribution (skewness = -.406, and kurtosis = .107). An

exploration of the means and standard deviations of the LOT-R scores indicated the presence of

outliers (defined as a score more than 3 SDs (198). The presence of these outliers did not affect

the objectives of the study (e.g. prevalence of the outcome variable) and were therefore reported

for transparency. Similarly, the presence of outliers did not affect the second and third

objectives of this study since this analysis used the robust maximum likelihood method (MLR),

which can handle non-normal data distributions (211). These descriptive statistics are detailed in

Appendix P. The items of the LOT-R are presented in Appendix J.

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8.5 Mediating Variables

8.5.1 Illness Representation

The Revised Illness Perceptions Questionnaire (IPQ-R) was developed to assess the cognitive

and emotional representations of illness, and is theoretically founded upon Leventhal’s

Common-Sense Model of Self-Regulation (103). The IPQ-R comprises 70 items confirming 7

theoretically derived factors: identity, timeline, consequences, control, illness coherence,

emotional representations, and causal (103). These dimensions are presented in three sections of

the IPQ-R. The first section comprises the identity subscale, which has been described above

(Chapter 4, Section 8.3.4). The second section comprises 38 items forming the Timeline,

consequences, control, illness coherence, and emotional representations subscales, where

participants use a 5-point scale to indicate from 1 (strongly disagree) to 5 (strongly agree) for

each statement (212). A higher score on the consequences and timeline subscales indicate more

negative consequences of the illness, stronger beliefs about the chronicity of the illness, and that

the nature of the illness is cyclical (212). Higher scores on the control and coherence dimensions

mean that the person has stronger beliefs about the controllability of their condition and have a

higher understanding of the condition (212). The third section comprises 18 items that assess the

person’s perceived causes of their illness, and use the same 5-point scale identified above (212).

The IPQ-R has documented acceptable internal consistency based on Cronbach’s alpha’s of .77

to .89, although lower Cronbach’s alpha’s of .23 and .67 have been demonstrated for 2 factors on

the causal dimension (103). Acceptable Cronbach’s alpha’s have been demonstrated in samples

of cancer survivors (42,46). Test-retest reliabilities have been demonstrated, as has discriminant

validity (103). The internal consistency of the IPQ-R subscales within this study’s sample

ranged from α=.737- .913. Using Ponterotto et al.’s (197) reliability matrix to estimate the

adequacy of internal consistency coefficients, all of the IPQ-R subscales had good or excellent

internal consistencies, except for the Treatment Control subscale which had a moderate

Cronbach’s alpha.

The scores of the subscales revealed normal distributions (skewness ranged from -.351 to .229

and kurtosis ranged from -.791 to -.036). An exploration of the means and standard deviations of

the subscale scores indicated the presence of outliers among all subscales (defined as a score

more than 3 SDs (198). The presence of these outliers did not affect the objectives of the study

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(e.g. prevalence of the outcome variable) and were therefore reported for transparency.

Similarly, the presence of outliers did not affect the second and third objectives of this study

since this analysis used the robust maximum likelihood method (MLR), which can handle non-

normal data distributions (211). These descriptive statistics are detailed in Appendix P. The

IPQ-R is presented in Appendix K.

8.5.2 Coping Styles

Coping measures can be categorized into those that assess coping skills (behaviours and

cognitions that change at the time of a stressful event) or those that assess coping style (a

descriptive concept that is trait-like) (213–215). As previously mentioned, this study utilized

measures that were developed upon the premise of a stable construct, such as the Brief COPE

(126), which was used to assess Coping Styles.

The Brief COPE (126) is an adaptation of the COPE Inventory (216) which was developed using

a theoretical model of coping (123), a model of self-regulation (181,217), and research findings

from pre-existing coping measures. Factor analyses resulted in a 60-item inventory with 15

subscales, which demonstrated acceptable internal consistencies, retest reliabilities, and

convergent and divergent validity with a number of personality measures (216). Furthermore, a

similar factor structure of the COPE Inventory was established via a test of dispositional versus

situational wording (216) appropriating it’s use to assess coping generally or specifically.

Based on the recognition of redundant items in the COPE Inventory, as well as the burden of

respondents to complete the entire measure, the Brief COPE was developed (126). The result

was a 28-item measure reflecting 14 different subscales: active coping, planning, positive

reframing, acceptance, humour, religion, using emotional support, using instrumental support,

self-distraction, denial, venting, substance use, behavioural disengagement, and self-blame (126).

The factor structure of the Brief COPE is similar to the full COPE Inventory (126), thus

suggesting its continued validity as a measure of coping. Respondents are asked about the ways

you’ve been coping with the stress in your life and use a 4-point Likert scale to respond (1 = I

haven’t been doing this at all to 4 = I’ve been doing this a lot). However, the developers claim

that the wording of the instructions, items and response options can be altered to assess

dispositional coping (126). Since dispositional characteristics were the focus of this study, the

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format of the Brief COPE was altered to reflect this (e.g. 1=I don’t do this at all, 2=I do this a

little bit, 3=I do this a medium amount, 4=I do this a lot).

Since the Brief COPE does not provide an overall coping score, the developer (218) suggests

reviewing each of the scales in relation to the variables, or that second-order factors be created

from the data to be used as predictors. In keeping with the latter, Bellizzi et al. (127) used this

strategy in a sample of breast cancer survivors finding that two factors (active adaptive and

escapist coping) explained 48% of the variance. Lydon (35) also followed this method, however

the variances of coping in FCR were not indicated. Following the coping factor results of

Bellizzi et al. (127) and Lydon (35), this study used all 28 items of the Brief-COPE (126) into 2

distinct Coping Styles: Active Coping and Escapist Coping4. Coping Styles were analyzed as

mediators of FCR.

Each of the 14 subscales of the Brief COPE has demonstrated acceptable reliabilities (126): 11

having internal consistencies greater than or equal to .60, and the others greater than or equal to

.50. The internal consistency of the Brief COPE subscales within this study’s sample ranged

from α=.527- .925. Using Ponterotto et al.’s (197) reliability matrix to estimate the adequacy of

internal consistency coefficients, only the Substance Use, Emotional Support, Instrumental

Support, Humour, and Religion subscales were classified as having good or excellent internal

consistency. Although the active, positive reframing, planning and self-blame subscales of the

Brief COPE are classified as having fair to moderate internal consistency reliabilities, the

reliabilities of the remainder of the Brief COPE subscales (self-distraction, denial, behavioural

disengagement, venting, and acceptance) were deemed to be unsatisfactory in this sample.

The scores of the substance use subscale revealed non-normal skewness (2.359), and all of the

subscale scores revealed a normal kurtosis (-1.399 - 5.789). An exploration of the means and

standard deviations of the subscale scores indicated the absence of outliers (defined as a score

more than 3 SDs (198). These descriptive statistics are detailed in Appendix P. The Brief COPE

is found in Appendix L.

4 The items within each of the Brief COPE subscales (126) remained together in the current study’s

operationalization of Coping Styles. Active Coping Style included the self-distraction items (Brief COPE items 1 &

19), active coping items (Brief COPE items 2 & 7), emotional support items (Brief COPE items 5 & 15), instrumental support items (Brief COPE items 10 & 23), venting items (Brief COPE items 9 & 21), positive

reframing items (Brief COPE items 12 & 17), planning items (Brief COPE items 14 & 25), acceptance items (Brief

COPE items 20 & 24), and religion items (Brief COPE items 22 & 27). An Escapist Coping Style included the

denial items (Brief COPE items 3 & 8), behavioural disengagement items (Brief COPE items 6 & 16), substance use

items (Brief COPE items 4 & 11), and self-blame items (Brief COPE items 13 & 26).

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9 Ethical Considerations

After approval was granted from the REB at WCH, an application for an Administrative Review

was submitted to the Office of Research and Ethics at the University of Toronto (219). Once

ethics approval was granted by both boards, study recruitment began.

Only subjects that offered free and informed consent were entered into the study. A signed

consent form was not required to be received by the investigator since implied consent was

obtained from participants, as was stated in the first statement of the survey package: “Clearly

print/type your full initials [F/M/L] and date of birth [mm/yy] indicating that you have read and

fully understand the information provided in the consent form”. With their consent, participants

allowed the researchers will access their medical charts to retrieve information to complete the

Data Extraction Form. Consent was ongoing throughout the study, whereby the participants

were free to withdraw from the study at any time, and the researchers would have promptly

inform the participants of any ethical issues that arise during the course of the study. No

participants withdrew consent from participating in the study and no ethical issues arose during

the conduct of the study.

Consideration was given to the privacy and confidentiality of participants. The completed

questionnaires and data extraction forms were ‘de-identified’, containing only participant study

numbers. These documents were securely stored in a locked cabinet located in an office that was

locked when the researcher was absent. The electronic surveys were collected and stored on the

FluidSurveys™ platform. FluidSurveys™ is compliant with Canadian privacy laws and

accessibility standards, and all data reside on Canadian servers (220).

A log of study numbers was linked to participant identifiers and consent forms were secured in

another locked cabinet within the researcher’s office. All electronically stored data were kept on

an encrypted device. The consent form assured participants that their privacy was of utmost

importance to the researchers alluding to the above-mentioned practices. Furthermore,

participants were informed that only aggregate findings would be presented to persons beyond

the research team.

The completion of this questionnaire was not expected to result in any negative effects.

However, should a participant have expressed a heightened amount of distress after completing

this questionnaire, they were encouraged to contact the ACTT clinic staff who would organize

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referrals to appropriate psychosocial professionals (S. Maura, personal communication, 2014).

There were no such concerns raised during the conduct of the study and therefore these resources

were not needed.

10 Data Analysis

10.1 Data Management

After each of the measures were scored per the developers guidelines, the data were entered into

Microsoft Excel 2013. A continuous sampling plan (CSP) (221) was employed to verify the

accuracy of data entry by the researcher. When using the CSP method, the researcher compared

the first ten entries in the data set of a single item to the corresponding item responses indicated

by the research subject on their survey (221). If these ten entries were correct, the researcher

continued with data entry assessing every tenth entry (221). If an inaccuracy was found, the

researcher made the correction and returned to checking 100% of the entries until ten entries

were correctly entered, and so forth (221).

10.2 Statistical Analysis

After the data were completely and accurately entered, IBM Statistical Package for the Social

Sciences (IBM SPSS Statistics version 22) was used to conduct descriptive analyses. Data about

geographical location in Ontario, and rural or urban location were abstracted from the clinical

database for the entire sampling frame and used to report on the characteristics of respondents

and non-respondents.

Next, the amounts of missing values for the raw data were explored. Where available, the

developer’s guidelines about acceptable amounts and patterns of missing data were used for

reference. Such information was available for only the FCRI (30) and IPQ-R (103). For the

remaining measures, cases with 0 versus ≥1 items missing on each measure were compared.

Independent t-test (for continuous data) and Chi-square test (for categorical data) were used to

determine if any significant differences existed between the cases with missing data and those

without (or with an acceptable amount of missing-ness, see above). Thereafter, cases missing

data for ≥1item on a measure without published guidelines about acceptable amounts of missing

data were excluded listwise from the analysis. Listwise deletion enables the analysis of a

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complete dataset without negative definite matrices (222) that is more amenable to Structural

Equation Modeling (SEM), which was analysis method used to explore Objectives 2 and 3.

Descriptive statistics were used to summarize each study variable (i.e. frequency tables with

percentages, measures of central tendency, and measures of dispersion). Thereafter, analyses to

address the research objectives, described in the following sections, were conducted using SPSS

(223) and Mplus (224) software, as appropriate. Statistical significance was set at α ≤ 0.05 for all

analyses.

10.3 Objective 1

To address the primary objective of this study, to estimate the prevalence of FCR in a sample of

adult cancer survivors, the score of the FCRI-Severity Subscale (range 0-36) was transformed

into a binary variable using the established cut off of ≥13 indicating a clinically-significant level

of FCR (138). In other words, this study calculated FCR prevalence by dividing the number of

cases with clinically-significant FCR by the total sample size. Although the descriptive statistics

for the FCRI-Severity Subscale were calculated, these were not applied to the prevalence

calculation but instead were reported for transparency.

10.4 Objectives 2 and 3

To address objectives 2 and 3, which explored the direct and indirect (i.e. mediating) effects of

demographic, clinical and psychosocial predictors on FCR, structural equation modeling (SEM)

was used. SEM is unique from other statistical approaches, such as regression analysis and path

analysis, because it allows researchers to explore the relationships among latent (unobserved)

variables and observed variables (191,225–227) as opposed to analysing observed variables only

(226,228). The most general type of SEM analysis is the Structural Regression (SR) Model,

which is a synthesis of path analysis and confirmatory factor analysis (CFA) (190,191,227) in

that it simultaneously tests 2 types of models: a theoretical/structural model and a measurement

model (191,229). In this way, the relationships of the variables are explored (similar to that of

multiple regression or path analysis), while also correcting for the measurement error through the

use of latent variables (similar to that of CFA) (226,227). Since the Predictors and Mediators of

Fear of Cancer Recurrence Conceptual Framework (Figure 1) that guided this study was

comprised of both latent and observed variables, an SR model was an appropriate method to use.

Mplus Version 7.2 (224) was used for this analysis.

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All Objective 2 and 3 analyses used the FCRI total scores as a continuous outcome variable.

Being that an intent of the current project was to add clarity to the conflicting empirical findings

related to the predictors and mediators of FCR (see Chapter 2 Section 6.1, and Chapter 3

Sections 6.0 and 7.0), and that most of the existent empirical understanding of FCR utilized a

continuous measure to capture FCR, a decision was made to analyze FCR as a continuous

variable. It was believed that this would facilitate comparisons of the current study’s results to

those published in the literature. Although an exploration of the predictors and mediators of

clinically-significant FCR (as described in Section 10.3 above) would have clinical utility,

researchers are cautioned against dichotomizing a continuous variable which reduces statistical

power among other analytic costs (230,231). For these reasons, the decision to analyze FCR as a

continuous variable was believed to be most ideal.

As this study included a large number of variables, prior to conducting the SEM, correlations or

regressions among variables were calculated to ensure that unnecessary or redundant variables

were not included. This process ensured that the models would be: 1) parsimonious (see Section

10.4.2); and 2) over-identified (see Section 10.4.1). The following criteria were used to identify

candidate variables for removal: 1) those very strongly correlated with another variable (r >.80);

2) those unrelated to FCR (p >0.05 and/or trivial size of effect (r <.10 or r2 <.01, (232)); or 3)

multicollinear variables, defined by a variable inflation factor (VIF) greater than 5 (233). The

detailed results of these analyses are found in Appendix Q.

Once the initial model trimming was completed, the SEM analysis was undertaken following 5

commonly-used steps: 1) model specification; 2) model identification; 3) estimation; 4) test of

fit; and 5) model re-specification or modification (190,191,228).

10.4.1 Model Specification

The first step, model specification, requires the researcher to specify hypothesized relationships

among the variables, and to determine how the latent variables will be measured (117,191). This

step is based upon knowledge of the theoretical and/or empirical literature, and results in the

production of a diagram of hypothesized multivariate relationships, referred to as the SR model

(191,228). The SR model is comprised of latent variables that are depicted as ovals, and

measured indicators that are depicted as rectangles. The arrows between the variables represent

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hypothesized relationships between the variables. Models should be a simple as possible,

referred to as parsimony (191,226).

Using the theoretically and empirically-based relationships in the Predictors and Mediators of

Fear of Cancer Recurrence Conceptual Framework (Figure 1), and keeping with the objectives of

this research, it is hypothesized that a variety of demographic, clinical and psychosocial variables

predict overall FCR. It is also hypothesized that illness representations and coping styles are

mediating variables between these predictors and FCR.

10.4.2 Model Identification and Model Estimation

The second step in SEM analysis, model identification, requires the researcher to determine

whether it is possible for statistical software to estimate the parameters of the model given the

amount of information available (191). Parameters, indicated by the arrows in the specified

model, can be understood as the hypothesized relationships among the variables (229), and are

resulted as path coefficients. As it will be shown in the subsequent chapter, all of the models

were over-identified as demonstrated by positive degrees of freedom (191).

Another criteria for model identification is that recursive models, those that contain only

unidirectional and not bidirectional relationships, can be identified (191). The Conceptual Model

for this study (Figure 1) does not have feedback loops, thus indicating that it was, indeed,

recursive.

The next step in SEM involves the estimation of model parameters (190). To do this, a variety of

estimation techniques are available, including, most commonly, maximum likelihood (234).

However, an assumption of maximum likelihood is multivariate normally (235), and although

scores on the FCRI appeared normally distributed (more on this later), those of some of the other

measures in the model deviated from normal. For the current analysis, therefore, a robust

maximum likelihood method estimator (MLR), which is robust in relation to non-normality

(211,224), was used.

10.4.3 Test of Fit

Anderson and Gerbing’s (1988) two-step approach to modeling is useful to guide the researcher

in the last step of the SEM process: test of fit. Model fit indices enable the researcher to

determine how well the hypothesized model (either measurement or structural) ‘fits’ the

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observed data (236), and is an important step in SEM analysis. In the first step, the measurement

aspects of the model are analyzed to determine how well they fit the data (191). To do this, a

CFA was conducted to determine the fit of the data to each measure. Goodness of fit was

assessed using the Root Mean Square Error of Approximation (RMSEA) and 90% Confidence

Interval (CI), the comparative fit index (CFI), and Tucker-Lewis Fit Index (TLI), which will be

described in the following paragraphs. Although the chi-square statistic is a commonly reported

index of model fit (237) it is sensitive to sample size and is often is statistically significant in

large samples (191,238). As such, it is reported herein for information purposes only.

The RMSEA is regarded as one of the most informative fit indices (239). The recommendations

for the RMSEA cut-off indicating ‘good fit’ ranges from 0.06 (240) to 0.07 (241). For this

study, a good fit of the models was indicated by an RMSEA ≤ 0.07 (241). Other commonly

referred to fit indices include the comparative fit index (CFI) and the Tucker-Lewis Fit Index

(TLI). For this study, good fit of the models was indicated by a CFI ≥ 0.94 and TLI ≥ 0.94

(240).

Each of the measurement models were initially fitted as per their original development and

method of scoring. Where a poor measurement fit was determined, alternative measurement

models were sought from the literature, while striving for the most parsimonious model possible.

When appropriate5, the items for each survey or subscale were ‘parcelled’ so as to reduce the

number of parameters to be estimated in each of the models. Item parcelling has demonstrated

benefits in SEM analyses, including the tendency to improve model efficiency and provide more

stable estimates and better data fit than item-based data (242). Furthermore, the use of item

parcels has a tendency to result in more normal-like distributions (242,243).

After the measurement models were fitted, the full SEM models for each objective were tested

(244). First, the direct effects of the independent variables on FCR were modeled (Objective 2).

Because this study included a large number of variables, prior to analyzing the models of indirect

effects (Objectives 3a and 3b), single mediation models were tested to estimate the direct and

indirect effects of each independent variable on FCR separately. Only independent variables that

had a significant (p-value =.05) direct or indirect effect with FCR (Appendix S) were retained

and included in the full mediation model for each objective. Thereafter, mediation in the full

5 Matsunaga (242) recommends that 3 parcels be formed per factor. Where a factor contained 3 or fewer items,

parceling was not conducted, and the individual items were used in the CFA. In all other instances, items within a

factor were randomly assigned to 1 of 3 parcels in any given factor.

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models were investigated and direct and indirect pathways were identified. Indirect effects were

tested using bootstrapped standard errors and 95% confidence intervals. Bootstrapping a

statistical technique in which many, in the case of this study 500 was selected (234),

pseudoreplicate samples are drawn from a dataset (235). The process is useful to calculate

confidence intervals (234) for the estimates resulting from an SEM analysis.

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Chapter 5 Results

The results are described in 5 sections. In the first section, an overview of the sampling frame is

provided, a comparison of participants to non-participants, and an analysis of missing data are

described. The subsequent 3 parts present the results corresponding to each of the 3 objectives.

The results of Objective 1 pertain to the prevalence of clinically-significant FCR. The results of

Objectives 2 and 3 relate to the direct and indirect relationships of the independent variables with

FCR.

1 Study Sample

1.1 Study Participation

All 2,143 patients from the After Cancer Treatment Transition (ACTT) clinic were mailed an

Information Letter about the study in January 2015. Respondents who returned the study

documents (described in Chapter 4, Section 8) were screened for eligibility using the information

provided in the study documents, as well as the data extracted from a medical chart review.

Based upon this information, as well as that generated during the telephone reminder calls, 128

patients were ineligible to participate in the study, due to language barriers (n=54), current use of

chemotherapy or radiation treatment for cancer (n=5), cognitive impairment as determined by

physician (n=3), were deceased (n=14), or lost to follow up (e.g., current address not available to

mail study documentation, n= 52). Of the 2,015 patients that met the eligibility criteria and were

mailed the Information Letter for participation, 1,002 consented to participate in the study and

completed the study measures (49.7 % participation rate). Nine hundred fifty-five (95%) of

these responders completed the study measures in hard-copy whereas the remainder completed

the measures electronically. Figure 3 presents a flow chart of recruitment and participation into

the study.

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Figure 3. Flow Diagram of Study Recruitment and Participation

Using the contact details that were readily available from the ACTT database, cross tabulations

were used to compare the geographical distribution (postal codes) of responders to non-

responders. Ethics approval was not obtained for a medical chart review of non-consenting

subjects, therefore no additional variables were available to be analyzed for non-responders. A

Kruskal-Wallis test was used to assess whether response status differed by geographical location

(denoted by the first letter of the postal code) and rural/urban location (denoted by the first

number of the postal code). Where the expected cell count was ≤ 5, the Fisher’s exact test was

used. There were no significant differences in the geographic distribution nor urban/rural status

by response status.

Table 3. Comparison of Responders to Non-Responders

Variable Kruskal-

Wallis/

Fisher’s

Exact

df 2-sided Sig.

Ontario Geography1 8.23 - 5 0.144

Urban/Rural Status - 0.630 1 0.595

1 Categories as defined by Canada Post Corporation’s definitions: Eastern Ontario; Central Ontario; Metro Toronto;

Western Ontario; Northern Ontario; Outside Ontario.

Potential participants (n=2,143) Ineligible (n=128)

Language barrier n=54

Current chemo/radiation n=5 Cognitive impairment n=3

Deceased n=14

Undeliverable n=52 Eligible participants (n=2,015)

Did not consent (n=1,013)

Decline participation n=273

No response n=740 Number of participants included in study (n=1,002)

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1.2 Participant Characteristics

Participant characteristics are shown in Tables 4 and 5. The mean age was 61.1 years (range 23-

98 years). Just over 85% of the sample was female, 61.8% of the sample was married, and

73.7% had children. Nearly 30% had received some graduate-level education, while nearly 46%

of the sample was currently employed. Most identified as Caucasian (77.4%) and 43.7% were

not born in Canada. The majority of the sample lived in an urban centre (96.8%). The

demographic characteristics of the sample are summarized in Table 4 and detailed in Appendix

N.

Sixty-six percent of the sample had a diagnosis of breast cancer. The average time since

diagnostic surgery was 9.1 years (range 1-36 years). Eighty-seven percent of participants had

had any type of cancer treatment. Nearly 56% received chemotherapy, 64.6% received radiation,

and 63.4% received another form of treatment (e.g. aromatase inhibitors for breast cancer

treatment). Of those who had received chemotherapy, the mean time since treatment completion

was 8.3 years (range 1-29 years). The mean time since radiation treatment was 8.0 years (range

0-36 years), and for those who had completed another form of cancer treatment, the mean time

since completing that treatment was 4.8 years (range 0-20 years). A third of the respondents

(33.3%) were currently receiving adjuvant cancer treatment (e.g. aromatase inhibitors) at the

time of survey completion.

The patients in this sample had a mean of 0.81 (ranged from 0-7) comorbid conditions, the most

common of which was arthritis or rheumatism experienced by 29.8% of participants. Study

participants had experienced a mean of 1.7 symptoms since completing treatment for cancer

(ranged from 0-12 symptoms). The clinical characteristics of the sample are summarized in

Table 5 and detailed in Appendix N.

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Table 4. Demographic Characteristics of Participants

Characteristic N (%)

Age in years, mean (SD) 61.1 (12.0)

Sex

Female 852 (85.2)

Male 148 (14.8)

Marital status

Married or common-law 681 (68)

All other groups 321 (32)

Parental Status

Not Parent 261 (26.1)

Parent 739 (73.7)

Level of Education

Up to some university 446 (44.5)

Undergraduate university graduate or higher & other 556 (55.5)

Employment Status

Actively employed 543 (54.2)

Not actively employed 459 (45.8)

Ethnicity

White, Caucasian, or European descent 773 (77.4)

All other ethnicities 229 (22.9)

Immigration Status

Not born in Canada 437 (43.6)

Born in Canada 565 (56.4)

Residential Location in Ontario

Metro Toronto 637 (63.6)

Outside of Metro Toronto 365 (36.4)

Rural or Urban Location

Rural 32 (3.2)

Urban 970 (96.8)

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Table 5. Clinical Characteristics of Participants


Time (years) since diagnosis, mean (SD) 9.1 (5.1)

Diagnosis type

Breast cancer 661 (66.0)

All other cancers 341 (34.0)

AJCC stage

Stages 0-1 418 (41.7)

Stages 2-4 and missing1 584 (58.3)

Another cancer/recurrence/metastasis 219 (21.8)

Treatment received

Chemotherapy 550 (55.6)

Radiation 640 (64.6)

Other Cancer Treatment 628 (63.4)

Any Cancer Treatment received1

Yes 873 (87.1)

No 98 (0.097)

Co-Morbid Conditions, mean number (SD) .81 (.972)

ACTT status

Followed at clinic 733 (73.2)

Discharged from clinic 269 (26.8)

Know someone with recurrence

Yes 482 (48.5)

No/Don’t know 511 (51.4)

Knowing someone with recur affects FCR

Yes 250 (25.1)

No/Don’t know 747 (74.9)

1 Includes only chemotherapy, radiation therapy, or other cancer therapy

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1.3 Missing Data

Next, the amounts of missing values for the raw data were explored. The percentage of missing

data for the measures ranged from 0-8.7% (Table 6).

Table 6. Amounts of Missing Data by Measure

Measure % of Items Missing N (%) of cases missing

data1

FCRI 0.3 – 2.4 18 (1.7)

RSES 0.4 – 1.6 47 (4.6)

BFI 0.6 – 1.4 22 (2.1)

LOT-R 0.7 – 1.2 20 (1.9)

IPQ-R 3.8 – 8.7 127 (12.6)

Brief COPE 1.6 – 3.2 40 (3.9)

Demographic 0.1 – 0.3 3 (0.3)

Clinical 0.1 – 1.3 12 (1.1) 1 Missing data is calculated per published guidelines of unacceptable amounts of missing data, or if published

guidelines are not available, the number (%) of cases missing 1+ items are reported.

The number of cases that were missing data by numbers of items (i.e. 1-item, 2-items, etc.) on

each measure were recoded. The developers of the FCRI (30) and IPQ-R (103) guidelines

regarding acceptable amounts and pattern of missing data were used for comparison analyses. In

all other cases, the participants with 0 versus ≥1 items missing on a measure were compared.

Independent t-test (for continuous data) and Chi-square test (for categorical data) were used to

determine if any significant differences existed between the cases missing any or missing

acceptable amounts of data to those not missing or with acceptable amounts of data. Thereafter,

cases missing data for ≥1-item on a measure without published guidelines about acceptable

amounts of missing data, were excluded listwise from the analysis (see Chapter 4, Section 10.2

for additional information). The results of the missing data analysis is found in Appendix O.

2 Objective 1

The primary objective of this study was to assess the prevalence of Fear of Cancer Recurrence,

using the FCRI-Severity Subscale, among survivors of adult cancers. Among this sample, the

mean FCRI-Severity Subscale score was 14.81 (95% CI 14.33, 15.28) and the standard deviation

was 7.61. The scores ranged from 0-34 of the total possible range of 0-34. Of the total study

respondents, 577 had a FCRI Severity Subscale score ≥13 indicating that their level of FCR was

clinically-significant. This proportion was used to determine the FCR prevalence as 58.6% (95%

CI 55.52, 61.68) within this sample.

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3 Objectives 2 and 3

To specify the direct and indirect effects of the independent variables on FCR, structural

equation modeling (SEM) was used to address Objectives 2, 3a and 3b. As described in Chapter

4, Section 10.4, the FCRI-Total Score was used to capture FCR as the continuous outcome

variable. Because this study included a large number of variables, prior to conducting the SEM,

the relationships among variables were explored to ensure that there were no unnecessary or

redundant variables included in the models6. A description of these results are described in the

following sections, and detailed in Appendix Q.

3.1 Demographic Characteristics

All demographic characteristics in Table 4 were explored with each other and in relation to FCR.

More specifically, correlations were used for continuous independent variables, and linear

regression was used for nominal independent variables. The results of these analyses are

detailed in Table 7.

There was no multicollinearity noted among any of the variables. Marital status (R2=0.003),

parental status (R2=0.002), level of education (R2=0.001), employment status (R2=0.004),

immigration status (R2=0.004), ethnicity (R2=0.008), and rural/urban status (R2=0.003), were

deemed as having either no effect on FCR or an effect that was trivial4 in size and were removed

from subsequent multivariate analyses. Based upon the criteria stated in Chapter 4, Section 10.4,

age and sex were both related to FCR and remained in the models.

6 Candidate variables for removal: 1) those very strongly correlated with another variable (r>.80); 2) those unrelated

to FCR (p<.05 and/or trivial size of effect (r<.10; r2 <.01, (232)); and 3) multicollinear variables, defined by a

variable inflation factor greater than 5 (233). See Chapter 4, Section 10.4 for a full methodological description.

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Table 7. Exploratory Analysis of Demographic Characteristics with FCR

Variable Mean (SD) t-test (Sig.) β (Sig.) R2 VIF

Age in years 61.1 (12.0) -0.233 (<0.001)1 2.160

Sex 7.090 (<0.001) 0.203 (<0.001) 0.041 1.772

Men 44.01

Women 60.29

Marital Status 1.687 (0.092) 0.054 (0.090) 0.003 1.200

Married/Common-Law 58.87

All other groups 55.55

Parental Status 1.348 (0.178) 0.043 (0.173) 0.002 1.233

Parent 58.56

Not Parent 55.75

Level of Education 0.896 (0.371) 0.029 (0.368) 0.001 1.171

Up to some university 56.87

Undergrad graduate or higher

and other 58.53

Employment status 2.038 (0.042) 0.065 (0.042) 0.004 1.610

Actively employed 59.81

Not actively employed 56.08

Ethnicity 2.770 (0.006) 0.090 (0.005) 0.008 1.529

Caucasian 56.39

Non-Caucasian 62.53

Immigration status 2.057 (0.040) 0.066 (0.039) 0.004 1.403

Not born in Canada 59.27

Born in Canada 56.14

Urban/Rural Status 1.660 (0.107) 0.051 (0.108) 0.003 1.066

Urban 58.07

Rural 49.67

1Reported result is r representing a bivariate correlation coefficient.

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3.2 Clinical Characteristics

All clinical characteristics in Table 5 were explored with each other and in relation FCR. As

above, correlations were used for continuous independent variables, and linear regression was

used for nominal independent variables. The results of these analyses are detailed in Table 8.

There was no multicollinearity noted among any of the variables. Cancer stage (R2=0.002),

having had another cancer diagnosis (R2=0.003), number of comorbidities (r=0.015), and time

since diagnosis (r=-0.052), were deemed as having either no effect on FCR or an effect that was

trivial4 in size and were removed from subsequent multivariate analyses. Based upon the criteria

stated in Chapter 4, Section 10.4, diagnosis (type), knowing someone with a cancer recurrence,

belief that knowing someone with a recurrence affects FCR, ACTT clinic status, receipt of any

cancer treatment, and symptom burden were each related to FCR and remained in the models.

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Table 8. Exploratory Analyses of Clinical Characteristics with FCR


Diagnosis Type 5.098 (<0.001) 0.160 (<0.001) 0.026 2.472

Breast Cancer survivors 61.11

Non Breast Survivors 51.46

Diagnosis Stage 1.305 (0.192) 0.042 (0.191) 0.002 1.459

AJCC Stages 0-1 56.39

AJCC Stages 2-4 & missing 58.81

Chemotherapy 4.268 (<0.001) 0.136 (<0.001) 0.018 1.728

Yes 61.38

No 53.54

Radiation 3.432 (<0.001) 0.109 (0.001) 0.012 1.595

Yes 60.27

No 53.73

Other Cancer treatment 3.721 (<0.001) 0.117 (<0.001) 0.014 1.649

Yes 60.49

No 53.53

Any Cancer Treatment -3.783 (<0.001) 0.109 (0.001) 0.012 1.000

Yes 48.54

No 58.97

Know someone with recurrence 4.387 (<0.001) 0.127 (<0.001) 0.016 1.459

Yes and Don’t know 61.35

No 53.33

Believe knowing someone with

recur affects FCR 14.101 (<0.001) 0.395 (<0.001) 0.156

1.647

Yes 77.25

No and Don’t know 51.22

Another cancer diagnosis (B) 1.740 (0.083) 0.055 (0.084) 0.003 1.206

Yes 54.92

No 58.67

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Table 8 continued: Exploratory Analyses of Clinical Characteristics with FCR

1Reported result is r representing a bivariate correlation coefficient


ACTT clinic status 3.886 (<0.001) 0.120 (<0.001) 0.014 1.231

Current patient 59.85

Discharged patient 52.06

Number of Comorbidities 0.015 (0.645)1 1.286

Symptom burden 0.378 (<0.001)1 1.489

Time Since Diagnosis -0.052 (0.109)1 1.417

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3.3 Self-Identity Variables

Table 9. Self-Identity Characteristics of Participants

Characteristic Measure

Min-Max

Mean (SD) Sample

Min-Max

r (Sig.) with

FCR

Self-Esteem (RSES) 0-30 23.77 (5.226) 0-30 -0.342 (<0.001)

Personality (BFI-10)

Extraversion subscale 2-10 6.63 (2.073) 1-10 -0.049 (0.122)

Agreeableness subscale 2-10 7.75 (1.674) 1-10 -0.073 (0.023)

Conscientiousness subscale 2-10 8.41 (1.756) 2-10 0.009 (0.768)

Neuroticism subscale 2-10 5.63 (2.260) 1-10 0.354 (<0.001)

Openness subscale 2-10 6.94 (1.793) 2-10 0.048 (0.136)

Generalized Expectancies (LOT-R) 0-24 16.00 (4.299) 0-24 -0.348 (<0.001)

Correlations among all self-identity variables in Table 9 were explored with each other and in

relation to FCR. There was no multicollinearity noted among any of these variables. Four of 5

subscales measuring personality had no or very little effect on FCR (extraversion [r=-0.049,

p=0.122], agreeableness [r=-0.073, p=0.023], conscientiousness [r=0.009, p=0.0768], and

openness [r=0.048, p=0.136]). Although the remaining personality subscale (neuroticism) had a

significant, medium-sized relationship with FCR (r=0.354, p<0.001), a decision was made to

remove all of the personality subscales from remaining analyses. The rationale for this decision

was twofold: 1) the intention of this study was to explore personality in its entirety as it related to

FCR, and not only a single element of personality; and 2) the unsatisfactory reliabilities of the

personality subscales7 raised concerns that the measure was not measuring what it intended to

measure. Therefore, the remaining analyses occurred without inclusion of the personality

variables. As a result, the self-identity characteristics included only self-esteem and generalized

expectancies.

7 Reliabilities of the BFI-10 subscales ranged from α=0.008-0.635. These are detailed in Chapter 4, Section 8.4.2

and Appendix P.

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3.4 Illness Representations Variables

Table 10. Illness Representation Characteristics of Participants

Illness Representation

Subscale

Measure

Min-Max

Mean (SD) Sample

Min-Max

r (Sig.) with

FCR

Identity 0-12 1.71 (2.354) 0-12 0.378 (<0.001)

Timeline (Acute/Chronic) 0-30 13.97 (4.80) 6-30 0.399 (<0.001)

Consequences 0-30 17.27 (5.52) 6-30 0.461 (<0.001)

Personal Control 0-30 20.46 (4.187) 6-30 -0.053 (0.104)

Treatment Control 0-25 19.62 (3.021) 11-25 -0.205 (<0.001)

Illness Coherence 0-25 22.45 (5.103) 6-30 -0.295 (<0.001)

Timeline (Cyclical) 0-20 9.19 (3.313) 4-19 0.339 (<0.001)

Emotional Representations 0-30 17.05 (5.884) 6-30 0.698 (<0.001)

Correlations among all illness representation variables in Table 10 were explored with each other

and in relation to the FCR. There was no multicollinearity noted among any of the variables.

Only the illness representation-personal control subscale was deemed as having a trivial effect

size (r=-0.053) and was removed from subsequent multivariate analyses. All other subscales

were included in subsequent modeling (i.e. timeline (acute/chronic), timeline (cyclical),

treatment control, illness coherence, and emotional representation subscales).

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3.5 Coping Styles Variables

Table 11. Coping Style Characteristics of Participants

Brief COPE Subscale Measure

Min-Max

Mean (SD) Sample

Min-Max

r (Sig.) with

FCR

Self-Distraction 2-8 5.86 (1.634) 1-8 0.315 (<0.001)

Active Coping 2-8 6.17 (1.609) 1-8 0.033 (0.310)

Denial 2-8 2.81 (1.297) 1-8 0.288 (<0.001)

Substance Use 2-8 2.56 (1.180) 1-8 0.082 (0.011)

Emotional Support 2-8 5.17 (1.842) 1-8 0.091 (0.005)

Behavioural Disengagement 2-8 2.62 (1.088) 1-8 0.253 (<0.001)

Venting 2-8 4.20 (1.496) 1-8 0.221 (<0.001)

Instrumental Support 2-8 4.96 (1.850) 1-8 0.125 (<0.001)

Positive Reframing 2-8 5.49 (1.656) 1-8 -0.008 (0.806)

Self-Blame 2-8 3.66 (1.569) 1-8 0.076 (0.019)

Planning 2-8 5.83 (1.734) 1-8 0.320 (<0.001)

Humour 2-8 3.98 (1.792) 1-8 -0.003 (0.923)

Acceptance 2-8 6.47 (1.432) 1-8 -0.046 (0.149)

Religion 2-8 4.66 (2.271) 1-8 0.158 (<0.001)

The correlations among all coping variables in Table 11 were explored with each other and in

relation to FCR. There was no multicollinearity noted among any of the variables. Seven of the

Brief COPE subscales (active [r=0.033, p=0.310], substance use [r=0.082, p=], emotional

support [r=0.091], positive reframing [r=-0.008], planning [r=0.076], humour [r=-0.003], and

acceptance [r=-0.046]) also were deemed to have no or very little effect on FCR. However, the

active and escapist coping factors (35) that were central to the conceptual model guiding the

study (Chapter 4, Section 8.5.2) were significant (see Appendix Q) and thus, retained within the

models.

3.6 Resulting variables to be included in the Structural Models

Considering the above analyses and explanations, the following variables were retained for the

SEM analyses: age, sex, diagnosis (type), knowing someone with a cancer recurrence, belief that

knowing someone with a recurrence affects FCR, ACTT clinic status, receipt of any cancer

treatment, symptom burden, self-esteem, generalized expectancies, illness representations

(timeline [acute/chronic], timeline [cyclical], treatment control, illness coherence, and emotional

representation subscales), and coping styles.

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3.7 Test of Fit

The overall model8 explored in the current SEM analysis 2 models: a theoretical/structural model

and a measurement model (191,229). Prior to determining the fit of the structural models

describing the relationships among the latent variables (235), a confirmatory factor analysis

(CFA) was conducted to determine the fit of the data to each measure. Each of the measurement

models (see Table 12 for the analyses of the measures) were initially fitted as per their original

development and method of scoring. Where a poor measurement fit was obtained, alternative

measurement models were sought from the literature (236), while striving for the most

parsimonious model possible. This process is detailed in the following pages. Because the

theoretical/structural model and measurement model collectively contain a great deal of

information that is challenging to report (236), tables displaying the relationships between the

observed and latent variables (e.g. the measurement models) are indicated in Appendix P.

8 A model is the term used to describe the series of statistical statements representing the relationships among latent variables, referred to as the structural model, or as relationships among the latent variables and their observable

indicators, referred to as the measurement model (235). Schreiber et al. (236) describe these models as hypotheses

and that fit statistics are useful to determine how well a hypothesized model fits the observed data. A good fit of the

model was indicated by an RMSEA ≤ 0.07 (241) a CFI ≥ 0.94, and a TLI ≥ 0.94 (240). See Chapter 4, Section

10.4.3 for additional details.

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Table 12. Analyses of the Measurement Models

Measurement

Model χ2 χ2 Sig. df

RMSEA

Estimate

RMSEA

90%CI CFI TLI

Outcome Variable

FCRI1 819.434 <.001 180 0.060 0.055,

0.064 0.953 0.945

Predictor Variables

RSES2 165.922 <.0001 34 0.062 0.053,

0.072 0.955 0.940

LOT-R2 31.057 0.0001 8 0.054 0.035,

0.074 0.980 0.963

Mediating Variables

IPQ-R2 553.900 <.0001 168 0.049 0.044,

0.053 0.956 0.945

Brief COPE2 54.516 <.0001 9 0.072 0.054,

0.091 0.965 0.941

Measurement Models

Full ModelA

(without mediating

variables)

1537.824 <.0001 476 0.047 0.045,

0.050 0.946 0.941

Full ModelB

(with IPQ-R

included)

3259.986 <.0001 1302 0.039 0.037,

0.040 0.939 0.933

Full ModelC

(with Brief COPE

included)

2288.086 <.0001 672 0.049 0.047,

0.051 0.929 0.921

1Second-order confirmatory analysis; 2First-order confirmatory analysis. AMeasurement model used for Objective 2; BMeasurement model used for Objective 3a; CMeasurement model used for Objective 3b.

3.7.1 FCRI Measurement Model

The items in the 7 FCRI subscales were explored as factors in a secondary-order factor analysis

that loaded onto an eighth factor, the overall FCRI score. This model (χ2=4408.466, p<.0001,

df=812, RMSEA=0.067 [0.065, 0.068], CFI = 0.845, TLI = 0.835) resulted in an acceptable

RMSEA, however the CFI and TLI were less desirable and therefore other measurement models

were explored. In pursuit of another model, and in attempt to improve the parsimony of the

measurement model, the items within each subscale were randomly assigned to 3 parcels9 per

subscale, and each subscale treated as a factor that loaded onto an eighth factor. This model

(χ2=1017.293, p<.0001, df=182, RMSEA=0.068 [0.064, 0.072], CFI = 0.938, TLI = 0.929)

resulted in an acceptable RMSEA, however the CFI and TLI were less desirable. As the

measurement model is the basis for the fit of the overall SEM (235) it is important that the

9 See Chapter 4, Section 10.4.3 for a full description of item parceling.

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individual measures fit the data well and, thus, modification indices of this FCRI measurement

model was reviewed. Following the recommendations of Nachtigall and colleagues (2003),

modifications to the models were made only if relatively minor and theoretically sound (235).

For the FCRI, there was some indication that correlating the residual variances between two sets

of factors would improve the fit: the Triggers and Severity factors, and the Functional

Impairments and Insight factors. According to the FCRI developers (30), the Triggers and

Severity subscales, as well as the Functional Impairments and Insight subscales, share similar

amounts of variance in overall FCR. Furthermore, the items addressed by each pair of factors

concentrate on similar concepts (30): the Triggers and Severity subscales evaluate the presence

of stimuli, thoughts or images pertaining to FCR, whereas the Functional Impairements and

Insight subscales evaluate the effects of FCR within and external to the cancer survivor. Finally,

the items of the Triggers and Severity as well as Functioning Impairments and Insight subscales

are adjacent in the FCRI and, thus, are more likely to be affected by similar errors in

measurement (117). As such, the residual variance (error) of these subscales were correlated in

the total measurement model. This revised measurement model revealed a good fit to the data

(see Table 12) and was retained for subsequent analyses.

3.7.2 RSES Measurement Model

The RSES was originally intended as a unidimensional measure of self-esteem and was therefore

tested as a single-factor CFA. This model proved to be a poor fit to the data (χ2=327.903,

p<.0001, df=35, RMSEA=0.091 [0.083, 0.101], CFI = 0.899, TLI = 0.871) and therefore a 2-

factor model whereby the negatively worded items and positively worded items were loaded

onto separate factors (245) was tested. The two-factor model resulted in a better fit (see Table

12) and was therefore retained in subsequent analyses. For comprehensiveness, these 1- and 2-

Factor models were explored when randomly grouping the respective items into 3 parcels per

factor. These models resulted in no fits or poor fits of the measurement models. Therefore, the

RSES measurement model indicated in Table 12 was used in subsequent analysis.

3.7.3 LOT-R Measurement Model

The developer of the LOT-R recommends that only the 6 “non-filler” items be summed (with

some items being reverse scored before summation) (174). Originally, only these 6-items were

explored in a first-order CFA, which resulted in a poor fitting measurement model (χ2=281.811,

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p<.0001, df=9, RMSEA=0.174 [0.157, 0.192], CFI = 0.767, TLI = 0.611), as has been similarly

reported by Hertzberg (2006). Subsequently, a 2-factor CFA was tested, wherein the “filler

items” and “non-filler items” were loaded onto separate factors. This improved the the

measurement fit (χ2=553.202, p<.0001, df=34, RMSEA=0.124 [0.115, 0.133], CFI=0.764,

TLI=0.688), although an acceptable model fit remained elusive. Following a previous CFA

study (246), a two factor model whereby the non-filler items were loaded separately onto

optimism or pessimism factors was tested, and greatly improved the fit of the measurement

model (see Table 12). Additionally, a 3 factor model whereby the non-filler items were loaded

onto a optimism or pessimism factor and the filler items were loaded onto a third factor was

tested, and proved to have a poorer fit than the previously tested model (χ2=197.867, p<.0001,

df=32, RMSEA=0.072 [0.063, 0.082], CFI=0.925, TLI=0.894). Therefore, the 2-factor model

using only the non-filler items was retained for subsequent analyses.

3.7.4 IPQ-R Measurement Model

Originally, the items in the IPQ-R subscales were explores as factors revealing a less than

acceptable fit to the data (χ2=2574.982, p<.0001, df=644, RMSEA=0.055 [0.053, 0.058],

CFI=0.860, TLI=0.847). In pursuit of another model, and in attempt to improve the parsimony

of the measurement model, the items within each subscale were randomly assigned to 3 parcels10

per subscale, and each subscale treated as a factor in a first-order factor analysis. According to

the model fit statistics reported in Table 12, this model had a good model fit and was retained in

subsequent analyses.

3.7.5 Brief COPE Measurement Model

Initially, the factor structure of the Brief COPE was tested, indicating a good fit of the subscales

as a 14-factor model (χ2=581.955, p<.0001, df=259, RMSEA=0.035 [0.032, 0.039], CFI=0.964,

TLI=0.948). However, this model treated the coping style variable as 14 distinct variables and

would have resulted in a complicated mediation model (e.g. 14 mediating variables in Objective

3b). In an effort to reduce the coping styles variable into the most parismonious measurement

model, the literature was searched for factor analyses that could be used to guide the

measurement model in the current analysis. Bellizi et al.’s (127) 2-factor model (Active and

10 See Chapter 4, Section 10.4.3 for a full description of item parceling.

109

Escapist Factors) was tested in a sample of breast cancer survivors however the humour and self-

blame subscales did not load onto either factor. Lydon (35) followed Bellizi et al.’s (127)

measurement model in her analysis of coping among breast cancer patients, confiming the two-

factor structure of the Brief COPE, in which the self-blame scale loaded onto the escapist factor.

This left only the humour subscale without a factor loading, and since the current study’s

exploratory bivariate analysis did not find the humour subscale to be associated with FCR,

Lydon’s (35) 2-factor model11 was tested using data from the current study. In accordance with

the desire for parsimony, the items representing each factor where randomly grouped into 3

parcels per factor as recommended in the literature (242). This model (see Table 12) resulted in

acceptable CFI and TLI, although the RMSEA was less than optimal. According to Hu et al.

(240), at least 2 fit indices should be used to assess model fit. Therefore, in light of the excellent

CFI and TLI fit of this data to this model, the large sample size, and the use of this factor

structure in other cancer samples (35,127), Lydon’s (35) measurement model12 was retained for

subsequent analyses.

3.7.6 Full Measurement Models

After the individual measurement models were fitted, the full measurement models, which

included all measures included in each study objective, were tested. The first included the

measurement models representing the variables included in Objective 2: FCRI, RSES, and LOT-

R. This model demonstrated a good fit to the data (see Full ModelA in Table 12). The second

full measurement model included the measurement models representing the variables included in

Objective 3a: FCRI, RSES, LOT-R, and IPQ-R. This model also demonstrated an acceptable fit

to the data (see Full ModelB in Table 12). Finally, the third full measurement model included the

measurement models representing the variables included in Objective 3b: FCRI, RSES, LOT-R,

and Brief COPE. In this model, the Coping Factor of the FCRI and the Active Coping factor

were correlated, as both of these factors include items that address similar coping activities13. As

11 The Active Coping Style factor was comprised of items within the self-distraction, active coping, emotional

support, instrumental support, venting, positive reframing, planning, acceptance, and religion subscales. The

Escapist Coping Style factor was comprised of items within the denial, behavioural disengagement, substance use,

and self-blame subscales. 12 Additionally, a measurement model that incorporated only those subscales that were significantly correlated with FCRI in the bivariate exploratory analyses was conducted. This exploratory model resulted in an inferior fit with the

data (χ2=75.341, p<.0001, df=8, RMSEA=0.092 [0.074, 0.112], CFI = 0.947, TLI = 0.901). 13 Items within the FCRI Coping strategies subscale (italicized) are similar to the Brief COPE subscales (in

parentheses) that were included in the Active Coping Style factor: I try to replace this thought with a more pleasant

one (positive reframing); I try to convince myself that everything will be fine or I think positively

110

already mentioned, small modifications to the models were made if theoretically sound (Section

3.7.1.). The revised measurement model that correlated the Active Coping factor and the Coping

Factor of the FCRI revealed a good fit to the data (see Full ModelC Table 12) and was retained

for subsequent analyses. Thereafter, the full SEM models for each objective were tested (244),

which will be described in the following sections.

4 Objective 2

The original intent of Objective 2 was to explore the direct effects of demographic variables







on level of FCR. As a result of the exploratory analyses described in Chapter 5, Sections 3.1-3.6,

which was undertaken in order to omit unnecessary or redundant variables in the model,

Objective 2 was revised to explore the direct effects of demographic variables (age and sex),

clinical variables (diagnosis type, receipt of any cancer treatment, symptom burden, knowing

someone with a recurrence, belief that knowing someone with a recurrence affects FCR, and

ACTT clinic status), and self-identity variables (self-esteem and generalized expectancies) on

level of FCR.

As described in Section 3.7 above, each of the measurement models revealed acceptable to good

fits to the data. In this way, the measurement aspects of the overall SEM model were already

tested, leaving the final component, the structural regression model, to be examined (247). Since

the estimated factor loadings in the measurement models remain unchanged in the analysis of the

overall model (247), the ensuing description of Objective 2 results will focus on the coefficients

of hypothesized structural paths between the latent constructs as well as the fit of the

hypothesized model to the observed data (236). According to Schreiber et al. (236) results of a

(acceptance/positive reframing); I try to distract myself (e.g. do various activities, watch TV, read, work) (self-

distraction); I try to understand what is happening and to deal with it (active); I pray, meditate or do relaxation

(religion); I try to find a solution (active); I talk to someone about it (emotional support).

111

SEM analysis should describe 2 distinct results: the model fit statistics14 as well as the

coefficients of the hypothesized relationships (236). A review of the resulting fit statistics for

Objective 2 revealed that the RMSEA suggested a good fit of model to the data, although the CFI

and TLI indicated a slightly less than optimal fit: χ2= 2188.923, p<.0001, df=732, RMSEA=0.045

(0.043, 0.047), CFI = 0.932, TLI = 0.926.

A path model displaying the significant (standardized) coefficients is found in Figure 4. As

shown, younger age had a direct positive effect on FCR, whereas being male had a direct

negative effect on FCR. Neither type of cancer diagnosis nor receipt of cancer treatment

influenced FCR; however, survivors who reported a higher number of symptoms to which they

attributed to cancer had higher FCR. Those who knew someone with a cancer recurrence had

significantly lower FCR, while survivors who believed that knowing someone with a recurrence

affected their FCR had significantly higher levels of FCR. In comparison to survivors who had

been discharged from the ACTT clinic, those who were on continued follow-up at the clinic had

higher FCR.

Only one of the factors representing self-esteem had a significant effect on FCR: lower self-

esteem, as measured by the factor containing the measure’s negatively worded items 15 was

associated with higher FCR. Also, survivors who had a more optimistic disposition had

significantly lower levels of FCR. Pessimism did not have an effect on FCR over and above all

other variables in the model.

A table detailing the unstandardized and standardized coefficients, as well as the unstandardized

standard errors and levels of significance, is found in Appendix R.

14 Schreiber et al. (236) describe a model as a hypothesis and that fit statistics are used to determine how well a hypothesized model fits the observed data (236). A good fit of the model was indicated by an RMSEA ≤ 0.07 (241)

a CFI ≥ 0.94, and a TLI ≥ 0.94 (240). See Chapter 4, Section 10.4.3 for additional details. 15 The items included in this factor were: At times, I think I am no good at all; I feel I do not have much to be proud

of; I certainly feel useless at times, I wish I could have more respect for myself; All in all, I am inclined to feel that I

am a failure.

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Figure 4. Structural Model Results for Objective 216:

5 Objective 3

5.1 Objective 3a

The original intent of Objective 3a was to explore the indirect effects of demographic variables







on level of FCR through illness representations. As a result of the exploratory analyses

described in Chapter 5, Sections 3.1-3.6, which was undertaken in order to omit unnecessary or

redundant variables in the model, Objective 3a was to investigate illness representation as a

mediator of FCR. In particular, the indirect effects of demographic variables (age and sex),

16 Note: only the statistically significant variable coefficients are displayed in this figure, as indicated by the solid

lines. Grey dotted lines indicate that these relationships were tested but were not significant. *p≤0.05,** p≤0.001.

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clinical variables (diagnosis type, receipt of any cancer treatment, symptom burden, knowing

someone with a recurrence, belief that knowing someone with a recurrence affects FCR, and

ACTT clinic status), and self-identity variables (self-esteem and generalized expectancies) on

level of FCR through illness representations were tested.

Due to the large number of variables in the study, exploratory single mediation models were first

tested to estimate the direct and indirect effects of each demographic, clinical, and self-identity

variable on FCR separately17. Only significant pathways (direct or indirect) were included in the

final mediation model. The results of these analyses are summarized in Appendix S.

As described in Section 3.7 above, each of the measurement models revealed acceptable to good

fits to the data. Since the estimated factor loadings in the measurement models remain

unchanged in the analysis of the overall model (247), the ensuing description of Objective 3a

results will appropriately focus on the coefficients of hypothesized structural paths between the

latent constructs as well as the fit of the hypothesized model to the observed data (236).

According to Schreiber et al. (236), results of a SEM analysis should describe 2 distinct results:

the model fit statistics18 as well as the coefficients of the hypothesized relationships (236). When

all the illness representation factors19 were included as mediators at once, the model did not

converge and no fit statistics were produced. In an attempt to obtain a better fitting model, a

model including just the direct effects of the illness representation subscales on FCR was run.

This model20 indicated that only three illness representation factors had a significant direct effect

upon FCR: timeline (acute/chronic), (B=0.188, SE= 0.051, β= 0.152, p= 0.001); illness

coherence (B= 0.076, SE= 0.035, β= 0.069, p= 0.031); and emotional representation (B= 0.936,

SE= 0.053, β= 0.798, p<0.001). The model used to address Objective 3a, therefore, was trimmed

to include just these 3 factors of illness representations (timeline [acute/chronic], illness

coherence, and emotional representation) as mediators of FCR. This model was over-identified

17 Only independent variables with a significant (p-value =.05) direct and/or indirect effect with the outcome

variable were included in the full mediation model. See Chapter 4, Section 10.4.3 and Appendix S for details. 18 Schreiber et al. (236) describe a model as a hypothesis and that fit statistics are used to determine how well a

hypothesized model fits the observed data (236). A good fit of the model was indicated by an RMSEA ≤ 0.07 (241)

a CFI ≥ 0.94, and a TLI ≥ 0.94 (240). See Chapter 4, Section 10.4.3 for additional details. 19 As outlined in Chapter 5 Section 3.4, the Personal Control factor was not associated with FCR in the exploratory bivariate analyses and therefore was not included in this SR. 20 The model fit the data well: χ2= 2329.873, p<.0001, df=782, RMSEA=0.044 (0.042, 0.047), CFI = 0.940, TLI =

0.934. The results for the other IPQR subscales were: timeline (cyclical), (B=-0.033, SE= -0.047, β= -0.024, p=

0.480); consequences (B= -0.025, SE= 0.033, β= -0.026, p= 0.443); treatment control (B= -0.071, SE= 0.095, β= -

0.035, p= 0.454); and personal control (B= 0.061, SE= 0.053, β= 0.038, p=0.250).

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and had an acceptable fit to the data: χ2= 3155.126, p<.0001, df= 1089, RMSEA= 0.044 (0.042,

0.046), CFI = 0.926, TLI = 0.918.

The significant direct effects (standardized coefficients) are depicted in Figure 5. The indirect

effects (tested using bootstrapped standard errors) are reported in Appendix T. The following

paragraphs present an overview of the direct effects of illness representations on FCR, the direct

effects of the demographic, clinical, and self-identity predictors on illness representations, and

the specific indirect effect of the predictors on FCR through the illness representations.

5.1.1 Timeline (acute/chronic) as mediator

Timeline (acute/chronic) had a significant direct effect on FCR (B=0.164, SE= 0.038, β= 0.137,

p<0.001), meaning survivors who regarded cancer as a chronic condition had higher FCR. None

of the self-identities had a significant effect on timeline (acute/chronic) and age was the only

demographic variable influencing this mediator, having a positive effect (B=0.016, SE= 0.004,

β= 0.118, p<0.001). In other words, older survivors more highly regarded cancer as a chronic

condition.

Only two of the clinical variables had a direct effect on timeline, both of which had a positive

influence: belief that knowing someone with a recurrence affects FCR (B=0.471, SE= 0.157, β=

0.127, p=0.003) and symptom burden (B=0.142, SE= 0.024, β= 0.207, p<0.001). These results

indicate that greater symptom burden and belief that knowing someone with a cancer recurrence

affects FCR were each associated with more highly regarding cancer as a chronic (as opposed to

acute) condition.

Focusing on the specific indirect effects of the independent variables on FCR through timeline

(acute/chronic), it was found that timeline (acute/chronic) mediated the association between three

independent variables and FCR (see Appendix T): age (B=0.003, SE= 0.001, β= 0.016, p=

0.006), symptom burden (B=0.023, SE= 0.007, β= 0.028, p≤.001) and the belief that knowing

someone with a recurrence affects FCR (B=0.077, SE= 0.032, β= 0.017, p= 0.016). Sex,

diagnosis (type), receipt of any cancer treatment, ACTT clinic status, knowing someone with a

recurrence nor any of the self-identity variables were mediated by timeline (acute/chronic) in

their relationship with FCR.

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5.1.2 Illness Coherence as mediator

Although none of the demographic variables had a significant effect on illness coherence,

knowing of someone with a recurrence and belief that knowing someone with a recurrence

affects FCR each had a significant direct effect on this mediator (B=0.348, SE= 0.149, β= 0.094,

p=0.020, and B=-0.368, SE= 0.172, β= -0.086, p=0.032, respectively). Of the self-identity

variables, only pessimism had a direct effect on this mediator, which was positive in its effect

(B=0.787, SE= 0.367, β= 0.307, p=0.032). That is, those who were more pessimistic believed

that they had a higher personal understanding of their cancer.

Illness coherence did not have a significant direct effect on FCR. As such, illness coherence did

not mediate any of the relationships between the independent variables and FCR.

5.1.3 Emotional Representation as mediator

Emotional representation had a significant positive effect on FCR (B=0.731, SE= 0.048,

β=0.613, p≤.001), meaning that survivors who exhibited a higher emotional response to cancer

had a higher FCR. Age and sex were the only demographic variables that had a direct effect on

emotional representation (B=-0.023, SE= 0.004, β= -0.169, p≤.001, and B=-0.487, SE= 0.158, β=

-0.106, p=0.002, respectively), indicating that older cancer survivors as well as men had a lower

emotional response to cancer. Of the clinical variables, only knowing someone with a recurrence

and belief that knowing someone with a recurrence affects FCR had an effect on emotional

representation (B=-0.393, SE= 0.120, β= -0.121, p=0.001, and B=1.037, SE= 0.138, β= 0.277,

p≤0.001, respectively). These results indicate that survivors who knew someone with a

recurrence had a lower emotional response to cancer, however, belief that knowing someone

with a recurrence affects FCR was associated with a higher emotional response to cancer. None

of the self-identity variables had an effect on survivors’ emotional representation. That is,

neither self-esteem nor generalized expectancies (both optimism and pessimism) influenced the

survivors’ emotional reaction to cancer.

Five independent variables had an indirect effect on FCR as mediated by emotional

representation. Age (B=-0.017, SE= 0.003, β= -0.103, p≤.001), sex (B=-0.356, SE= 0.120, β= -

0.065, p= 0.003), and knowing someone with a recurrence (B=-0.287, SE= 0.087, β= -0.074, p=

0.001) each had a negative indirect effect on FCR. Positive indirect effects were found for

believing that knowing someone with a recurrence affects FCR (B=0.758, SE= 0.112, β= 0.170,

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p≤.001), and symptom burden (B=0.092, SE= 0.017, β= 0.112, p≤.001). Diagnosis (type),

receipt of any cancer treatment, ACTT clinic status, nor any of the self-identity variables were

mediated by emotional representation in their relationship with FCR.

5.1.4 Total Effects

In looking at the total effects (which are made up of the direct and indirect effects described

above and detailed in Appendix T), it can be seen that the strongest overall influence on FCR

came from the belief that knowing someone with a cancer recurrence affects FCR (total

[standardized] effect = 0.375), just less than half of which was mediated through the 3 illness

representation variables tested in the model (total indirect [standardized] effect = .184).

Symptom burden also had a large overall influence on FCR (total [standardized] effect = 0.229),

more than half of which was mediated through the 3 illness representation variables tested in the

model (total [standardized] indirect effect = 0.141).

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Figure 5. Structural Model Results for Objective 3a21:

5.1.5 Overview of Objective 3a results

The results of Objective 3a are summarized in Appendix T and described in the subsequent

paragraphs.

In addition to having a negative direct effect, age indirectly predicted FCR through its positive

impact on timeline and negative influence on emotional representation. Older age was

associated with a higher regard of cancer as a chronic condition, which in turn was related to

higher FCR. These results indicate that some of the total negative effect of age on FCR was

mitigated by the positive effect of age on timeline. Older age was associated with a lower

emotional response to cancer, which, in turn was positively associated with FCR. Over half of

21 Note: only the significant variable coefficients (standardized) of direct effects are displayed in this figure. The

absence of lines indicate that these relationships were tested but were not significant. *p≤0.05,** p≤0.001.

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Table 13: An Overview of the Direct and Indirect Effects on FCR in Objective 3a

Characteristic Direct Effect

on FCR

Indirect Effect on FCR

Through

Timeline

(acute/chronic)

Through

Illness

Coherence

Through

Emotional

Representation

Age

Sex Marital status

Parental Status

Level of Education

Employment Status

Ethnicity

Immigration Status

Rural/Urban

Time (years) since diagnosis

Diagnosis type

Symptom Burden AJCC stage

Another cancer/recur/metastasis

Any Cancer Treatment

Co-Morbid Conditions

ACTT status

Know someone with recurrence Knowing someone with recur affects

FCR

Negatively worded Self-Esteem

(RSES)

Positively worded Self-Esteem

(RSES)

Optimism (LOT-R)

Pessimism (LOT-R)

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the total negative effect of age on FCR was accounted for by the negative effect of age on

emotional representation.

In addition to its direct, negative effect, sex indirectly predicted FCR through its negative impact

on emotional representation. That is, part of the total negative effect of sex on FCR can be

explained by men having a lower emotional response to cancer.

Neither type of diagnosis nor receipt of any cancer treatment had an effect on FCR in the model.

Symptom burden had both direct and indirect positive effects on FCR: It was associated with a

higher regard for cancer as a chronic condition, which, in turn, was positively associated with

FCR. Similarly, it was positively associated with emotional representation, which was directly

related to FCR. Approximately half of the total effect of symptom burden on FCR was

accounted for by a higher emotional response to cancer.

Although knowing someone with a recurrence did not have a direct influence on FCR, it had an

indirect negative effect on FCR through lower emotional representation. Furthermore, it was

positively associated with illness coherence; however, illness coherence was not associated with

FCR and, therefore, was not a mediator of this relationship. By contrast, belief that knowing

someone with a recurrence affects FCR had both direct and indirect positive effects on FCR.

That is, part of the overall positive effect of belief that knowing someone with a recurrence has

on FCR is explained by positive relationships with regarding cancer as a chronic condition and

having an emotional response to it. Similar to above, while the belief that knowing someone with

a recurrence affects FCR was negatively associated with illness coherence, illness coherence was

not associated with FCR and, therefore, was not a mediator in this relationship.

ACTT clinic status had only a direct effect on FCR, in that survivors who had continued follow-

up at the ACTT clinic had higher levels of FCR. Neither self-esteem nor generalized

expectancies had direct or indirect effects on FCR in the model.

5.2 Objective 3b

The original intent of Objective 3b was to explore the indirect effects of demographic variables





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on level of FCR through coping styles. As a result of the exploratory analyses described in

Chapter 5, Sections 3.1-3.6, which was undertaken in order to omit unnecessary or redundant

variables in the model, Objective 3b was revised to explore the indirect effects of demographic

variables (age and sex), clinical variables (diagnosis type, receipt of any cancer treatment,

symptom burden, knowing someone with a recurrence, belief that knowing someone with a

recurrence affects FCR, and ACTT clinic status), and self-identity variables (self-esteem and

generalized expectancies) on level of FCR through coping styles.

In attempt to remove unnecessary or redundant variables in the model, exploratory single

mediation models were first tested to estimate the direct and indirect effects of each

demographic, clinical, and self-identity variable on FCR separately22. Only significant pathways

(direct or indirect) were included in the final mediation model. The results of these analyses are

summarized in Appendix S.

As reported in the previous SEM results, two distinct results (236) will be provided herein: the

model fit statistics23 as well as the coefficients of the hypothesized relationships (236). A review

of the resulting fit statistics for the model addressing Objective 3b revealed that although the

RMSEA suggests the model fit the data well, the CFI and TLI indicated less than optimal fit: χ2=

2991.214, p<.0001, df=961, RMSEA=0.046 (0.044, 0.048), CFI = 0.915, TLI = 0.907.

The significant direct effects (standardized coefficients) are depicted in Figure 6. The indirect

effects (tested using bootstrapped standard errors) are reported in Appendix T. The following

paragraphs present an overview of the direct effects of coping styles on FCR, the direct effects of

the independent variables (demographic, clinical, and self-identities) on coping styles, and the

specific indirect effect of the independent variables on FCR through the coping styles.

22 Only independent variables with a significant (p-value =.05) direct and/or indirect effect with the outcome

variable were included in the full mediation model. See Chapter 4, Section 10.4.3 and Appendix S for details. 23 Schreiber et al. (236) describe a model as a hypothesis and that fit statistics are used to determine how well a

hypothesized model fits the observed data (236). A good fit of the model was indicated by an RMSEA ≤ 0.07 (241)

a CFI ≥ 0.94, and a TLI ≥ 0.94 (240). See Chapter 4, Section 10.4.3 for additional details.

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5.2.1 Active coping style as mediator

Active coping style had a significant direct effect on FCR (B=0.084, SE= 0.028, β= 0.113,

p=0.003) meaning that survivors who exhibited a higher degree of active coping strategies (self-

distraction, active coping, emotional support, instrumental support, venting, positive reframing,

planning, acceptance, and religion) had higher FCR. Self-esteem (negatively-worded factor) (B=

-0.609, SE= 0.213, β= -0.272, p=0.004) and sex (B= -0.693, SE= 0.309, β= -0.094, p=0.025) each

had a significant negative effect on active coping, whereas the effects of self-esteem (positively-

worded factor) (B= 0.796, SE= 0.368, β= 0.249, p=0.031) and optimism (B= 1.540, SE= 0.516,

β= 0.322 p=0.003) were positive. In other words, women, and those who were more optimistic

adopted more active coping strategies than men or were pessimistic.

Only two of the clinical variables had a direct effect on this mediator, both of which had a

positive influence: receipt of any cancer treatment (B=0.980, SE= 0.312, β= 0.112, p=0.002), and

belief that knowing someone with a recurrence affects FCR (B=0.663, SE= 0.243, β= 0.110,

p=0.006). These results indicate that survivors who received any type of treatment for cancer, or

survivors who believed that knowing someone with a recurrence affected their FCR, exhibited a

higher degree of active coping strategies.

Focusing on the specific indirect effects of the independent variables on FCR through active

coping, it was found that active coping style mediated the association between 4 independent

variables and FCR (see Appendix T). More specifically, receipt of any cancer treatment

(B=0.082, SE= 0.038, β= 0.013, p= 0.031), belief that knowing someone with a recurrence

affects FCR (B=0.055, SE= 0.027, β= 0.012, p= 0.044), self-esteem (negatively worded factor)

(B= -0.051, SE= 0.024, β= -0.031, p= 0.033), and optimism (B=0.129, SE= 0.063, β= 0.036, p=

0.040) were each mediated by active coping style in their effect on FCR. Age, sex, diagnosis

(type), ACTT clinic status, knowing someone with a recurrence, symptom burden, self-esteem

(positively worded factor), nor pessimism were mediated by active coping style in their

relationship with FCR.

5.2.2 Escapist coping style as mediator

Escapist coping style had a significant direct effect on FCR (B=0.437, SE= 0.111, β= 0.113,

p≤0.001) meaning that survivors who exhibited a higher degree of escapist coping strategies (i.e.

denial, behavioural disengagement, substance use, and self-blame) had higher FCR. None of the

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demographic nor clinical characteristics had a significant effect on escapist coping style. Of the

self-identity variables, only self-esteem (negatively-worded factor) had a direct on this mediator

(B=-0.262, SE= 0.059, β= -0.475, p<0.001), meaning that those with lower self-esteem displayed

a higher degree of escapist coping strategies.

Focusing on the specific indirect effects of the independent variables on FCR through escapist

coping, it was found that escapist coping style only mediated the association between self-esteem

(negatively worded items) and FCR (see Appendix T). This factor had a negative indirect effect

(B=-0.114, SE= 0.039, β= -0.069, p= 0.003) on FCR. Age, sex, diagnosis (type), receipt of any

cancer treatment, ACTT clinic status, knowing someone with a recurrence, belief that knowing

someone with a recurrence affects FCR, symptom burden, self-esteem (positively worded

factor), optimism, nor pessimism were mediated by escapist coping style in their relationship

with FCR.

5.2.3 Total Effects

Finally, looking at the total effects (which are made up of the direct and indirect effects

described above and detailed in Appendix T), it can be seen that the strongest overall influence

on FCR came from the belief that knowing someone with a cancer recurrence affects FCR (total

[standardized] effect = 0.376), a small portion of which was mediated through the coping styles

(total [standardized] indirect effect = 0.019). Symptom burden and optimism also had relatively

large overall influences on FCR (total [standardized] effects = 0.232 and -0.236, respectively),

although on the effect of optimism was mediated by active coping. Self-esteem (negatively

worded factor) also had a relatively large overall influence on FCR (total [standardized] effect =

-0.229), but in this case, nearly half of the effect was mediated through the coping styles (total

[standardized] indirect effect = -0.100).

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Figure 6. Structural Model Results for Objective 3b24:

24 Note: only the significant variable coefficients (standardized) of direct effects are displayed in this figure. The

absence of lines indicate that these relationships were tested but were not significant. *p≤0.05,** p≤0.001

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5.2.4 Overview of Objective 3b results

The results of Objective 3b are summarized in Table 14 and described in the subsequent

paragraphs.

Table 14. An Overview of the Direct and Indirect Effects on FCR from Objective 3b

Characteristic Direct Effect

on FCR

Indirect Effect on FCR

Through

Active

Coping

Through

Escapist

Coping

Age

Sex

Marital status

Parental Status

Level of Education

Employment Status

Ethnicity

Immigration Status

Rural/Urban

Time (years) since diagnosis

Diagnosis type

Symptom Burden

AJCC stage

Another cancer/recur/metastasis

Any Cancer Treatment

Co-Morbid Conditions

ACTT status


Knowing someone with recur affects

FCR

Negatively worded Self-Esteem

(RSES)

Positively worded Self-Esteem

(RSES)

Optimism (LOT-R)

Pessimism (LOT-R)

Results indicated that age had only a direct effect on FCR, in that older survivors had lower

FCR. Sex was negatively associated with FCR, meaning that men had lower FCR than women.

Men also had a lower active coping style, which, in turn, was positively associated with FCR, but

the magnitude of this effect was insignificant in the mediation model. Although type of cancer

diagnosis had no direct effect on FCR in the model, attributing a greater number of symptoms to

cancer had a direct, positive, influence. Active coping mediated the relationship between receipt

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of cancer treatment and FCR, in that those who received cancer treatment exhibited a more

active coping style25 , which, in turn, was associated with higher levels of FCR.

Knowing someone with a recurrence and ACTT clinic status had direct effects on FCR: knowing

someone with a recurrence was negatively associated with FCR, whereas ACTT clinic status was

positively related to it. Cancer survivors’ belief that knowing someone with a recurrence affects

their FCR had both a direct positive effect on FCR and an indirect positive effect through active

coping. In other words, belief that knowing someone with a recurrence affects FCR is associated

with a higher degree of active coping, which in turn, is associated with higher FCR. Of the total

effects in this relationship, active coping style represented a small, but significant effect.

Neither of the self-esteem factors had a direct effect on FCR; however, the factor containing

negatively worded RSES items had a negative indirect influence through inverse relationships

with each of the coping styles. Pessimism had no effect on FCR in the model; however,

optimism had both direct and indirect effects. Survivors who were more optimistic had lower

levels of FCR (direct effect); however, this negative effect was mitigated, somewhat, by the

positive association between optimism and active coping, the latter of which predicted higher

FCR.

6 Overall Summary of Results

The results of this study indicate that more than half of the sample (58%) had a level of FCR that

was clinically significant at a mean time of 9.1 years post-diagnostic surgery (range 1-36 years).

Age and sex were the only demographic variables that predicted FCR directly or indirectly. Both

had negative direct effects, such that older cancer survivors and men had lower levels of FCR.

When the mediators of the relationship between age and FCR were investigated, two types of

illness representations (timeline and emotional representation) were significant, but emotional

representation was the largest contributor to the overall effect. As for the mediators of the sex-

FCR relationship, only emotional representation was found to be significant, representing nearly

half of the total effect on FCR. Neither of the coping styles mediated relationship between these

demographic characteristics (age and sex) and FCR.

25 The Active Coping Style factor was comprised of the items within the self-distraction, active coping, emotional


Escapist Coping Style factor was comprised of the items within the denial, behavioural disengagement, substance

use, and self-blame subscales.

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Among the clinical variables, only symptom burden predicted FCR such that a higher symptom

burden was associated with greater FCR. When considering the mediators of this relationship,

both types of illness representations (timeline [acute/chronic] and emotional representation) were

found to be significant, but, again, emotional representation had a much larger influence,

representing over half of the total effect. Neither coping style mediated the relationship between

symptom burden and FCR.

Knowing someone who had had a cancer recurrence predicted lower FCR, however, when illness

representations where added to the model as mediators, the direct effect disappeared. Instead,

the effect was mediated by emotional representation, which represented nearly half of the total

effect. Neither coping style mediated the relationship between knowing someone with a

recurrence and FCR.

Belief that knowing someone with a recurrence affects FCR was associated with higher FCR in

all models. Both illness representations (timeline [acute/chronic] and emotional representation)

and active coping style were found to be significant mediators of the relationship, each having a

positive effect on FCR.

Continuing in active follow-up at the ACTT clinic was directly associated with higher FCR in

each of the models; however, the relationship was not mediated by the variables investigated.

Pessimism did not predict FCR in any of the models. However, optimism was negatively

associated with FCR, meaning that those who were more optimistic had lower FCR. In the

coping mediation model, an active coping style represented a small, positive portion of the total

effect of optimism on FCR. Neither of the illness representation variables mediated the

relationship between optimism and FCR.

The negatively-worded factor of self-esteem negatively predicted FCR, indicating that those with

a higher self-esteem had lower FCR. Although this direct effect was not observed in any of the

mediation analyses, the specific indirect effect of this self-esteem factor were significant through

each of the coping styles on FCR, and the escapist coping factor represented the largest portion

in this total effect.

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Chapter 6 Discussion

This is the first known study that was specifically designed to determine the prevalence,

predictors, and mediators of FCR in a large sample of mixed cancer survivors using a valid and

reliable measure of FCR. Strengthening the credibility of these results is that the measure used

to appraise FCR, the FCRI (30,138), regards FCR as a multi-dimensional construct (30), which

corroborates with the consensual view of FCR among experts (30,58). Of greater importance,

the FCRI-Severity Subscale has demonstrated sensitivity (87.5%) and specificity (75%) to

determine a clinically-significant level of FCR (138) among mixed cancer survivors. This

feature enables clinician and researcher confidence in the precision of the FCRI-Severity

Subscale to correctly identify persons with a level of FCR that needs professional assessment and

intervention.

The prevalence results of the current study are largely aligned with the exiting body of evidence

indicating that even years after diagnosis and completion of cancer treatment, FCR continues to

be a prominent issue for cancer survivors. The results of this study are also useful to extend the

knowledge about the predictors and mediators of FCR. Collectively, these findings are of

paramount importance to clarify the magnitude of FCR among cancer survivors, ascertain the

characteristics (predictors) of survivors with highest levels of FCR, as well as identify

characteristics (mediators) of survivors that may be amenable to intervention. The subsequent

sections of this chapter will address each of this study’s objectives in terms of the descriptive

and/or multivariate results in the context of the existing literature. The final section will address

the limitations of the current study to provide context for the application of results.

1 Prevalence of FCR

As outlined in Chapter 2, a variety of measures are available to assess FCR, however, only the

valid and reliable FCRI has been explored to determine a value that is specific and sensitive to

identify multi-dimensional FCR that is clinically-significant (84). Of the few studies that have

used the FCRI, specifically the FCRI-Severity subscale, to assess FCR prevalence among

samples of cancer survivors, the sample used in the current study was lowest. In 2012, Thewes

et al. (24) reported that 70% of their sample of breast cancer survivors had a level of FCR that

was clinically-significant on the FCRI-Severity Subscale (84), whereas Costa et al. (83) reported

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the same among 72% of their sample of melanoma survivors. Seemingly, the varied cancer

diagnoses, the aforementioned homogenous samples (24,83) versus the heterogeneous sample

used herein, may be reason for these differing prevalence rates. Nevertheless, the relationship

between cancer type and level of FCR was inconclusive in a recent systematic review (54) and

refuted in the current study. In considering alternative explanations for these differing

prevalence rates, differences in the average time since cancer diagnosis were noted between

Thewes et al. (24), Costa et al. (83), and current study. Interestingly, as the time since cancer

diagnosis variable increased among these studies, the prevalence of FCR among these studies

decreased. Despite the fact that each of these studies were cross-sectional, reviewing their

collective results may suggest that FCR reduces with time. However, time since diagnosis was

not associated with FCR within this study nor among a group of cross-sectional studies included

in systematic reviews (54,55). A more plausible rationale for the lack of association between

time and FCR may pertain to the perceptions held by the cancer survivor, which is further

discussed in Chapter 6, Section 2.2 below. Although no studies have used the FCRI to assess the

prevalence of FCR among cancer survivors over time, longitudinal studies assessing the FCR

among head and neck cancer patients suggest that FCR remains stable over time (37,46). In

considering these collective findings, further longitudinal inquiry is needed to clarify the FCR of

cancer survivors over time.

2 Direct and Indirect Effects of Variables on FCR

As identified in Chapter 3, the demographic characteristics, clinical characteristics, and self-

identities explored in this study were included because of gaps in the existent empirical

literature, or because of their theoretical importance to the study of FCR. In the following

sections, these findings will be discussed and contrasted with other reports.

2.1 Demographic Characteristics and FCR

The findings of this study support the existing literature in that demographic characteristics

predict FCR. Specifically, this study revealed that age and sex were the only demographic

variables that directly predicted FCR as determined by the Total Score of the FCRI. Marital

status, parental status, level of education, employment status, ethnicity, immigration status and

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rural/urban location did not predict FCR, although these variables have had contrasting results in

the available literature as will be discussed below.

Regarding the association between FCR and age, this study’s finding is consistent with the

majority of FCR literature (15,31–35,37,39) and systematic reviews (54,55) that report an

association between older age and lower FCR. In reviewing these studies, all but the current

study and that of Ghazali (37) were determined in samples of breast cancer survivors, raising

concerns about the generalizability of these results to non-breast cancer survivors, particularly in

light that the majority (66%) of the current study sample was represented by breast cancer

survivors. In samples of testicular cancer (38) and thyroid cancer (16) survivors, age was not

correlated with FCR suggesting that younger age may not play as large a role in the FCR of non-

breast cancer survivors. Although age has not been correlated with FCR in other samples of

breast cancer patients (87,88) the collective research suggests that more study is needed to clarify

the relationship between age and FCR within samples of non-breast cancer survivors.

Notwithstanding the previously identified discrepancies, the current state of the FCR literature

suggests that increasing age is in and of itself is protective against FCR. Older persons have

been identified to more quickly appraise their illness symptoms and seek out professional

assessment (248). Leventhal et al. (249) suggest that these swift actions may be due to older

persons’ more extensive experience in responding to and managing health and illness

behaviours. In other words, older persons have a larger bank of experiences to which they can

make comparison when a new symptom is experienced. Minimizing delay in seeking

professional assessment has been found to reduce the depletion of energy and the risk of

developing advanced disease (141). Acquiring a greater ‘experiences bank’ therefore provides

reassurance to older persons, and in the case of the current population of interest, during the

period of post-treatment cancer survivorship.

In the analyses of indirect effects, only timeline (acute/chronic) and emotional representation

were found to mediate the relationship between age and FCR in the current study. These

mediators, which can be understood as a mechanisms through which an independent variable is

able to influence a dependent variable (51), each had an independent positive association with

FCR. The positive associations of these mediators with FCR suggests that they disrupt any

protective effect that age itself has upon FCR. In regard to the timeline (acute/chronic) as

mediator, older survivors who regarded cancer as a chronic condition may not have as much of a

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protective effect against FCR since timeline (acute/chronic) is itself positively associated with

FCR. Chronicity of symptoms have been determined as a powerful predictor of care seeking

(250) suggesting that those with a chronic illness regard themselves as someone who remains ill

and in need of medical care (141). As such, the results of this study indicate that educational

interventions to clarify misconceptions about disease trajectory could be useful to mitigate the

rise of FCR among cancer survivors, especially among older cancer survivors. Similarly, the

results of the emotional representation as mediator indicate that older survivors had a lower

emotional representation, and because of emotional representation’s positive association with

FCR, the protective effect of age was reduced. Emotional representation is regarded as the

emotional responses generated by illness (103). Emotional reactions are proposed to be the first

reaction to any given stimuli (251) which then acts as information that guides ensuing

judgements and decisions (142). In light of the current study’s results, interventions intended to

equip cancer survivors with skills to emotionally respond differently to cancer could be

particularly useful. One such intervention is mindfulness-based cognitive therapy (MBCT)

(252). MBCT teaches survivors to become more aware of, and relate differently to their

thoughts, feelings, and bodily sensations, and teaches skills that allow individuals to disengage

with the automatic/habitual dysfunctional routines (253). In this way, MBCT could alter one’s

emotional response to cancer, which in turn could have a positive effect on the survivor, such as

reduced FCR. Considering the results of this study, interventions to equip younger survivors to

emotionally respond differently to cancer could be especially useful to reduce FCR.

Besides age, sex was the only other demographic variable associated with FCR in this study.

Although this study found that being male had a direct association with lower FCR, systematic

reviews (54,55) draw attention to the inconsistent association between sex and FCR. In

reviewing the original studies included in these reviews (54,55), only one (30) of the studies that

found an association between FCR and sex/gender was specifically undertaken to explore FCR

and this finding did not hold when cancer diagnosis was controlled for. In other words, studies

that have explored FCR as a major study concept (22,28,39,40,46,49,150) have mainly found no

association between sex/gender and FCR. As such, this study presents a novel finding in regard

to the association between sex and FCR.

In the current analysis of indirect effects, only emotional representation was found to mediate the

relationship between sex and FCR. As indicated above, results indicated that emotional

representation was itself positively associated with FCR and therefore would disrupt any

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protective effect that an independent variable had with FCR. In other words, because of its

positive association with FCR, lowering emotional representations can have positive

implications for FCR (e.g. lowers FCR). In light of the study’s findings, an intervention to

reduce the emotional response for women, such as MBCT described previously, could be

especially useful to reduce their FCR.

Although inconsistent (54,55), results from most of the existing literature has refuted a

relationship between FCR and level of education (15,21,32,38,42) and employment/economic

status (21,22,35,38,42). Similarly, the current work failed to support these relationships adding

strength to the lack of association between these variables and FCR. Collectively, these findings,

as determined from a variety of cancer samples and using a variety of measures used to assess

FCR, add generalizability to the literature negating the relationship between FCR and these

socioeconomic variables.

The current study did not find an association between FCR and marital status, which is consistent

with the majority of findings that have explored this relationship (15,22,31,32,39,46). In

considering the sample compositions of these and the current study, the lack of association

between FCR and marital status has been largely determined within samples of breast cancer

survivors (15,31,32,39). This raises concerns about the generalizability of this finding to other

cancer groups, especially in light of the lower FCR found among partnered, versus not partnered,

prostate cancer patients (41). Notwithstanding these differences in disease types, the above

studies did not collect information about the survivor’s perception of their relationships which

has been determined to be an important correlate of FCR (31,44,45,47,50). Such perceptions

may be reason for the positive association between FCR and parental status (38,78), however this

association was not found within the current study.

An ethnically rich sampling frame was used for this study with the intent to explore the

association between FCR and ethnicity and immigration status. However, neither ethnicity nor

immigration status had a direct effect with FCR in the bivariate analysis. In light of the current

sample size, these findings add clarity to the inconsistent findings between ethnicity and FCR

(31,40,42,49). However, ethnic minorities have been identified as vulnerable populations to

which cancer resources needed to be improved (165) therefore suggesting the need for further

research addressing appropriate interventions for coping with FCR among ethnic minorities. In

regard to immigration status, the results of this study adds validity to refuting the relationship

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between immigration status and FCR, especially in regard to the importance of acculturation

level and the importance of self-care health practices (161–163).

2.2 Clinical Characteristics and FCR

The findings of this study partially support the existing literature whereby clinical characteristics

predict FCR as measured by the FCRI-Total Score. Most of the clinical characteristics explored

in this study (diagnosis [type and stage], another cancer diagnosis, time since diagnosis, any

cancer treatment, and number of comorbidities) were not associated with FCR, although these

variables have had differing results as indicated in systematic reviews (54,55).

Across a diversity of cancer diagnoses and using a variety of FCR measures, type of diagnosis

(22,28,40,49,254), stage of diagnosis (22,28,32,39,40,45,46,78,150), and time since diagnosis

(11,15,21,30,32,38,40,49,78,150) have been largely unrelated with FCR. As such, the results of

the current study, which also failed to find a relationship between these variables and FCR,

strengthens the generalizability of findings. However, the findings between FCR and receipt of

another cancer diagnosis (i.e. another primary, recurrent, or metastatic diagnosis) are discordant.

The majority of studies that specifically set out to assess the FCR among cancer samples report a

positive association between receipt of another cancer diagnosis and FCR (26,30,255,256),

which supports Lee-Jones et al.’s (58) formulation of FCR. However, the results of current study

and one other (78) oppose the former results and proposed formulation of FCR (58). Although

the former studies were conducted in a variety of cancer samples and used an assortment of FCR

measures, the sample sizes of the latter studies each surpassed 1,000 participants, promoting

generalizability for the lack of relationship between receipt of another cancer diagnosis and FCR.

Nevertheless, such generalizable results were determined among breast (78), and the in the case

of the current study, largely breast cancer survivors, and caution should be used to deduce these

findings to survivors of other cancers.

The three main cancer treatment modalities, surgery, chemotherapy and radiation, had each

received attention as they relate to FCR, albeit primarily among samples of breast cancer

survivors (31,32,42). As such, an intent of this study was to explore these variables in a large

sample of mixed cancer survivors. The results of this study’s multivariate analysis adds

generalizability to the lengthy list of studies that have failed to find a direct association between

cancer treatment modality and FCR (32,40,42). However, in the analysis of indirect effects,

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receipt of any cancer treatment had an indirect effect on FCR through an active coping style. In

other words, survivors who received any cancer treatment exhibited a higher degree of active

coping which in turn was associated with higher FCR. This finding suggests that when cancer

patients are actively involved in the health care system receiving treatments, they have a greater

need to rely on, and hence seek out, active coping strategies which in turn increases FCR.

Specifically, coping strategies used in these instances, based upon the Brief COPE (126)

subscales included in the Active Coping Style factor, may include support seeking (i.e. emotional

and instrumental support, or religion (126)), or active attempts to adapt (i.e. positive reframing or

planning (126)). Although further empirical inquiry is needed in order to clarify this proposition,

Lydon (35) similarly found that Active Coping predicted FCR.

Collectively, the results of the previously described clinical characteristics failed to explore the

survivors’ perceptions of these characteristics and the role that these perceptions play on FCR.

The CSM (141,154), upon which the current study was conceptualized, describes the importance

of an individual’s interpretations of their experiences (167), in addition to their social

observations and comparisons (140) and somatic experiences (143), as contributing factors to an

illness representation, which can be described as how an individual “makes sense of” (p.142)

their condition (120). The current study included survivors’ perceptions on FCR via the

symptom burden and associations with cancer (knowing someone with a cancer recurrence,

belief that knowing someone with a cancer recurrence affects FCR, receipt of another cancer

diagnosis, and ACTT clinical status) variables. This study’s findings revealed that symptom

burden and most of the associations with cancer variables (knowing someone with a cancer

recurrence, belief that knowing someone with a cancer recurrence affects FCR, and ACTT

clinical status) were the only clinical variables that directly predicted FCR.

In alignment with the CSM (141,154), the conceptualization of FCR proposed by Lee-Jones et

al. (58) suggests that both internal and external stimuli play a role in activating FCR. More

specifically, Lee-Jones et al.’s (58) formulation of FCR claims that somatic stimuli interpreted as

illness symptoms are antecedents to FCR. Symptom burden, defined as an experienced symptom

that is believed to be related to illness (103), had a direct positive association with FCR in the

current study. In other words, survivors who experience a higher number of symptoms that they

believed to be related to their cancer diagnosis had a higher FCR. Similarly, symptom

attribution, defined as the beliefs that cancer survivors have about a symptom and its relation to

their cancer (42,104), has been positively correlated with FCR. These findings, coupled with the

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insignificant relationship between number of comorbidities and FCR (see Chapter 5, Section

3.2), suggest that the survivor’s interpretation of symptoms are more influential on their level of

FCR than number of symptoms that they experience.

In the analyses of indirect effects, only timeline (acute/chronic) and emotional representation

were mediators of symptom burden and FCR. As stated above, timeline and emotional

representation were each positively associated with FCR suggesting that they further enhance the

influence that symptom burden itself has upon FCR. These results suggest that education about

which symptoms are and are not attributed to cancer may have positive implications for FCR.

For example, correcting cancer survivors’ misconceptualizations about symptom burden (e.g.

which symptoms are NOT attributed to cancer) can reduce symptom burden which would lower

FCR. Furthermore, since symptom burden is positively associated with timeline and emotional

representation, which are positively associated with FCR, an intervention to correct

misconceptions about symptom burden in addition to correcting misconceptions about disease

timeline and emotional representation could also reduce the negative effects of FCR via these

mediating relationships.

In addition to identifying antecedents of FCR, Lee-Jones et al. (58) propose that past experiences

with cancer and/or its treatment are a component of FCR. To capture this variable, the current

study explored cancer survivors’ personal knowledge of someone with a cancer recurrence. The

results of this study indicated a significant direct effect of knowing someone with a recurrence

and FCR, in that knowing someone with a recurrence was associated with lower FCR. In other

words, these results suggest that knowing someone with a recurrence is in and of itself protective

against FCR. This result conflicts with that of Ziner et al. (36) who failed to find a statistically

significant difference in the mean FCR scores of breast cancer survivors who did and did not

know someone with a recurrence. In the analyses of indirect effects, the results of the current

study revealed that only emotional representation, or having a lower emotional response to

cancer, accounted for over half of the total effect of knowing someone with a recurrence on FCR.

This result proposes that emotional reactions play an important role as a contributor of FCR.

Lee-Jones et al. (58) also suggest that a personal perception of risk to a recurrence is an

additional component of FCR. Building on the variable that assessed knowledge of someone

with a recurrence, the current study assessed participants’ belief about knowing someone with a

recurrence and whether this affects their FCR. Although only 25% of the current sample

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believed that knowing someone with a recurrence affected their level of FCR, this variable was

associated with a significantly higher level of FCR. This finding adds validity to the importance

of survivor perceptions in affecting their level of FCR.

The results of the analyses between FCR and knowing someone with a recurrence and belief that

knowing someone with a recurrence affects FCR, suggest that the perceptions of cancer

survivors are an important consideration in their level of FCR. Similarly, other studies have

found various perceptions of cancer survivors significantly contribute to a higher level of FCR.

These perceptions include the belief that one’s own psychological stress caused their cancer (44),

regarding one’s disease trajectory as either chronic or cyclic (47), one’s own general health

perceptions (45), the perceived necessity of taking prescribed Aromatase Inhibitors (88) as well

as illness representations (88). The power of survivors’ perceptions may be precipitated or

compounded by their selective processing. Selective processing is explained as an attentional

bias toward threatening information (257) and such biases are proposed to be a perpetuator of

anxiety disorders (258), with which FCR has been consistently associated (22,31,37,105).

Indeed, attentional bias has been found to be independently associated with having a diagnosis of

cancer, regardless of the survivors’ level of FCR (257,259). Collectively, these points suggest

that having received a diagnosis for cancer singly heightens a cancer survivors’ attentional bias

toward threatening information, which in turn influences their perceptions that predict FCR.

Although this hypothesized sequence of events remains to be empirically tested, the collective

findings suggest that interventions to support changes toward positive thinking among cancer

survivors could be important.

The conceptualization of FCR proposed by Lee-Jones et al. (58) suggest that both internal and

external stimuli play a role in activating FCR, and specifically identify contact with health

professionals as an external stimuli precursory to FCR. At the time of the study, 73.2% of the

sample were actively receiving care at the ACTT clinic and the analysis of direct effects

suggested that these patients had higher levels of FCR. Consistent results have been determined

among samples of breast cancer survivors finding that those who had more reminders about their

cancer experience had higher levels of FCR (36,129). Neither illness representations nor coping

styles mediated the relationship between ACTT clinic status and FCR indicating that ACTT

clinic status was an independent predictor of FCR. Collectively, these findings support the direct

influence that external stimuli play in activating FCR, however, the high prevalence of clinically-

significant FCR among cancer survivors within this and other studies (24,83) point to the

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importance of cancer survivor-specific resources for survivors during the post-treatment period.

The findings discussed within these pages identify content that could be included within

educational resources and/or interventions targeted at a predominant issue for cancer survivors

during the post-treatment period, their FCR.

2.3 Self-Identities and FCR

As stated above, the CSM (141,154), upon which the current study was conceptualized, proposes

that one’s progression through the formulation of, and coping with, an illness representation is

influenced by the characteristics of the self (140). Specifically cited are self-esteem (140), sense

of meaning and purpose, self-concept, the physical self, self-motives, self-definitions (151), and

biological or psychological traits (143). Similarly, Lee-Jones et al. (58) regard a person’s

disposition and past coping style as an antecedent of FCR. Considering these theoretical bases,

as well as the understudied elements of the self in relation to FCR, served as rationale to include

the variables of self-esteem, generalized expectancies (optimism-pessimism), and personality in

the current study.

Prior to this study, self-esteem had been explored in relation to FCR in a single study (38) in

which the significance of an inverse correlation did not persist into regression analyses. The

current study’s multivariate analysis revealed that items within the negatively worded self-

esteem factor26 were significantly negatively associated with FCR, suggesting that those with

lower self-esteem had higher levels of FCR. This study presents the first known multivariate

finding that self-esteem is inversely associated with FCR. This novel finding isn’t surprising

given the previously stated theoretical rationale (58) and inverse association between self-esteem

and distress (171). Although a direct inverse effect was found between self-esteem (negatively-

worded factor) and FCR, this direct effect disappeared with the inclusion of the coping mediators

suggesting that self-esteem has important direct and indirect contributions to FCR.

Other components of the self-system, such as a person’s level of optimism and pessimism (182),

had received little attention in relation to FCR. Results of the current study are consistent with

the available literature (40,46) indicating that less optimistic cancer survivors had higher levels

of FCR. This finding has similarly been determined between optimism and distress (260).

26 The items included in this factor were: At times, I think I am no good at all; I feel I do not have much to be proud

of; I certainly feel useless at times, I wish I could have more respect for myself; All in all, I am inclined to feel that I

am a failure.

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Although optimism has been found to indirectly impact the psychological distress of breast

cancer patients (184), only one of the indirect effects explored in the current study (active

coping) was found to be significant. As with self-esteem, this finding suggests the importance of

the self-system as an important determinant of a person’s level of FCR. These findings, backed

by theoretical rationale (58), allude to the importance of interventions to strengthen the self-

system as a consideration to reduce the FCR of cancer survivors.

Prior to this study, personality traits had received little attention in the oncology literature. Due

to this empirical gap, as well as theoretical rationale of the CSM (141,154), personality traits

(Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness) were explored as

predictors of FCR. As discussed in Chapter 5, only neuroticism was correlated with FCR in the

exploratory bivariate analyses that were conducted to remove redundant variables. This finding

corroborates with other publications relating neuroticism to FCR (38) and psychological

adjustment (261), suggesting that survivors who have a more neurotic personality have a higher

FCR. However, this study’s subsequent multivariate analyses excluded the measures of

personality, since the inclusion of only one personality measure failed to regard personality as a

complete construct, particularly in light of the low reliabilities of the measurement scales. This,

in addition to the current study’s finding that pessimism, an identified characteristic of

neuroticism (115), did not predict FCR in any of the analyses, suggest that further empirical

exploration is needed. Clarifying these discordant findings would be especially useful since

theoretical formulations (58,141,154) suggest that personality is an important antecedent to FCR

that clinicians and researchers need to consider.

2.4 Overall Understanding of Mediators of FCR

As can be inferred from the preceding discussion, a number of predictors of FCR have been

explored in the existing literature. Mediators of FCR have also received attention within the

empirical literature, although to a much lesser extent. Indeed, the current project represents the

first known study to explore mediators of FCR beyond samples of breast cancer survivors

(35,36,42), only one (35) of which explored a concept (coping) that can be reliably compared to

the current study’s results.

As previously referenced, the current study represents the first known study that had explored

illness representations as a mediator of FCR. However, Freeman-Gibb (42) explored the

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components of illness representations as predictors of FCR finding that the timeline

(acute/chronic) variable was not associated with FCR but that emotional representation, among

others, were positively associated with FCR. Reasons for these opposing results may be due to

the different cancer populations under study (breast cancer versus mixed cancer) or measures

used to assess FCR, or the nature of the statistical analyses. Notwithstanding the reasons for

these differences, these collective results imply that illness representations are an important

precursor of FCR.

Emotional representation, which is described as the emotional response (103) or emotional

impact generated by illness (262), is consistently related with FCR both in this study and others

(46,262). High correlations, such as the r=0.62 or r=0.69 determined by Freeman-Gibb et al.

(262) and this study respectively, suggest that these variables share a large percentage of the

variance (263). However, Cohen (232) argues that a correlation of .50 is the highest achievable

correlation between measures of different concepts, suggesting instead that the high correlations

observed in this study and that of Freeman-Gibb et al. (262) may actually indicate that the

measurement of the intended concepts (e.g. emotional representation and FCR) is redundant.

Such conceptual redundancy has recently been suggested to exist within the FCRI whereby the

total FCRI score has been proposed to represent a combination of concepts (56). Although this

proposition remains to be further explored, some of the inter-factor correlations of the FCRI (30)

attest to, in light of Cohen’s (232) perspective, the plausibility of conceptual redundancy.

Notably, the Psychological Distress subscale of the FCRI, which includes items that capture how

an individual “feels” (30), which may be conceptually similar to an emotional representation,

was highly correlated (r=.69 (30)) with the FCRI Severity subscale that is used as a brief

measure of FCR (84). Collectively these points support to the proposition that FCR may not be

as multidimensional as originally proposed (56) and that further work is necessary to clarify the

concept.

Contrary to expectations, both coping factors27 explored in this study were positively associated

with FCR. Similar findings were reported by Lydon (35), who also explored these Active and

Escapist Coping factors as mediators of FCR. Urbaniec et al. (10) similarly explored the

association of coping style with FCR, finding that the self-distraction, behavioural

27 The Active Coping Style factor was comprised of the items within the self-distraction, active coping, emotional


Escapist Coping Style factor was comprised of the items within the denial, behavioural disengagement, substance

use, and self-blame subscales.

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disengagement, venting, and self-blame subscales were positively correlated with FCR. None of

these correlations met the stated criteria (r≥.50) for inclusion into the subsequent regression

analysis (10) and therefore the predictive ability of coping style on FCR was not determined. Of

note, however, is that the significant correlations revealed in the study by Urbaniec et al. (10)

represented both of the Active and Escapist Coping factors examined within the current study

and that of Lydon (35). Collectively, these findings provide support to Leventhal et al.’s

(141,143) CSM, upon which the current study was conceptualized, in that a wide variety (143) of

“procedures” (p.24), or Coping Styles referred to herein, may be used to control or eliminate

illness threats (141) such as FCR.

While it could be expected that an escapist coping style, because of the inclusion of seemingly

unhealthy coping strategies, would be associated with higher FCR, it was surprising to discover

that an active coping style, comprised of seemingly constructive strategies, was associated with

higher FCR. As previously alluded to, survivors’ perceptions can be a powerful influence in the

cancer experience, and the current results may not provide a complete picture of the survivors’

perception of their coping style, or their evaluation of their coping effectiveness, as these were

not assessed herein. The coping effectiveness of breast cancer survivors has been improved by

mindfulness-based stress reduction (MBSR) (264). Mindfulness-based strategies have also been

helpful to reduce the FCR among cancer survivors (265–267) further highlighting the utility of

this strategy among cancer survivors.

Most of the mediators in the current study’s models (timeline [acute/chronic], emotional

representation, active coping and escapist coping, but not illness coherence) had a positive

association with FCR. In other words, regarding cancer as a chronic condition, expressing a

higher emotional response to cancer, as well as higher active and escapist coping tendencies,

were all associated with higher FCR. These findings suggest that any independent variables that

were negatively associated with these mediators, would lessen these attributes which in turn

would lessen the level of FCR. Such independent variables, when considering these mediators,

serve as a sort of protective effect against FCR.

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3 Limitations

3.1 Response rate

The response rate for this study (50%) is lower than a previous survey study in this clinic (61%)

and lies mid-point to other FCR studies among cancer survivors. Simard et al. (30) reported the

highest response rate in a cross-sectional study of FCR, claiming that 68% of approached mixed

cancer patients participated in the study. The response rates of other studies of FCR were 41.4%

(25), 40% (147) among mixed cancer survivors, and 35% (24) among breast cancer survivors.

These results collectively illustrate the challenges to recruitment in studies addressing the FCR

of cancer survivors and may even suggest that those experiencing the concept understudy are

more like to participate in the research (268). If such is the case, the reported prevalence of FCR

may overestimate the true population prevalence.

An anticipated benefit of this study was that employed a mixed-mode survey method whereby

potential participants could complete the study measures in the modality most convenient for

them (internet or hard-copy). However, Leece et al. (269) caution that such rationale may not

actually be the case in clinical research. Such was the case in this study where 95% of

respondents chose to complete the study measures in hard-copy. Related to the response rates of

other postage surveys, the responses for this study was higher than the typical 20% of postal

survey studies (187).

The statistical comparisons of responders to non-responders in the sampling frame indicate that

there were no differences in terms of geographical location in Ontario and urban/rural status.

Although these limited number of variables available from the clinic database for which statistics

could be compared suggest that sampling bias was not an issue, it would have been useful to

compare other variables in order to assess response rates. For example, a comparison by age,

sex, ethnicity, disease site and stage, would be useful to more fully illustrate the response biases

in this study, but would also highlight some of the challenges to recruitment in FCR research.

However, collecting this data would have involved the researcher entering into the patients’

charts, which was beyond the ethical approval of this study. Therefore, the available variables

from the clinical database were explored and suggested no differences in response status.

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3.2 Limitations related to the resulting sample

As identified in the review of the literature (Chapter 2), a great deal of what is known about FCR

stems from research generated in samples of Caucasian cancer survivors as well as survivors of

breast cancer. As such, the current study explored FCR in a sample of mixed cancer survivors

from a multi-ethnic urban centre with the intent to extend knowledge about FCR beyond

Caucasian samples and breast cancer survivors. However, the variability that was originally

sought was not obtained and the intention of this study to expand knowledge about FCR beyond

Caucasian and breast cancer survivors was not achieved. The resulting frequency distribution of

this study revealed that 66% of this sample was comprised of breast cancer survivors, higher than

the 49%, 41%, and 38% of mixed cancer samples reported by Simard (30), Simard (147), and

Lebel (25), respectively. Similarly, 77% of study respondents identified as Caucasian leaving

questions about the applicability of findings to non-Caucasian survivors. Although results

indicated that neither disease type nor ethnicity were significant predictors of FCR, the dearth of

FCR literature in these subgroups would be useful to expand our understanding of FCR.

The frequency distribution of disease sites in this sample are not representative of the Canadian

rates of cancer. In keeping with the disease sites represented in the sampling frame of this study,

the Canadian Cancer Society (270) estimated the overall Canadian cancer incidences to be 13%

breast cancer, 13% colorectal, 5% gynecological, 3% melanoma, 3% thyroid and 0.5% testicular.

The composition of cancer survivors in this sample greatly differs from that of the Canadian

landscape and limits the generalizability of findings to Canadian cancer survivors generally.

This study’s mean sample age was 61.1 years, younger than the Canadian median age at cancer

diagnosis that occurs between 65-69 years (270). Considering that this study sample’s mean

time since diagnosis was 9.1 years, this study’s sample average age at diagnosis was much

younger than the national average. The reason for this may be due to the sampling frame from

which the current sample was drawn. The sampling frame used for this study was drawn from a

clinic utilizing a novel model of care to transition survivors from tertiary to primary care, which

in and of itself reduces the generalizability of the current study’s findings to cancer survivors

more generally. Survivors in this transition clinic were followed at an academic-affiliated urban

hospital where research is a major focus. As such, it may have been likely that patients treated in

this hospital were younger or had higher risk disease than that of their cross-national

counterparts. Regardless of the rationale, the inclusion of older cancer survivors’ perspective of

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FCR may not have been included in this sample and may restrict the generalizability of findings

to cancer survivors younger than the national average age at cancer diagnosis.

3.3 Missing data

Missing data is a reality of clinical research despite a research team’s best efforts to minimize it.

The researcher for this study acknowledged the length of the self-report aspect of the study (182

items) which may have resulted in respondent fatigue and accounted for the amounts of missing

data. Such burden was acknowledged by some participants in their text added in survey margins.

One participant explicitly commented on the last page of the survey “too many questions!”

(FCR0860).

The percentage of missing raw data for the study measures ranged from 0-8.7%, where the 8.7%

was represented as the amount of data missing for some of the IPQ-R items that referred to

cancer treatment and symptoms (missing data for the items on this measure ranged from 3.8-

8.7%). This percentage was not surprising since many participants wrote comments to the

researcher about this measure, such as “these questions are not applicable because my cancer

was diagnosed long ago” (FCR0063). In future research, as suggested by Streiner et al. (117),

careful consideration should be given toward the tense of the items in order to seek participants’

recollection of their illness perceptions when they were diagnosed, rather than asking about their

illness perceptions right now. Similarly, the amount of missing data for the COPE subscales

may be explained by their latter positions in the survey, further highlighting the need to consider

response burden in survey research.

3.4 Limitations of the data analysis

Structural Equation Modeling (SEM) is a powerful method for statistical analysis in that it

simultaneously assesses the measurement and structural models proposed in a research question

(191,229). In this way, readers of an SEM analysis can be confident in the precision of the

results describing the relationships among the concepts. However, the current study explored

FCR as a continuous variable, which although supported with sound rationale (see Chapter 4

Section 10.4), may not necessarily identify the characteristics of patients with the greatest needs.

In other words, understanding the predictors and mediators of highest levels (e.g. clinically-

143

significant (138) FCR) would provide another means of identifying adult cancer survivors who

require professional intervention for their FCR.

As described in the previous chapters, this study included a large number of variables, too many

for the SEM software to simultaneously analyze. Therefore, prior to conducting the SEM

analysis, correlations (for continuous variables) or regressions (for nominal or categorical

variables) were calculated to exclude unnecessary or redundant variables from the SEM analysis.

In this way, the resulting models were derived by the data and represent a concise description of

the variables’ relationships. Although achieving such parsimony is a goal of SEM analyses

(191), a full mediation model in which all 7 of the illness representation factors were tested (as

opposed to 3; see Chapter 5, Section 5.1 for details) would have provided the most accurate

representation of study findings. Furthermore, because this analysis strategy was, in part, data

driven, it deviated from the theoretical foundation upon which the study was developed and thus,

further testing of the model in different samples is suggested.

Being that an existing conceptualization of FCR (58) did not address mediators of FCR about

which the current study sought out to explore, a new conceptual framework was developed.

Although this new framework was useful to guide an examination of the predictors and

mediators of FCR herein, it brought limitations in relation to the analysis of data. Specifically,

Illness Representation and Coping Style were regarded as mediators within distinct relationships

in the new framework, and as such, were analyzed in separate mediation models. This outlook

deviated from those outlined in CSM (141–143,151), which regarded an Illness Representation

as a predictor of Coping which in turn predicted one’s Appraisal (141–143,151). In other words,

the CSM (141–143,151) regarded both an Illness Representation and Coping as mediators in a

single sequential relationship of which an Appraisal, or FCR as was the case in the current study,

was the outcome. The similarly high coping and emotional representation scores determined

within the current sample may actually attest to the sequential relationship among constructs

outlined in the CSM (141–143,151). However, since this study examined the coping variable

and illness representation variables in separate mediation models, the determination of such a

relationship could not be determined herein. This limitation, in addition to the lack of empirical

support for coping as a mediator between illness representations and various outcomes

(42,120,155), suggest that further empirical inquiry is needed.

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A final limitation of the current study’s data analysis was the method in which the Coping Style

variables were analyzed. Recognizing that coping was an important concept to explore in light

of FCR (35,42,46,58) and the CSM (141,143) upon which the current study was established, the

Coping Style variables were deemed as important to study herein. However, it was also

recognized that that coping was a complicated concept (123,141) with a broad number of

available measures (126) and therefore careful consideration was made of these points during the

conceptualization of this study. Being that the overarching goal of this study was to explore the

prevalence, predictors and mediators of FCR, established measures and analytic tools were used.

For example, in the case of the Coping Style variable, similar conceptualizations (e.g. factor

analysis) using the selected measure (126) were sought. This decision was made in order to

facilitate comparisons between studies rather than developing a new coping conceptualization

(e.g. exploratory factor analysis) from the current study’s data, which was beyond the purpose of

this project. Notwithstanding this rationale, the contribution that a specific coping strategy,

embedded within a Coping Style factor, had toward FCR was impossible to ascertain from this

analytic method. As such, further empirical inquiry, including but not limited to secondary

analyses of the current study data, would be useful

145

Chapter 7 Implications for Research, Practice and Theory

1 Main Conclusions

The prevalence of FCR among participants in this sample indicated that FCR is a major concern

for a large number of cancer survivors years after they’ve completed treatment for cancer.

Furthermore, these cross-sectional results indicate that time since diagnosis was not associated

with FCR suggesting that FCR remains constant over time.

The findings of this study clarify and add novel findings related to the predictors and mediators

of FCR. These findings have important implications for clinicians and researchers to identify

persons at risk for developing highest levels of FCR, in addition to their utility for intervention

development and testing. Furthermore, as this research was established upon existing theory, the

results have implications for theory validation and refinement.

2 Implications for Research

Although this study is among the first to use the FCRI-Severity Subscale to determine prevalence

in a sample of mixed cancer survivors, no known studies have used the FCRI to assess the

trajectory of FCR over time. Since the FCRI is valid and reliable (30) multidimensional (58)`

measure of FCR with a sensitive and specific cut-off to determine clinically-significant FCR

(84), it would be especially useful to determine the trajectory of FCR among survivors

throughout the post-treatment survivorship period. This information would be useful for

clinicians and policy makers to understand the needs of survivors over time. Although the

current study and this suggestion for future research pertain to using the entire FCRI as a

continuous outcome variable, research with alternative clinical utility could use the FCRI-

Severity Subscale as a dichotomous outcome variable to clarify the trajectory of clinically-

significant FCR.

As indicated in the previously identified limitations (Chapter 6, Section 3.2), the current study

failed in its intent to acquire a disease- and ethnically-diverse sample. This intention stemmed

from the dearth of literature describing the FCR of these subgroups. Although the current study

found no association between these variables and FCR, systematic reviews consistently report a

146

lack of clarify among these relationships (53–55) suggesting that it is an important area for

further inquiry.

In addition to the cancer experience itself, FCR has been determined to be a catalyst for post-

treatment self-management (271). This, in light of the prevalence findings in the current and

other studies (11,15,24,38,43,46,62), and because a large proportion of cancer survivors report

unmet needs during the immediate post-treatment period (272), point to the importance of

interventions during this time. However, the widespread effectiveness of FCR interventions

remains allusive, although a number of FCR-specific interventions (149,266,273–275) exist in

various phases of the research trajectory (276,277). In light of the negative consequences of

FCR (13–24) and its impact on health care resources (24,25), an intervention to facilitate coping

with FCR before cancer patients enter the post-treatment period would be especially useful to

circumvent the rise of FCR among those at greatest risk. However, no such FCR-specific

interventions are available for cancer survivors highlighting an import area for future study.

The mediators explored in this study represent variables that are amenable to intervention (e.g.

they address internal processes of the individual). Because of the consistent positive direct effect

of these mediators on FCR, any intervention intended to reduce the significance of these

variables in the lives of cancer patients should have positive contribution on reducing the FCR of

survivors. For example, the results of the timeline (acute/chronic) mediating variable suggest

that an educational intervention to correct misconceptions that survivors have about their disease

timeline could be useful to reduce their FCR.

3 Implications for Practice

Notwithstanding the unexplained reason for differing FCR prevalence (see Chapter 6, Section

1.0), the literature is consistent in that FCR is an issue for a large number of cancer patients

(11,15,24,38,43,46,62) highlighting the importance of systems-level policies to support them.

The results of the study support the existent literature, but also extend it in that the current study

used a measure able to identify FCR that is clinically-significant (84). This is particularly

relevant for cancer clinicians, because it identifies that greater than 1 in 2 survivors in their

practice has a level of FCR that is clinically meaningful and could benefit from professional

intervention to facilitate coping with FCR. This, in light of the negative consequences of FCR

147

on both the individual (13–24) and health care resources (24,25), highlight the importance of

routinely assessing FCR among cancer survivors. However, clinicians may not have the luxury

of time for this detailed assessment and therefore an awareness of the characteristics of persons

with highest levels of FCR would be useful. The predictors of FCR identified in this study could

be useful to educate clinicians, either by means of traditional education classes or by use of

screening tools, pertaining to the characteristics of survivors likely to have highest levels of FCR.

These resources could facilitate the identification of these survivors in their clinic. For example,

knowing that younger cancer survivors and women may have higher levels of FCR could prompt

clinicians to initiate a conversation about FCR with these survivors. Subsequently, a more

detailed assessment of FCR could take place and appropriate resources could be enacted.

Until recently, the emotional representation concept has received little empirical attention to

support its theoretical basis. Affect, a concept closely related to emotion (142) has been

suggested to redirect people’s attention from the information that is before them, and also serve

as a motivator for action or processing of information (142). Applying this understanding of

affect in light of the current study’s results point to the importance of clinicians’ repeated

evidence-based health teaching with patients each time they meet. Similarly, educational

resources, such as evidence-based survivorship care plans, may be useful for cancer survivors to

keep and refer to as needed. This is especially important considering that only 17% of survivors

accurately perceive their risk of recurrence 6-months post-operatively (118). This suggested

educational intervention, in addition to the use of MBCT previously described (see Chapter 6

Section 2.1), collectively align with the illness representation mediating results of the current

research, as well as a summary of proposed research outlined by Leventhal (140). Furthermore,

a combined education and MBCT intervention aligns with Lee-Jones et al.’s (58) theoretical

formulation of FCR, whereby “educational and psychotherapeutic approaches” (p.103) are

identified as important components of FCR interventions for cancer survivors.

4 Implications for Theory

This study supports the commonly referred to formulation of FCR presented by Lee-Jones et al.

(58) whereby internal and external cues are antecedents to FCR. More specifically, the

associations with cancer variables (knowledge of someone with a recurence, belief that knowing

someone with a recurrence affects FCR, and ACTT clinic status) support Lee-Jones et al.’s (58)

formulation that cues external to the survivor as well as their cognitions (i.e. experiences,

148

knowledge, and beliefs) are antecedents of FCR. Furthermore, the perceptions that a survivor

places on the cause of their physical symptoms (i.e. from cancer or benign causes) provides the

internal cues that Lee-Jones et al. (58) propose as antecedents of FCR.

Although the preceding paragraph provides consistent support for the predictors explored in this

study and their alignment with the antecedents of FCR proposed by Lee-Jones et al. (58), the

mediation models explored in this study extends the work of Lee-Jones et al. (58) suggesting that

such mediators are important considerations in FCR work. The mediation results of the current

study provide empirical support that coping is a precursor of FCR whereas, Lee-Jones et al.’s

(58) formulation regards coping as a behavioural response or consequence of FCR. For example,

the “seeking advice” (p.102) referred to by Lee-Jones et al. (58) may be equated with

components found within the active coping factor assessed in this study. Similarly, the CSM,

from which Lee-Jones et al.’s (58) work heavily draws, theorizes that coping is influenced by an

illness representation (140). However, Leventhal’s (140) CSM goes onto suggest that a selected

coping procedure is appraised by the individual for effectiveness which provides feedback to

alter the representation. In this regard, the results of the current study support the premise that

coping is an antecedent FCR, although it should be acknowledged that theoretical formulations

also propose it to be a consequence of FCR.

5 Conclusion

This study adds clarity to inconsistent findings in the FCR literature as well as introduces novel

findings related to FCR. These findings are discussed in light of implications for clinicians and

researchers as well as advances in the theoretical understanding of FCR. For these reasons, the

outcomes from this project are expected to have broad implications for the growing number of

cancer survivors among whom FCR is a common concern.

149

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Appendices

177

Appendix A: Overview of cancer survivors attending the ACTT clinic and

Canadian 10-year cancer prevalence data

ACTT Population

(January 2014)

Canadian Cancer Prevalence

(January 2009)(2)

Disease Site Actual Numbers Proportion Actual Numbers Proportion

Testicular 170 9% 7, 936 1%

Melanoma 130 7% 39, 494 4.7%

Breast 1200 62% 158, 428 18.9%

Gastrointestinal 200 10% 115, 355 13.7%

Gynecological 160 8% 52, 507 6.2%

Thyroid 75 4% 30, 926 3.7%

Total 1935

178

Appendix B: Sample Size Estimations

1. Sample Size Estimation for Primary Objective (Descriptive):

(Source: Aday and Cornelius, 2006, p.160)

The one-group formula using proportions as estimates is:

z21-α/2 P(1-P)

n = d2

where, P = estimated proportion

d = desired precision

Therefore, using a 95% confidence interval the standard error (z21-α/2) would be 1.96. Using the

estimated population proportion (58.3%), and a desired precision is 1 based on α=0.05, these

values are entered into the above equation:

1.962 x (.583)(1-.583)

n = (.05)2

3.8416 x (.243)

= .0025

.9339

= .0025

= 373.57 or 374 participants

179

Appendix C: Information Letter

Dear After Cancer Treatment Transition (ACTT) clinic patient,

All of the patients who are being followed at the After Treatment Transition (ACTT) clinic

are invited to participate in a research study of cancer survivors. You are invited to participate in

this research because you have completed treatment for cancer and are a current patient at the

ACTT clinic. This research study partially fulfills the requirements of a Doctor of Philosophy

(PhD) degree for Jacqueline Galica, who is being supervised by Dr. Carol Townsley.

The purpose of this research study is to explore the thoughts, feelings and activities of cancer

survivors, and any thoughts and feelings that they may have about the possibility of the cancer

returning. This fear of the possibility of the cancer returning is known as ‘fear of cancer

recurrence’, which survivors say is a common issue for them and they want help to cope with it.

If you are interested in participating in this study, you will be asked to complete a one-time

questionnaire. The questionnaire will help the researchers to learn about the different

experiences, thoughts and feelings of cancer survivors, as well as their fears about cancer

recurrence. This information will be useful for healthcare professionals to identify people at

highest risk for these fears after treatment, and to develop interventions to improve the care

provided to cancer survivors.

The questionnaire takes approximately 30-45 minutes to complete. Your identity and all of

your responses will be kept confidential. Your care at the ACTT clinic will not be affected by

your decision to participate or not in this study. At this time, only ACTT patients who can read,

write, and understand English are invited to participate in this study.

There is no need to contact the researchers or staff at the ACTT clinic right now. If you

would like to move forward with participating in this study, you have 2 options:

1. You can review the consent form online, and complete the survey

electronically at www.fluidsurveys.com/.

OR

2. In approximately 10 days, you will be mailed a package containing a consent

form, study questionnaires, and a postage-paid return-addressed envelope.

Please 1) read and sign the consent form in the package, 2) complete the

study questionnaires, and 3) return these documents in the return-addressed,

postage-paid envelope that will be provided.

If you do not want to be contacted again about this study, please call 416-351-3800 x 2761, or

email [email protected], and leave your full name so that you can be removed

from the researcher’s contact list.

Thank you for considering to participate in this study.

Kind regards,

Carol Townsley, MD, MSc

Medical Director, After Cancer Treatment Transition Clinic

180

Appendix D: Consent Form

STUDY TITLE: Fear of Cancer Recurrence Among Survivors of Adult Cancers

INVESTIGATOR: Dr. Carol Townsley (416) 323-6400 Ext 3297

CO-INVESTIGATOR: Jacqueline Galica

INTRODUCTION

You are being asked to take part in a research study. Before agreeing to participate in this

study, it is important that you read and understand the following explanation of the proposed

study procedures. The following information describes the purpose, procedures, benefits,

discomforts, risks and precautions associated with this study. It also describes your right to

refuse to participate or withdraw from the study at any time. In order to decide whether you wish

to participate in this research study, you should understand enough about its risks and benefits to

be able to make an informed decision. This is known as the informed consent process. Please ask

the study staff to explain any words you don’t understand before signing this consent form. Make

sure all your questions have been answered to your satisfaction before signing this document.

BACKGROUND

The purpose of this research study is to explore the thoughts, feelings and activities of cancer

survivors, and any thoughts and feelings that they may have about the possibility of the cancer

returning. This fear of the possibility of the cancer returning is known as ‘fear of cancer

recurrence’, which survivors claim is a dominant issue in their lives with which they want help to

cope.

You have been asked to participate in this research study because you have completed

treatment for a diagnosis of cancer, and are being followed as a cancer survivor in the After

Cancer Treatment Transition (ACTT) clinic. All of the cancer survivors at the ACTT clinic are

being invited to participate in the study. This research partially fulfills the requirements of a

Doctor of Philosophy (PhD) degree for Jacqueline Galica, who is being supervised by Dr. Carol

Townsley.

PROCEDURES

If you agree to participate in this research study, you will be asked to complete the

questionnaires in this study package and return them in the return-addressed postage-paid

envelope. Or, you may still complete these documents at FluidSurveys.com using the access

code provided in the previously mailed Information Letter. The questionnaires ask about any

thoughts that you may have about the cancer returning, your cancer and treatment experiences,

how you perceive these experiences, how you generally feel and cope, about your personality,

how you describe yourself generally, as well as some demographic information. The

questionnaire should take approximately 30-45 minutes to complete, and you may take small

breaks in between the sections of the questionnaire as you need. When complete, this consent

form and the questionnaires can be returned to the investigator in the return-addressed postage-

paid envelope provided in this study package. After you have completed and returned all study

documents to the investigator, your name will be included into a draw for an IPAD mini. You

will be asked to complete this questionnaire one-time only.

In addition to agreeing to complete this survey, you are giving the investigator permission to

review your medical chart at the ACTT to retrieve information about your cancer diagnosis,

surgery (if applicable), and treatment (if applicable).

POTENTIAL RISKS OR BENEFITS

We know of no harm that taking part in this study could cause you. However, the ACTT

clinic staff will refer you to appropriate services and resources if necessary. Taking part in this

181

study will not affect your medical treatment in any way. There are also no direct benefits to you.

The aim is to find out more information about the experiences of cancer survivors so that

information learned from this study may benefit other patients in the future. Individual study

results will not be given to participants.

CONFIDENTIALITY

We will respect your privacy. Any of your personal information (information about you and

your health that identifies you as an individual) collected or obtained, whether you choose to

participate or not, will be kept confidential and protected to the fullest extent of the law. All

personal information collected will be kept in a secure location. The study staff, the WCH

Research Ethics Board, employees of sponsor or funder of study, Health Canada may look at

your personal information for purposes associated with the study. The mentioned authorized

personnel may view your records only under the supervision of the Principal Investigator and

will be obligated to protect your privacy and not disclose your personal information. None of

your personal information will be given to anyone without your permission unless required by

law.

The data produced from this study will be stored in a secure location. Only numbers of the

research team will have access to the data. This could include external research team members.

Following completion of the research study the data will be kept as long as required then

destroyed as required according to WCH policy. Published studies will not reveal your identity.

PARTICIPATION

Your participation in this study is voluntary. You can choose not to participate or you may

withdraw at any time without affecting your medical care.

QUESTIONS

If you suffer any side effects or other injuries during the study, or if you have any general

questions about the study, please call Dr. Townsley at (416) 323-6400 ext. 3297. If you have

any questions about your rights as a research participant, please call the Chair of Women’s

College Hospital Research Ethics Board at (416) 351-3732 ext. 2325. This person is not involved

with the research project in any way and calling will not affect your participation in the study. If

you would like some assistance to complete the study documents, please call please call 416-

351-3800 x 2761.

CONSENT

I have had the opportunity to discuss this study and my questions have been answered to my

satisfaction. I consent to take part in the study with the understanding I may withdraw at any

time without affecting my medical care. I also give the investigator permission to access my

medical chart at the ACTT, in order to have information about my cancer diagnosis, surgery and

treatment reviewed. I voluntarily consent to participate in this study.

182

Appendix E: Fear of Cancer Recurrence Inventory (30)

184

Appendix F: Demographic Form Study ID (investigator use only): ______________

Clearly print/type your full initials and date of birth indicating that you have read and

fully understand the information provided in the consent form:

______________ _________________

Initials (F/M/L) DOB (mm/yy)

This section of the survey lists some general questions about you and your health. These

questions will help the investigators to understand the characteristics of the cancer survivors

attending the ACTT clinic.

1. What is your age (in years) right now: ___________

2. What is your marital status? Circle one only.

i. Common-law

ii. Married

iii. Widowed

iv. Divorced

v. Separated

vi. Single (never-married)

vii. Other (specify) _______

3. a) How many children do you have? ____

b) What are their ages? _________________________

4. What is the highest level of education that you have completed? Circle one only.

i. No formal education

ii. Some elementary school

iii. Some high school

iv. High school graduate

v. Some community college or trade/technical school

vi. Community college or trade/technical school graduate

vii. Some university

viii. University graduate (Undergraduate Level)

ix. Some university (Graduate-Level)

x. University graduate (Graduate-Level)

xi. Other (specify) _________________________

5. Which statement most accurately describes your current work status? Circle one only.

i. Working at a job/business

ii. With a job/business but not at work

iii. Not working with a job/business

iv. Looking for work

v. Other (specify) _______

185

6. Which of the following best describes where your ancestors originated from? Circle one only.

i. White, Caucasian, or European descent

ii. Chinese, Southeast Asian, Korean, Japanese

iii. Filipino

iv. South Asian (East Indian, Pakistani, Sri Lankan, etc.)

v. Black or African American/African Canadian

vi. Hispanic, Latino, Mexican American, or Central American

vii. Arab, or West Asian

viii. Native Canadian (Inuit, Indigenous)

ix. Mixed (parents are from 2 different groups)

x. Other (specify) _________________________

7. How many generations of your family have been born in Canada? Circle one only.

i. I am the 1st generation born in Canada (my parent(s) were not born in Canada)

ii. I am the 2nd generation born in Canada (my grandparent(s) were not born in Canada)

iii. I am the 3rd or higher generation born in Canada.

iv. I was not born in Canada.

8. As far as you know, do you have any of the following health conditions at the present time?

i. Asthma, emphysema, chronic bronchitis ………….............................. yes no

ii. Arthritis or rheumatism ………………………………………………. yes no

iii. Diabetes ………………………………………………………………. yes no

iv. Digestive problems (such as ulcer, colitis, or gallbladder disease) …… yes no

v. Heart trouble (such as angina, congestive heart failure, or

coronary artery disease) ………………………………………………. yes no

vi. HIV illness or AIDS ………………………………………………....... yes no

vii. Kidney disease ……………………………………………………....... yes no

viii. Liver problems (such as cirrhosis) ……………………………………. yes no

ix. Stroke …………………………………………………………………. yes no

x. Other (specify all) ___________________________________________________

9. In your personal life, is/was there someone close to you who has had a diagnosis and

treatment for cancer, and then the cancer came back (cancer recurrence)?

Yes No Don’t Know

b) Has that person’s cancer returning affected your fear that your cancer may come back?

Yes No Don’t Know

10. What is your relationship with the ACTT clinic? Circle one only.

i. I am currently being followed by the ACTT clinic staff.

ii. I have been discharged from the ACTT clinic and am no longer followed by the ACTT

clinic staff.

11. What are the first 3 characters of your postal code? ___ ___ ___

186

Appendix G: Data Extraction Form

Study ID (investigator use only): ___________

1. Sex:

i. Male

ii. Female

iii. Other/Not indicated

2. Year of diagnostic surgery: ___________ (yyyy)

3. Cancer type:

i. Breast

ii. GI

iii. Testicular

iv. Gynecological

v. Melanoma

vi. Thyroid

vii. Other

5. Chemotherapy:

i. No

ii. Yes. Completed regimen:

i. No, completed treatment earlier than planned.

Date of last treatment: ________________ (mm/yyyy)

ii. Yes.

Date of last treatment: ________________ (mm/yyyy) iii. Other (specify) _____________________

6. Radiation:

i. No

ii. Yes. Completed regimen:



ii. Yes.


4. AJCC Stage: __________

187

7. Other treatment:

i. No

ii. Yes (specify) __________________________

a. Ongoing: Y N

b. Completed regimen:



ii. Yes.


8. Has this patient ever been diagnosed with metastatic/recurrent disease or another primary?

iii. No

iv. Yes (specify type) __________________________

c. Currently receiving treatment: Y N

d. Completed regimen:

iv. No, completed treatment earlier than planned.


v. Yes.

Date of last treatment: ________________ (mm/yyyy) vi. Other (specify) _____________________

188

Appendix H: Rosenberg Self-Esteem Scale (174)

Below is a list of statements dealing with your general feelings about yourself. If you strongly

agree, circle SA. If you agree with the statement, circle A. If you disagree, circle D. If you

strongly disagree, circle SD.

1. On the whole, I am satisfied with myself. SA A D SD

2. At times, I think I am no good at all. SA A D SD

3. I feel that I have a number of good qualities. SA A D SD

4. I am able to do things as well as most other people. SA A D SD

5. I feel I do not have much to be proud of. SA A D SD

6. I certainly feel useless at times. SA A D SD

7. I feel that I’m a person of worth, at least on an equal plane with

others. SA A D SD

8. I wish I could have more respect for myself. SA A D SD

9. All in all, I am inclined to feel that I am a failure. SA A D SD

10. I take a positive attitude toward myself. SA A D SD

Str

on

gly

Ag

ree

Ag

ree

Dis

agre

e S

tro

ng

ly

Dis

agre

e

189

Appendix I: Big Five Inventory -10 (BFI-10) (180)

How well do the following statements describe your personality?

I see myself as someone

who…

Disagree

strongly

Disagree

a little

Neither agree

nor disagree

Agree a

little

Agree

strongly

…is reserved 1 2 3 4 5

… …is generally trusting 1 2 3 4 5

…tends to be lazy 1 2 3 4 5

…is relaxed, handles stress

well 1 2 3 4 5

…has few artistic interests 1 2 3 4 5

…is outgoing, sociable 1 2 3 4 5

…tends to find fault with

others 1 2 3 4 5

…does a thorough job 1 2 3 4 5

…gets nervous easily 1 2 3 4 5

…has an active imagination 1 2 3 4 5

190

Appendix J: Revised Life Orientation Test (LOT-R) (115)

Please be as honest and accurate as you can throughout. Try not to let your response to one

statement influence your responses to other statements. There are no "correct" or "incorrect"

answers. Answer according to your own feelings, rather than how you think "most people"

would answer.

Strongly

Disagree Disagree Neutral Agree

Strongly

Agree

1. In uncertain times, I usually

expect the best. 0 1 2 3 4

2. It’s easy for me to relax. 0 1 2 3 4

3. If something can go wrong for

me, it will. 0 1 2 3 4

4. I'm always optimistic about my

future. 0 1 2 3 4

5. I enjoy my friends a lot. 0 1 2 3 4

6. It's important for me to keep

busy. 0 1 2 3 4

7. I hardly ever expect things to go

my way. 0 1 2 3 4

8. I don't get upset too easily 0 1 2 3 4

9. I rarely count on good things

happening to me. 0 1 2 3 4

10.Overall, I expect more good

things to happen to me than bad. 0 1 2 3 4

191

Appendix K: Illness Perception Questionnaire – Revised (IPQ-R) (103)

YOUR VIEWS ABOUT YOUR CANCER DIAGNOSIS

Listed below are a number of symptoms that you may or may not have experienced since

completing treatment for cancer. Please indicate by circling Yes or No, whether you have

experienced any of these symptoms since completing treatment for cancer, and whether you

believe that these symptoms are related to your cancer diagnosis.

I have experienced this

symptom since completing This symptom is related

treatment for cancer to my cancer diagnosis

Pain Yes No -------------------------------- Yes No

Sore Throat Yes No -------------------------------- Yes No

Nausea Yes No -------------------------------- Yes No

Breathlessness Yes No -------------------------------- Yes No

Weight Loss Yes No -------------------------------- Yes No

Fatigue Yes No -------------------------------- Yes No

Stiff Joints Yes No -------------------------------- Yes No

Sore Eyes Yes No -------------------------------- Yes No

Wheeziness Yes No -------------------------------- Yes No

Headaches Yes No -------------------------------- Yes No

Upset Stomach Yes No -------------------------------- Yes No

Sleep Difficulties Yes No -------------------------------- Yes No

Dizziness Yes No -------------------------------- Yes No

Loss of Strength Yes No -------------------------------- Yes No

We are interested in your own personal views of how you now see your cancer diagnosis.

Please indicate how much you agree or disagree with the following statements about your cancer

diagnosis by ticking the appropriate box.

VIEWS ABOUT YOUR CANCER

DIAGNOSIS Strongly Disagree

Disagree Neither Agree nor

Disagree Agree

Strongly Agree

IP1

My cancer will last a short time IP2

My cancer is likely to be permanent rather than

temporary

IP3

My cancer will last for a long time IP4

This cancer will pass quickly IP5

IP6

I expect to have this cancer for the rest of my life

My cancer is a serious condition IP7

My cancer has major consequences on my life IP8

IP9

IP10

IP11

My cancer does not have much effect on my life

My cancer strongly affects the way others see me

My cancer has serious financial consequences

My cancer causes difficulties for those who are

close to me

192

VIEWS ABOUT YOUR CANCER

DIAGNOSIS

Strongly

Disagree Disagree

Neither Agree nor

Disagree Agree

Strongly

Agree

IP12 There is a lot which I can do to control my

symptoms

IP13

IP14

What I do can determine whether my cancer gets better or worse

The course of my cancer depends on me IP15

IP16

IP17

IP18

IP19

Nothing I do will affect my cancer

I have the power to influence my cancer

My actions will have no effect on the outcome of

my cancer

My cancer will improve in time

There is very little that can be done to

improve my cancer

IP20

My treatment will be effective in curing my cancer IP21

IP22

IP23

IP24

IP25

IP26

IP27

IP28

The negative effects of my cancer can be

prevented (avoided) by my treatment

My treatment can control my cancer

There is nothing which can help my condition

The symptoms of my condition are puzzling to me

My cancer is a mystery to me

I don’t understand my cancer

My cancer doesn’t make any sense to me I have a clear picture or understanding of my

condition

IP29 The symptoms of my cancer change a great

deal from day to day

IP30

My symptoms come and go in cycles IP31

My cancer is very unpredictable IP32

I go through cycles in which my cancer gets better and worse.

IP33

I get depressed when I think about my cancer IP34

When I think about my cancer I get upset IP35

My cancer makes me feel angry IP36

My cancer does not worry me IP37

Having this cancer makes me feel anxious IP38

My cancer makes me feel afraid

193

CAUSES OF MY CANCER

We are interested in what you consider may have been the cause of your cancer. As people are

very different, there is no correct answer for this question. We are most interested in your own

views about the factors that caused your cancer rather than what others including doctors or

family may have suggested to you. Below is a list of possible causes of your cancer. Please

indicate how much you agree or disagree that they were causes for you by ticking the appropriate

box.

POSSIBLE CAUSES Strongly Disagree

Disagree

Neither

Agree nor Disagree

Agree Strongly Agree

C1

Stress or worry C2

C3

C4

C5

C6

Hereditary - it runs in my family

A Germ or virus

Diet or eating habits

Chance or bad luck

Poor medical care in my past C7

C8

C9

C10

Pollution in the environment

My own behaviour

My mental attitude e.g. thinking about life

negatively

Family problems or worries caused my

illness

C11

Overwork C12

C13

C14

C15

My emotional state e.g. feeling down, lonely, anxious, empty

Ageing

Alcohol

Smoking C16

Accident or injury C17

My personality C18

Altered immunity

In the table below, please list in rank-order the three most important factors that you now believe

caused YOUR cancer. You may use any of the items from the box above, or you may have

additional ideas of your own.

The most important causes for me:

1. _______________________________________

2. _______________________________________

3. _______________________________________

194

Appendix L: Brief COPE (126)

These items deal with ways that you cope with any stress in your life. There are many ways to

try to deal with problems. These items ask what you do to cope. Obviously, different people

deal with things in different ways, but I'm interested in how you deal with things. Each item

says something about a particular way of coping. I want to know to what extent you do what the

item says. How much or how frequently. Don't answer on the basis of whether it’s worked or

not—just whether or not you do it. Use the response choices. Try to rate each item separately in

your mind from the others. Make your answers as true FOR YOU as you can.

I don’t

do this at

all

I do this

a little

bit

I do this a

medium

amount

I do this a

lot

1. I turn to work or other activities to take

my mind off things. 1 2 3 4

2. I concentrate my efforts on doing

something about the situation I'm in. 1 2 3 4

3. I say to myself "this isn't real.". 1 2 3 4

4. I use alcohol or other drugs to make

myself feel better 1 2 3 4

5. I get emotional support from others. 1 2 3 4

6. I give up trying to deal with it. 1 2 3 4

7. I take action to try to make the situation

better. 1 2 3 4

8. I refuse to believe that it has happened. 1 2 3 4

9. I say things to let my unpleasant

feelings escape. 1 2 3 4

10. I get help and advice from other people. 1 2 3 4

11. I use alcohol or other drugs to help me

get through it. 1 2 3 4

12. I try to see it in a different light, to

make it seem more positive 1 2 3 4

13. I criticize myself. 1 2 3 4

14. I try to come up with a strategy about

what to do. 1 2 3 4

15. I get comfort and understanding from

someone 1 2 3 4

16. I give up the attempt to cope. 1 2 3 4

17. I look for something good in what is

happening. 1 2 3 4

195

I don’t

do this at

all

I do this

a little

bit

I do this a

medium

amount

I do this a

lot

18. I make jokes about it. 1 2 3 4

19. I do something to think about it less,

such as going to movies, watching TV,

reading, daydreaming, sleeping, or

shopping.

1 2 3 4

20. I accept the reality of the fact that it has

happened. 1 2 3 4

21. I express my negative feelings. 1 2 3 4

22. I try to find comfort in my religion or

spiritual beliefs. 1 2 3 4

23. I try to get advice or help from other

people about what to do. 1 2 3 4

24. I learn to live with it. 1 2 3 4

25. I think hard about what steps to take. 1 2 3 4

26. I blame myself for things that

happened. 1 2 3 4

27. I pray or meditate. 1 2 3 4

28. I make fun of the situation. 1 2 3 4

196

Appendix M: Follow up Telephone Call Script

Researcher: Hello, may I speak to [patient name] please?

Researcher: Hello Mr/Ms. [patient surname]. My name is Jacqueline Galica, and I’m a

researcher working under Dr. Carol Townsley at the ACTT clinic at Women’s College Hospital.

Recently, all of the ACTT clinic invited to participate in a research study of cancer survivors.

You were also invited to participate in this research because you have completed treatment for

cancer and are a current patient of the ACTT clinic. Did you receive information about this

study?

Patient: Yes.

Researcher: I’m calling you because we have not received any study documents from you. I

wanted to remind you that we appreciate your time to complete this study in order for us to learn

more about the thoughts, feelings and activities of cancer survivors, and any thoughts and

feelings that they may have about the possibility of the cancer returning. Have you given any

thought to participating in this study?

Patient: No.

Researcher: Could I answer any questions that

you have, or will you be declining participation

in this study?

Patient: Asks questions. Patient: Decline

Researcher: Answers Researcher: questions.

For our records,

may I ask

you if

you’ll be

completing

the study

online, or if

not

participating

your

reasons?

Patient: Yes.

Researcher: Could I answer

any questions that you have,

or can I redirect you to the

study documentation?

197

Patient responds: No.

Researcher: I’m calling you because we have not received any study documents from you, and

now I know that you haven’t received these from us. To repeat, all of the ACTT clinic have

been invited to participate in this research study of cancer survivors. You are also invited to

participate in this research because you have completed treatment for cancer and are a current

patient of the ACTT clinic. The researchers appreciate your time to complete this study in order

for us to learn more about the thoughts, feelings and activities of cancer survivors, and any

thoughts and feelings that they may have about the possibility of the cancer returning. This fear

of the possibility of the cancer returning is known as ‘fear of cancer recurrence’, which survivors

claim is a common issue in their lives and they want help to cope with it.

If you are interested in participating in this study, you will be asked to complete a one-time

questionnaire. The questionnaire will help the researchers to learn about the different

experiences, thoughts and feelings of cancer survivors, as well as their fears about cancer

recurrence. This information will be useful for healthcare professionals to identify people at

highest risk for these fears after treatment, and to develop interventions to improve the care

provided to cancer survivors. Your care at the ACTT clinic will not be affected by your decision

to participate or not, in this study. Your identity and all of your responses will be kept

confidential.

The questionnaire takes approximately 30-45 minutes to complete. If you would like to

participate, you have 2 options: you can review the consent form and complete the survey online;

or I can mail you a package that contains a consent form, study questionnaires, and a postage-

paid return-addressed envelope. Could I answer any questions that you have? ___ May I ask

which option you would prefer?

Online By Mail

Please 1) read and sign the consent form in the package, 2)

complete the study questionnaires, and 3) return these documents

in the return-addressed, postage-paid envelope that will be

provided.

Researcher (when concluding all discussions): Thank you for considering this study. We

appreciate your time. If you’d like again/at a later date, please call 416-351-3800 x 2761. Bye.

NOTE: The following message will be left on voicemail if no one picks up:

Hello, M- (patient surname), this is Jacqueline Galica calling. I’m calling to remind you about

some questionnaires that were mailed to you approximately 2 weeks ago. I’ve noticed that we

haven’t received the completed questionnaires from you and wanted to let you know that we

really value your perspective. If you’d like to discuss the questionnaires I’d be happy to help

you. Otherwise, please consider completing and returning them as soon as you’re able. You can

call my team at (416) 351-3800 x 2761. Good-bye.

198

Appendix N: Detailed Sample Characteristics

Table N.1: Detailed Characteristics of the sample


Age in years, mean (SD) 61.1 (12.0)

Sex

Female 852 (85.2)

Male 148 (14.8)

Marital Status

Common-law 62 (6.2)

Married 619 (61.8)

Widowed 85 (8.5)

Divorced 91 (9.1)

Separated 23 (2.3)

Single (never married) 119 (11.9)

Other 2 (0.2)

Parental Status

Not Parent 261 (26.1)

Parent 739 (73.7)

Highest level of Education

No formal education 5 (0.5)

Some elementary school 18 (1.8)

Some high school 39 (3.9)

High school graduate 100 (10.0)

Some community college or

trade/technical school

49 (4.9)

Community college or

trade/technical school graduate

145 (14.5)

Some university (Undergraduate Level) 90 (9.0)

University graduate (Undergraduate Level) 248 (24.8)

Some university (Graduate Level) 40 (4.0)

University graduate (Graduate Level) 255 (25.5)

Other 12 (1.2)

Employment Status

Working at a job/business 459 (45.8)

With a job/business but not at work 24 (2.4)

Not working with a job/business 116 (11.6)

Looking for work 27 (2.7)

Other 374 (37.3)

199

Table N.1 continued: Detailed Characteristics of the sample


Ethnicity

White, Caucasian, or European descent 773 (77.4)

Chinese, Southeast Asian, Korean, Japanese 66 (6.6)

Filipino 39 (3.9)

South Asian (east Indian, Pakistani, Sri Lankan, etc.) 32 (3.2)

Black or African American/African Canadian 27 (2.7)

Hispanic, Latino, Mexican American, or Central

American

13 (1.3)

Arab, or West Asian 13 (1.3)

Native Canadian (Inuit, Indigenous) 2 (0.2)

Mixed (parents are from 2 different groups) 13 (1.3)

Other 21 (2.1)

Immigration Status

First-generation born in Canada 184 (18.4)

Second-generation born in Canada 134 (13.4)

Third-generation or higher born in Canada 244 (24.4)

Not born in Canada 437 (43.7)

Residential Location in Ontario

Eastern Ontario 24 (2.4)

Central Ontario 307 (30.6)

Metro Toronto 637 (63.6)

Western Ontario 21 (2.1)

Northern Ontario 8 (0.8)

Resides outside of Ontario 5 (0.5)

Rural or Urban Location

Rural 32 (3.2)

Urban 970 (96.8)

200

Table N.2: Detailed Clinical Characteristics of the sample

Characteristic N (%)1

Time (years) since diagnosis, mean (SD) 9.1 (5.1)

Diagnosis Type

Breast 661 (66.2)

Gastro-Intestinal 88 (8.8)

Testicular 52 (5.2)

Gynecological 79 (7.9)

Melanoma 77 (7.7)

Thyroid 36 (3.6)

Other 5 (0.5)

AJCC Staging

0 25 (2.5)

1 393 (39.4)

2 374 (37.5)

3 183 (18.3)

4 10 (1.0)

Another cancer/recurrence/metastasis 219 (21.8)

Treatment received

Chemotherapy 550 (55.6)

Radiation 640 (64.6)

Other Cancer Treatment 628 (63.4)

Co-Morbid Conditions, mean (SD) .81 (.972)

ACTT status

Followed at clinic 733 (73.2)

Discharged from clinic 269 (26.8)


Yes 482 (48.5)

No 446 (44.9)

Don’t know 65 (6.5)

Knowing someone with recur affects FCR

Yes 250 (25.1)

No 403 (40.4)

Don’t know 344 (34.5) 1 Unless otherwise stated.

201

Table N.3: Additional Clinical Characteristics of Participants



Co-Morbid Conditions, mean (SD) .81 (.972)

Asthma, Emphysema, Bronchitis 85 (8.5)

Arthritis or rheumatism 298 (29.8)

Diabetes 89 (8.9)

Digestive Problems (ulcers, colitis, gallbladder) 76 (7.6)

Heart Trouble (angina, CHF, CAD) 55 (5.5)

HIV/AIDS 0 (0)

Liver Problems (cirrhosis) 10 (1.0)

Stroke 14 (1.4)

Other 169 (17) 1 Unless otherwise stated

Symptoms

experienced since

completing treatment

N (%)

Believe that the symptom is

caused by cancer

No (N[%]) Yes (N[%])

Pain 541 (54.9) 666 (69.8) 288 (30.2)

Sore throat 358 (36.0) 935 (97.3) 26 (2.7)

Nausea 280 (28.4) 903 (94.3) 55 (5.7)

Breathlessness 268 (27.0) 868 (90.9) 87 (9.1)

Weight loss 171 (17.3) 906 (95.4) 44 (4.6)

Fatigue 626 (63.2) 628 (65.5) 331 (34.5)

Stiff joints 575 (58.2) 755 (79.5) 195 (20.5)

Sore eyes 230 (23.3) 904 (95.1) 47 (4.9)

Wheeziness 124 (12.6) 928 (97.3) 26 (2.7)

Headaches 349 (35.4) 903 (94.6) 52 (5.4)

Upset stomach 374 (37.9) 873 (91.3) 83 (8.7)

Sleep difficulties 549 (55.4) 770 (80.6) 185 (19.4)

Dizziness 265 (26.8) 897 (93.4) 63 (6.6)

Loss of strength 433 (43.9) 722 (75.8) 230 (24.2)

202

Appendix O: Analyses of Missing Data

Missing data on the FCRI

The demographic and clinical characteristics of participants who had acceptable or unacceptable

amounts of missing data (per the developer’s guidelines) for the dependent variable (FCRI) were

compared. Independent T-tests and chi-square analyses were run for the continuous and

categorical variables, respectively. Having had radiation treatment was the only variable that

significantly differed between respondents who had acceptable and unacceptable amounts of

missing data on the FCRI. This chi-square was 7.14 (Fisher’s Exact 2-sided significance = .005).

204

Missing Data on the IPQ-R

Acceptability (per Developer’s Guidelines) of Missing Data on the IPQ-R Subscales

Timeline

(Acute/

Chronic)

Consequ-

ences

Personal

Control

Treatment

Control

Illness

Coherenc

e

Timeline

Cyclical

Emotional

Represent-

ations

N (%) N (%) N (%) N (%) N (%) N (%) N (%)

Acceptable

amount of

missing data

951

(94.9)

958

(95.6) 956 (95.4) 926 (92.4) 935 (93.3)

921

(91.9) 933 (93.1)

Unacceptabl

e amount of

missing data

51 (5.1) 44 (4.4) 46 (4.6) 76 (7.6) 67 (6.7) 81 (8.1) 69 (6.9)

The demographic and clinical characteristics of participants who had acceptable or unacceptable

amounts of missing data (per the developer’s guidelines) on the subscales of the IPQ-R subscales

were compared. Independent T-tests and chi-square analyses were run for the continuous and

categorical variables, respectively. Significant differences are reported herein.

Marital status and employment status significantly differed between the amounts of acceptable

and unacceptable missing data on the Timeline Acute/Chronic subscale. Those that were

married or common-law had more acceptable amounts of missing data on the Timeline

Acute/Chronic subscale. Those that were not actively employed had greater amounts of

acceptable and unacceptable missing data on the Timeline Acute/Chronic subscale.

Marital status, employment status, and age, significantly differed between the amounts of

acceptable and unacceptable missing data on the Consequences subscale. Those that were

married or common-law had more acceptable amounts of missing data on the Consequences

subscale. Those that were not actively working had greater amounts of acceptable and

unacceptable missing data on the Consequences subscale.

Marital status, employment status, and age, significantly differed between the amounts of

acceptable and unacceptable missing data on the Personal Control subscale. Those that were

married or common-law had greater amounts of acceptable missing data on the Personal Control

subscale. Those that were not actively working had greater amounts of acceptable and

unacceptable missing data on this subscale.

205

Marital status, education level, employment status, and age, significantly differed between the

amounts of acceptable and unacceptable missing data on the Treatment Control subscale. Those

that were married or common-law or were baccalaureate graduates or higher had greater amounts

of missing data on the Treatment Control subscale that was acceptable per the developer’s

guidelines. Those that were not actively working and lower AJCC stages (Stages 0-2) had greater

amounts of missing data, both acceptable and unacceptable amounts, on the Treatment Control

subscale.

A comparison of acceptable-unacceptable amounts of missing data on the IPQ-R

IPQ-R Subscale * Variable1 Chi-

Square

Fisher’s Exact

(2-sided Sig.)

t-test for Equality

of Means (2-tailed

Sig.)

Timeline Acute/Chronic * Marital 6.49 .015 -

Timeline Acute/Chronic * Employment 5.31 .024 -

Consequences * Marital 4.59 .038 -

Consequences * Employ 5.82 .022 -

Consequences * Age - - .066

Personal Control * Marital 4.91 .041 -

Personal Control * Employment 7.02 .011 -

Personal Control * Age - - .024

Treatment Control * Marital 5.517 .025 -

Treatment Control * Education 6.47 .013 -

Treatment Control * Employment 6.29 .014 -

Treatment Control * AJCC Stage 7.25 .006 -

Treatment Control * Age - - .002

Illness Coherence * Education 7.27 .008 -

Illness Coherence * Employment 4.44 .037 -

Illness Coherence * AJCC Stage 8.46 .002 -

Illness Coherence * Age - - .001

Timeline Cyclical * Employment 4.12 .044 -

Timeline Cyclical * AJCC Stage 6.87 .008 -

Timeline Cyclical * Age - - .003

Emotional Representation * Education 4.71 .038 -

Emotional Representation * Employment 5.35 .021 -

Emotional Representation * AJCC Stage 7.18 .006 -

Emotional Representation * Cancer Type 3.85 .058 -

Emotional Representation * Age - - .005 1 Only significant differences have been reported.

Level of education, employment status, AJCC stage, and age, significantly differed between the

amounts of acceptable and unacceptable missing data on the Illness Coherence subscale.

Baccalaureate graduates or higher, as well as those with lower AJCC stage (Stage 0-2) had

higher amounts of acceptable missing data, and those that weren’t actively working had greater

amounts of unacceptable missing data.

206

Employment status and AJCC stage significantly differed between amounts of acceptable and

unacceptable missing data on the Timeline Cyclical subscale. Those that were not actively

working, and those with lower AJCC stage (Stages 0-2) had higher amounts of unacceptable and

acceptable missing data on the Timeline Cyclical subscale than those that were actively working

or had higher AJCC stages (stages 3-4).

Education level, AJCC Stage, type of cancer, and age, significantly differed between the

amounts of acceptable and unacceptable missing data on the Emotional Representations

subscale. Those that were baccalaureate graduates or higher had higher amounts of acceptable

missing data on the Emotional Representation subscale. Those that had lower AJCC stages

(stages 0-2), and those with breast cancer had higher amounts of acceptable and unacceptable

missing data on the Emotional Representation subscale.

Missing Data on the Brief COPE

Frequencies of 0 or 1+ Missing Items on the Brief COPE Subscales

No missing

data

N (%)

Missing data

for ≥ 1 item

N (%)

Self-Distraction subscale 976 (97.4) 26 (2.6)

Active Coping subscale 968 (96.6) 34 (3.4)

Denial subscale 976 (97.4) 26 (2.6)

Substance Use subscale 979 (97.7) 23 (2.3)

Emotional Support subscale 975 (97.3) 27 (2.7)

Behavioural Disengagement

subscale 970 (96.8) 32 (3.2)

Venting subscale 967 (96.5) 35 (3.5)

Instrumental Support subscale 972 (97.0) 30 (3.0)

Positive Reframing subscale 977 (97.5) 25 (2.5)

Self-Blame subscale 976 (97.4) 26 (2.6)

Planning subscale 962 (96.0) 40 (4.0)

Humour subscale 978 (97.6) 24 (2.4)

Acceptance subscale 970 (96.8) 32 (3.2)

Religion subscale 975 (97.3) 27 (2.7)

The demographic and clinical characteristics of participants who did not have, or at least had one

missing item on the each of the Brief COPE subscales were compared. Independent T-tests and

chi-square analyses were run for the continuous and categorical variables, respectively.

Significant differences are reported herein.

207

The presence of missing versus not missing any data on the Brief COPE Denial and Self-Blame

subscales significantly differed by knowing someone who had a recurrence that affected the

participant’s FCR (yes/no).

The presence of missing versus not missing any data on the Brief COPE Positive Reframing

subscale significantly differed by Other Treatment (yes/no).

The presence of missing versus not missing any data on the Brief COPE Planning subscale

significantly differed by Employment status (actively working versus not actively working),

knowing someone who had a recurrence that affected the participant’s FCR (yes/no), having had

Other Treatment (yes/no), and age.

The presence of missing versus not missing any data on the Brief COPE Acceptance subscale

significantly differed by Employment status (actively working versus not actively working).

A comparison of missing/non-missing data on the Brief COPE subscales

1 Only significant differences have been reported.

Brief COPE Subscale * Variable1 Chi-

Square

Asymp. Sig.

(2-sided)

Fisher’s Exact

(2-sided Sig.)

t-test for Equality

of Means (2-tailed

Sig.)

Denial * A person’s Recurrence

Affects my FCR 6.09 .047 - -

Positive Reframing * Other

Treatment 6.07 .014 .019 -

Planning * Employment 7.26 .007 .009 -

Planning * A person’s Recurrence

Affects my FCR 12.73 .002 - -

Planning * Other Treatment 6.10 .013 .018 -

Planning * Age - - - .021

Self-Blame * A person’s

Recurrence Affects my FCR 7.07 .029 - -

Acceptance * Employment 4.16 .041 .047 -

208

Missing Data on the RSES

Frequencies of 0 or 1+ Missing Items on the RSES

No missing data

N (%)

Missing data for ≥

1 item

N (%)

RSES 955 (95.3) 47 (4.7)


missing item on the RSES, were compared. Independent T-tests and chi-square analyses were

run for the continuous and categorical variables, respectively. Significant differences are

reported herein.

Employment status (actively working vs not actively working) and age significantly differed

between those that did not miss or had at least one-item missing on the RSES.

A comparison of missing/non-missing data on the RSES

Variable1 Chi-Square Fisher’s Exact

(2-sided Sig.)

t-test for Equality of Means

(2-tailed Sig.)

Employment status 6.54 .011 -

Age - - .003 1 Only significant differences have been reported.

209

Missing Data on the BFI-10

Frequencies of 0 or 1+ Missing Items on the BFI-10 subscales

No missing data

N (%)


1 item

N (%)

Extraversion subscale 980 (97.8) 22 (2.2)

Agreeableness subscale 987 (98.5) 15 (1.5)

Conscientiousness subscale 980 (97.8) 22 (2.2)

Neuroticism subscale 984 (98.2) 18 (1.8)

Openness subscale 982 (98.0) 20 (2.0)


missing item on the BFI-10 were compared. Independent t-tests and chi-square analyses were run

for the continuous and categorical variables, respectively.

Having received other cancer treatment (yes/no) significantly differed between those that did not

miss or had at least one-item missing on the BFI-10 Extraversion subscale, while the presence of

another cancer (yes/no) significantly differed in terms of missing data on the BFI-10

Conscientiousness subscale. Age significantly differed in the presence or absence of missing

data on all of the BFI-10 subscales.

A comparison of missing/non-missing data on the BFI-10 subscales

BFI-10 Subscale * Variable1 Chi-

Square

Fisher’s Exact

(2-sided Sig.)

t-test for

Equality of

Means (2-sided

Sig.)

Extraversion * Other Treatment 4.59 .038 -

Extraversion * Age - - .005

Conscientiousness * Another Cancer 4.56 .045 -

Conscientiousness * Age - - .004

Agreeableness * Age - - .029

Neuroticism * Age - - .030

Openness * Age - - .018 1 Only significant differences have been reported.

210

Missing Data on the LOT-R

Frequencies of 0 or 1+ Missing Items on the LOT-R

No missing data

N (%)


1 item

N (%)

LOT-R 982 (98.0) 20 (2.0)


missing item on the LOT-R were compared. Independent T-tests and chi-square analyses were

run for the continuous and categorical variables, respectively.

Employment status (actively working vs not actively working), ethnicity (White/Caucasian vs all

other ethnicities), and immigration status (born vs not born in Canada) significantly differed

between those that did not miss or had at least one-item missing on the LOT-R. All other

characteristics did not significantly differ.

A comparison of 0-1+ items of missing data on the LOT-R

Variable1 Chi-

Square

Fisher’s Exact

(2-sided Sig.)

Employment status 10.54 .001

Ethnicity 5.67 .028

Immigration status 5.77 .021 1 Only significant differences have been reported.

211

Appendix P: Details of Measures Used

Table P.1: Characteristics of Participants

Characteristic Measure

Min-Max

Mean (SD) Sample

Min-Max

Fear of Cancer Recurrence Inventory

(FCRI) 0-164 57.80 (28.66) 0-155

FCRI-Severity Subscale 0-34 14.81 (7.61) 0-34

Self-Esteem (RSES) 0-30 23.77 (5.226) 0-30

Personality (BFI-10)

Extraversion subscale 2-10 6.63 (2.073) 1-10

Agreeableness subscale 2-10 7.75 (1.674) 1-10

Conscientiousness subscale 2-10 8.41 (1.756) 2-10

Neuroticism subscale 2-10 5.63 (2.260) 1-10

Openness subscale 2-10 6.94 (1.793) 2-10

Generalized Expectancies (LOT-R) 0-24 16.00 (4.299) 0-24

Illness Representation (IPQ-R)

Identity 0-12 1.71 (2.354) 0-12

Timeline (Acute/Chronic) subscale 0-30 13.97 (4.80) 6-30

Consequences subscale 0-30 17.27 (5.52) 6-30

Personal Control subscale 0-30 20.46 (4.187) 6-30

Treatment Control subscale 0-25 19.62 (3.021) 11-25

Illness Coherence subscale 0-25 22.45 (5.103) 6-30

Timeline (Cyclical) subscale 0-20 9.19 (3.313) 4-19

Emotional Representations subscale 0-30 17.05 (5.884) 6-30

Coping Styles

Self-Distraction subscale 2-8 5.86 (1.634) 1-8

Active Coping subscale 2-8 6.17 (1.609) 1-8

Denial subscale 2-8 2.81 (1.297) 1-8

Substance Use subscale 2-8 2.56 (1.180) 1-8

Emotional Support subscale 2-8 5.17 (1.842) 1-8

Behavioural Disengagement subscale 2-8 2.62 (1.088) 1-8

Venting subscale 2-8 4.20 (1.496) 1-8

Instrumental Support subscale 2-8 4.96 (1.850) 1-8

Positive Reframing subscale 2-8 5.49 (1.656) 1-8

Self-Blame subscale 2-8 3.66 (1.569) 1-8

Planning subscale 2-8 5.83 (1.734) 1-8

Humour subscale 2-8 3.98 (1.792) 1-8

Acceptance subscale 2-8 6.47 (1.432) 1-8

Religion subscale 2-8 4.66 (2.271) 1-8

212

Table P.2: Internal Consistencies of Measures and Subscales

Measure N of

items

α

Fear of Cancer Recurrence Inventory (FCRI) 42 .953

Triggers subscale 8 .917

Severity subscale 9 .881

Psychological Distress subscale 4 .891

Functioning Impairments subscale 6 .938

Insight subscale 3 .881

Reassurance subscale 3 .761

Coping Strategies subscale 9 .892

Rosenberg Self-Esteem Scale (RSES) 10 .897

Big Five Inventory-10 (BFI-10)

Extraversion subscale 2 .553

Agreeableness subscale 2 .325

Conscientiousness subscale 2 .472

Neuroticism subscale 2 .635

Openness subscale 2 .008

Revised Life Orientation Test (LOT-R) 6 .804

Illness Perception Questionnaire-Revised (IPQ-R)

Timeline (acute/chronic) subscale 6 .858

Consequences subscale 6 .822

Personal Control subscale 6 .796

Treatment Control subscale 5 .737

Illness Coherence subscale 5 .875

Timeline Cyclical subscale 4 .829

Emotional Representation subscale 6 .913

Coping Styles

Self-Distraction subscale 2 .550

Active Coping subscale 2 .740

Denial subscale 2 .607

Substance Use subscale 2 .925

Emotional Support subscale 2 .844

Behavioural Disengagement subscale 2 .627

Venting subscale 2 .527

Instrumental Support subscale 2 .835

Positive Reframing subscale 2 .723

Planning subscale 2 .728

Self-Blame subscale 2 .709

Humour subscale 2 .842

Acceptance subscale 2 .638

Religion subscale 2 .908

213

Table P.2: Unstandardized Coefficients and Standard Errors, and Standardized Coefficients of

the Parceled items in the FCRI Subscales/Factors

Subscale/Factor B SE B β P

Triggers

Parcel 1 (items 1,2,8) 1.000 0.000 0.866 999.000

Parcel 2 (items 3,5,7) 1.205 0.029 0.946 <0.001

Parcel 3 (items 4,6) 0.775 0.019 0.884 <0.001

Severity

Parcel 1 (items 10,15,17) 1.000 0.000 0.880 999.000

Parcel 2 (items 9,11,12) 0.922 0.022 0.910 <0.001

Parcel 3 (items 13,14,16) 0.508 0.020 0.651 <0.001

Psychological Distress

Parcel 1 (items 18,20) 1.000 0.000 0.931 999.000

Parcel 2 (items 19) 0.556 0.012 0.870 <0.001

Parcel 3 (items 21) 0.492 0.013 0.795 <0.001

Functional Impairment

Parcel 1 (items 25,26) 1.000 0.000 0.891 999.000

Parcel 2 (items 22,24) 0.858 0.024 0.913 <0.001

Parcel 3 (items 23,27) 0.937 0.022 0.966 <0.001

Insight

Parcel 1 (items 30) 1.000 0.000 0.841 999.000

Parcel 2 (items 28) 1.190 0.059 0.900 <0.001

Parcel 3 (items 29) 0.935 0.052 0.803 <0.001

Reassurance

Parcel 1 (items 31) 1.000 0.000 0.847 999.000

Parcel 2 (items 32) 0.983 0.048 0.815 <0.001

Parcel 3 (items 33) 0.792 0.056 0.559 <0.001

Coping

Parcel 1 (items 38,40,42) 1.000 0.000 0.825 999.000

Parcel 2 (items 34,36,41) 1.157 0.032 0.869 <0.001

Parcel 3 (items 35,37,39) 1.165 0.032 0.885 <0.001

214


the FCRI Subscales/Factors with the Total FCRI Score


Triggers 1.000 0.000 0.800 999.000

Severity 1.324 0.045 0.886 <0.001

Psychological Distress 0.910 0.038 0.944 <0.001

Functional Impairments 0.608 0.037 0.674 <0.001

Insight 0.260 0.018 0.740 <0.001

Reassurance 0.172 0.018 0.385 <0.001

Coping 0.588 0.044 0.447 <0.001

215


the RSES items with the RSES Factors


the LOT-R items with the LOT-R Factors

Factor B SE B β P

Negatively-worded

Item 2R 1.000 0.000 0.784 999.000

Item 5R 0.799 0.036 0.673 <0.001

Item 6R 1.056 0.033 0.796 <0.001

Item 8R 1.006 0.041 0.688 <0.001

Item 9R 0.815 0.033 0.796 <0.001

Positively-worded

Item 1 1.000 0.000 0.019 999.000

Item 3 0.638 0.041 0.031 <0.001

Item 4 0.807 0.045 0.025 <0.001

Item 7 0.785 0.045 0.035 <0.001

Item 10 0.992 0.042 0.023 <0.001

Factor B SE B β P

Optimism

Item 1 1.000 0.000 0.561 999.000

Item 4 1.291 0.087 0.740 <0.001

Item 10 1.213 0.103 0.780 <0.001

Pessimism

Item 3R 1.000 0.000 0.676 999.000

Item 7R 1.091 0.062 0.760 <0.001

Item 9R 1.234 0.072 0.811 <0.001

216


the Parceled items in the IPQ-R Subscales/Factors


Timeline (acute/chronic)

Parcel 1 (items 2, 4) 1.000 0.000 0.877 999.000

Parcel 2 (items 3, 18) 0.794 0.030 0.822 <0.001

Parcel 3 (items 1, 5) 0.994 0.029 0.861 <0.001

Timeline (cyclical)

Parcel 1 (items 29, 31) 1.000 0.000 0.826 999.000

Parcel 2 (items 30) 0.555 0.025 0.771 <0.001

Parcel 3 (items 32) 0.515 0.027 0.786 <0.001

Consequences

Parcel 1 (items 7, 11) 1.000 0.000 0.920 999.000

Parcel 2 (items 6, 10) 0.693 0.026 0.742 <0.001

Parcel 3 (items 8, 9) 0.764 0.026 0.791 <0.001

Personal Control

Parcel 1 (items 13, 14) 1.000 0.000 0.688 999.000

Parcel 2 (items 16, 17) 1.109 0.061 0.810 <0.001

Parcel 3 (items 12, 15) 0.849 0.057 0.729 <0.001

Treatment Control

Parcel 1 (items 19, 21) 1.000 0.000 0.695 999.000

Parcel 2 (items 20, 23) 1.189 0.072 0.857 <0.001

Parcel 3 (items 22) 0.530 0.035 0.652 <0.001

Illness Coherence

Parcel 1 (items 26, 27) 1.000 0.000 0.913 999.000

Parcel 2 (items 24, 28) 0.626 0.029 0.741 <0.001

Parcel 3 (items 25) 0.554 0.014 0.897 <0.001

Emotional Representation

Parcel 1 (items 36, 37) 1.000 0.000 0.830 999.000

Parcel 2 (items 33, 35) 1.103 0.035 0.868 <0.001

Parcel 3 (items 34, 38) 1.239 0.033 0.956 <0.001

217


the parceled Brief COPE items with the Coping Style Factors

Factor B SE B β P

Active Coping Style

Parcel 1 (items 1, 9, 12, 17, 20, 22) 1.000 0.000 0.788 999.000

Parcel 2 (items 5, 10, 15, 19, 21, 23) 0.867 0.058 0.521 <0.001

Parcel 3 (items 2, 7, 14, 24, 25, 27) 1.207 0.074 0.859 <0.001

Escapist Coping Style

Parcel 1 (items 3, 6, 16) 1.000 0.000 0.442 999.000

Parcel 2 (items 4, 8, 26) 2.110 0.174 1.000 <0.001

Parcel 3 (items 11, 13) 1.090 0.116 0.607 <0.001

218

Appendix Q: Exploratory Bivariate Analyses

Table Q.1: Nominal Independent Variables with FCRI: Exploratory Bivariate Analysis


Sex - 7.090 (<0.001) 0.203 (<0.001) 0.041 1.772

Men 44.01

Women 60.29

Marital Status 1.687 (0.092) 0.054 (0.090) 0.003 1.200

Married/Common-Law 58.87

All other groups 55.55

Parental Status - 1.348 (0.178) 0.043 (0.173) 0.002 1.233

Parent 58.56

Not Parent 55.75

Level of Education 0.896 (0.371) 0.029 (0.368) 0.001 1.171

Up to some university 56.87

Undergrad graduate or higher

and other 58.53

Employment status - 2.038 (0.042) 0.065 (0.042) 0.004 1.610

Actively employed 59.81

Not actively employed 56.08

Ethnicity 2.770 (0.006) 0.090 (0.005) 0.008 1.529

Caucasian 56.39

Non-Caucasian 62.53

Immigration status 2.057 (0.040) 0.066 (0.039) 0.004 1.403

Not born in Canada 59.27

Born in Canada 56.14

Urban/Rural Status 1.660 (0.107) 0.051 (0.108) 0.003 1.066

Urban 58.07

Rural 49.67

Diagnosis Type 5.098 (<0.001) 0.160 (<0.001) 0.026 2.472

Breast Cancer survivors 61.11

Non Breast Survivors 51.46

219

Table Q.1 continued: Nominal Independent Variables with FCRI: Exploratory Bivariate Analysis


Diagnosis Stage 1.305 (0.192) 0.042 (0.191) 0.002 1.459

AJCC Stages 0-1 56.39

AJCC Stages 2-4 & missing 58.81

Chemotherapy 4.268 (<0.001) 0.136 (<0.001) 0.018 1.728

Yes 61.38

No 53.54

Radiation 3.432 (<0.001) 0.109 (0.001) 0.012 1.595

Yes 60.27

No 53.73

Other Cancer treatment 3.721 (<0.001) 0.117 (<0.001) 0.014 1.649

Yes 60.49

No 53.53

Any Cancer Treatment -3.783 (<0.001) 0.109 (0.001) 0.012 1.000

Yes 48.54

No 58.97

Know someone with recurrence 4.387 (<0.001) 0.127 (<0.001) 0.016 1.459

Yes and Don’t know 61.35

No 53.33

Believe knowing someone with

recur affects FCR 14.101 (<0.001) 0.395 (<0.001) 0.156

1.647

Yes 77.25

No and Don’t know 51.22

Another cancer diagnosis (B) 1.740 (0.083) 0.055 (0.084) 0.003 1.206

Yes 54.92

No 58.67

ACTT clinic status 3.886 (<0.001) 0.120 (<0.001) 0.014 1.231

Current patient 59.85

Discharged patient 52.06

220

Table Q.2: Continuous Independent Variables with FCRI: Exploratory Bivariate Statistics

Measure r (Sig.) VIF

Age -0.233 (<0.001) 2.160

Number of Comorbidities 0.015 (0.645) 1.286

Symptom burden 0.378 (<0.001) 1.489

Time Since Diagnosis -0.052 (0.109) 1.417

Rosenberg Self-Esteem Scale (RSES) -0.342 (<0.001) 2.639

Big Five Inventory-10 (BFI-10)

Extraversion -0.049 (0.122) 1.240

Agreeableness subscale -0.073 (0.023) 1.293

Conscientiousness 0.009 (0.768) 1.376

Neuroticism subscale 0.354 (<0.001) 1.608

Openness 0.048 (0.136) 1.148

Revised Life Orientation Test (LOT-R) -0.348 (<0.001) 2.386

Illness Perception Questionnaire-Revised (IPQ-R)

Timeline (acute/chronic) subscale 0.399 (<0.001) 1.791

Consequences subscale 0.461 (<0.001) 2.158

Personal Control subscale -0.053 (0.104) 1.434

Treatment Control subscale -0.205 (<0.001) 1.862

Illness Coherence subscale -0.295 (<0.001) 1.543

Timeline Cyclical subscale 0.339 (<0.001) 1.493

Emotional Representation subscale 0.698 (<0.001) 2.407

Coping Styles

Self-Distraction subscale 0.315 (<0.001) 1.356

Active subscale 0.033 (0.310) 1.989

Denial subscale 0.288 (<0.001) 1.352

Substance Use subscale 0.082 (0.011) 1.176

Emotional Support subscale 0.091 (0.005) 2.504

Behavioural Disengagement subscale 0.253 (<0.001) 1.511

Venting subscale 0.221 (<0.001) 1.598

Instrumental Support subscale 0.125 (<0.001) 2.592

Positive Reframing subscale -0.008 (0.806) 1.752

Planning subscale 0.076 (0.019) 2.093

Self-Blame subscale 0.320 (<0.001) 1.820

Humour subscale -0.003 (0.923) 1.343

Acceptance subscale -0.046 (0.149) 1.380

Religion subscale 0.158 (<0.001) 1.461

Coping Styles (used in CFA’s)

Active factor 0.172 (<.001) 1.001

Escapist factor 0.389 (<.001) 1.001

221

Appendix R: Analysis of Direct Effects

Table R.1: Direct Effects of Variables on Fear of Cancer Recurrence

Predictor Variables B SE B β P

Age -0.024 0.005 -0.149 <0.001

Sex -0.758 0.179 -0.139 <0.001

Diagnosis (type) -0.068 0.144 -0.017 0.637

Any Cancer Treatment 0.089 0.179 0.014 0.620

Symptom burden 0.190 0.029 0.232 <0.001

Know someone with a recurrence -0.417 0.120 -0.108 0.001

Believe knowing someone with recur

affects FCR 1.667 0.164 0.375 <0.001

ACTT clinic status 0.302 0.118 0.069 0.010

Self-Esteem (RSES)

Negatively worded items factor -0.374 0.139 -0.227 0.006

Positively worded items factor 0.192 0.219 0.081 0.383

Generalized Expectancies (LOT-R)

Optimism factor -0.776 0.281 -0.220 0.004

Pessimism factor -0.161 0.149 -0.060 0.281

222

Appendix S: Exploratory Mediation Analyses

Table S.1: P-values of Exploratory Mediation Analyses prior to Objective 3a

Paths

Direct

(Unstandardized/

Standardized)

Specific Indirect

(Unstandardized/

Standardized)

Age→Timeline (acute/chronic)→FCR <0.001/<0.001 0.629/0.629

Age→Timeline (cyclical)→FCR <0.001/<0.001 0.004/0.004

Age→Consequences→FCR 0.006/0.006 <0.001/<0.001

Age→Treatment Control→FCR <0.001/<0.001 0.667/0.667

Age→Personal Control→FCR <0.001/<0.001 0.161/0.160

Age→Illness Coherence→FCR <0.001/<0.001 0.938/0.938

Age→Emotional Representation→FCR 0.047/0.046 <0.001/<0.001

Sex→Timeline (acute/chronic)→FCR <0.001/<0.001 0.015/0.015

Sex→Timeline (cyclical)→FCR <0.001/<0.001 0.027/0.027

Sex→Consequences →FCR <0.001/<0.001 0.529/0.529

Sex→ Treatment Control→FCR <0.001/<0.001 0.227/0.227

Sex→ Personal Control→FCR <0.001/<0.001 0.732/0.732

Sex→ Illness Coherence→FCR <0.001/<0.001 0.113/0.111

Sex→Emotional Representation→FCR 0.002/0.002 <0.001/<0.001

Diagnosis(type) →Timeline (acute/chronic)→FCR <0.001/<0.001 0.018/0.017

Diagnosis(type) →Timeline (cyclical)→FCR <0.001/<0.001 0.437/0.436

Diagnosis(type) →Consequences →FCR <0.001/<0.001 0.152/0.151

Diagnosis(type)→ Treatment Control→FCR <0.001/<0.001 0.304/0.305

Diagnosis(type)→ Personal Control→FCR <0.001/<0.001 0.582/0.583

Diagnosis(type)→ Illness Coherence→FCR 0.001/0.001 0.463/0.462

Diagnosis(type)→Emotional Representation→FCR 0.033/0.032 0.001/0.001

Any Cancer Treatment→Timeline

(acute/chronic)→FCR 0.006/0.006 0.743/0.743

Any Cancer Treatment→Timeline (cyclical)→FCR <0.001/<0.001 0.329/0.329

Any Cancer Treatment→Consequences →FCR 0.620/0.619 <0.001/<0.001

Any Cancer Treatment→ Treatment Control→FCR <0.001/<0.001 0.010/0.010

Any Cancer Treatment→ Personal Control→FCR 0.004/0.004 0.867/0.867

Any Cancer Treatment→ Illness Coherence→FCR 0.010/0.010 0.093/0.092

Any Cancer Treatment→Emotional

Representation→FCR 0.536/0.536 0.004/0.004

223

Table S.1 continued: P-values of Exploratory Mediation Analyses prior to Objective 3a

Paths

Direct

(Unstandardized/

Standardized)

Specific Indirect

(Unstandardized/

Standardized) Know someone with a recurrence→ Timeline

(acute/chronic)→FCR 0.001/0.001 0.037/0.036

Know someone with a recurrence →Timeline

(cyclical)→FCR <0.001/<0.001 0.813/0.814

Know someone with a recurrence →Consequences

→FCR <0.001/<0.001 0.106/0.103

Know someone with a recurrence→ Treatment

Control→FCR <0.001/<0.001 0.775/0.775

Know someone with a recurrence→ Personal Control→FCR

<0.001/<0.001 0.731/0.731

Know someone with a recurrence→ Illness

Coherence→FCR <0.001/<0.001 0.149/0.149

Know someone with a recurrence→Emotional

Representation→FCR <0.001/<0.001 0.067/0.064

Believe knowing someone with recur affects FCR

→Timeline (acute/chronic)→FCR <0.001/<0.001 <0.001/<0.001


→Timeline (cyclical)→FCR <0.001/<0.001 <0.001/<0.001


→Consequences →FCR <0.001/<0.001 <0.001/<0.001

Believe knowing someone with recur affects FCR→ Treatment Control→FCR

<0.001/<0.001 0.005/0.005

Believe knowing someone with recur affects FCR→

Personal Control→FCR <0.001/<0.001 0.255/0.254

Believe knowing someone with recur affects FCR→

Illness Coherence→FCR <0.001/<0.001 0.016/0.015


→Emotional Representation→FCR <0.001/<0.001 <0.001/<0.001

ACTT clinic status →Timeline (acute/chronic)→FCR <0.001/<0.001 0.145/0.144

ACTT clinic status →Timeline (cyclical)→FCR <0.001/<0.001 0.868/0.868

ACTT clinic status →Consequences →FCR <0.001/<0.001 0.195/0.193

ACTT clinic status → Treatment Control→FCR <0.001/<0.001 0.384/0.383

ACTT clinic status → Personal Control→FCR <0.001/<0.001 0.563/0.562

ACTT clinic status → Illness Coherence→FCR <0.001/<0.001 0.374/0.373

ACTT clinic status →Emotional Representation→FCR <0.001/<0.001 0.013/0.012

Symptom Burden→Timeline (acute/chronic)→FCR <0.001/<0.001 <0.001/<0.001

Symptom Burden→Timeline (cyclical)→FCR <0.001/<0.001 <0.001/<0.001

Symptom Burden→Consequences →FCR <0.001/<0.001 <0.001/<0.001

Symptom Burden→ Treatment Control→FCR <0.001/<0.001 <0.001/<0.001

Symptom Burden→ Personal Control→FCR <0.001/<0.001 0.364/0.364

Symptom Burden→ Illness Coherence→FCR <0.001/<0.001 0.017/0.016

Symptom Burden→Emotional Representation→FCR <0.001/<0.001 <0.001/<0.001

224


Paths

Direct

(Unstandardized/

Standardized)

Specific Indirect

(Unstandardized/

Standardized) Self-Esteem1 (positively worded factor) →Timeline

(acute/chronic)→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (positively worded factor) →Timeline

(cyclical)→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (positively worded factor)


Self-Esteem1 (positively worded factor)→ Treatment

Control→ FCR <0.001/<0.001 0.004/0.004

Self-Esteem1 (positively worded factor)→ Personal Control→FCR

<0.001/<0.001 0.685/0.684

Self-Esteem1 (positively worded factor)→ Illness

Coherence→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (positively worded factor) →Emotional

Representation→FCR 0.009/0.007 <0.001/<0.001

Self-Esteem1 (negatively worded factor) →Timeline

(acute/chronic) →FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (negatively worded factor) →Timeline

(cyclical)→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (negatively worded factor)


Self-Esteem1 (negatively worded factor) → Treatment Control→FCR

<0.001/<0.001 0.002/0.002

Self-Esteem1 (negatively worded factor) → Personal

Control→FCR <0.001/<0.001 0.839/0.840

Self-Esteem1 (negatively worded factor) → Illness

Coherence→FCR 0.001/0.001 <0.001/<0.001

Self-Esteem1 (negatively worded factor) →Emotional

Representation→FCR <0.001/<0.001 <0.001/<0.001

1Rosenberg Self-Esteem Scale (RSES) (174)

225


Paths

Direct

(Unstandardized/

Standardized)

Specific Indirect

(Unstandardized/

Standardized)

Generalized Expectancies2 (optimism)





→Consequences →FCR <0.001/<0.001 0.020/0.049

Generalized Expectancies2 (optimism)→

Treatment Control→FCR <0.001/<0.001 0.543/0.527

Generalized Expectancies2 (optimism)→ Personal Control→FCR

<0.001/<0.001 0.040/0.028

Generalized Expectancies2 (optimism)→ Illness

Coherence→FCR <0.001/<0.001 0.866/0.870

Generalized Expectancies2

(optimism)→Emotional Representation→FCR <0.001/<0.001 <0.001/<0.001

Generalized Expectancies2 (pessimism)






Generalized Expectancies2 (pessimism)→

Treatment Control→FCR <0.001/<0.001 0.514/0.518


Personal Control→FCR <0.001/<0.001 0.339/0.335


Illness Coherence→FCR <0.001/<0.001 0.153/0.160


→Emotional Representation→FCR 0.007/0.006 <0.001/<0.001

2 Revised Life Orientation Test (LOT-R) (115)

226

Table S.2: P-values of Exploratory Mediation Analyses prior to Objective 3b

Paths

Direct

(Unstandardized/

Standardized)

Specific Indirect

(Unstandardized/

Standardized)

Age→Active Coping→FCR <0.001/<0.001 0.958/0.958

Age→ Escapist Coping →FCR <0.001/<0.001 0.001/0.001

Sex→ Active Coping→FCR <0.001/<0.001 0.595/0.595

Sex→ Escapist Coping→FCR <0.001/<0.001 0.609/0.609

Diagnosis(type)→ Active Coping →FCR <0.001/<0.001 0.429/0.428

Diagnosis(type)→ Escapist Coping →FCR <0.001/<0.001 0.624/0.624

Any Cancer Treatment→ Active Coping→FCR 0.007/0.007 0.389/0.388

Any Cancer Treatment→Escapist

Coping→FCR 0.010/0.010 0.317/0.317

Know someone with a recurrence→ Active Coping →FCR

<0.001/<0.001 0.714/0.741

Know someone with a recurrence→ Escapist

Coping →FCR <0.001/<0.001 0.335/0.333

Believe knowing someone with recur affects

FCR → Active Coping→FCR <0.001/<0.001 0.617/0.617


FCR →Escapist Coping →FCR <0.001/<0.001 0.002/0.001

ACTT clinic status → Active Coping→FCR <0.001/<0.001 0.447/0.446

ACTT clinic status → Escapist Coping→FCR <0.001/<0.001 0.441/0.440

Symptom Burden→ Active Coping →FCR <0.001/<0.001 0.548/0.547

Symptom Burden→ Escapist Coping →FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (positively worded factor) →

Active Coping→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (positively worded factor) →

Escapist Coping→FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (negatively worded factor) →

Active Coping →FCR <0.001/<0.001 <0.001/<0.001

Self-Esteem1 (negatively worded factor) →

Escapist Coping →FCR <0.001/<0.001 <0.001/<0.001

Generalized Expectancies2 (optimism) →

Active Coping→FCR <0.001/<0.001 <0.001/<0.001


→Escapist Coping →FCR <0.001/<0.001 0.002/0.002

Generalized Expectancies2 (pessimism) →

Active Coping→FCR <0.001/<0.001 0.002/0.001


→Escapist Coping →FCR <0.001/<0.001 <0.001/<0.001

1Rosenberg Self-Esteem Scale (RSES) (174); 2Revised Life Orientation Test (LOT-R) (115)

227

Appendix T: Analyses of Indirect Effects

Table T.1: Unstandardized coefficients (95%CI), standard errors, and standardized coefficients of effects in Objective 3a

Paths Direct Specific Indirect Total Indirect Total Effect

Age→FCR -0.010* (-0.020,0.004)

0.004, -0.061

-0.014** (-0.023,0.002)

0.003, -0.090

-0.024**(-0.035, -0.013)

0.005, -0.151

Age→Timeline (acute/chronic)→FCR 0.003*(<0.001, 0.009)

0.001, 0.016

Age→Illness Coherence→FCR 0.000 (-0.004, 0.003)

0.000, -0.002

Age→Emotional Representation→FCR -0.017**(-0.030,<0.001)

0.003, -0.103

Sex→FCR -0.424*(-0.871, -0.014)

0.150, -0.077

-0.348* (-0.661, 0.228)

0.127, -0.064

-0.773** (-1.131, -0.341)

0.181, -0.141

Sex→Timeline (acute/chronic)→FCR -0.006 (-0.074, 0.076)

0.030, -0.001

Sex→Illness Coherence →FCR 0.014 (-0.030, 0.258)

0.014, 0.002

Sex→Emotional Representation→FCR -0.356* -0.625, 0.008)

0.120, -0.065

Diagnosis(type)→FCR -0.089 (-0.318, 0.219)

0.116, -0.022

0.026 (-0.171, 0.236)

0.092, 0.006

-0.063 (-0.331, 0.285)

0.145, -0.015

Diagnosis(type)→Timeline

(acute/chronic)→FCR

0.021 (-0.014, 0.159)

0.022, 0.005

Diagnosis(type) →Illness Coherence→FCR 0.005 (-0.037, 0.137)

0.008, 0.001

Diagnosis(type)→Emotional

Representation→FCR

0.000 -0.200, 0.201)

0.086, 0.000

Any Cancer Treatment→FCR 0.003 (-0.322, 0.436)

0.153, 0.000

0.083 (-0.162, 0.411) 0.127, 0.013

0.086 (-0.251, 0.497) 0.182, 0.013

Any Cancer Treatment→Timeline


-0.045 (-0.162, 0.042)

0.034, -0.007

Any Cancer Treatment→Illness

Coherence→FCR

-0.009 (-0.165, 0.109)

0.011, -0.001

Any Cancer Treatment→Emotional


0.137 (-0.101, 0.439)

0.118, 0.021

** p≤.001; *p≤.05. 1Rosenberg Self-Esteem Scale (RSES); 2Revised Life Orientation Test (LOT-R).

228

Table T.1 continued: Unstandardized coefficients (95%CI), standard errors, and standardized coefficients of effects in Objective 3a



Know someone with a recurrence →FCR -0.125 (-0.432, 0.317)

0.100, -0.032

-0.283*(-0.556, 0.130)

0.093, -0.073

-0.409**(-0.615,-0.108)

0.123, -0.105

Know someone with a recurrence →Timeline


-0.011 (-0.067, 0.035)

0.022, -0.003

Know someone with a recurrence →Illness

Coherence→FCR

0.014 (-0.103, 0.185)

0.014, 0.004

Know someone with a recurrence →Emotional


-0.287**(-0.502, 0.060)

0.087, -0.074


FCR→FCR

0.854**(0.140, 1.877)

0.137, 0.191

0.820**(0.068, 0.967)

0.119, 0.184

1.674** (1.377, 2.051)

0.164, 0.375


FCR →Timeline (acute/chronic)→FCR

0.077*(0.003,0.283)

0.032, 0.017


FCR →Illness Coherence→FCR

-0.015 (-0.132, 0.264)

0.014, -0.003


FCR→Emotional Representation→FCR

0.758** (0.326, 1.625)

0.112, 0.170

ACTT clinic status →FCR 0.300* (0.091, 0.582)

0.100, 0.068

0.016 (-0.124, 0.262)

0.081, 0.004

0.316*(0.058, 0.628)

0.120, 0.072 ACTT clinic status →Timeline


0.017 (-0.17, 0.097)

0.020, 0.004

ACTT clinic status →Illness Coherence→FCR -0.001 (-0.071, 0.050)

0.006, 0.000

ACTT clinic status →Emotional


0.000 (-0.141, 0.202)

0.077, 0.000

Symptom Burden→FCR 0.072* (-0.035, 0.230)

0.024, 0.088

0.116** (0.047, 0.305)

0.019, 0.141

0.188** (0.125, 0.266)

0.029, 0.229

Symptom Burden→Timeline


0.023** (0.001, 0.080)

0.007, 0.028

Symptom Burden→Illness Coherence→FCR 0.000 (-0.007, 0.014)

0.001, 0.000

Symptom Burden→Emotional


0.092** (0.044, 0.270)

0.017, 0.112

229

Table T.1 continued: Unstandardized coefficients (95%CI), standard errors, and standardized coefficients of effects in Objective 3a



Self-Esteem1 (negatively worded factor)→FCR -0.213 (-9.638, 4.166)

0.120, -0.128

-0.260 (-5.838, 6.742)

0.279, -0.157

-0.473 (-10.451, 1.874)

0.316, -0.285

Self-Esteem1 ( negatively worded

factor)→Timeline (acute/chronic)→FCR

-0.027 (-1.155, 0.782)

0.053, -0.016

Self-Esteem1 ( negatively worded factor )→Illness Coherence→FCR

0.020 (-0.008, 4.000)

0.027, 0.012

Self-Esteem1 ( negatively worded factor )

→Emotional Representation→FCR

-0.253 (-4.345, 6.926)

0.250, -0.153

Self-Esteem1 (positively worded factor) →FCR 0.200 (-7.817, 30.883)

0.201, 0.084

0.222 (-2.471, 22.512)

0.571, 0.093

0.422 (-0.449, 26.242)

0.604, 0.178

Self-Esteem1 (positively worded

factor)→Timeline (acute/chronic) →FCR

0.074 (-0.040, 2.631)

0.111, 0.031

Self-Esteem1 (positively worded factor)→Illness

Coherence→FCR

-0.014 (-6.475, 0.050)

0.040, -0.006


→Emotional Representation→FCR

0.162 (-2.753, 14.383)

0.502, 0.068

Generalized Expectancies2 (optimism)→FCR -0.185 (-10.789, 14.495)

0.259, -0.052

-0.769 (-18.839, 12.662)

0.566, -0.217

-0.954 (-19.009, 4.473)

0.589, -0.269 Generalized Expectancies2 (optimism)→Timeline


-0.221 (-2.470, 1.646)

0.120, -0.062

Generalized Expectancies2 (optimism)→Illness

Coherence→FCR

-0.010 (-0.106, 6.017)

0.032, -0.003


(optimism)→Emotional Representation→FCR

-0.538 (-9.381, 11.410)

0.490, -0.152

Generalized Expectancies2 (pessimism)→FCR -0.022 (-3.631, 9.448)

0.129, -0.008

-0.141 (-1.093, 7.046)

0.258, -0.052

-0.162 (-0.759, 8.625)

0.264, -0.060


(pessimism)→Timeline (acute/chronic)→FCR

-0.019 (-0.335, 0.997)

0.051, -0.007

Generalized Expectancies2 (pessimism)→Illness

Coherence→FCR

0.033 (-0.851, 0.593)

0.027, 0.012

Generalized Expectancies2 (pessimism) →Emotional Representation→FCR

-0.154 (-0.562, 5.555)

0.217, -0.057

230

Table T.2: Unstandardized coefficients (95%CI), standard errors, and standardized coefficients of effects in Objective 3b


Age→FCR -0.022** (-0.032, -0.009)

0.005, -0.135

-0.002 (-0.004, 0.001)

0.001, -0.010

-0.023** (-0.034, -0.010)

0.005, -0.145

Age→Active Coping→FCR 0.000 (-0.002, 0.001)

0.001, -0.002

Age→Escapist Coping→FCR -0.001 (-0.003, 0.000)

0.001, -0.008

Sex→FCR -0.655**(-1.033, -0.264)

0.182, -0.122

-0.051 (-0.147, 0.062)

0.046, -0.009

-0.716**(-1.073, -0.290)

0.180, -0.131

Sex→Active Coping→FCR -0.058 (-0.136, 0.000)

0.033, -0.011

Sex→Escapist Coping→FCR 0.007 (-0.044, 0.089)

0.028, 0.001

Diagnosis(type)→FCR -0.040 (-0.312, 0.278)

0.143, -0.010

-0.029 (-0.099, 0.052)

0.033, -0.007

-0.070 (-0.352, 0.281)

0.144, -0.017

Diagnosis(type)→Active Coping→FCR -0.032 (-0.087, 0.020)

0.022, -0.008

Diagnosis(type)→Escapist Coping→FCR 0.002 (-0.038, 0.057)

0.021, 0.000

Any Cancer Treatment→FCR -0.006 (-0.330, 0.458)

0.184, -0.001

0.077 (-0.004, 0.209)

0.050, 0.012

0.071 (-0.249, 0.490)

0.179, 0.011

Any Cancer Treatment→Active Coping→FCR 0.082* (0.029, 0.203)

0.038, 0.013

Any Cancer Treatment→Escapist Coping→FCR -0.004 (-0.060, 0.082)

0.028, -0.001

Know someone with a recurrence→FCR -0.392*(-0.602. -0.049)

0.118, -0.101

-0.034 (-0.108, 0.046)

0.030, -0.009

-0.426**(-0.637, -0.127)

0.119, -0.110

Know someone with a recurrence →Active

Coping→FCR

-0.030 (-0.083, 0.006)

0.020, -0.008

Know someone with a recurrence →Escapist

Coping→FCR

-0.004 (-0.053, 0.048)

0.021, -0.001


FCR→FCR

1.587**(1.290,.977)

0.161, 0.356

0.086*(0.013, 0.214)

0.040, 0.019

1.673**(1.381, 2.043)

0.164, 0.376


FCR→Active Coping→FCR

0.055*(0.011, 0.160)

0.027, 0.012


FCR→Escapist Coping→FCR

0.031 (-0.011, 0.130)

0.027, 0.007

** p≤.001; *p≤.05. . 1Rosenberg Self-Esteem Scale (RSES); 2Revised Life Orientation Test (LOT-R).

231

Table T.2 continued: Unstandardized coefficients (95%CI), standard errors, and standardized coefficients of effects in Objective 3b

** p≤.001; *p≤.05. . 1Rosenberg Self-Esteem Scale (RSES); 2Revised Life Orientation Test (LOT-R).


ACTT clinic status →FCR 0.293* (0.059, 0.602)

0.116, 0.067

0.014 -0.044, 0.083)

0.028, 0.003

0.307*(0.064, 0.623)

0.118, 0.070

ACTT clinic status→Active Coping→FCR 0.022 (-0.006, 0.075)

0.018, 0.005

ACTT clinic status→Escapist Coping→FCR -0.008 (-0.048, 0.041)

0.019, -0.002

Symptom Burden→FCR 0.181** (0.127, 0.259)

0.028, 0.221

0.008 (-0.003, 0.026) 0.006, 0.010

0.190**(0.129, 0.265) 0.029, 0.232

Symptom Burden→Active Coping→FCR 0.004 (-0.001, 0.015)

0.003, 0.004

Symptom Burden→Escapist Coping→FCR 0.005 (-0.003, 0.018)

0.005, 0.006

Self-Esteem1 (negatively worded factor )→FCR -0.213 (-0.572, 0.137)

0.145, -0.129

-0.165** (-0.306, -0.068)

0.048, -0.100

-0.378*(-0.708, -0.051)

0.141, -0.229

Self-Esteem1 (negatively worded factor )→Active

Coping→FCR

-0.051*(-0.133, -0.008)

0.024, -0.031

Self-Esteem1 (negatively worded factor )

→Escapist Coping→FCR

-0.114*(-0.225, -0.038)

0.039, -0.069

Self-Esteem1 (positively worded factor) →FCR 0.100 (-0.300, 0.820)

0.213, 0.043

0.094 )-0.020, 0.278)

0.060, 0.040

0.195 (-0.204, 0.906)

0.221, 0.083 Self-Esteem1 (positively worded factor) →Active

Coping→FCR

0.066 (0.012, 0.204)

0.037, 0.028


→Escapist Coping→FCR

0.028 (-0.050, 0.135)

0.036, 0.012

Generalized Expectancies2 (optimism)→FCR -0.942*(-1.599, -0.248)

0.298, -0.267

0.109 (-0.028, 0.414)

0.087, 0.031

-0.833*(-1.422, -0.182)

0.289, -0.236

Generalized Expectancies2 (optimism)→Active

Coping→FCR

0.129*(0.042, 0.379)

0.063, 0.036

Generalized Expectancies2 (optimism)→ Escapist

Coping→FCR

-0.020 (-0.109, 0.121)

0.043, -0.006

Generalized Expectancies2 (pessimism)→FCR -0.162 (-0.422, 0.236)

0.144, -0.060

0.011 (-0.063, 0.128)

0.038, 0.004

-0.151 (-0.426, 0.272)

0.150, -0.056

Generalized Expectancies2 (pessimism)→Active Coping→FCR

0.011 (-0.025, 0.087)

0.023, 0.004


Escapist Coping→FCR

0.000 (-0.050, 0.079)

0.023, 0.000

by jacqueline patricia galica for the degree of …...1.1 fear of cancer recurrence (fcr) cancer...

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