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A mixed methods study exploring weight related bias in undergraduate
and qualified nurses
Elisabeth Jane Goad
Submitted for the Degree of
Doctor of Psychology(Clinical Psychology)
School of PsychologyFaculty of Health and Medical Sciences
University of SurreyGuildford, SurreyUnited KingdomSeptember 2017
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Statement of Originality
This thesis and the work to which it refers are the results of my own efforts. Any ideas, data, images, or text resulting from the work of others (whether published or unpublished) are fully identified as such within the work and attributed to their originator in the text. This thesis has not been submitted in whole or in part for any other academic degree or professional qualification.
Name: Elisabeth Jane Goad
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Portfolio Overview
There is substantial evidence suggesting that nurses’ do hold weight bias
towards patients with obesity. The evidence is also suggestive of a range of
psychological and physical health implications for patients experiencing
such bias. Despite this, weight bias research in nurses is not only limited but
also contradictory. This thesis aimed to determine how a range of factors
might relate to weight bias in nurses. Part one of this portfolio presents a
literature review of several factors associated with weight bias in nurses.
The findings of the review suggested that due to limitations in the amount
and quality of the literature surrounding weight bias in nurses, a consensus
about factors relating to weight bias could not be reached. Part two presents
an empirical paper that investigated the relationships between nurses’ self-
esteem, BMI, qualification status, stress and burnout; and their associations
with weight bias in nurses. The quantitative findings suggested that there
were no clear relationships between these variables and weight bias.
However, the qualitative analysis helped to interpret the quantitative
findings with more clarity, suggesting that social identities may influence
weight bias in addition to the conceptual frameworks nurses use to make
sense of obesity. Part three of this portfolio consists of a brief description of
all five placements and a summary of the opportunities and experiences I
had for each one. Finally, part four outlines each academic assessment
completed throughout my three years of training.
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Contents Page
Acknowledgements………………………………………………..………..1
Part 1: MRP Literature Review.………………………………………2-64
Abstract……………………………………………………………………...3
Introduction…………………………………………………………….....4-9
Methods………………………………………………………………...10-17
Results………………………………………………………………….17-29
Discussion……………………………………………………………...29-36
References……………………………………………………………...37-50
Appendix 1……………………………………………………………..51-52
Appendix 2……………………...……………………………………...61-64
Part 2: MRP Empirical paper……………..……………………….65-219
Abstract………………………………………………………………...66-67
Introduction…………………………………………………………….68-75
Methods……………………………...…………………………………75-84
Results………………………………………………………………...84-100
Discussion…………………………………………………………...100-115
References……………………………………………………….......116-134
List of appendices……………………………………………………..…135
Appendices…………………………………………………………..136-219
Part 3: Summary of clinical experience……...….………………….220-222
Part 4: Table of assessment………………………………………….….223
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Acknowledgements
As with anything worthwhile, this research was not completed in
isolation. Firstly, a big thank-you to all of the research participants, and
countless ward managers who gave their time to either completing the
research or supporting the recruitment process. I know how busy they were
and thus their support was much appreciated. Without their input this
research would not have been possible. The support I have received from
my friends and family throughout the process has given me the strength to
keep going through the difficult moments and for which I am eternally
grateful. A heartfelt thank-you to my fellow trainee clinical psychologist
colleagues whose knowledge, advice and friendship continue to prove
invaluable. Finally, a very special thank-you to my two research
supervisors, Dr Kate Gleeson and Dr Sue Jackson, whose passion and
mountainous knowledge has been truly inspiration. Their endless patience,
sensitivity and willingness to guide me to a place of understanding ‘what it
really means to know something’ has without doubt changed my research
and my clinical practice for the better.
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Research part 1
Literature Review
Personal factors associated with the
attitudes of UK nurses toward
patients with obesity: A literature
review
Word Count: 7642
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Abstract
Weight bias towards patients with obesity is prevalent within
healthcare settings and may compromise care quality causing negative
consequences for the patient; both psychologically and physically. Yet
relatively little is known about factors that influence weight bias in
healthcare staff and particularly in nurses who spend the most time caring
for patients directly.
This literature review focuses on the association between BMI,
qualification status, self-esteem, levels of stress and burnout in nurses,
alongside their attitudes towards patients with obesity. These variables have
been found to be relevant to weight bias, or with prejudice more generally,
but findings are inconclusive. Searches were conducted on five databases
using terms relating to ‘attitudes’ ‘healthcare staff or nurses’ and ‘obesity’.
Ten studies met the inclusion criteria and were tabulated and critiqued .
The literature reviewed focused on the association between BMI and
weight bias, qualification status, self-esteem, stress and burnout. The
literature covered a time span of over 30 years, the type and quality of study
methodologies varied. Research was particularly limited within a UK
population and was rarely underpinned by theory. Given these shortfalls; no
consensus was reached in drawing together the findings.
In conclusion, further research should focus on developing the
literature for each of these variables in a UK nursing population in relation
to weight bias. This should be undertaken using an appropriate theoretical
underpinning in order to make sense of the research that has begun further
a field.
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Obesity is a global challenge affecting developed and developing
countries across the world (WHO, 2000). In 2014, 39% of people over 18
years old were classified as overweight (BMI>25) and 13% were classified
as obese (BMI>30) globally (WHO, 2015). In the United Kingdom (UK)
63.4% of people are overweight and 28.1% are obese (WHO, 2015). The
ramifications of this on the systems in which the individual resides are
significant, with the cost of obesity to the NHS estimated to be around £6.1
billion a year, and around £27 billion to the wider economy (Department of
Health, 2011). Indeed, by 2050, the Department of Health suggest that the
costs of obesity may rise to almost £50 billion (Department of Health,
2011).
However, on an individual level, obesity itself increases mortality
rates (Duncan, Griffith, Rutter & Goldacre, 2010) with co-morbid
conditions such as cardiovascular disease, diabetes and some cancers,
causing complications at best, and fatality at worst (Haslam & James, 2005).
The Department of Health, (2011) suggests that obese men are two and a
half times more likely to have high blood pressure than non obese men, and
five times more likely to develop type two diabetes. Obese woman are three
times more likely to have a heart attack and 13 times more likely to develop
type two diabetes than non obese woman (Department of Health, 2011).
In acknowledgement of the impact obesity has on society as a whole
and on the person individually, a ‘whole systems’ effort by the UK
government and the NHS has been undertaken in order to tackle this
widespread issue (BPS, 2011). However, whether a ‘whole systems’
approach includes tackling the pervasive negative attitudes that people with
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obesity often face is debatable. Despite research suggesting that weight bias
may exceed the stigma notoriously projected towards other stereotyped
groups, (Latner, O’Brien, Durso, Brinkman & MacDonald, 2008) such as
race and gender (Andreyeva, Puhl, & Brownell 2008), weight bias is often
seen as the last acceptable form of prejudice within modern society (Puhl &
Heuer, 2009). The British Psychological Society’s publication examining
obesity from a psychological perspective (BPS, 2011), although mentioning
the existence of stigma and prejudice in some specific settings, does not
elaborate on how widespread the issue is and the phenomenal impact of it
on the person themselves, whether physically (Brown, 2006) or
psychologically (Kolotkin, Meter & Williams, 2001). However, exploring
the impact of and reasons for weight bias may be a key component of
understanding obesity in a truly psychosocial way.
Weight bias is pervasive across all settings, including education, (Puhl
& Brownell, 2001), employment (Puhl, Henderson & Brownell, 2005) and
worryingly in healthcare (Budd, Mariotti, Graff & Falkenstein, 2011).
Within health services weight bias has been reported across professional
groups, including those specializing in obesity (Schwartz, Chambliss,
Brownell, Blair & Billington, 2003).
The importance of recognizing weight bias within healthcare lies in
the impact it has on patients, whether that is the impact on their care or the
physical and psychological effect on the individual concerned. Widespread
attitudes relate to beliefs about patients who are obese being lazy, lacking
willpower, being undisciplined (Zhu, Norman & While, 2011), unintelligent
(Puhl & Heuer, 2010) and noncompliant with treatment (Brown, 2006).
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Some research suggests that healthcare providers may show less respect
towards obese patients (Puhl & Heuer, 2009; Hebl & Xu, 2001), spend less
time with them and provide fewer treatment options; including preventative
treatments (Swift, Hanlon, El-redy, Puhl, & Glazebrook, 2013). The
suggestion that negative attitudes of some healthcare staff may translate into
poor clinical care is extremely concerning.
Research exploring the perspective of patients with obesity suggests
that they are well aware of such attitudes directed towards them, reporting
feeling disrespected, receiving unhelpful advice, and finding that they were
discriminated against by not being provided with equipment to
accommodate their size (Amy, Aalborg, Lyons, Keranen, 2006).
Psychologically, being on the receiving end of weight bias has a range of
serious adverse consequences which include an increased vulnerability to
depression, low esteem, anxiety and suicide (Puhl & Heuer, 2009).
In addition to the psychological implications of weight bias, patients
with obesity are likely to experience adverse physical health consequences
as well. Research has indicated that patients who have experienced weight
bias within healthcare are less likely to engage in weight management
(Mold & Forbes, 2011), may increase unhealthy eating behaviours (Schvey,
Puhl & Brownell, 2012) and tend to experience poorer outcomes on weight
loss programmes (Carels et al., 2009). Understandably, patients
experiencing weight bias are also more likely to avoid using healthcare
services despite the co-morbidities associated with obesity (Hebl & Xu,
2003). The implications of poorer care from healthcare staff, additional co-
morbid health conditions as well as possible increases in behaviours that
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may exacerbate physical health problems mean that the potential to identify
and treat serious co-morbid conditions quickly may be missed. As such,
weight bias amongst healthcare staff has the potential to exacerbate obesity
and its associated health problems, the consequences of which are for the
individual and for healthcare services, catastrophic.
Overall, the research focusing on weight bias in healthcare is rising
(e.g. Berryman, Dubale, Manchester & Mittelstaedt, 2006; Forhan & Salas,
2013; Poon & Tarrant, 2009) but has mostly focused on the presence of
weight bias (Crandall, 1994; Bacon, Scheltema & Robinson, 2001), the
experience of weight bias and stigma from the perspective of the person
with obesity (Puhl, Moss-Racusin, Schwartz & Brownell, 2009) and
exploring the efficacy of weight bias reduction interventions (Hoppe &
Ogden, 1997; O’Brien, Puhl, Latner, Mir & Hunter, 2010).
The research exploring factors that may be associated with weight bias
is considerably more sparse and has focused on demographic variables such
as age, level of experience, gender or BMI (Brown, Stride, Psarou, Brewins
& Thompson, 2007; Swift, Hanlon, El-Redy, Puhl & Glazebrok, 2013;
Harvey, Summerbell, Kirk & Hills, 2002) and qualification status (Poon &
Tarrant, 2009). However, overall there remains little consensus on the
relationship between these variables and weight bias in healthcare.
Interestingly, despite the fact that in the literature focusing on
attitudes, self-esteem has long been considered a contributor to prejudiced
attitudes towards others (Duckitt, 1992; Fein & Spencer, 1997; Cheng,
Robins, & Trzesniewski, 2009, Tajfel & Turner, 1986), it does not appear to
have been extensively explored within weight bias research. The research
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suggests that prejudice towards stereotyped groups often occurs when the
group identity of the perpetrator is threatened in some way (Fein & Spencer,
1997). Thus in the context of prejudice occurring between a member of one
social group (nurses) towards members of another (patients with obesity) it
is reasonable to question how the impact of a group member’s own self-
esteem may relate to that.
Overall, the research in this field has largely been conducted in the
USA (e.g. Puhl & Heuer, 2009; Puhl & Brownell, 2001) rather than the UK.
Developing an understanding of the factors that are associated with weight
bias in the context of a UK population is particularly important given its
unique healthcare system, the National Health Service (NHS). The NHS
faces challenging times with particular stressors including staff shortages
and high patient demand, pay restraints and constant organizational change
(Cox, Randall & Griffiths, 2002), all the while with the expectation to
continue improving the quality and safety of its care (NHS Employers,
2009). As such, UK nurses are particularly vulnerable to the effects of stress
(NHS Employers, 2009) and burnout (Heinen et al., 2013) but the impact of
this on nurses’ attitudes towards patients with obesity is unknown.
Weight bias literature often refers to ‘healthcare professionals’, which
is a broad term encompassing groups of individuals who hold different skill
sets, and have differing priorities and pressures. The level, length and type
of training is very different between healthcare professionals and thus it
cannot therefore be assumed that the factors that may affect the attitudes
they hold towards stereotyped groups such as those who are obese, will be
unanimous. Nurses play an important role in providing care and support to
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patients who are obese (National Audit Office, 2001) and generally provide
the majority of one to one care (American Nurses Association, 1996). In
order to develop a more integrated understanding of the influences on
weight bias in nurses, an area that is currently under represented within
weight bias research, this literature review focuses on collating the current
research by examining current key variables and their relationship with
weight bias in nurses globally. The variables were chosen based on those
most frequently explored within current literature for example BMI and
qualification status combined with the variables most relevant to intergroup
theories of prejudice such as self-esteem. Finally, the variables stress and
burnout were chosen in light of the evidence of their commonality in UK
nurses and thus the importance of this social context on the attitudes of
nurses towards patients with obesity.
Research questions:
1) Are nurses BMI associated with the attitudes they hold towards
patients who are obese?
2) Is there a difference between the attitudes held towards patients who
are obese by student and qualified nurses?
3) Is the self-esteem of healthcare staff associated with the attitudes
they hold towards obese patients?
4) Is stress in healthcare staff associated with the attitudes they hold
towards patients who are obese?
5) Is burnout in healthcare staff associated with the attitudes they hold
towards patients who are obese?
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MethodSearch strategies
The electronic databases Psychology Cross search (Medline,
PsychINFO, PsychARTICLES & Psychology & Behavioural Sciences
Collection) Pubmed, Web of Science, Proquest Allied Health Professionals
and Google Scholar were searched by one researcher (EG) between January
1st and February 28th 2016. Search terms were used within each database as
shown in table 1:
Table 1:
Search terms
Search Category Search Terms Used Health care staff AND psych* OR nurs* OR phsyi (phys*)OR
doctor* OR clinician* OR counsellor* OR therap* OR occupational therap* OR profess* OR employ* OR staff* OR qualif* OR unqualified OR student* OR trainee* OR healthcare*
Stigma and discrimination AND
Stigma OR discriminat* OR anti-fat* OR bias* OR prejudice* OR attitude*
Obesity Obes* OR fat OR overweight OR BMI or body mass index OR Obesity Or Obesity bariatric* OR weight*
Each category of words were linked together with ‘AND’ to produce
results containing at least one word from each category. Preliminary
searches suggested that there would be limited literature exploring the
variables self-esteem, stress and burnout within the nursing population. As
such, terms relating to healthcare professionals more broadly, in addition to
nurses, were used in order to capture the wider literature on these variables.
No date limitations were applied during the search in order to collate
all prior research and allow for the development of the whole picture. The
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Psychology Cross Search N=422Pubmed N= 186Web of Science N=477Proquest N=765Google Scholar N=1Total N= 1851
Exclusion of duplicates N= 991
Potentially eligible recordsN= 860
Remaining eligible recordsN= 98
Exclusion of articles using criteria two N=89
Exclusion of articles using criteria one N= 762
Remaining eligible records N=9
References hand searched N=4
Remaining eligible records N=13
Two hand searched references not found
Remaining eligible records N=10
full search strategy is presented in figure 1.
Figure 1: Prisma flow diagram
Criteria one = exclusion based on title and abstractCriteria two = exclusion based on examination of the whole study
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The searches were also rerun to include the terms ‘self-esteem’ ‘body
image’ ‘self confidence and ‘self efficacy’ as well as ‘stress’ ‘burnout’
‘depersonali*’ ‘cynicism’ ‘fatigue’ and ‘exhaustion’ but this did not return
any additional results.
The quantity of research for each area differed significantly, which led
to the stipulation of slightly different inclusion criteria for each variable. For
example, literature was searched more widely when exploring self-esteem,
stress and burnout in order to contextualise them within the wider research
given their limited representation within this specific field. The inclusion
and exclusion criteria utilised for this literature review are illustrated in
Table 2 and table 3 below.
Table 2:
Inclusion & exclusion criteria for papers examining the relationship
between nurses BMI, qualification status & attitudes towards patients with
obesity.
Exclusion criteria Inclusion criteria
Studies not looking specifically at BMI or body weight in relation to weight biasWeight bias by any population other than nurses Weight related bias not directed towards patients Weight related bias directed towards childrenAttitudes towards weight management rather than attitudes towards the person with obesity more generally
Studies exploring nurses attitudes towards obese adult patients AND The relationship with nurses own BMI or body weight and weight related biasStudent nursesStudies from any country Studies from any time period
Table 3:
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Exclusion criteria Inclusion criteriaStudies not looking specifically at self esteem, stress, burnout or any aspect of these in relation to weight related biasWeight bias not directed towards patients Weight bias directed towards childrenWeight bias in participants who are not healthcare staff
Studies exploring healthcare professionals attitudes towards obese adult patients AND The relationship with the healthcare professionals own self esteem, stress, burnout or any aspect of these and weight related biasStudents within healthcare professionsStudies from any country Studies from any time period
Inclusion and exclusion criteria for papers examining the relationship
between nurses’ own self esteem, burnout or stress towards patients who
were overweight/obese.
Definition of termsIn the wider literature there is some variation between the definitions
of terminology used depending on the theoretical framework they are
situated within. The majority of research located for this literature review
focused on ‘attitudes;’ traditionally situated within a social psychology
framework. The definitions chosen for this literature review reflect this.
Attitude
As early as 1935, attitudes were described within social psychology
as, ‘a mental or neural state of readiness, organised through experience,
exerting a directive and/or dynamic influence upon the individual’s
responses to all objects and situations (Allport, 1935, p1). However, social
psychologists have more recently been criticised for their individualistic
approach towards attitude formation and for neglecting the social context in
which they arise (Hogg & Smith, 2007). As such, for this review, the term
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attitude will be defined as ‘an individual’s evaluation of any part of their
social world’ (Olson & Maio, 2003). This may be stable or dynamic
dependent on the context in which it has arisen (Schwarz & Bohner, 2001).
Weight bias
A variety of terminology has been used to describe negative affective
responses (e.g. prejudice), negative cognitive responses (e.g. negative bias,
negative stereotype) and differential behaviour (e.g. discrimination) directed
towards individuals or groups of people. Within this review, the
terminology ‘bias’ will be used to describe a non-neutral cognitive state
directed towards members of a particular social group. The direction of the
bias will be denoted in the text where appropriate. Deviation from this
language will be clarified when required.
Self-esteem
The term self-esteem is commonly defined as ‘self evaluations about
ones own worth or abilities’ (Oxford Dictionaries, 2016). However, self-
esteem has long been located at the centre of prejudice towards others
(Tajfel & Turner, 1986). In the context of attitudes research self-esteem is
integrally linked with interpersonal dynamics (Fein & Spencer, 1997) with
an inherently social nature. Indeed, key theorists (Tajfel & Turner, 1986)
suggest that negative attitudes are expressed in order to positively
distinguish collective self-esteem from those individuals belonging to other
group memberships. Thus the term self-esteem does not assume an
individualistic focus. However, to collate the research on self-esteem in
weight bias, more inclusive terms such as ‘body image’ have been included
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in recognition that body image is often represented as one component of
self-esteem across the wider literature.
Stress
Definitions of stress are often poorly defined within the literature with
no single definition in existence (Pines & Keinan, 2005). Most commonly it
is defined as a psychological response to situations or events that are
appraised to be threatening or otherwise demanding and the person has
insufficient resources available to cope (Lazurus, 1977). However, this
focuses more on momentary appraisals of stressful situations rather than
stress as an ongoing and chronic response to stressors that this review
considers. This review focuses on chronic work-related stress. For example
stress in the context of healthcare, which has been associated with increased
workload, time pressures, coping with the emotional needs of the patients
and shift work (McVicar, 2003). This type of stress has been related to the
development of emotional exhaustion and ultimately burnout in nurses
(Bakker, Blanc & Schaufeli, 2005; Lederer, Kinzl, Traweger, Dosch &
Sumann, 2008).
Burnout
Maslach, Jackson & Leiter define burnout as ‘a syndrome of
emotional exhaustion, depersonalisation and reduced personal
accomplishment that can occur among individuals who do “people work” of
some kind’ (p1, 1996). The term depersonalisation has previously been
construed as meaning alienation from self within a psychiatric model
(Scaufeli, & Salanova, 2014). However, in this context it is referred to as an
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impersonal and dehumanized perception of recipients rather than an
impersonal view of self (Maslach, Jackson & Leiter, 1996).
Nurse
For the purpose of this review, student and qualified nurses were
included and were defined as individuals who have completed or are
completing a formally recognised programme of nursing education that is
authorised by the appropriate governing nursing body within their country
(ICN, 2015).
Obesity and overweight
The World Health Organization defines being overweight as a body
mass index greater than or equal to 25; and defines obese as having a body
mass index of greater than or equal to 30 (WHO, 2015). Although these
definitions will loosely aid understanding of the terms obesity and
overweight in this review, it is participants perceptions of those overweight
or obese that are of interest and thus their judgement on what it means to be
overweight or obese will likely vary. Participants identifying their attitudes
of both overweight and obese patients will be included within this review.
Findings
Thirteen suitable studies met the inclusion criteria including one
systematic review, four dissertations and eight quantitative studies. Two of
the dissertations were unpublished (Carson and Carson, 1987 & Clevenger,
1983) and despite contacting the authors and universities where they were
written, these were not located and thus were removed from the final
selection. The literature review (Brown, 2006) identified only two studies
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that met the criteria for the current review but these two studies had already
been located and included in the final selection (Culbertson & Smolen,
1995; Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989) and therefore
the Brown, (2006) literature review was not included. As such, in total, 10
studies were analysed within this literature review.
The variables explored within this literature review were generally
only included as one aspect of a wider research question in the studies
reviewed. As such, only the elements of each study directly relating to the
research questions developed within the current literature review were
critiqued. The Critical Appraisal Skills Programme Checklists (Critical
Appraisal Skills Programme, 2013) were used to appraise the systemic
review and the STROBE checklist (Strobe statement, 2009) was used as a
guideline to review the quantitative design studies.
Results
Is a nurses BMI associated with weight bias? As nurse BMI increases level of weight bias decreases
Four studies were identified that suggested that nurses with a higher
body mass index (BMI) demonstrated more positive attitudes towards
patients with obesity than nurses with lower BMI’s (Brown, Stride, Psarou,
Brewins & Thompson, 2007; Garcia, 2012; Geckle, 2001; Lilliot, 2000).
The studies were all cross sectional survey designs spanning a time period
of 12 years (2000-2012). All four studies were from western countries such
as the USA (Garcia, 2012; Geckle, 2001 & Lilliot, 2000) or the UK (Brown,
Stride, Psarou, Brewins, & Thompson, 2007) and thus the cultural narratives
surrounding what it means to be obese were construed as reasonably similar.
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Each of the four studies concluded that higher BMI or higher
perceived weight was associated with more positive attitudes in nurses
although there were significant differences between the studies requiring
consideration. Three studies (Brown, Stride, Psarou, Brewins & Thompson,
2007; Garcia, 2012 & Lilliot, 2000) utilised the measurement tool BMI
requiring participants to report their estimated weight and height. On the
other hand, Geckle (2001) used self-categorization (underweight,
appropriate weight or overweight), representing a different underlying
mechanism required for participants to respond. For example, weight and
height measurements can be recalled relatively objectively by the individual
and do not assume the necessity of a socially relational comparison in order
to do so. However, categories such as ‘underweight’ or ‘overweight’ are
entirely socially constructed. To use such categories the individual must
organize themselves in to specific group memberships by making
comparisons with others in each group of reference; and then establish
where they best fit. Although a direct numerical measurement of weight
(such as kg or pounds) may have social meaning attached to it, it remains an
objective measure that does not require social comparisons to be made in
order to report it. Thus the different underlying mechanisms highlighted in
measurement technique between the studies may query whether each of the
studies are measuring the same constructs; or indeed the constructs in which
they had intended to measure.
Interestingly, the three studies that used BMI as a measurement tool
(Brown, Stride, Psarou, Brewin & Thompson, 2007; Garcia, 2012 & Lilliot,
2000) reported statistically significant correlations between BMI and weight
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bias although the magnitude of the correlations for these three studies were
weak. The study requesting participants to self-categorize (Geckle, 2001)
demonstrated a significant difference between weight categories although
did not provide an effect size. None of the studies explored both BMI and
self-categorization of weight thus it is unclear whether the weaker
correlations detected in the three studies using BMI were actually indirectly
identifying a relationship between weight bias and how nurses perceived
their weight rather than what they objectively weighed.
Each of the four studies (Brown, Stride, Psarou, Brewin & Thompson,
2007; Garcia, 2012; Geckle, 2001; Lilliot, 2000) utilised questionnaires
designed to measure various attitudes towards patients with obesity.
However, it is noteworthy that each questionnaire measured slightly
different aspects of attitudes towards patients with obesity as summarized in
table 4. As such, although a broad spectrum of attitudes were assessed
across these studies, it may also make comparisons between findings
difficult and thus if a more detailed understanding of specific attitudes is
required then the generalizability of the findings should be treated
cautiously.
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Table 4:
The different attitudes towards patients with obesity measured by each
questionnaire
Study Questionnaire Attitudes measured Brown,Stride, Psarou,-Brewins
& Thompson (2007)
Developed by the researchers
Personal effectiveness in caring for an obese patientBeliefs that obesity is an important health service development issueExternal causes of obesity
Garcia (2012) NATOOPS Nurse response to obese patients Attitudes towards the characteristics of of the obese patient Attitudes towards controllability f factors in obesity Stereotypic characteristics of patients with with obesity ……. Supportive roles in caring for obese patients
Geckle (2001) ANTOAP Attitudes towards nursing management of obese patientsLifestyle characteristics of obese patients
Lilliot, (2000) BATOS Negative views towards obese patientsOrganizational support in caring for obese patientsObesity causationPerceived characteristics towards patients with obesity
The reliability estimates for each of the studies were between
‘adequate’ and ‘good’1 for the range of questionnaires used to measure
participant attitudes towards patients with obesity. However, the ‘negative
views’ subscale in Brown, Stride, Psarou, Brewin & Thompson’s (2007)
study had a Cronbach alpha at .69, falling just short of adequate reliability.
Equally, although Garcia (2012) suggests an overall Cronbach alpha of .81,
a number of subscales did fall below the cut off of .7 (Kline, 1999), which 1 The reliability estimate cut off criteria used was that of Kline (1999) which suggests .7 or above is adequate reliability.
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may impact, on the reliability of some items. The majority of the
questionnaires were validated within nursing populations, however, the
BATOS, utilised by Lilliot (2000) was not. As the general population may
have a different relationship with the meaning of obesity than nurses do due
to nurses health education and training as well as the impact obesity may
have on their ability to nurse effectively, the validity of this questionnaire
amongst a nursing population may be questionable.
As nurse BMI increases their level of weight bias increases In contrast to the previous studies discussed, only one study suggested
that as nurse BMI increased, negative attitudes towards patients with obesity
also increased. This was a study of cross sectional survey design in a USA
nursing population (Torrey, 2013). The results suggested that nurses within
higher BMI categories tended to have more negative attitudes than those in
lower BMI categories, reporting medium to large effects. Although the
NATOOPS (Watson, Oberle & Deutscher, 2008) was the same
questionnaire as the Garcia, (2012) study used to measure nurses attitudes
towards patients with obesity, in this instance, the reliability estimates
calculated were at best adequate and for some subscales were poor; with
Cronbach alphas ranging from .45-.78. Details of which subscales were of
poor reliability were not reported, making interpreting subscale results
reliably difficult.
In considering the validity of the study, higher BMI categories also
appeared to correlate with higher levels of body image guilt and shame.
However, neither guilt or shame were controlled for when exploring the
other which made it difficult to interpret how they related to the nurses
21
attitudes and how they related to each other. However, it is one of the few
studies that captured both BMI and the subjective experience of how
participants felt about their body image and its appropriate method draws on
a large sample size and adequate power to its credit.
There is no relationship between level of weight bias and nurse BMI
Finally, three studies (Culbertson & Smolen, 1995; Poon & Tarrant,
2009; Young, 1985) found no association between nurse BMI and their
attitudes towards patients with obesity. The publication dates of these
studies spanned a time period of over 20 years. This is relevant because the
relationship the world has with obesity has changed over time. Since the
1980’s worldwide obesity has nearly doubled (WHO, 2015) which clearly
has a significant impact on healthcare, the economy and the individual. Thus
the attitudes of nurses in the earlier Young (1985) study are likely situated
within the context of a very different culture than those in the later Poon and
Tarrant study (2009). Equally, cross culturally, studies situated in western
cultures are more likely to perceive obesity as a one-dimensional visible
flaw (Puhl & Brownell, 2003) as the values of western culture continue to
shift towards an emphasis on thinness which will likely impact on attitudes.
Culturally, the Chinese based Poon and Tarrant (2009) study may also be
subject to differing cultural bias. For example, China has historically been
considered to have one of the leanest populations worldwide (WHO, 1989).
Although its population is fast catching up with the west in terms of the
proportion of its population with obesity (Wu, 2006), it has not been
perceived as a long standing drain on the economy as it perhaps has in
22
western cultures. As such, the historical context may be important in
interpreting the findings of these studies in the present day.
There was also variation within how obesity was measured within
these studies as well. More recent studies have tended to use either self-
categorization of weight or BMI (e.g. Garcia, 2012 or Poon & Tarrant,
2009) the problems of which have been discussed. However, Young (1985)
used an older measurement system, the ‘Metropolitan Life Tables’
(Metropolitan Life Insurance Company, 1959), which are not comparable
with the other measurement systems used in this review. The Metropolitan
Life Tables were developed using populations of insured people and given
that the literature suggests that those with health insurance are much more
likely to be ‘healthy’ than those without (Hadley, 2003), this is likely
reflected in average weight differences between these two populations. As
such, the population used to develop this system of measurement were very
unlikely to be representative of the general population at the time; let alone
over 30 years later.
In examining each of the nine studies in consideration of the question
‘are nurses own BMI associated with the attitudes they hold towards
patients with obesity?’ the results were inclusive. Methodological
weaknesses were found across studies but particularly in the older studies
(e.g. Young, 1985) where the operationalization of variables was
questionable, reliability of measures inadequate and where there was poor
detail regarding the methodology. Combining these issues with the
historical and cultural differences between studies means interpretation of
the results in a meaningful and helpful way is difficult.
23
Are there differences between weight bias in undergraduate or post-
graduate nurses?
One study was identified within this review that reported differences
in weight bias between undergraduate and post-qualified nurses (Poon and
Tarrant, 2009). The results indicated that qualified nurses held more bias
towards patients with obesity than undergraduate nurses did. The study was
adequately powered with an appropriate sample size. The F scale, the
questionnaire used to measure attitudes, was reported to be reliable in other
studies (e.g. Bacon, Scheltema & Robinson, 2001), although the study was
conducted in the USA with a non-nurse sample and reliability estimates for
the current study were not provided. In examining the results undergraduate
nurses were reported to be significantly younger than qualified nurses were
which was not controlled for within the results. As such, it is unclear
whether the result is attributable to age (with older nurses having more bias)
or professional status. In considering the wider literature, older nurses have
been associated with more negative attitudes (Bagley, Conklin, Isherwood,
Pechiulis, Watson, 1989), although research has also found no association
between these variables (Bocquier et al., 2005; Brown, Stride, Psarou,
Brewins & Thompson, 2007; Miller et al., 2013). In contradiction, other
studies have suggested that older nurses have also shown more positive
attitudes than younger nurses (e.g. Culbertson & Smolen, 1999; Puhl,
Latner, King & Luedicke, 2013; Wise, Harris & Olver, 2014) even when
other demographic variables were controlled for (e.g. Schwartz, Chambliss,
Brownell, Blair & Billington, 2003). The significant relationships between
24
age and qualification status make it difficult to differentiate between which
variable actually relates to weight bias. The wider literature on age and
weight bias is also contradictory and thus does not clarify this picture.
Are negative attitudes towards patients with obesity linked to nurse’s own
self-esteem?
The initial results yielded few studies exploring the relationship
between nurses’ self-esteem and their attitudes towards obesity and thus the
review was expanded to contain studies including participants of all types of
healthcare professional. Three studies were included within this review all
of which were published in the USA but spanned 20 years (Bagley, Conklin,
Isherwood, Pechiulis & Watson, 1989 & Puhl, Luedicke & Grilo, 2013;
Torrey, 2013). Puhl, Leudicke & Grilo (2013) suggested that nurses self-
esteem or weight concerns were not associated with negative attitudes
towards patients with obesity although it did indicate that those with
increased weight concerns were more likely to perceive weight bias in
others around them. The psychometric properties for the questionnaires used
in thus study were reliable. However, there was little detail on the
methodology in general; including whether adequate power and sample size
was reached. Social desirability bias may have also have been a factor as
participants appeared able to report bias in others but not in relationship to
themselves. This may represent participants who with weight or shape
concerns of their own feel more sensitive to bias recognized in others, but
equally may highlight a discrepancy between nurses actual attitudes and
what they feel able to report in terms of their own prejudice towards those
with obesity.
25
The second two studies were conducted on nursing populations
(Bagley, 1989; Torrey, 2013) and focused on body dissatisfaction rather
than self-esteem more generally. Both studies suggested that nurses
dissatisfied with their own body weight held more negative attitudes
towards patients with obesity than those who were more satisfied. However,
the Bagley (1989a) study, although a validation study for a weight bias
measure within a nursing population was only four paragraphs long. As
such, it contained very little detail about the measure itself, its psychometric
properties, its sample, and indeed its results which were all significant
limitations. Other authors appear to have had similar difficulties locating the
full length article (Brown, 2006) despite being cited frequently throughout
the literature (e.g. Maroney & Golub, 1992; Culbertson & Smolen, 1989).
There was not enough detail produced to assess how robust the
methodology was or the reliability of its findings within this review.
However, the measurement scale has since been reproduced in other studies
who report reliable psychometric properties (e.g. Yuker at al., 1995) and
who have published the items in full highlighting the range of attitudes the
questionnaire covers.
The second study conducted on a nursing population explored the
relationship between body image guilt and shame in relation to negative
attitudes in nurses towards patients with obesity (Torrey, 2013). The results
suggested that nurses in the overweight and obese categories had
significantly higher levels of body image guilt and shame comparatively to
average weight nurses with a medium to large effect. Those with higher
body image guilt and shame in the overweight group had more negative
26
attitudes towards patients with obesity than those with less body image guilt
and shame in the average weight group. However, clearly as BMI increased
so did body image guilt and shame thus both correlating with increased
negative attitudes in nurses towards patients with obesity. As such, again the
question is raised as to whether it is BMI itself, or whether it is the nurses’
perception of their own body size and the associated emotional impact of
that; which relates to their attitudes towards patients who are obese.
The wider literature on self-esteem and prejudice
Given the limited literature on self-esteem in nurses or healthcare staff
and their relationship with weight bias towards patients with obesity, an
overview of the wider literature is summarized here. Within social
psychology, self-esteem is considered a contributor to prejudiced attitudes
towards others (see Duckitt, 1992; Hogg & Smith, 2007) Studies in this area
have suggested that prejudice against a range of stereotyped groups (for
example race or sexuality) is common after threats to self-image/esteem and
serve to protect the perpetrator from feeling bad about themselves (Fein &
Spencer, 1997). Social Identity Theory (Tajfel & Turner, 1986) encapsulates
this concept within their self-esteem hypothesis which suggests that
negative attitudes may serve to protect against or maintain social self-
esteem. Thus prejudice is directed towards members of other social groups
in order to manage the identity of their own social group positively and thus
their own self-esteem. There is a small amount of research conducted in the
field of weight bias which suggests that students with lower self body image
have higher levels of implicit and explicit weight bias; in part mediated by
the tendency to make physical appearance comparisons (O’Brien, Hunter,
27
Halberstadt & Anderson, 2007). That is, people may compare themselves
favourably against people with obesity in order to make themselves feel
better and thus this is associated with greater weight bias. These findings
have not yet been replicated in a healthcare professional population.
However, this body of literature does corroborate with the literature
explored within this review which suggests that those with high body
dissatisfaction are more likely to express negative attitudes towards people
with obesity.
The wider literature on stress and burnout
No studies were identified within this review examining the impact of
stress and or burnout in nurses or healthcare professionals and their attitudes
towards patients with obesity. This is despite the vast body of literature
suggesting that burnout is a particular problem within the ‘caring
profession’ (Maslach, 2003). Indeed, burnout is rife in nurses around the
globe (McFeely, 2007) but particularly within the UK which has the highest
reported rate of burnout at 42% compared to the 28% average across the rest
of Europe (Heinen et al., 2013). The evidence suggests that nurses who are
burnt out tend to have poorer attitudes towards their jobs and have less
concern for patients (Abushaikha & Saca-Hazbun, 2009). Indeed, by
definition, burnout includes cynicism, a negative or callous detached
response to aspects of the job (Maslach, Schaufeli & Leiter, 2001). In
addition, 30% of NHS staff sickness relates to stress in England, a
significant contributor to burnout itself (Maslach, 2006) which not only puts
a financial strain on the system itself but also negatively impacts on patient
experience and quality of care (NHS, employers 2009). Yet despite this
28
evidence the impact of stress or burnout on nurses’ attitudes towards
particular social groups, such as patients who are obese, remains unknown.
Discussion
There is global recognition that obesity is a public health concern
(Brown, 2006) with the associated negative social attitudes of healthcare
professionals towards patients with obesity documented for over three
decades (e.g. King, Latner, Puhl & Luedicke, 2013;Young, 1987). Yet
despite this body of research, the factors relating to weight bias in healthcare
staff remains unclear. This may in part relate to the varying focus,
methodological issues and contradictory results of previous research. This
literature review focused specifically on studies which examined the
relationship between BMI, qualification status, self-esteem, stress and
burnout in nursing populations and their attitudes towards patients with
obesity in order to draw together previous research and draw on current
theory to help develop the picture in this field. Overall, the results were in
some areas limited and often contradictory. As such, no meaningful
conclusions in relation to how specific factors may influence weight bias in
nurses were drawn.
The range of methodological issues identified when examining the
relationship between BMI and weight bias may have contributed to the
conflicting results. Given the variability across studies in relation to their
adequate power, sample size (Culbertson & Smolen, 1999), reliability,
method of measurement (Brown, Stride, Psarou, Brewin & Thompson,
2007), and ability to control for confounding variables (Poon & Tarrant,
2009), drawing conclusions was difficult. Additionally, there were
29
differences in how weight was operationalized across the studies (e.g.
Geckle, 2001 versus Garcia, 2012). However, one might argue that even the
studies that did use BMI to categorise participants weight in to socially
constructed categories may not have been able to do so accurately. For
example, BMI cannot distinguish between body fat and muscle (Centre for
Disease Control and Prevention, 2009) and thus may not be the most
appropriate determinant of obesity, especially when taken alone. Finally, in
some studies the methodologies were so poorly documented that it was
difficult to interpret the findings at all (e.g. Culbertson & Smolen, 1999).
These difficulties were not unique to studies examining the impact of weight
on nurses attitudes towards obesity. The literature on self-esteem and body
image also had methodological difficulties (e.g. Bagley, 1989) which
limited how able this review was in interpreting these findings.
The lack of research exploring the relationship between nurses stress
and burnout and their relationship with weight bias is interesting given that
both stress and burnout is extremely common in UK nurses (Heinen, 2013).
This high level of stress may relate to the NHS’ current financial difficulties
(NHS Employers, 2009) including the reality of privatization (Health and
Social Act, 2012) and associated problems with workload and low staff
morale (Kings Fund, 2015). Intergroup theories of prejudice such as
Relative Deprivation Theory (Stouffer, Suckman, DeVinney, Star &
Williams, 1949) suggest that at times of social change, group members may
strive to re-evaluate the position of the group (Moghaddam, 2002). If social
changes are deemed unfair in relation to the social group the person situates
themselves within then they may act out frustration or anger towards the
30
‘other’ (Smith, Pettigrew, Pippin & Bialosiewiczi, 2011). In a climate where
resources are scarce, the impact of this on nurses is clear in relation to the
highlighted levels of stress and burnout. It is possible that displaying such
frustration in the form of negative attitudes towards more vulnerable ‘out’
groups such as patients with obesity is likely. The research clearly states that
many nurses are stressed and burnt out and that they often hold negative
attitudes towards obese patients, yet currently, there is no clarity about the
relationship between the two.
Reviewing the research on self-esteem in healthcare professionals and
weight bias also did not clarify the relationship between them. This may in
part relate to the limited research found but may also in part relate to the
more individual approach taken to understanding self-esteem which may not
have captured self-esteem in the social context it is generally seen within
attitudes research. For example, in considering how an individual may feel
about him or herself, the definition must invariably be situated within a
social context. To acknowledge a person as ‘average’ or ‘over’ weight, a
comparison to what is considered ‘normal’ or ‘over’ weight, thus to the
normative reference group of which that weight category represents, must
be made. In other words, an individual can only be average, under or over
weight in relation to another. Indeed, from a Social Identity Theory
perspective (Tajfel & Turner, 1986), the social comparisons that are made
between the individual and those from other group memberships help
develop and maintain a sense of identity (Brewer, 1979) by positively
differentiating characteristics of their own social group from the
characteristics of the ‘outside’ comparison group which are generally
31
devalued (Tajfel & Turner, 1986). Thus there is a strong element of de-
valuing attitudes towards others serving a function for the benefit of the
individual’s own self-esteem which cannot be ignored.
However, individuals often operate within numerous social groups at
one time and thus have numerous social identities and group memberships
(Hogg & Abrams, 1988). The social group the individual is interacting
within provides the context for the person’s social identity at that time
(Torrey, 2013). However, this is problematic when two social identities
oppose each other. For example, nurses belong to an elite group of
healthcare professionals (Torrey, 2013) symbolized as role models to their
patients and are often expected to meet the social norm for their own body
weight (Brown, Stride, Psarou, Brewins & Thompson, 2007). To be part of
such a respected group representing good health yet also to be overweight or
obese, a group generally personifying poor health (Torrey, 2013) represents
a significant conflict in identity. Social Identity Theory (Tajfel & Turner,
1986) argues that individuals gravitate towards the most well thought of part
of their identity, thus suggesting that nursing identity is likely to be more
salient than a weight related identity one, potentially giving rise to nurses
treating patients with obesity as the ‘out-group’. However, other research
suggests that people are likely to continue to identify with their in-group and
increase their commitment to its cause even if it is relatively low status
(Ellemers, Spears & Doosje, 1997). Thus, despite self-esteem being central
to theories of prejudice for some time (e.g. Tajfel & Turner, 1986), there
remains many arguments about exactly how it actually fits within these
theories along with debates about the evidence for such assertions (Abram
32
& Hogg, 1988; Brown, 2005; Rubin & Hewstone, 1999). Although current
understandings of the relationship between self-esteem and prejudice are
more comprehensive (Hogg & Smith, 2007), the evolving history is likely
reflected in the limited and inconclusive results of these study.
In considering the impact of group identity on prejudice, the cultural
narrative surrounding nurse identity should also be considered. It is visible
from the results of this review that even in studies suggesting that nurses
that did show weight bias towards patients with obesity, the effect sizes
were often relatively weak and the overall reported attitudes were actually
neutral or slightly positive (Geckle, 2001; Garcia, 2012). In the context of
Social Identity (Tajfel & Turner, 1986), nurses discriminating against
certain groups do not fit with their ascribed identity, for example, as the face
of compassion to patients and their families (Peplau, 1991). Thus, a nurse
openly ‘owning’ negative attitudes towards patients with obesity would
create a conflict between these identities and threaten their own assured
identity as a nurse. As such, weak or non significant relationships between
weight bias measures and the variables explored may represent the social
desirability bias required to protect their identity as a nurse rather than a true
representation of weight related attitudes. Further research may consider the
use of implicit as well as explicit measures of weight bias to produce more
consistent and accurate results.
However, changing the methodology to hone consistency assumes that
consistency is the benchmark to achieve, a benchmark that critical social
psychologists would likely disagree with (e.g. Potter & Wetherell, 1987).
For example, more discursive approaches suggest that inconsistent results
33
are to be expected and are a normal part of the variation that occurs within
language depending on its function (Potter & Wetherell, 1987). As such, it
is not unreasonable to suggest that inconsistencies will occur between
individuals as well as within them and indeed the ability to accept
variability as an expected part of language allows for a richer analysis of
human experience. In relation to the cross sectional methodologies typically
used within the weight bias literature, critical social psychologists argue that
they restrict variability in an attempt to locate consistent attitudes but that in
doing so they may misinterpret what is real, in favour of what is the same
(Potter & Wetherell, 1987). Therefore, in this context, the inconsistent
results found in this review, may arguably suggest that answering the
questions posed in the studies reviewed may have different functions
dependent on the differing context in which individuals were responding
from within. Given the wide range of cultures, countries, healthcare systems
and time periods of studies, this review located, it is possible that the
inconsistent results do indeed relate to this.
Various theoretical frameworks have been used within the attitudes
literature generally and in some cases, more specifically within the weight
bias literature. Although the literature within attitudes research has tended to
ground its research within, both traditional and more recently critical social
psychological approaches, the weight bias literature that is grounded in
theory, has tended to remain within the more traditional or experimental
social psychology paradigms. However, in examining the research within
this review, although some of the more recent studies were underpinned
with relevant theory (e.g. Torrey, 2013), often they were not. This meant
34
that it was difficult to situate the research that was reviewed within current
theory. The limited literature located for each variable was problematic as it
meant that in order to conduct a comprehensive review, literature was
reviewed of varying quality. This made it difficult to interpret the findings
accurately and compare studies systematically. As such, contextualizing the
literature reviews findings within the wider research was difficult.
Conclusion
In conclusion, this review aimed to examine the research focusing on
the relationship between nurses’ own BMI, qualification status, self-esteem
and stress with weight bias towards patients with obesity. The results found
that within some areas, such as when examining BMI, the results were
contradictory. In other areas, such as with qualification status, self-esteem,
stress and burnout, there was limited research conducted within nursing
populations and thus the wider literature was included in order to make
sense of findings. As such, the disjointed nature of both the historic and
current research in this area has been highlighted. This may relate to the fact
that studies are often not grounded within the theoretical frameworks
commonly used within the wider literature on attitudes which means making
sense of them in the context of prior or wider research difficult. This is
despite attempts to highlight theoretical frameworks and their evidence base
within the weight bias literature (e.g. Puhl & Brownell, 2007). Although
there are criticisms of traditional social psychological approaches to
attitudes, within the wider weight bias literature, these approaches have
been more commonly used. As such, before considering the appropriateness
of alternative approaches to understanding attitudes, drawing together the
35
research using a traditional social psychological framework may be helpful
prior to considering where the focus of future research should lie and the
most useful theories to underpin this within.
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50
Appendix 1 – Quality Appraisal Tools
Strobe Checklist
51
Appendix 1 (Continued)
52
Appendix 2 – Study quality analysis summary tables Authors (year)
Aim Location
Design Sampling Response rate
Instruments Reliability Comments
Bagley, Conklin, Isherwood, Pechiulis & Watson (1989)
To develop a scale to measure nurses attitudes about obese patients
USA Cross validation study
107 RN graduate nurses Convenience sample.
N/A Measure of dissatisfaction of own body image isn’t specified Questionnaire not named, but subscales include 15 item Nursing Management Scale and 13 item Personality and Lifestyle Scale,
Psychometricproperties not provided.
Nurses who were dissatisfied with their own body weight were linked to negative attitudes towards obese patients (r= -.26) hospital effect was found (p<.05) independent of age and education.
Brown, Stride, Psarou, Brewin & Thompson, 2007)
Does BMI relate to negative attitudes towards obese patients in nurses?
UK Cross sectional survey design
564 nurses across four Primary Care Trusts. Convenience sample
72.3% Questionnaire developed by researchers.
a= .69 Weak positive correlation r= 0.12 (higher BMI less negative attitudes)
Culbertson & Smolen (1995)
Exploring the effects of RN students demographic variables on their attitudes toward obesity
USA Cross sectional survey design
73 nurse students Convenience sample.
N/A Self reported whether they thought needed to loose 10IB or not BMI! NATOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989b). Internal reliability.92
a= .92 No statistical significant difference in attitudes between those needing/not needing to loose 10Ib.
61
62
Appendix 2 – Quality analysis summary tables (Continue)
Authors (year) Aim Location Design Sampling Response rate
Instruments Reliability Comments
Garcia (2012) Assessing weight bias in nursing staff
USA Cross sectional survey design
113 nurses Convenience sample across three hospitals.
42.9% BMI calculated from self reported weight and heightNATOOPS (Watson, Oberle & Deutscher, 2008).
a = .97Individual subscales between .83 & .97
Weak positive correlation between BMI and weight bias p= -.121 (higher BMI less negative attitudes). One controllability factor statistically significant with underweight nurses having more bias p<.05
Geckle (2001) Assessing the relationship between nurses perception of their weight & attitudes towards patients with obesity
USA Cross sectional survey design
300 nurses
Convenience sample
44.7%. ANTOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989a) questionnaire. Chronbach alpha 0.97, individual subscales between .83 and .97Weight categorised by weight category groups
a = .97Individual subscales a = .83 & .97
Significant difference between appropriate weight & overweight group and their attitudes p<.05 (overweight more positive) No effect size reported.
Lilliot (2000) Is there a relationship between nurse BMI and attitudes towards obese patients?
USA Cross sectional survey design
143 nurses Convenience sample across three sites.
29%. BATOS (Bray, 1972) a= 0.74 in previous studies
Weak positive correlation r=.17 (higher BMI less negative attitudes)
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Appendix 2 - Quality analysis summary tables (Continued)
Authors (year)
Aim Location
Design Sampling Response rate Instruments Reliability
Comments
Poon & Tarrant (2009)
To examine the attitudes of registered and undergraduate nurses towards obesity
China Cross sectional survey design
352 undergraduate nurses199 registered nurses
88% recruited over two years due to recruitment issues
ATOAP (Bagley, Conklin, Isherwood, Pechiulis & Watson, 1989a) reliability .79 and Fat Phobia Scale (Bacon, Scheltema, Robinson, 2001).
a = .79
a= .82
The data for BMI is not shown but overall there were no significant differences on ATOAP p=0.29 or FPS p=0.08 and BMI, sample to detect small effect. Registered nurses showed more weight bias but were also older, not controlled for.
Puhl, Leudicke & Grilo (2013)
To examine weight bias among trainee health students in relationship to characteristics such weight, shape and self esteem
USA Cross sectional survey design
107 postgraduate healthcare students, range of professions, recruited at university,
91% EDE-Q, (body image concerns)Rosenberg Self-esteem scale (Rosenberg, 1965), UMB-FAT (Latner, O’Brien & Durso 2008),
a =.94 a =.88,
a =.87
Self-esteem was not correlated with attitudes questionnaire. It was correlated with four outcome variables, including perceived weight bias but none significant. EDE-Q was significantly associated with perceptions of weight bias in HC setting.
64
Appendix 2– Quality analysis summary tables (Continue)
Authors (year)
Aim Location
Design Sampling Response rate Instruments Reliability
Comments
Torrey (2013)
Assessing weight bias in nursing staff
USA Cross sectional survey design
114 nurses, systematic sampling, sent questionnaire through post.
31% NATOOPS (Watson, Oberle & Deutscher, 2008).
a = .45- .78
Higher BMI associated with more bias.As body image guilt and shame increased so did negative attitudesBMI, guilt and shame not controlled for
Young (1985)
Differences in attitudes toward obesity between obese and non obese nurses
USA Cross sectional survey design
59 female nurses recruited from one federal hospital Convenience sampling
N/A The Obesity QuestionnaireMetropolitan Life Insurance Company’s desired weight standards (1959)
Overall reliability reported as r=.58
Mann-Whitney U test suggested no stat sig difference between obese and non obese participants (mean 31.31/29.43, no effect sizes reported
65
Part 2
MRP Empirical paper
A mixed methods study exploring
weight related bias in
undergraduate and qualified nurses
Word Count: 9998
Abstract
66
There is good evidence to suggest that nurses’ bias towards patients
with obesity has adverse psychological and physical health implications for
patients in terms of poorer care from healthcare staff and the avoidance of
healthcare. Despite important clinical implications the literature yields no
consensus about specific factors relating to weight bias and no consistently
used theoretical framework to interpret findings. Therefore this study aimed
to draw on intergroup theories of weight bias to explore the relationship
between weight bias in nurses and their self-esteem, BMI, qualification
status, stress and burnout.
The study used a cross sectional mixed method design, involving an online
survey using standardized weight bias, self-esteem, stress and burnout
measures and an open ended question about bias. Participants were 218
undergraduate and postgraduate nurses practicing within the United
Kingdom.
There was no evidence of weight bias and hence limited correlations
detected between weight bias and self-esteem, BMI, qualification status,
stress and burnout. Analysis of the open-ended responses suggests that
social identity may influence weight bias, and the conceptual frameworks
that nurses use to make sense of obesity.
The used of standardised measures to explore factors relating to
weight bias did not add clarity to the literature. However, qualitative data
in this study enabled a better understanding of the complexity of attitudes
towards obesity. Attitudes are portrayed in the context of a hierarchy of
complex social identities situated within a broader social context. The
qualitative analysis revealed that both these issues may make it difficult for
nurses to ‘own’ more negative attitudes, which may explain the inability of
67
more restrictive survey design methodologies to reveal the complexity of
attitudes within a social context. Future research that uses methodologies
that enable exploration of the complexity around the nursing role may
further enhance our understanding of weight bias in nurses.
68
Historically, prejudice towards marginalized social groups has been
explicitly expressed (Sears, 2007). Brownell and Fairburn (1995) suggest
that more recently overt prejudice and discrimination have become subtler
and less acceptable. However, prejudice towards people with obesity has
remained explicit, suggested to be the last acceptable form of prejudice (e.g.
Puhl & Heuer, 2009) even exceeding that of other marginalized groups
including race and gender (Andreyeva, Puhl & Brownell, 2008).
Prejudice towards people with obesity is well evidenced across a
range of social contexts, including education (Puhl & Brownell, 2001),
employment (Puhl, Henderson & Brownell, 2005), and the media (Yoo,
2013). Equally, within healthcare, weight bias is pervasive across a range of
professional groups (see Phelan, Dovidio, Puhl, Burgess, Nelson, Yeazel,
Hadreman, Perry & van Ryn, 2013; Bleich, Bandara, Bennett, Cooper &
Gudzune, 2014). Of particular concern is the convincing evidence that
nurses hold negative attitudes towards patients with obesity, viewing them
as overindulgent and lazy (Brown, 2006), and feeling hostile and angry
when caring for them (Crandall et al, 2001). As frontline professionals
spending the most time directly caring for patients of all healthcare
professionals (National Audit Office 2001), there is a real concern that such
attitudes may translate into poor clinical care and patient experience.
The evidence suggests that healthcare staff who display weight bias
demonstrate less respect for patients with obesity (Puhl & Heuer, 2009),
spend less time caring for them (Swift, Hanlon, El-redy, Puhl &
Glazebrook, 2013), less time discussing treatment options with them and are
less likely to provide intervention (Forhan, 2013). They also provide
preventative health screening less often comparatively to those of an
69
average weight (Bertakis & Azari, 2005). They do not provide appropriate
resources to help accommodate patients’ size as often or as willingly (Amy,
Aalborg, Lyons, Keranen, 2006).
In addition to the psychological implications of such bias on the
patient with obesity, which include lower self-esteem, poorer mental health
and an increased risk factor in the likelihood of suicide (Puhl & Heuer,
2009), there are also significant physiological clinical implications. Obese
men are five times, and woman thirteen times, more likely to develop type
two diabetes than non-obese men and woman (Department of Health, 2011).
There are increased risks for cardiovascular disease (de Koning, Merchant,
Pogue & Anand, 2007), asthma (Beuther & Sutherland, 2007) and various
cancers (e.g. Renehan, Tyson, Egger, Heller & Zwahlen, 2008; Larsson,
2007). The physical co-morbidities (Department of Health, 2011) associated
with obesity are significant in relation to weight bias because patients
experiencing such bias are less likely to engage with health services (Hebl
& Xu, 2003) and increase unhealthy eating behaviours (Schvey, Puhl, &
Brownell, 2012). As such, presenting co-morbid conditions are more
advanced and difficult to treat by the time the person accesses services
(Phelan, Burgess, Yeazel, Hellerstedt, Griffin & van Tyn (2015). Moreover,
when the patient does access services they may be less adherent to
prescribed treatment and self care (Cohen, Steele & Ross, 1999), further
reducing treatment success. Thus, the combination of poorer care from
healthcare professionals and the avoidance of healthcare from the patient
risks serious complications (Haslam & James, 2005).
Despite the clarity surrounding the clinical implications of weight bias
in healthcare and in nurses, a recent comprehensive review suggests that the
70
research is surprisingly fragmented (Goad, 2016). The focus of research is
variable and has identified no specific factors that unanimously relate to
weight bias. In fact, the results of these studies have often contradicted each
other, for example when exploring the relationship between weight bias and
nurses BMI (e.g. Garcia, 2012 & Torrey, 2013).
The variability in research and contradictions in findings may relate to
the lack of a coherent body of theory that interprets of findings. A variety of
theoretical frameworks have been utilized to underpin weight bias (see Puhl
& Brownall, 2003 for a review). For example, Attribution Theory (Crandall,
2001) and Social Identity Theory (Tajfel & Turner, 1986) but these have not
been used consistently to conceptualize studies in relation to earlier research
making the bigger picture harder to understand.
Any exploration of the attitudes of nurses towards patients with
obesity involves exploring the attitudes of one social group towards
members of another; thus a theoretical framework that incorporates
intergroup theories of prejudice would seem logical. One theory with
explanatory potential is Social Identity Theory (Tajfel & Turner, 1986)
which posits that discrimination may occur due to group processes (Rubin &
Hewstone, 1998). One of Social Identity Theories key hypotheses suggests
that group members protect or enhance their own self-esteem through
positive identification with the in-group; often achieved through
discrimination against the out-group (Martiny & Rubin, 2016).
Yet, despite self-esteem being indicated at the heart of prejudice and
discrimination (Tajfel &Turner, 1986) the only study explicitly exploring
self-esteem in healthcare professional trainees found no association with
weight bias (Puhl, Leudicke, & Grilo (2013). However, tentative
71
relationships have been found between weight bias and other factors relating
to self-esteem such as lower levels of body dissatisfaction (e.g. Bagley,
1989) or body guilt and shame (Torrey, 2013). Research outside of
healthcare also suggests that students with lower self body image have
higher levels of implicit, and explicit weight bias mediated by downward
social comparison (O’Brien, Hunter, Halberstadt & Anderson, 2007). Thus,
although people may compare themselves favorably against patients with
obesity in order to improve their own view of themselves, the impact of
self-esteem itself on weight bias remains unclear.
An individual’s physical appearance has been linked to self-esteem
(Crocker, Luhtanen, Copper & Bouvrette, 2003), for example with much
more research exploring weight bias and nurses own weight (e.g. Garcia,
2012; Geckle, 2001; Poon & Tarrant, 2009), although the rationales do not
generally relate to the self-esteem hypothesis (Tajfel & Turner, 1986).
However, one study (Torrey, 2013) exploring the relationship between BMI
did so, highlighting the conflict between the ‘in-group’ membership of a
nurse, often held in high esteem as a health promoter, and the characteristics
of those who are also overweight or obese which would simultaneously
place them in the out-group (Torrey, 2013). The salience of group
membership as well as group identification is key in determining how
attitudes are expressed towards the ‘out-group’ (Hogg & Smith, 2007). Thus
the salience and identification of a nursing identity versus a weight related
identity may determine the expression of the nurses attitudes towards
patients with obesity. However, the complex interplay of these identities and
their expression is often unclear, perhaps explaining why previous studies
have been contradictory with some suggesting that as nurse BMI increases
72
weight bias decreases (Brown, Stride, Psarou, Brewin & Thompson, 2007;
Garcia, 2012; Geckle, 2001; Lilliot, 2000), as nurse BMI increases, weight
bias increases (Torrey, 2013) and some indicating no relationship at all (e.g.
Culbertson & Smolen, 1995; Poon & Tarrant, 2009; Young, 1985). The lack
of theoretical underpinning in many studies makes deciphering these mixed
findings difficult.
If, alongside group salience, group identification partially predicts
how attitudes are expressed towards out-groups (Hogg & Smith, 2007), then
exploring the strength of identification with nursing membership in relation
to weight bias is imperative. Although not situated within intergroup
relations theory, one study did explore the differences between qualified and
student nurses and weight bias (Poon and Tarrant, 2009). Debatably,
qualified nurses may be expected to identify with their nursing identity more
strongly than those in training and thus more weight bias may be expected.
This study did indicate that qualified nurses held more weight bias than
nurses in training thus aligning with this hypothesis. However, the
undergraduate nurses were also significantly younger than qualified nurses,
and thus the interplay with age should be considered, particularly as the
literature on weight bias and age in healthcare staff is also contradictory
(e.g. Bagley, Conklin, Isherwood, Pechiulis, Watson, 1989; Wise, Harris &
Olver, 2014; Miller et al., 2013).
Finally, traditional attitudes research has been heavily criticised for its
lack of focus on the wider social context, instead favouring attitudes as
internal cognitive representations (Hogg & Smith, 2007). The reality is that
the changes in modern society are numerous and rapid (Rogers, 2003) and
do of course influence attitudes held within groups (Prislin & Wood, 2005).
73
This is particularly true in the context of the NHS, where the organization is
constantly facing restructuring and monetary cuts (Warner & O’Sullivan,
2014) translating to high staff turnover, increased workloads and staff
shortages (Van Bogaert et al., 2009). With 30% of staff sickness within the
NHS related to stress (NHS Employers, 2009); nurses are likely struggling
with those pressures. Burnout is also increasingly common, for nurses
globally (McFeely, 2007). In the UK the rate of reported burnout in nurses
is 14% higher than the European average (Heinen et al., 2013).
In times of monumental change within the NHS, Relative Deprivation
Theory (RDT; Stouffer, Suckman, DeVinney, Star & Williams, 1949),
recently seen within the realm of intergroup theories of prejudice, suggests
that in times of social change, group members are continually re-evaluating
the position of their group (Moghaddam, 2002). If re-evaluation deems the
impact of social change as a) disadvantageous and b) unfair, then members
are likely feel increased frustration to which they may respond (Smith,
Pettigrew, Pippin & Bialosiewicz, 2011). If group members experience the
impact of this personally (Walker & Smith, 2002); they are likely to feel
more stressed on an individual level, but if it threatens their group identity
they are more likely to exhibit prejudice towards other groups (Walker &
Smith, 2002). Theories preceding Relative Deprivation Theory (e.g.
Dollard, Doob, Miller, Mowrer, & Sears, 1939) have suggested that such
frustration is rarely expressed towards the actual perpetrator of the
perceived deprivation but is often displaced on to more vulnerable groups
(Brown, 1995). In the context of nurses, it may be patients with obesity who
are targeted because they are more easily accessible for blame than the
wider political system and they may represent an increased workload, which
74
is then used to justify the negative attitudes directed towards them. Research
unequivocally suggests that many nurses are highly stressed (NHS
Employers, 2009) and burnt out (Heinen et al., 2013). It also indicates that
they may hold negative attitudes towards patients with obesity (Brown,
2006). Yet despite grave concerns about the impact on clinical care, no
research has explored the relationship between stress and burnout in relation
to weight bias in nurses.
Research rationale
Negative attitudes towards patients with obesity are well evidenced
(e.g. Brown, 2006) alongside the serious clinical repercussions of that bias
when exhibited by nurses (Haslam & James, 2005). Yet despite this, there
appears to be no clear pattern that explains or predicts this bias. This may in
part relate to the lack of consistent theoretical frameworks underpinning
weight bias research conducted so far. However, attitudes research has often
historically been situated within intergroup theories of prejudice (e.g.
Stouffer, Suckman, DeVinney, Star & Williams, 1949; Tajfel & Turner,
1987). As such, this study draws on intergroup theory to explore the
relationship between weight bias and self-esteem, BMI, qualification status,
stress and burnout using a mixed method design.
Research questions
1) Is nurse self-esteem associated with weight bias?
2) Is nurse BMI associated with weight bias?
3) Are there differences between undergraduate and qualified nurses and
weight bias?
4) Is nurse stress associated with weight bias?
5) Is nurse burnout associated with weight bias?
75
Method
Design
A cross-sectional mixed method design was employed comprising an
online survey using standardized questionnaires plus a demographic
questionnaire with one open-ended question enabling participants to provide
unconstrained responses.
Participants
Undergraduate and qualified adult nurses were contacted through one
local NHS Foundation Trust, undergraduate and postgraduate nursing
programmes at two UK universities, and through nursing groups on the
social network sites Twitter and Facebook.
Eligibility criteria
English speaking adults enrolled on adult nursing programmes within
the UK or qualified adult nurses currently practicing in the UK were eligible
to participate.
Sample Size
Statistical power calculations using G* Power 3.1.7 (Faul, Erdfelder,
Buchner & Lang, 2009) were conducted in order to establish the sample size
needed to detect a medium effect size as detected in prior studies (e.g.
Brown, Stride, Psarou, Brewins & Thompson, 2007) when using the
relevant statistical analysis. The power analysis calculated that a sample size
of 109 participants per group (student and qualified nurses) were required
for analyses comparing groups in order to achieve a power of 80% and
detect a medium effect between variables at the 5% level using a two-sided
test. For correlation analyses the power analysis suggested that a sample
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size of 82 participants overall would detect a medium effect at the 5% level
using a two-sided test (see appendix 1).
Participant demographic information (appendix 2)
In total, 218 nurses completed the questionnaires of which 113 were
undergraduate nurses and 105 were qualified nurses. Seventeen were male
(7 undergraduate and 10 qualified nurses) and 201 were female (106
undergraduate and 95 qualified). The mean age across all 218 participants
was 32.02 (±11.36) with a mean of 26.8 (±9.1) for undergraduates and 37.66
(±10.99) for qualified nurses. The majority of the participants were white
British (84 undergraduate and 78 qualified nurses) although a small number
of other ethnicities were represented. The mean BMI for the 218
participants was 25.63 (±4.73), for undergraduate nurses was 24.7 (±4.5)
and for qualified nurses was 26.7 (±17.4).
Of 218 data sets, 197 were complete and 21 were incomplete with
the demographic and Anti Fat Attitudes (AFA) questionnaires completed
but missing data amongst all of the other questionnaires (see appendix 3).
However, as the AFA questionnaire was the only questionnaire required in
comparison of undergraduate and qualified nursing groups, this did not
reduce the power of the study.
Ethical Considerations
Ethical approval was granted by The Faculty of Health and Medical
Science at the University of Surrey, the University of the West of England
(appendix 4) and through the local NHS Research and Development
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approval process (appendix 5). The study was conducted in accordance with
the Code of Human Research Ethics (British Psychological Society, 2010).
Procedure
Data was collected between December 2015 and May 2016.
Participants were recruited from two universities through emails containing
the study link, online learning portals, poster advertising and lecture
attendance by the researcher for adult undergraduate and postgraduate
nurses (appendix 6). Participants were also recruited from one local hospital
site through email distribution and poster advertisements as well as
circulated on nursing group social networks including Facebook and
Twitter. Advertising emails were re-circulated monthly to improve response
rates. Participants could opt in to the online survey by clicking on the link to
the survey included with the advertisements. The study was configured to
ensure that the information sheet (appendix 7) was presented first, followed
by the consent form (appendix 8). Participants were required to confirm
consent online prior to being able to access the survey. Participants were
offered the opportunity to provide their email address in order to receive a
summary of the results or to be entered in to a prize draw for one of five £20
Amazon vouchers. On completion links to organizations able to provide
emotional support were provided in the event of any emotional distress
caused (see appendix 9).
Measures
The survey was developed to include a set of self-administered
questionnaires aimed at capturing information on participant demographic
information, attitudes about obesity, self-esteem, perceived stress and level
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of burnout. Measures were chosen based on the strength of their
psychometric properties as described in current and relevant literature; as
well as their suitability for use with a nursing population accessing them
online. A participant demographic questionnaire was developed by the
researcher to gather the basic information required for the analysis
(appendix 10). An unrestricted character text box was provided to facilitate
the participant’s responses to the question, ‘what are your views on why
nurses might hold negative attitudes towards patients with obesity?’ The
standardized questionnaires (appendix 11) are described below in the order
they were presented to the participants.
Anti Fat Attitudes (AFA) questionnaire (Crandall, 1994)
This 13-item assessment of anti-fat attitudes, has three subscales,
‘Dislike,’ ‘Fear of Fat,’ and ‘Willpower.’ Participants were required to
indicate their level of agreement on a scale of 0 (very strongly disagree) to 9
(very strongly agree). The AFA has shown good internal reliability on all
three subscales with coefficient alphas of .88, .88 & .72, respectively
(Robinson, Ball & Leveritt, 2014).
Attitudes towards Obese Persons (ATOP) (Allison, Basile & Yuker,
1991)
This 20-item questionnaire is a general measure of attitudes towards
people who are obese including attitudes towards their quality of life,
personality and self-esteem. Participants indicate their agreement to each
statement on a scale of -3 (strongly disagree) to +3 (strongly agree).
Coefficient alphas ranging from .8 to .84 across populations indicate its
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reliability (e.g. Puhl & Brownell, 2006; Brewis & Wutich, 2012). It has
good construct validity, correlating positively with the Beliefs about Obese
Persons Scale (BAOP) (r=.4, p<.05 ) (Allison, Basile, & Yuker, 1990).
Rosenberg’s Self-Esteem scale (RSE) (Rosenberg, 1965)
This widely used measure (Donnellan, Trzesniewski, & Robins, 2011)
is a 10 item scale with item responds represented on a four point Likert
scale. Substantial evidence supports the predictive validity and internal
reliability of the scale both historically (i.e. Byrne, 1983 & Kaplan, 1980)
and recently (Sinclair, Blais, Gansler, Sandberg, Bistis & LoCicero, 2010).
More recent studies cite coefficient alphas of .88 and good construct validity
with the RSE positively correlating with optiminism (r=.44, p <.5) and
negatively with shyness (r= -.26, p<.28) (Robins, Hendin & Trzezniewski,
2001). The scale is validated in nursing (Takase, Yamamoto, Sato, Nittani &
Uemura, 2015) and UK populations (Bagley & Mallick, 2012).
Perceived Stress Scale (PSS) (Cohen, Kamarck, & Mermelstein, 1983)
This 14-item scale measures how participants perceive their own
stress through item responses on a five point Likert scale from 0 (never) to 4
(very often). Its internal consistency using Cronbach alpha is 0.75 and it
shows good construct validity e.g. correlating positively with depressive
symptomology r=.65 and .76, p<0.05 (Cohen, Kamarck, & Mermelstein,
1983).
Maslach’s Burnout inventory (MBI) (Maslach & Jackson, 1981)
This 22-item measure of burnout includes three subscales, emotional
exhaustion, depersonalization and lack of personal accomplishment with
item responses represented using how frequently, from ‘never’ to ‘every
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day’, they related to each item. Reliability coefficients for the emotional
exhaustion subscale were .9, for the depersonalization subscale, .79 and for
the personal accomplishment subscale .71. Each dimension correlated
highly with ratings given by peers who knew the individual well, for
example, the item ‘higher emotional exhaustion’ was positively correlated
with the MBI, (r=. 56, p< .001) (frequency) and (r= .57, p< .001) (intensity;
Maslach & Jackson, 1981) suggesting good convergent validity.
The normative data for each questionnaire, as established by the
respective authors is shown in table 1.
Table 1.
Normative questionnaire data
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Reliability estimates
Table 2 indicates that the majority of the questionnaires and associated
subscales had Cronbach alphas of above .7, deemed within the acceptable
range (Kline, 1999). The Cronbach alphas for the ‘willpower’ subscale of
the AFA and the ‘depersonalization’ subscale on the MBI were slightly
lower than this cut off but may be accounted for by each subscale having a
smaller number of items than their counterparts, a factor known to reduce
reliability estimates (Cortina, 1993).
Table 2.
Reliability estimates. Questionnaire Subscale Cronbach alphaAFA Dislike .888
Fear of Fat .839Willpower .685
Questionnaire Normative questionnaire data AFA dislike Scale based on averages, average score = 5AFA fear Scale based on averages, average score = 5AFA willpower Scale based on averages, average score = 5ATOP total High numbers= more positive attitudes. Score of 60
is average (0-120) RSE Total Higher scores from 0-40 = higher self esteem PSS Total Scores of around 13 are average, scores of 20 are
considered ‘high stress levels’ MBI DP 13 and over = High
7-12 = Moderate0-6 = Low
MBI PA 39 and over = High32 to 38 = Moderate0 to 31 = Low
MBI EE 27 and over = High17 to 26 = Moderate0 to 16 = Low
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ATOP N/A .735RSE N/A .874PSE N/A .837MBI Depersonalization .618
Personal Accomplishment .815Emotional Exhaustion .866
Quantitative analysis
Descriptive statistics were conducted prior to full analysis. An
independent t-test was used to test whether there was a difference in the
AFA weight bias measure between undergraduate and qualified nurses.
Correlational analyses examined the relationships between the two weight
bias measures (AFA and ATOP), the measure of self-esteem (RSE),
perceived stress (PSS) and burnout (MBI).
Qualitative analysis
A qualitative methodology was chosen to complement the quantitative
methodology due to a longstanding critique of quantitative methodologies in
attitudes literature which holds reservation about both experimental and
survey designs in representing ‘attitudes’ (see Potter & Wetherell, 1987).
Qualitative methodologies allow for a deeper level of analysis in relation to
understanding human experience (Harper & Thompson, 2012) and do not
seek to restrict data in the way that traditional quantitative methodologies do
(Rogers, Stenner, Gleeson & Rogers, 1995) allowing participants to share
their views of nurses attitudes towards patients with obesity in their own
language (see appendix 12 for a summary critique of the attitudes literature).
A range of qualitative analyses were considered (appendix 13) but a
thematic analysis was chosen given the exploratory nature of the study.
Thematic analysis is not attached to any specific theoretical framework
(Braun & Clarke, 2006), allowing it to be used more flexibly as long as its
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chosen theoretical position is made clear. Given the limited theoretical
underpinning of weight bias literature (Zhu, Norman & While, 2011), an
inductive approach was employed to enable a ‘bottom up’ analysis (Frith &
Gleeson, 2004) with the development of themes strongly linked to data
(Patton, 1990). The guidelines established by Braun & Clarke (2006) for
completing a thematic analysis were followed (appendix 14).
Predominantly, themes were detected at a semantic level in the
context of how nurses made sense of negative attitudes towards patients
with obesity. Although thematic analysis primarily focuses on either
semantic or latent themes, latent themes were also detected and were
important in interpreting the data in the context of the research question, and
thus were included and demarcated as such.
Epistemological position
A theoretical position of social constructionism was assumed in
conducting the analysis, seeking to interpret data within the sociocultural
context in which it resides (Braun & Clarke, 2006). It is based on the
assumption that meaning is socially produced rather than the product of the
individual (Burr, 1995).
Researcher position and reflexivity
The social constructionist position assumed also aligns with my own
stance as a researcher and a trainee clinical psychologist. My reflections in
relation to this can be found in appendix 15.
Credibility
This study was conducted in line with Yardley’s four characteristics
indicative of credible qualitative research (Yardley, 2000). The integration
of these principles in the context of this research can be found in appendix
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16. Appendices 17, 18 and 19 also provide examples of the coding themes
alongside the development of each thematic map to aid transparency.
Results
Data screening
A thorough data screening process was undertaken, the full analysis of
which can be located in appendix 202.
Table 3 illustrates the mean scores for each questionnaire/subscale
total for all 218 participants.
Table 3.Mean scores for each questionnaire and subscales.
Questionnaire N Mean (S.D.)AFA dislike average 218 7.5 (1.8)AFA fear average 218 3.8 (2.7)AFA willpower 218 4.3 (2.2)ATOP total 196 70.6 (14.4)RSE Total 198 21.1 (6.1)PSS Total 195 19.4 (4.8)MBI DP 170 4.5 (3.8)MBI PA 185 31.1 (6.3)MBI EE 184 25.8 (8.7)
Table 1 in the methods section illustrate the comparative norms for
each questionnaire. The mean scores in table 3 above suggest that nurses’
attitudes towards patients who are obese were neither negative nor positive
overall. On both the AFA subscales and the ATOP, nurses attitudes fell
close to average (as ‘slightly positive’ or ‘slightly negative’). Nurse’s self-
esteem measured by the RSE was also average. Nurse’s overall perceived
stress was within the ‘high range’ on the PSS. In the measure of burnout
(MBI), low levels of depersonalization were detected in nurses, but
2 The data screening analysis was initially illustrated in the main body of this thesis but can now be located in appendix 20. As such, appendices 21-25 are referenced from within appendix 20 rather than in the main text.
85
moderate levels of emotional exhaustion and low levels of personal
accomplishment.
Table 4.
Mean scores for the AFA and the ATOP split by qualification status.
Questionnaire (subscale)
Qualifications status N Mean (S.D.)
AFA (dislike) Undergraduate 112 7.3 (2.0)Qualified 106 7.7 (1.5)
AFA (fear of fat) Undergraduate 112 3.6 (2.9)Qualified 106 4.0 (2.5)
AFA (willpower) Undergraduate 112 4.5 (2.2)Qualified 106 4.1 (2.1)
For research question three, participants were grouped by qualification
status to explore differences in their responses on the AFA. As such, the
means for the qualified and undergraduate nurses separately are illustrated
in table 4. The means between qualification groups combined were very
similar to the means when undergraduate and qualified nurses were
separated.
The Spearman’s correlation coefficient was used for correlation
analyses involving the AFA as the data did not meet the assumptions of
normality required for parametric testing. The second weight bias
questionnaire (ATOP) was analysed using the parametric Pearson’s
correlation as it did meet the parametric assumptions required.
Table 5.
Spearman’s rho for the AFA questionnaire and Pearson’s correlation for
the ATOP when correlated with BMI, RSE, PSS and MBI.
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AFA dislike
AFA fear
AFA willpower
ATOP
BMI Correlation Coefficient
.092 -.004 -.015 .056
Sig. (2 tailed) .174 .955 .828 .435N 218 218 218 196
RSE Correlation Coefficient
-.134 -.189** .091 -.104
Sig. (2 tailed) .060 .008 .202 .146N 198 198 198 198
PSS Correlation Coefficient
-.156* -.142* .040 -.066
Sig. (2 tailed) .029 .048 .575 .358N 195 195 195 195
MBI DP Correlation Coefficient
-.322** -.163* -.098 -.319**
Sig. (2 tailed) .000 .033 .206 .000N 170 170 170 169
MBI PA Correlation Coefficient
.075 -.013 .104 .178*
Sig. (2 tailed) .308 .865 .158 .016N 185 185 185 183
MBI EE Correlation Coefficient
-.067** -.023 .049 -.093
Sig. (2 tailed) .005 . .004 .213N 184 184 184 182
* Correlation significant at the .05 level (2- tailed) **Correlation significant at the .01 level (2- tailed)
Of note, the direction of the ATOP questionnaire is opposite to that of the
AFA, with higher scores meaning more positive attitudes on the ATOP but
equalling more negative attitudes on the AFA. The meaning of the direction
of scores for each questionnaire are represented in table 6 below.
Table 6.
The direction of scores meaning for each questionnaire
Standardized questionnaire Direction of scoring
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AFA (all subscales) Increasing AFA scores across subscales mean higher levels of weight bias.
ATOP Increasing ATOP scores mean lower levels of weight bias
RSE Increased RSE scores mean higher self-esteem
PSS Increased PSS scores mean higher perceived stress
MBI - DP - EE - PA
Increased scores on the MBI subscales mean higher levels of DP, EE and PA.
Research question one: Is nurses own self-esteem associated with their
attitudes towards patients with obesity?
A significant negative correlation was detected between the RSE and
the AFA fear subscale (p <.01), such that as nurses own self-esteem
increased, their ‘fear of fat’ decreased (table 5). However, the correlation
coefficient suggested that the relationship was of a weak to moderate effect3
and the scatter plot representing this correlation (appendix 26) does not
depict a clear relationship between the two variables suggesting that the
magnitude of this result may be small. No relationship was detected
between the RSE and second two AFA subscales, dislike and willpower
(p>.05). The Pearson’s correlation conducted on the RSE and the ATOP
was non-significant (table 5), which suggests that there was no relationship
between nurses self-esteem and their overall attitudes towards patients who
are obese (p>.05).
Research question two: Is nurses own BMI associated with the attitudes
they hold towards patients with obesity?
Questionnaire Qualification status
N Mann-Whitney U
Z Asymp. Sig (2- tailed)
3 The correlation coefficient is considered to be a standardised measure of the observed effect and thus may be used as an effect size. A small effect is represented to be <.1 or <-1, a medium effect is represented by .1 to .3 or -.1 to -.3 and a large effect .3-.5 or -.3 to -.5.
88
AFA (dislike) Undergraduate 112 5091.5 -1.8 .07Qualified 106
AFA (fear of fat)
Undergraduate 112 5264.5 -1.4 .1
Qualified 106AFA (willpower)
Undergraduate 112 5310.5 -1.3 .2
Qualified 106ATOP Undergraduate 112 4110.00 -1.5 .1
Qualified 84Table five shows no significant relationship was detected between
nurses own BMI and each of the three subscales on the AFA (p>.05). The
Pearson’s correlation replicated this result suggesting no relationship
between nurses own BMI and the ATOP (p>.05).
Research question three: Is there a difference between undergraduate
and qualified nurses in their attitudes towards patients with obesity?
No significant difference was detected between the ATOP or each of
the three AFA subscales and qualification status, p > .05, suggesting that
attitudes towards patients who are obese do not differ between
undergraduate and qualified nurses (table 7).
Table 7.
Mann-Whitney U Test - differences between qualified and undergraduate
nurses attitudes towards patients with obesity.
Research question four: Is there an association between nurses
perceived levels of stress and their attitudes towards patients with
obesity?
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The Spearman’s correlation (table 5) indicated that there was a
significant negative correlation between the PSS and the AFA dislike
subscale (r = -.156, p <.05) and also between the PSS and the AFA fear of
fat subscale (r = -.142, p <.05). This indicated that as dislike and fear of fat
attitudes increased, perceived stress decreased. However, the correlation
coefficients suggested a weak to moderate effect and the scatter plot
representing each correlation (appendix 26) did not depict clear
relationships between each of the two variables. No significant relationship
was detected between the PSS and the AFA willpower subscale (p>.05).
The Pearson’s correlation conducted (table 5) between the PSS and the
ATOP was non-significant indicating that there was no relationship between
nurse’s overall attitudes towards obese patients and their perceived level of
stress (p>.05).
Research question five: Is there an association between nurse’s level of
burnout and their attitudes towards obese patients?
The Spearman’s correlation indicated (table 5) that there was a
significant weak to moderate correlation between the AFA dislike subscale
and the MBI DP subscale (r = -.322, p < .01) such that as depersonalization
decreased, dislike towards the person increased. There was a weak
correlation between the AFA fear and the MBI DP subscale (r = -.163, p
<.05) such that as ‘fear of fat’ increased, level of depersonalization
decreased. No significant relationships between the AFA willpower
subscale and the MBI DP subscale (p >.05) or any of the AFA subscales and
the MBI PA and EE subscales (p >.05) were detected.
The Pearson’s correlation between the MBI and the ATOP indicated a
significant weak to moderate negative correlation between the MBI
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depersonalization subscale and the ATOP (r = -.319, p < .01) such that as
level of depersonalization reduced, ATOP attitudes became more positive
(higher scores equal more positive attitudes). There was also a significant
weak positive correlation between the MBI PA, and the ATOP (r = .178,
p>.05) such that as feelings of personal accomplishment increase nurses
attitudes towards patients who are obese become more positive.
The results between the two weight bias measures were contradictory
when correlated with the MBI questionnaire. As such outliers previously left
in were removed and the data re-analyzed but this did not significantly alter
the results (appendix 24).
Thematic analysis
The thematic analysis was conducted on the responses from the
optional opened ended question, ‘what are your views on why nurses might
hold negative attitudes towards patients with obesity?’ This question was
completed by 196 of the 218 participants with responses ranging from 7 to
217 words giving an average of 44.9 words per response. The analysis
revealed six key themes as shown in the thematic map in figure 1 overleaf.
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Wider society
Media
NHS moral discourses
Cultural context
Pragmatics of caring
Lack of resourcesComplicationsIn caring
Acknowledging wider factors Blame
Deservingness
Preventability
Responsibility
Identity
Identity management strategies
De-Identification
Denying impact of attitudes on careStake Inoculation
Weight related Identity
Personal Identity
Nursing Identity
Figure 1.
Thematic map
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The identity theme related to the three identities nurses appeared to
speak from including nursing, personal or weight related identities. Three
themes related to how nurses made sense of their own attitudes, the first
through acknowledging the wider factors that influence obesity and the
second, ‘pragmatics of caring’ theme, related to the nurses experience of the
complexities in caring for someone with obesity. The third was a theme of
‘blame’, particularly relating to beliefs about responsibility, preventing
obesity and the person’s deservingness of healthcare. More broadly, nurses
referred to the narratives held about obesity in the NHS, the media or wider
society; captured in a theme of cultural context. Finally, further analysis
focusing more on latent patterns than on explicitly stated semantic content,
appeared to demonstrate a range of identity management strategies employed
in order to manage the negative attitudes that were expressed.
1) Identity The participants expressed their opinions through three visible
identities; as a nurse, a person, and in relation to their own weight.
a) Nursing identity: The participant’s perception of what it meant to be
a nurse appeared to inform their attitudes towards patients with obesity.
‘I did not become a nurse to judge someone I became a nurse to help them’.
‘As a nurse it is my job to learn their story…’
The participants drew on specific characteristics associated with their
nursing identity such as providing ‘help and support regardless of
appearance’ and of treating all patients ‘the same despite their size.’ They
clearly articulated their view that in their role ‘as a health care professional
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there shouldn’t be negative attitudes’. The nurses’ characterized their
identity as non-judgmental and understanding. However, expressed ideas
about nurses as health promoters with the ‘duty of healthcare staff to gently
highlight or educate the benefits of not being overweight,’ illustrated
instances where judgments were made about the impact of being
overweight.
b) Identity as a person: In addition to drawing on their nursing identities to
inform their attitudes towards patients with obesity, they also drew on their
values as a human being.
‘As humans, we should not judge/discriminate others when we do not know
anything about them’
Here, similar values were cited as those associated with their nursing
identity, for example, treating others ‘equally and with respect.’ However,
these values were explicitly placed in the context of being a human rather
than specifically a nurse, tending to extrapolate out to ‘any people’ rather
than only in the context of their attitudes towards patients:
‘I believe in equal and fair treatment, regardless of race, religion and
certainly appearance i.e. weight.’
Thus of note, both the characteristics associated with the identity as a
nurse and as a person were portrayed positively alongside the associated
attitudes towards obesity.
c) Weight related identity: Nurses identified with their own weight which
impacted on their attitudes towards patients with obesity in different ways.
For example, sometimes more negatively:
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‘I was obese and lost 5.5 stone in 1 year. I get frustrated when people don't
try to lose weight’.
Yet others voicing their own weight struggles having ‘nothing but
empathy’ and thus impacting on their attitudes more positively:
‘It's much easier to understand and be empathetic if you have experienced
it yourself’.
Thus the experience of weight difficulties in itself did not appear to
influence attitudes per se, rather the nurses experience of their own
difficulties did.
2) Acknowledgement of wider factors
Some participants appeared to draw on their knowledge of the
development and maintenance of obesity as more complex and multifaceted
than perhaps the dominant narrative surrounding them might suggest:
‘That some patients may have other more complex reasons for being
obese, other than the assumed self inflicted, lifestyle choice that some
staff may adopt’.
Participants acknowledged a range of factors including ‘medical
conditions’, ‘social circumstances’ and ‘financial difficulties;’ their
acceptance of these alternative explanations appeared protective against
negative attitudes.
‘I do not have a negative attitude towards obese patients as there is
always more to it than people know’
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3) The pragmatics of caring Alternatively, participants often appeared to relate their attitudes
towards patients with obesity to their view of the pragmatic difficulties in
caring for them.
a) Complications of caring: The complexity of caring for a person with
obesity related to both the impact on staff, for example with ‘moving and
handling being more challenging’ as well as ‘turning, washing and wound
dressing’, and also the level of complexity in providing effective care:
‘HCP’s may feel that obese patients, can present a more complex
treatment course than necessary e.g. co-morbidities, heightened risks
or difficult ventilation when in the theatre...’
b) Lack of resources: The lack of a range of resources available to care
adequately for patients with obesity including time, staff, equipment and
funding were often raised:
‘I feel that the need for extra staff in some cases puts strain o nurses
and healthcare professionals and clouds their objectiveness…’
‘Obese patients can add a lot of extra effort onto an already busy
workload’
The complicated nature of caring, the lack of adequate resources to
care and the impact of this on staff were represented through participants
tending to illustrate more negative attitudes within this context.
4) Blame A clear framework of blame permeated the analysis through the
analysis, attributing blame either for the obesity itself or by ‘blaming the
patients for the state of their health’ suggesting that, ‘obesity is a long-term
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condition that is self-inflicted over a period of time’. Three distinct
subthemes, responsibility, preventability and deservingness were each used
in the context of justifying their position of blame.
b) Responsibility: Nurses often attributed blame when they indicated that the
patient with obesity was responsible for their own weight and the associated
health problems.
‘I feel they are not taking responsibility for their own health care such
as people with diabetes shortness of breath or cardiac problems.’
Beliefs about responsibility also extend to ‘abdicated responsibility’
where patients may believe nurses to be responsible for their health rather
than themselves:
‘Some patients do expect us as health care professionals to have all
the answers and solve their problems. They may not always want to do
the hard work themselves.’
c) Preventability: Participants voiced their belief that obesity and its health
consequences were preventable:
‘They may feel that they've made themselves unwell by living an
unhealthy lifestyle and that they could have prevented their illness’
Commonly, the language used indicates that participants could not
only have prevented their health problems if they had adopted a healthier
lifestyle, but that they have actively ‘made themselves unwell’ which may
have then justify taking a position of blame.
d) Deservingness: Beliefs about the extent to which patients with obesity
deserved services were infiltrated through the text, visible through a
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consistent choice of language. For example, ‘using up’ resources, being a
‘waste of resources’ or ‘burdening’ services.
‘Obesity also costs our NHS huge amounts of money each year. Since
nurses are having to campaign and fight for even a 1% pay rise, this
could be seen by many as an unfair spending of money - why spend
millions on treating fat people who hurt themselves when it could be
spent increasing the wages of nurses...’
The beliefs about deservingness often appear to be relational, that is
patients with obesity are less deserving of funding than nurses doing ‘the
hardest job in the world’. Thus deservingness for funding is seen as a direct
competition between groups of patients with obesity and nursing groups.
5) Cultural Context
Participants often directly acknowledged that cultural narratives
influenced their attitudes towards patients with obesity, whether through
moral discourses about the NHS, the media and within wider society.
a) Moral discourse about the NHS: A discourse about the NHS in ‘crisis’
was illustrated throughout the analysis and the discourse itself was directly
acknowledged in relation to obesity:
‘…currently seems to be an acceptable prejudice towards the obese in
the media, where the state of the NHS crisis is blamed on the obese
epidemic’.
At times, narratives about the pressures on the NHS appeared to lead
nurses towards the belief that patients with obesity ‘are slightly resented for
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putting extra pressure on an already stretched workload using up resources
and staff time’.
b) Media: Societal messages about obesity are often delivered through the
media with participants frequently citing ‘a lot of stereotyping by the
media…’
‘…I believe that there are negative messages in the media…who
attributes many health issues with being obese….with the sub text of if
you are not slim/fit you are not trying hard enough…’
Participants indicated that these messages were predominately
negative in relation to identity with common themes around being ‘thin is
beautiful and fat is ugly’ with examples of ‘celebrities who are idolized in
newspapers, magazines etc tend to be slim’. Messages that had
‘conditioned’ them in to believing obesity was ‘wrong’.
c) Wider Society: In addition to the negative messages communicated
through the media, participants were also aware that they were also held in
wider society suggesting that, ‘widespread societal weight bias…affects
most people’. Unsurprisingly these messages were similar to those portrayed
through the media:
‘Thin privilege is a very real and unfortunate thing in our society.’
The participants directly linked the impact of these messages on their
own attitudes towards patients with obesity for example, as they are ‘carried
into the workplace’.
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6) Identity management strategies
Through repeated engagement with the data, another layer of
interpretation emerged that provided an insight into the tolerant and liberal
stance expected of a nurse by acknowledging the negative biases towards
obesity in a context where bias is normalized by cultural discourses. Themes
emerged that appeared to describe strategies used to manage the difference
between the positive identities that nurses had often portrayed alongside the
negative attitudes that they were aware were available to them. Three
separate strategies, stake inoculation, de-identifying, and by justifying
attitudes through denying the impact on care were identified.
a) Stake inoculation: There appeared to be a vested interest in reporting
negative attitudes, but not directly. Often it appeared that negative attitudes
towards patients with obesity where reported in ‘other staff’ rather than the
participants owning the attitudes themselves:
‘Food is an addiction and patients need support with that. However I
feel other staff members do take a more negative approach…’
This, ‘I don’t but others do’ approach was often used as a pre-requisite
to expressing a negative attitude in the form of someone else’s opinion:
‘I personally don't hold any negativity towards obese people, however,
I have heard that some people see obese people as a strain and lazy.’
Participants often then appeared to add their own judgment to this
‘other’ opinion, for example by suggesting that this, ‘of course this is the
wrong way of thinking and highly unprofessional’.
100
b) De-identification: Other ways of managing negative attitudes towards
patients with obesity in relation to their own identity was to directly de-
identify with their nursing identity slightly:
‘We all have our own hang ups, we're only human’.
‘I think it's just human to have certain thoughts go through your mind
and nurses aren't immune to this.’
In de-identifying with their nursing identities the participants actively
appeared to bring forth their identities as people. The pretext of ‘nurses are
humans too’ being that unlike nurses, humans are imperfect and it is perhaps
more acceptable to hold negative attitudes as a human than as a nurse.
c) Denying the impact of attitudes on care: Finally, where participants
acknowledged their own negative attitudes towards patients with obesity it
was often done in the context of being explicit about such attitudes not
impacting on patient care:
‘…these brief thought have never caused me or any colleague I know
to compromise the care of an obese person...’
This perhaps seems to indicate that ‘brief’ negative attitudes towards
patients with obesity are more acceptable as long as they do not impact on
care.
DiscussionThis study aimed to explore weight bias towards patients with obesity
in UK nurses. As there appeared to be no clear pattern in the literature that
explained or predicted this bias, this study explored the relationship between
weight bias and nurses’ qualification status, BMI, self-esteem, stress and
burnout in the context of intergroup relation theories. The analysis of
101
quantitative data failed to identify a simple relationship between a single
factor and weight bias. The qualitative results tentatively suggest that bias
may be understood in terms of a complex hierarchy of interacting social
identities that this discussion will seek to explain.
The findings give a mixed message about the relationship between
obesity and weight bias, with some of the quantitative measures utilized to
help develop a better understanding of this relationship, unable to clarify
this picture. The quantitative analysis indicated that attitudes towards
patients with obesity were reported as neutral on both the AFA and the
ATOP. This is a finding that has been replicated in previous studies (Poon &
Tarrant, 2009) although not consistently (e.g. in Brown, 2006). There were
no significant relationships detected between the AFA and the ATOP with
nurses’ own BMI or qualification status. There was one significant
relationship between the RSE measure of self-esteem and the ‘fear of fat’
subscale on the AFA such that as self-esteem increased, ‘fear of fat’
decreased. There was no relationship between the second two AFA subscale
or the ATOP. The PSS, measure of perceived stress and the AFA ‘dislike’
and ‘fear of fat’ scales suggested that as dislike and fear of fat attitudes
increased, perceived stress decreased. There was no detected relationship
between the third subscale on the AFA or on the ATOP. Finally, there were
contradictions between the AFA and ATOP in relation to the MBI
depersonalization subscale with the AFA ‘dislike’ and ‘fear of fat’ subscales
increasing as the MBI depersonalisation reduced yet on the ATOP weight
102
bias increased as MBI depersonalisation decreased. The significant
relationships that were detected were all of weak to moderate effect.
The suggestion that nurses’ attitudes towards patients with obesity are
neutral is interesting given that there is no dispute in the literature about the
fact that patients with obesity do experience prejudice in healthcare settings
(e.g. Friedman, Ashmore & Applegate, 2008; Merrill & Grassley; 2008;
Puhl & Brownell, 2006). Thus, this anomaly may relate to the complexity of
nursing identity. Nursing has historically struggled with its professional
image (McAllister, Downer & Opresou, 2014) being characterized
differently by the media, politics and within the profession itself (Andrews,
Ferguson, Wilkie, & Simpson, 2009; Santry, 2010). Yet perhaps owing to
the legacy of iconic characters such as Florence Nightingale (McAllister,
Downer & Opresou, 2014), one consistency has been the portrayal of nurses
as self-sacrificing and altruistic (Gordon & Nelson, 2005). With such a
strong historical view on the meaning of nursing still permeating modern
society, nurses may be more vulnerable to social desirability bias in order to
protect themselves from the incongruence weight bias would have with this
ascribed identity. The ramifications for this research are that reported neutral
attitudes do not necessarily indicate that negative attitudes do not exist;
rather that social desirability bias may limit their expression reliably.
However, the idea that the RSE self-esteem scores increased as the
AFA ‘fear of fat’ scores decreased is interesting. Social Identity Theory
(Tajfel & Turner, 1986) suggests that self-esteem is central to prejudice,
originally postulating within the second corollary of its self-esteem
103
hypothesis that ‘threatened self-esteem motivates discrimination’ (Martiny
& Rubin, 2016 p.3). Thus higher self-esteem may reduce the likelihood that
obesity threatens identity, rendering nurses’ comparisons with this perceived
subordinate group unnecessary. Indeed, although limited, previous research
suggests that nurses who feel better themselves in someway (e.g. with
higher body satisfaction; Bagley, 1989, or with lower body image guilt and
shame; Torrey, 2013) are less likely to hold weight bias.
However, the relationship between the AFA ‘fear of fat’ and the RSE
measure of self-esteem was weak. This may relate to the limitations of data
potentially influenced by social desirability bias, but perhaps also to how
self-esteem is constructed within Social Identity Theory (Tajfel & Turner,
1987). In this context, attitudes expressed are to positively distinguish
collective self-image from the alternative group in order to manage social
self-esteem (Rubin & Hewstone, 2004). However, the RSE (Rosenberg,
1965) is a measure of personal self-esteem and may not be sensitive to
testing hypotheses conceptualizing self-esteem socially (Rubin & Hewstone,
2004). There is though a distinct lack of adequate social self-esteem
measures available as many do focus on global, personal self esteem (see
Rubin & Hewstone, 1998) which makes choosing an appropriate measure
difficult.
Moreover, how self-esteem relates to prejudice has long been debated
(Abrams & Hogg, 1988; Brown, 2005; Hogg & Abrams 1990). Since its
inception, their has been limited evidence found for discrimination that is
motivated by the need for self-esteem (see Rubin & Hewstone, 1998) which
104
further confuses the picture as to whether self-esteem relates to weight bias.
More recently, reformulations of this hypothesis may though better capture
its complexity (see Martiny and Rubin, 2016). For example, social norms
play a part in determining the impact of self-esteem in motivating prejudice
(Scheepers, Spears, Manstead & Dooske, 2009), often interwoven with the
individuals personal norms (Hogg & Smith, 2007). The nuanced and
dynamic nature of group norms, subtly fitting with the cultural contexts of
the moment (Hogg & Smith, 2007), indicate that if norms of nurse identity
centre around compassion and altruism; negative attitudes may actually
reduce rather than increase self-esteem as such attitudes represent a
deviation from that particular groups norm.
Overall, the complexity surrounding nursing identity may influence
how openly nurses express their attitudes towards patients with obesity in a
quantitative methodology where they were asked to directly state attitudes
which may force them to confront a conflict in their identity which is
uncomfortable and more easily reconciled through changing the expression
of attitude, rather than changing identity. However, the contradictions
between the AFA and ATOP with elements of the measure of perceived
stress (PSS) and burnout (MBI) are more difficult to explain in the context
of quantitative analysis. However, the qualitative analysis may also help to
provide a tentative interpretation of this complexity.
Thematic analysis
Although the AFA and the ATOP standardized weight bias measures
indicated that nurses attitudes were neutral, the thematic analysis suggests
105
quite a complex picture where negative attitudes were clearly visible but
were also variable both across and within participant responses. A complex
hierarchy of interacting social identities were revealed; with the conflicts
between them being actively managed by nurses in a range of ways. This
framework of understanding and the relationships between themes are
presented in figure 2.
Before elaborating on the diagram presented, it is important to draw
attention to the fact that while the qualitative data provides good evidence
for some of the links produced in figure 2, some links are less strongly
evidenced and drawn more from current theory in order to realize the
potential explanatory power of the diagram. The relationship of each link
and its evidence depicted in the text is illustrated using the width of line.
106
Wider society
Media
NHS moral discourses
Cultural Context
Pragmatics of caring
Lack of resourcesComplicationsIn caring
Acknowledging wider factors Blame
Deservingness
Preventability
Responsibility
Identity
Identity management strategies
De-Identification
Denying impact of attitudes on careStake Inoculation
Weight related Identity
Personal Identity
Nursing Identity
Figure 2.
Theme relationships.
Conceptual frameworks
107
Figure 2 represents how the range of identities expressed may interact with
the wider cultural context around them to inform which one of three
competing frameworks the individual may use to make sense of their
attitudes towards patients with obesity. However, given that these
frameworks were not always associated with positive attitudes, nurses
appear to operationalize a range of identity management strategies in order
to manage the conflict that their attitudes portray between the framework
they choose to understand obesity within and their most salient identity.
Identity
The assumption that people belong to multiple social memberships
(Gergen, 1971) is evidenced within the theme of ‘identity’ where a range of
perspectives relating to nursing identities, identities as people or weight
related identities were apparent. The social context may determine which
identity is most salient at one given time, which in turn is associated with
attitude expression (Hogg & Smith, 2007). Although primarily an automatic
process, which identity is presented can also be used strategically to create a
positive representation of the self (Hogg, 2009), which may explain why
each of the three represented identities were often positively portrayed.
However, there were also multiple components to each identity evidenced
which appeared to shape attitudes in different ways. For example, within the
nursing identity subtheme sometimes nurses portrayed themselves as ‘health
promoting’, which given the health complications associated with obesity
may associate with more negative attitudes than those who portrayed their
nursing identity as non judgmental. Equally, weight related identity relating
predominantly to nurses experience of their own weight difficulties, are not
likely to predict attitudes in and of itself but how nurses make sense of their
own experiences of weight difficulties may do. For example, those viewing
their own successful weight loss as within their control are more likely to
hold negative attitudes than nurses acknowledging their own weight
struggles, who exhibit more empathy. This variability may explain the
quantitative findings where no relationship was detected between BMI and
the two weight bias measures, the AFA and ATOP, as well as the mixed
results produced by previous research in this area (e.g. Garcia, 2012; Poon
& Tarrant, 2009; Torrey, 2013). Thus, the identities presented are complex
and multi-faceted with the salience of each identity influencing attitudes in
different ways.
Attitudes in the context of three conceptual frameworks
There were also three themes that appeared to represent conceptual
frameworks that may be used to understand nurses’ attitudes towards
patients with obesity. Interestingly, despite the identity themes portrayed
depicting mainly positive characteristics, the conceptual frameworks used to
understand obesity that were not wholly positive representing somewhat of
a-conflict.
Research suggests that the causes of obesity are a complex
combination of biopsychosocial and environmental factors, (BPS, 2011).
The ‘acknowledgement of wider factors’ theme captured this complex
understanding of obesity. Those acknowledging the medical, social and
psychological factors relating to obesity tended to demonstrate more
accepting attitudes towards patients with obesity overall which was
congruous with the theme illustrating positively expressed identities.
109
However, the ‘pragmatics of caring’ theme demonstrated the nurses
awareness of the difficulties involved in caring for a patient with obesity for
example, the complexity involved in caring and the lack of adequate
resources required for caring properly. This theme appeared to be more
associated with a more negative outlook on obesity.
The third framework used to conceptualize nurses’ attitudes was one
of blame. Where attitudes appeared to be justified through ideas about
obesity being preventability, the person taking responsibility for their own
health and also their judgment of how deserving the obese person was of
receiving support from NHS services. Perhaps unsurprisingly, these ideas
also appeared to be associated with overtly negative attitudes from nurses
towards patients with obesity.
The framework used to inform nurses understanding of obesity
appears to relate to the types of attitudes expressed, Yet this is not always
congruent with other themes within the analysis, primarily that of positively
presented identity. This suggests that the expression of attitudes is
dependent on more than just the salience and identification of a particular
constructed identity in that it is also influenced by a much wider social
context such as social norms and normalized discourses.
Cultural context
Despite the acknowledgement that attitudes research cannot be
conducted within a socio-cultural vacuum (Taijfel, 1981), the importance of
the wider social context has arguably been traditionally under represented
(e.g. Allport, 1935; Hogg & Vaughan, 2002). Yet the organizational,
institutional and historical cultures that permeate attitudes are paramount
110
(Howarth, 2006). Firstly, the UK is part of western society where obesity is
viewed as a preventable, controllable (Crandall et al, 2001), visible flaw
(Puhl & Brownell, 2003). This view of individualism and accountability,
coupled with the westernized aspiration towards thinness (Budd, Mariotti,
Gradd & Falkenstein, 2009) will likely develop a more blaming culture than
where obesity is seen as a sign of happiness, health and prosperity (Budd,
Mariotti, Gradd & Falkenstein, 2009). Nurses were certainly explicit about
the direct influence of such views communicated culturally on their attitudes
towards the patient with obesity.
Secondly, narratives relating to ‘care and cash crises threatening to
debilitate the wider public sector and economy’ are shared within the NHS
but also within wider society (Warner & O’Sullivan, 2014, p8). However,
there are also culturally available narratives about shared values with the
NHS being seen as the ‘nearest thing this country has to a religion’ (Warner
& O’Sullivan, 2014, p7) suggesting a certain protectiveness and pride in the
NHS. The moral discourses theme recognized the nurses’ acknowledgement
of the difficulties facing the NHS. Their alignment with its plight is perhaps
more likely to draw them towards either attributing blame for obesity or to
one acknowledging the pragmatic difficulties of caring for a person with
obesity within the current climate.
Conflict management strategies
The qualitative analysis suggests that how a given identity is
constructed and its associated salience; alongside the influence of narratives
held within the wider culture help to make sense of the attitudes that nurses
held towards patients with obesity within this study. However, people
111
generally endeavour to create an overall integrated sense of self where
identity and attitudes do not clash (Bannister, 1998) which may account for
why the final theme appeared to illustrate a range of ‘identity management
strategies’ which nurses appeared to use to manage conflict. For example,
nurses often ‘de-identified’ or, played down, one identity over another
(Hogg & Smith, 2015). These are not behaviours that they acknowledged
and described as their own but were observed in the kinds of explanations
they gave and the ‘disclaimers’ they used in presenting their opinions. Those
exhibiting negative attitudes also tended to justify them by reaffirming their
minimal impact on clinical care. Most commonly though, there was a theme
of stake inoculation whereby nurses displaced their own attitudes on to that
of others (‘I don’t but others do’) which appeared to allow them to express
negative attitudes in a way that did not jeopardize their own identity.
Overall, the analysis of quantitative data depicted a confusing picture
that failed to identify a simple relationship between a single factor and
weight bias. However, the qualitative analysis helps to interpret these
findings by suggesting that nurses attitudes may be influenced by a complex
hierarchy of interacting social identities and that when those identities
conflict with their attitudes towards patients with obesity, they may be
employing identity management strategies to aid reconciliation. The
qualitative analysis was more sensitive to this level of complexity due to the
analysis on freely expressed data than the more restrictive nature of the
quantitative data allowed for.
Historically research has suggested that subtle variations in the
wording of questionnaires can create large differences in responses (Marsh,
112
1982) and that contradictions are not uncommon (Kinder & Sears, 1985).
By using both the AFA and the ATOP weight bias measures in order to gain
a range of beliefs about obesity, the variability in responses that
standardized questionnaires usually restrict (Potter & Wetherell, 1987)
became visible but were difficult to interpret in isolation. The qualitative
analysis supports this hypothesis, as variability across themes were clearly
observable and the theme of ‘identity management’ suggested that nurses
may find negative attitudes difficult to own outright, precisely what the
objective measures asked them to do. Thus a more complex
conceptualization was required than the interpretation of the standardized
questionnaire results could provide alone.
Limitations
Previous authors have suggested that survey designs tend to create
social environments of their own and do not allow for naturally occurring
variability due to their restrictive nature (Rogers, Stenner, Gleeson &
Rogers, 1995). They often favour what is consistent over what is real;
problematic in understanding attitudes which are often dynamic, conflicting
and changing (Potter & Wetherell, 1987). Within the quantitative analysis it
is possible that the small effect sizes found may be the result of a by-product
of the large sample size deployed for this research rather than true effects
meaning that these results may be negligible. Secondly, the AFA and the
ATOP measured different constructs which may partly relate to the
difference in results between them. Additionally, the AFA weight bias
measure did not meet parametric assumptions and thus non parametric tests
were used for tests involving this measure, whilst the parametric equivalents
113
were used for the ATOP as part of testing the same hypotheses. The
difference in the ability of each test to detect power may also in part account
for the variability in the two measures within each hypothesis.
The study was situated within the context of intergroup theories of
prejudice, primarily Social Identity Theory (Tajfel & Turner, 1987) given
that the use of theoretical frameworks to understand weight bias has
previously been limited (Zhu, Norman & While, 2011). Other theories can
be used to underpin weight bias research, for example, the emerging themes
in both the ‘pragmatics of caring’ and the ‘moral discourses about the NHS’
could be explained using Realistic Conflict Theory (Stouffer, Suckman,
DeVinney, Star & Williams, 1949) although this does not appear to be used
widely the literature. Attribution Theories of prejudice are more strongly
evidenced (Crandall, 1994, Puhl & Brownell, 2006) and may account for the
theme of blame, but neither theory was able to account for the complexity of
weight bias and its interaction with the social environment in the way that
Social Identity Theory is able to.
Nevertheless, alongside traditional attitudes research, Social Identity
Theory has received its fair share of criticism, with many authors suggesting
it should be better able to consider attitudes in relation to the wider social
environment of group memberships, norms, identities and intergroup
relations (See Prislin & Wood, 2005) as it has previously focused on
attitudes as cognitive representations within the individual and perhaps
neglected the wider social context (Hogg & Smith, 2007). However, since
its origins (e.g. Tajfel, 1972) it has developed in to a comprehensive and
114
integrated theory of self-concept and intergroup behaviour (Hogg & Smith,
2007) and it is within this context that this study presumes.
Conclusion
In conclusion, this study explored the relationship between weight
bias and nurses qualification status, BMI, self-esteem, stress and burnout in
the context of intergroup relation theories such as Social Identity Theory
(Tajfel & Turner, 1987). Although the analysis of quantitative data failed to
identify a simple relationship between a single factor and weight bias, the
qualitative analysis illustrates that a complex hierarchy of conflicting social
identities may influence nurses’ weight bias. The identity management
strategies employed to manage this suggest that ‘owning’ these attitudes
may be difficult, accounting for why they are not visible within the
quantitative analysis. Overall, exploring individual factors in relation to
weight bias may not yield success; the complexity illustrated may partially
explain why the results of previous literature are also contradictory.
Further research should first and foremost be situated within a
theoretical framework of weight bias to aid the further development of
knowledge in the context of previous research. Future studies should
consider using qualitative methodologies to enable the complexity of
attitudes, particularly in populations who might find their attitudes difficult
to ‘own’, to be expressed fully. However, where quantitative survey
methodologies are utilized, implicit rather than explicit measures may
enable the process of automatic versus strategic social identity processes to
be further understood (Hogg & Smith, 2007). The model presented in the
discussion represents a range of evidenced and less well evidenced concepts
115
which provide the basis for further research. Priorities based on this might
consider how manipulating the salience of the various social identities
impact on attitudes as well as exploring the impact of wider cultural
discourses on attitudes. Clinically, working across multiple levels to
challenge weight bias may be helpful. For example, weight bias training
could be integrated across nurse training and supervision. On a broader
level, working within the context of the media may help to shift attitudes
towards obesity more generally given that nurses raised the media as an
influencing factor on their own attitudes within this research. However,
replication studies should be considered prior to deciding how best to
influence weight bias in nurses given that this study represents the first
study to explore weight bias using a mixed methods design. However, what
can be drawn from this research with more certainty is knowing that there is
a place for psychologists to change perceptions of obesity, replication
studies in this area would help to determine how best to do this. Only
through developing a better understanding of these issues may their impact
on clinical care be understood and thus challenged.
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List of appendices
Appendix 1 Power calculations…………………………………...............136Appendix 2 Participant demographic information…………………...137-138Appendix 3 Missing data summary tables…………………………...139-144Appendix 4 Ethical approval documentation………………………...145-146Appendix 5 NHS Research and Development approval………………….147Appendix 6 Advertisement email template……………………………….148Appendix 7 Participant information sheet…………………………...149-150Appendix 8 Participant consent form………………………………….….151Appendix 9 Emotional support information page…………………….…..150Appendix 10 Demographic information questionnaire……………….…..153Appendix 11 Standardized questionnaires…………………………...154-159
135
Appendix 12 A summary critique surrounding attitudes literature….160-161Appendix 13 Choice of qualitative analysis………………………….…..162Appendix 14 Phases of thematic analysis………………………………...163Appendix 15 Researcher reflexivity…………………………………164-165Appendix 16 Yardley’s principles of credibility…………………….166-167Appendix 17 Thematic map examples and discussion………………168-170Appendix 18 Examples data and coding……………………………..173-175Appendix 19 Final coding categories……………………………......176-177Appendix 20 Full data screening analysis…………………………...178-183Appendix 21 Chi Squared analysis- missing data and demographic___________variables……………………………………………….184-193 Appendix 22 Chi Squared analysis- demographic factors & qualification ___________status…………………………………………………..194-195Appendix 23 Normality distribution histograms…………………….196-203Appendix 24 Correlation analysis with AFA & MBI outlier…………….204Appendix 25 Normality tests post transformations………………….205-209Appendix 26 Scatterplots for correlation analyses…………………..210-219
Appendix 1 – Power calculations (G Power 3.1: Faul, Erdfelder, lang, Buchner, 2007)
All power calculations were completed a priori using G* Power 3.1.7 (Faul, Erdfelder, Lang & Buchner, 2007). In order to complete this calculation, effect size was estimated through examination of previous literature that had identified a medium effect size when examining the relationship between weight related bias and other variables in nurses (e.g. Brown, Stride, Psarou, Brewins & Thompson, 2007). As such, in calculating sample size for correlation analysis, a power of 0.8 was assumed, to detect a medium effect (r=0.3), with a 2 tailed
136
hypothesis and an alpha of 0.05 using a point biserial model. This a priori calculation suggested a sample of 82 participants should be obtained. Power calculations were also completed for a multiple regression analysis. Assuming power of 0.8 to detect a translated medium effect (r=0.15), using a 2 tailed hypothesis and an alpha of 0.05 for a linear multiple regression, fixed model, R2, deviation from zero, a sample size of 109 participants was suggested. Finally, power calculations were also completed for an independent samples t test. Assuming power of 0.8 in order to detect a medium effect (d=0.5), using a 2 tailed hypothesis and an alpha of 0.05 using a Means: difference between two independent means (two groups) test, a sample size of 64 participants per group was suggested. In order to have a large enough sample size to complete correlation and regression analysis on each group separately, the largest sample size calculated was be used. As such, a sample size of 109 participants per group was obtained, a total sample size of 218 participants.
Appendix 2- Participant demographic information
Gender Undergrad Qualified Both
MaleFemale
7105
1095
17201
AgeUndergraduat Qualified Both
137
e18-21 49 4 5322-30 30 32 6231-40 22 27 4941-50 9 22 3151-60 2 20 22>60 0 1 1Mean (S.D) Age 26.8 (9.1) 37.66 (10.9) 32.02 (11.36)
EthnicityUndergraduate Qualified Both
White British 84 78 162White Irish 9 9White Other 6 5 11White and Black Caribbean
1 0 1
White and Black African
1 0 1
White and Asian 1 2 3Mixed other 3 0 3Indian 2 2 4Pakistani 2 1 3Asian other 4 2 6Black or black British Caribbean
1 0 1
Black or black British African
4 5 9
Black or black British other
1 0 1
Chinese 1 0 1Other 2 1 3
Appendix 2- Participant demographic information
BMIUndergraduate Qualified Both
<18.5 5 2 718.5-24.9 62 42 10425-29.9 32 40 72>30 13 20 33Mean (S.D) 24.7 (4.5) 26.7 25.63 (4.73)Range 23.10 (16-39.1) 27.6 (17.4-45) 29.8 (16-45.2)
138
Body appearance satisfaction Undergraduate Qualified Both
Dissatisfied 27 20 47Somewhat Dissatisfied
34 37 73
Not dissatisfied or satisfied
14 9 23
Somewhat Satisfied 18 26 44Satisfied 19 12 31Mean 2.71 (1.43) 2.73 (1.33) 2.72 (1.38)
Demographic details (data collected for qualified only)
Do you currently work in the NHS? Response Number of participants Yes 79No 17No response
How long have you worked in the NHS for?
Number of years Numbers of participants 0-10 5411-20 1921-30 1131-40 841-50 0Missing 13Mean (S.D) 11.17
Appendix 3 - Missing data summary tables
Anti fat Attitudes Questionnaire (AFA)AFA item number Number missing
(from total)Percentage missing %
1 0 (218) 0%2 0 (218) 0%3 0 (218) 0%4 0 (218) 0%5 0 (218) 0%6 0 (218) 0%7 0 (218) 0%8 0 (218) 0%
139
9 0 (218) 0%10 0 (218) 0%
Attitudes Towards Obese Persons (ATOP) ATOP item number Number missing
(from total)Percentage missing %
1 1 (218) 0.52 1 (218) 0.53 1 (218) 0.54 1 (218) 0.55 1 (218) 0.56 1 (218) 0.57 6 (218) 2.88 6 (218) 2.89 6 (218) 2.810 6 (218) 2.811 1 (218) 0.512 7 (218) 3.213 8 (218) 3.714 1 (218) 0.515 7 (218) 3.216 8 (218) 3.817 7 (218) 3.218 1 (218) 0.519 7 (218) 3.220 20 (218) 9.2
140
Appendix 3 - Missing data summary tables (continued)
Rosenberg Self Esteem Scale (RSES)RSES item number Number missing
(from total)Percentage missing %
1 20 (218) 9.22 20 (218) 9.23 20 (218) 9.24 20 (218) 9.25 20 (218) 9.26 20 (218) 9.27 20 (218) 9.28 20 (218) 9.29 20 (218) 9.210 20 (218) 9.2
Perceived Stress Scale (PSS)PSS item number Number missing
(from total)Percentage missing %
1 20 (218) 9.22 20 (218) 9.23 20 (218) 9.24 20 (218) 9.25 20 (218) 9.26 20 (218) 9.27 20 (218) 9.28 20 (218) 9.29 20 (218) 9.210 22 (218) 10.1
141
Appendix 3 - Missing data summary tables (continued)
Maslach Burnout Inventory (MBI)MBI item number Number missing
(from total)Percentage missing %
1 22 (218) 10.12 23 (218) 10.63 22 (218) 10.14 22 (218) 10.15 22 (218) 10.16 22 (218) 10.17 22 (218) 10.18 22 (218) 10.19 22 (218) 10.110 22 (218) 10.111 22 (218) 10.112 22 (218) 10.113 22 (218) 10.114 22 (218) 10.115 22 (218) 10.116 22 (218) 10.117 22 (218) 10.118 22 (218) 10.119 22 (218) 10.120 22 (218) 10.121 22 (218) 10.122 39 (218) 17.9
Appendix 3 - Missing data summary tables (continued)
142
Missing data analysis split by professional group (undergraduate or qualified nurse)
Anti Fat Attitudes (AFA) QuestionnaireUndergraduate nurses Qualified nurses
AFA item number
Number missing
(from total)
Percentage missing %
Number missing
(from total)
Percentage missing %
1 0 (112) 0 0 (106) 0 2 0 (112) 0 0 (106) 03 0 (112) 0 0 (106) 04 0 (112) 0 0 (106) 05 0 (112) 0 0 (106) 06 0 (112) 0 0 (106) 07 0 (112) 0 0 (106) 08 0 (112) 0 0 (106) 09 0 (112) 0 0 (106) 010 0 (112) 0 0 (106) 0
Appendix 3 - Missing data summary tables (continued)
143
Attitudes Towards Obese Persons (ATOP)Undergraduate nurses Qualified nurses
Atop item number
Number missing
(from total)
Percentage missing %
Number missing
(from total)
Percentage missing %
1 0 (112) 0 1 (106) 0.92 0 (112) 0 1 (106) 0.93 0 (112) 0 1 (106) 0.94 0 (112) 0 1 (106) 0.95 0 (112) 0 1 (106) 0.96 0 (112) 0 1 (106) 0.97 0 (112) 0 6 (106) 5.78 0 (112) 0 6 (106) 5.79 0 (112) 0 6 (106) 5.710 0 (112) 0 6 (106) 5.711 0 (112) 0 1 (106) 0.912 0 (112) 0 7 (106) 6.613 0( 112) 0 8 (106) 7.514 0 (112) 0 1 (106) 0.915 0 (112) 0 7 (106) 6.616 0 (112) 0 8 (106) 7.517 0 (112) 0 7 (106) 6.618 0 (112) 0 1 (106) 0.919 0 (112) 0 7 (106) 6.620 0 (112) 0 20 (206) 18.9
Rosenberg self esteem Scale (RSES)
Undergraduate nurses Qualified nursesRSES item
number
Number missing
(from total)
Percentage missing
%
Number missing (from
total)
Percentage missing %
1 0 (112) 0 20 (106) 18.92 0 (112) 0 20 (106) 18.93 0 (112) 0 20 (106) 18.94 0 (112) 0 20 (106) 18.95 0 (112) 0 20 (106) 18.96 0 (112) 0 20 (106) 18.97 0 (112) 0 20 (106) 18.98 0 (112) 0 20 (106) 18.99 0 (112) 0 20 (106) 18.910 0 (112) 0 20 (106) 18.9
Appendix 3 - Missing data summary tables (continued)
144
Perceived Stress Scale (PSS) Undergraduate nurses Qualified nurses
PSS item number
Number missing
(from total)
Percentage missing %
Number missing
(from total)
Percentage missing %
1 0 (112) 0 20 (106) 18.92 0 (112) 0 20 (106) 18.93 0 (112) 0 20 (106) 18.94 0 (112) 0 20 (106) 18.95 0 (112) 0 20 (106) 18.96 0 (112) 0 20 (106) 18.97 0 (112) 0 20 (106) 18.98 0 (112) 0 20 (106) 18.99 0 (112) 0 20 (106) 18.910 0 (112) 0 22 (106) 20.8
Maslach Burnout Inventory (MBI)
Undergraduate nurses Qualified nursesMBI item number
Number missing (from
total)
Percentage missing %
Number missing
(from total)
Percentage missing %
1 0 (112) 0 22 (106) 20.82 0 (112) 0 23 (106) 21.73 0 (112) 0 22 (106) 20.84 0 (112) 0 22 (106) 20.85 0 (112) 0 22 (106) 20.86 0 (112) 0 22 (106) 20.87 0 (112) 0 22 (106) 20.88 0 (112) 0 22 (106) 20.89 0 (112) 0 22 (106) 20.810 0 (112) 0 22 (106) 20.811 0 (112) 0 22 (106) 20.812 0 (112) 0 22 (106) 20.813 0 (112) 0 22 (106) 20.814 0 (112) 0 22 (106) 20.815 0 (112) 0 22 (106) 20.816 0 (112) 0 22 (106) 20.817 0 (112) 0 22 (106) 20.818 0 (112) 0 22 (106) 20.819 0 (112) 0 22 (106) 20.820 0 (112) 0 22 (106) 20.821 0 (112) 0 22 (106) 20.822 0 (112) 0 39 (106) 36.8
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Appendix 4 – Ethical approval documentationPSYCHD CLINICAL PSYCHOLOGY
Review of MRP Proposal for RGC
Trainee Name/URN: 6338210 Date: 22 July 2015
Comments
RGC Decision
Please tick one:
Proceed Proceed with considerations Resubmit proposal
Comments from the committee:
It might be the case that you recruit more students than qualified nurses so you might have an issue with applicability and, if the levels of stress and burnout are low, then this might limit the size of correlation with attitudes to obesity. You might need to take this into consideration in your write up should you have such difficulties.
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Appendix 4 – Ethical approval documentation (continued)
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Appendix 5 – NHS Research and Development approval
Note: This letter has been cropped to exclude the names and addresses of the organization it represents.
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Appendix 6 – Advertising email template
As a qualified or undergraduate nurse can you help us understand nurses attitudes towards obesity?
Your chance to be entered in to a prize draw to win a £20 Amazon Voucher!
Please click on the link below to take part in a short survey.
www.link provided here
or contact the researcher at [email protected] for the link or more information
Your views matter, we want to hear from you.Thank you!
This study has received a favourable opinion from the University of Surrey Ethics Committee
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Appendix 7 – Participant information sheetStudy title: Exploring attitudes and beliefs about obesity in healthcare
professionals
Information sheet
My name is Elisabeth Goad, a Trainee Clinical Psychologist studying at the University of Surrey. I would like you to take part in a research project details of which are given below.
The current literature suggests that there is obesity related bias in the general population but also in healthcare staff as well. Such bias may result in negative consequences such as an increase in unhealthy eating behaviours and reduced engagement with healthcare. This study examines the beliefs of healthcare staff about obesity and considers factors that might influence these attitudes.
Participation is completely voluntary and if you do decide to take part you have the right to withdraw your participation at any stage and your data until data is analysed (31st July 2016) without giving reason.
If you decide to take part in the study after reading this information sheet you can proceed to a consent form before continuing on to complete a series of short questionnaires which should take no longer than 30 minutes to complete. The unique participant identifier on the consent form will enable us link your consent form to your questionnaire if required without using your name and thus maintaining anonymity. If you wish to withdraw your data from the study at a later date, we will need your participant identifier to do so. All the information you provide will be kept confidentially and made anonymous prior to being entered into a database for analysis. Anonymised data will be kept by the University for 10 years. Group data may be published in an academic journal, but no details which could be used to identify individual participants will be published. There is one optional open ended question within the questionnaire, the anonymised responses of which will be seen by the researcher, two research supervisors and also examiners assessing the research.
Your participation will help us understand how best nurses can be supported in working with patients with obesity. Completing the questionnaires might evoke difficult feelings so a list of contact details for organisations that you can talk to is included at the end of the questionnaire pack.
All participants are eligible for entry in to a prize draw to win one of four £20 Amazon vouchers as a small token of our appreciation. The prize draw will take place at the end of data collection on 30th May 2016 and the winners will be notified by email.
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Thank you for taking the time to read this information sheet. If you would like more information please contact us. For any complaints or concerns please contact the principle researcher in the first instance or another member of the research team. Study Contact details Elisabeth Goad (Principle researcher)Trainee Clinical Psychologist PsychD Doctoral Training Programme University of Surrey [email protected]
Dr Sue Jackson Teaching Fellow (Research & Development)PsychD Doctorate Training ProgrammeSchool of PsychologyUniversity of [email protected]
Appendix 8 – Participant consent form
Dr Kate Gleeson (supervisor)Research Director PsychD Doctoral Training Programme School of PsychologyUniversity of Surrey [email protected]
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Study title: Exploring attitudes and beliefs about obesity in healthcare professionals (in training and post-qualified)
I have read and understood the information sheet provided (Version 1, 08.09.15). I have been given a full explanation by the researchers of the nature, purpose and duration of the study and what I will be expected to do.
I have been advised about any disadvantages of taking part in the study
I have been given time to consider taking part in this research
I agree for my anonymised data to be used for this study and any future research that will have received all relevant legal, professional and ethical approvals.
I understand that all research data will be held for at least 10 years in accordance with University policy and that my personal data is held and processed in the strictest confidence, and in accordance with the UK Data Protection Act (1998).
I understand that the group data may be published in an academic journal, but the information I provide will be kept confidential and made anonymous. I understand open ended question responses will be seen by the researcher, and anonymised versions seen by the research supervisors and the examiners assessing the research.
I understand that I can withdraw my participation from the study at any time without needing to justify my decision and without my legal rights being affected.
I understand that I can withdraw my data from the study until July 31 st 2016 when data analysis has been completed.
I have had the opportunity to ask questions about the study and all questions have been answered to my satisfaction.
I agree to provide my email address for receipt of a results summary
Signed:_________________________ (participant)
Date:___________________________
To generate your unique participant number, please provide the following information:
First 3 letters of your mother’s maiden name: ___ ___ ___First 2 digits of your date of birth: ___ ___My email address for the results summary is:……………………………
Appendix 9 – Emotional support page
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Helpline numbersIf, after completing this questionnaire, you need to talk to someone confidentially about how you are feeling, information about some support services and organisations is provided below. Careline is a confidential national telephone counselling service. ‘Our highly trained counsellors are experienced in supporting you through issues that include living with critical illness, emotional heartbreak and sexuality.’Tel: 0845 122 8622 Monday to Friday 10am - 1pm & 7pm to 10pm Website www.carelineuk.org NHS Direct provide information and advice about health, illness and health services, to enable patients to make decisions about their healthcare and that of their families. Helpline (24 hour): 0845 4647. Calls charged at local rate. Website www.nhsdirect.nhs.uk Samaritans provide confidential emotional support for people who are experiencing feelings of distress or despair.’ We are here for you if you're worried about something, feel upset or confused, or just want to talk to someone.’Helpline (24 hour): 08457 90 90 90. Calls charged at local rate. Website: www.samaritans.org SANE provides practical information, crisis care and emotional support for anybody experiencing mental health problems and their families and carers. This could include anxiety or depression, distress following treatment, concern over side-effects of drugs. SANEline: 08457 678 000 open from1pm – 11pm each day. Calls charged at local rates. Website: www.sane.org.uk
Appendix 10- Demographic information questionnaire
Male ___ Female ___
Age: ____ years
Are you currently working for the NHS? Yes ___ No ___
If yes, what do you do? _______________________________________________
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If yes, are you full-time ___ part-time ___ or other (e.g. maternity leave)? ___
How many years have you worked in the NHS for?____ What band is your job role? _____
If a student, what qualifications are you studying for? ________________________
If a student, which institution to you study at?_____________________________ How many hours per week do you spend in direct contact with patients?_________
What is your height? _________
What is your weight? _________
Appendix 11 – Standardized questionnaires
Anti Fat Attitudes Questionnaire4 (AFA) Crandall, 1994) For each item below, please circle the number that best represents your answer to each statement:1. I really don’t like fat people much
Very strongly 0 1 2 3 4 5 6 7 8 9 Very strongly
4 This is the Anti Fat Attitudes Questionnaire, given with kind permission of the author Christian Crandall. Published by the American Psychological Association. Copyright 1994 by the American Psychological Association, Inc. Permission given only for the use of this questionnaire in this research.
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disagree agree
2. I don’t have many friends that are fatVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
3. I tend to think that people who are overweight are a little untrustworthy
Very strongly disagree
0 1 2 3 4 5 6 7 8 9 Very strongly agree
4. Although some fat people are surely smart, in general, I think they tend not to be quite as bright as normal weight people
Very strongly disagree
0 1 2 3 4 5 6 7 8 9 Very strongly agree
5. I have a hard time taking fat people too seriouslyVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
6. Fat people make me somewhat uncomfortableVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
7. If I were an employer looking to hire, I might avoid hiring a fat person
Very strongly disagree
0 1 2 3 4 5 6 7 8 9 Very strongly agree
8. I feel disgusted with myself when I gain weightVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
9. One of the worst things that could happen to me would be if I gained 25 pounds
Very strongly disagree
0 1 2 3 4 5 6 7 8 9 Very strongly agree
10. I worry about becoming fatVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
11. People who weigh too much could lose at least some part of their weight through a little exercise
Very strongly disagree
0 1 2 3 4 5 6 7 8 9 Very strongly agree
12. Some people are fat because they have no willpowerVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
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13. Fat people tend to be fat pretty much through their own faultVery strongly
disagree0 1 2 3 4 5 6 7 8 9 Very strongly
agree
Appendix 11 – Standardized questionnaires (continued)
Attitudes Towards Obese Persons Scale (ATOP)5 (Allison, Basile & Yuker, 1991)Please mark each statement below in the left margin, according to how much you agree or disagree with it. Please do not leave any blank. Use the numbers on the following scale to indicate your response.
5 This is the Attitudes To Obese Persons Scale, author Dr D.B Allison, taken from Allison, D.B., Basile, V.C. & Harold, Y.E. (1991). The measurement of attitudes toward and beliefs about obese persons. International Journal of Eating Disorders, 10, 5, (599-607). Published by John Wiley & Sons. © 1991 by John Wiley & Sons, Inc. Permission kindly given to use the ATOP for this research only.
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Be sure to place a minus or plus sign ( - or +) beside the number that you choose to show whether you agree or disagree.
-3 -2 -1 +1 +2 +3
I strongly disagree
I moderately
disagree
I slightly disagree
I slightly agree
I moderately
agree
I strongly
agree
1. Obese people are as happy as non obese people.2. Most obese people feel that they are not as good as other people.3. Most obese people are more self-conscious than other people.4. Obese workers cannot be as successful as other workers.5. Most non obese people would not want to marry anyone who is obese.6. Severely obese people are usually untidy.7. Obese people are usually sociable.8. Most obese people are not dissatisfied with themselves.9. Obese people are just as self-confident as other people.10. Most people feel uncomfortable when they associate with obese people.11. Obese people are often less aggressive than non obese people.12. Most obese people have different personalities than non obese people.13. Very few obese people are ashamed of their weight.14. Most obese people resent normal weight people.15. Obese people are more emotional than non obese people.16. Obese people should not expect to lead normal lives.17. Obese people are just as healthy as non obese people.18. Obese people are just as sexually attractive as non obese people.19. Obese people tend to have family problems.20. One of the worst things that could happen to a person would be for him
to become obese.
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Appendix 11 – Standardized questionnaires (continued)
Rosenberg Self Esteem Scale (RSES)6 (Rosenberg, 1965)
The scale is a ten item Likert scale with items answered on a four point scale - from strongly agree to strongly disagree. Instructions: 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.
E1 On the whole, I am satisfied with myself. SA A D
SD
E2 At times, I think I am no good at all. SA A D
SD
E3 I feel that I have a number of good qualities. SA A D
SD
E4 I am able to do things as well as most other people. SA A D
SD
E5 I feel I do not have much to be proud of. SA A D
SD
E6 I certainly feel useless at times. SA A D
SD
E7 I feel that I’m a person of worth, at least on an equal plane with others.
SA A D
SD
E8 I wish I could have more respect for myself. SA A D
SD
E9 All in all, I am inclined to feel that I am a failure. SA A D
SD
E10 I take a positive attitude toward myself. SA A D
SD
Appendix 11 – Standardized questionnaires (continued)
Perceived Stress Scale (PSS)7 (Cohen, Kamarck & Mermelstein, 1983)
6 This is the Rosenberg Self Esteem Scale taken from the Measures in Health Psychology Portfolio, permission for The University of Surrey to use for the purpose of this research. With thanks to the author, M Rosenberg. 7 This is the Perceived Stress Scale taken from Measures in Health Psychology Portfolio, permission for The University of Surrey to use for the purpose of this research. With thanks
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The questions in this scale ask you about your feelings and thoughts during the last month. In each case, you will be asked to indicate by circling how often you felt or thought a certain way. Name ____________________________________________________________ Date _________ Age ________ Gender (Circle): M F Other_____________0 = Never 1 = Almost Never 2 = Sometimes 3 = Fairly Often 4 = Very Often
1. In the last month, how often have you been upset because of something that happened unexpectedly?
2. In the last month, how often have you felt that you were unableto control the important things in your life?
3. In the last month, how often have you felt nervous and “stressed”? 4. In the last month, how often have you felt confident about your ability to handle
your personal problems? 5. In the last month, how often have you felt that things were going your way?6. In the last month, how often have you found that you could not cope
with all the things that you had to do?7. In the last month, how often have you been able to control irritations in your life?8. In the last month, how often have you felt that you were on top of things? 9. In the last month, how often have you been angered because of things that were
outside of your control? 10. In the last month, how often have you felt difficulties were piling up so high that
you could not overcome them?
Appendix 11 – Standardized questionnaires (continued)
Maslach Burnout Inventory (MBI)8 (Maslach & Jackson, 1981)Health Survey Form9
The purpose of this survey is to assess how staff members view their job and their reactions to their work.Instructions: On the following pages are 16 statements of job-related feelings. Please read each statement carefully and decide if you ever feel this way about your job.
to the author Sheldon Cohen.8 MBI-Human Services Survey: Copyright ©1981 Christina Maslach & Susan E. Jackson. Published by Mind Garden. Permission kindly given for the use of the MBI-Human Services Survey only. Copyright did not extend to include the entire questionnaire within the appendices.
9
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If you have never had this feeling, select the button under the Never column. If you have had this feeling, indicate how often you feel it by selecting the phrase that best describes how frequently you feel that way. The phrases describing the frequency are:How Often:-Never -A few times a year or less -Once a month or less -A few times a month -Once a week -A few times a week -Every day
Example questions 1. I feel emotionally drained from my work.2. In my opinion, I am good at my job.3. I doubt the significance of my work.
Appendix 12 – A summary critique surrounding attitudes literature
The ‘attitudes’ literature has traditionally been situated within experimental or ‘traditional’ social psychology and has been a subject of interest since the discipline itself began (Rogers, 2003). However, 21st
century social psychology is a divided discipline, often seen with two opposing sides, experimental or traditional social psychology and critical social psychology (Rogers, 2003). Experimental social psychology has primarily taken a positivist approach to attitudes, assuming a cause and effect model (Rogers, Stenner, Gleeson & Rogers, 1995) typical of experimental methodologies. Yet a ‘cause and effect’ model of attitudes has not proven fruitful (discussed below) and critical approaches to attitudes research have heavily condemned the survey and experimental methodologies typically used in line with this
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cause and effect model of thinking. For example, discourse analysts suggest that experimental designs control variables so much that they lose sight of what is real, or would be considered in discourse terms as normal variability in the construction of language rather than a problem to be controlled (Potter & Wetherall, 1987). Equally survey designs also seek to reduce natural variability, seeing it as problematic and indeed produce responses in line with the designers own predetermined conceptualisation rather than a representation of the participant’s social world (Harre, 1979). A knowledge of these critiques are important, given that the majority of contemporary knowledge about attitudes has been conducted within experimental research methods. In addition to a heavy critique of the methodologies employed by experimental social psychologists, another considerable criticism has been locating attitudes historically within the mind of the individual (Hogg & Smith, 2007). This widely held view of attitudes is not extinct; it is still widely accepted that attitudes are ‘a psychological tendency that are expressed by evaluating a particular entity’ (Eagly & Chaiken, 1993, p.1). Yet given attitudes are studied within ‘social’ psychology, the absence of the ‘social’ has not gone unnoticed. Traditional social psychologists themselves have attempted to redress the balance, suggesting that the social context of attitudes have not been denied, but have not perhaps been the primary focus (Prislin & Christensen, 2005). Many theories have been redeveloped to draw back in the social nature of attitudes, for example Social Identity Theory (Tajfel & Turner, 1986; see Hogg & Smith, 2007) but critical social psychologists suggest that the concept of an ‘attitude’ itself cannot incorporate the ‘social’ in an adequate way (Howarth, 2006). One example of this, social representations theory (Farr & Moscovivi, 1984) focuses primarily on the dynamic and interactive relationship between social practices and identity (Howarth, Foster & Dorrer, 2004) For example, Puddifoot, (1997) suggests that the environment is not something that is responded to via an individuals ‘attitudes,’ rather people actually co-produce the realities that constitute that environment. As such, social representations are a far more encompassing concept than the attitude itself could ever be. Indeed discourse analysts also argue against the notion of the “individual” attitude. Potter & Wetherall (1987) highlight the difficulty traditional social psychology has had in evidencing the link between attitudes and behaviour. The social psychology crisis of the 70’s drew attention to the fact that there was actually weak evidence for the link between attitudes and their impact on behaviour, whereby the development of a large range of modifiers has enabled significant flexibility in responses to be explained (Potter & Wetherell, 1987), the argument remains that if so many modifying factors are needed to explain the ‘attitudes’ relationship to behaviour then it may no longer be helpful to preserve the notion of an underlying attitude at all (Potter & Wetherell, 1987). Yet despite the critiques that now surround attitudes research, the majority of research is still experimental and based on the concept of the attitude and much of our current understandings in to attitudes is based on this although this of course needs to be understood within the social context in which it resides. And attitude is a term that clearly has a place in the social world and is used and understand as part of everyday language.
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However, despite, the longevity of this dominant field of research in to attitudes, in relation to weight bias it remains fragmented and disjointed. Drawing together the research as it currently stands, and using a survey methodology within the current study in order to do this, made it possible to relate to existing research but to do so critically.
Appendix 13 - Choice of qualitative analysis
A thematic analysis was chosen as the analysis of choice for this research due the considerable advantage of its flexibility. It can be used within both constructionist and essentialist paradigms (Braun & Clarke, 2006), is compatible to use alongside positivist paradigms (Hayes, 2000), such as in the quantitative aspect of this research, and can be theory lead or data driven (Braun & Clarke, 2006). Its flexibility also allows one to identify themes on a semantic and/or an interpretive level and enables analysis of a range of data types. Finally, in recognition of my novice status as a qualitative researcher, it is an accessible form of analysis that does not necessarily require the detailed theoretical knowledge of its approach making it suitable for those early in qualitative research careers (Braun & Clarke, 2006). Content analysis
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The initial plan for data analysis of the open-ended responses in the free text box was to use content analysis. As there was only one optional opened ended question per participant, a content analysis was initially deemed sufficient to support the interpretation of the quantitative data collected, and would have enabled further analysis using descriptive and potentially inferential statistics. However, during the early stage of analysis which involved familiarization with the data, the depth, richness and subtly of the data became apparent, thus making a reductionist approach inappropriate to capture the experience of the participants well enough. My reflections on changing from content analysis to thematic analysis can be located in appendix 15. Grounded theory A grounded theory analysis would have required an opportunity to engage in theoretically guided sampling to build theory, and the use of constant comparison in the analysis until saturation is reached. This was not an option given the survey design, and the limited focus of the open-ended response material. Additionally, would typically be conducted on unstructured interviews of participant observation data (Hayes, 2000) and is used to develop new models of thinking. Its iterative process makes it time consuming and given the time constraints of this research project it was not deemed possible to complete a grounded theory analysis thoroughly enough within the available time.Interpretative Phenomenological Analysis (IPA)IPA was not selected due to the large number of participant responses analyzed with a view of exploring themes across participants. IPA intends to infiltrate deeply in the world of each participant in great detail to enable a complete understanding of the phenomenon in question (Hayes, 2000). Thus given the type of data collected, penetrating the world of each participant deeply enough for this analysis to be suitable was not possible.
Appendix 14 – Phases of the thematic analysis
Phases of a thematic analysis (Braun & Clarke, 2006)
Description of how each phase was operationalized for this study
1) Familiarization with the data
Data was removed from each participants survey and collated in one document, double spaced and line numbered by sentence where possible, before reading and re-reading the whole data set from the beginning.
2) Generating codes Initial codes or protothemes were written alongside each sentence giving equal attention to each extract.
3) Searching for themes Themes were developed by cutting out each
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separate code and organizing them to ‘theme piles’ which were then represented in visual mind maps.
4) Reviewing the themes Step 3 was fine tuned and repeated alongside a second researcher removing themes with little data to support them, condensing overlapping themes or sub-themes that did not add to the research questions, and expanding themes with sub-themes that were relevant to the research questions, until the majority of data was accounted for and there was agreement between researchers about thematic categories.
5) Defining and naming the themes
Step 4 and 5 were repeated with the researchers reviewing and amending themes until definitions were distinct.
6) Producing the report The thematic analysis was reported as part of the mixed methods design of this study.
Appendix 15 – Researcher reflexivity
Reflective conversations were undertaken within the supervisory relationship and documented within my supervision notes in order to explore how my own position, attitudes and assumptions have influenced the design, data collection and analysis in this study. Three particularly important reflections are summarized below in order to provide examples of these conversations to aid the transparency of the research process. 1) The context of the NHS Early supervision conversations lead to debate as to whether my recruitment strategy should target ‘NHS’ nurses or whether I should recruit for UK nurses generally. This highlighted to me immediately that I had specific assumptions about NHS nurses that for me, made them ‘different’ to nurses within private or third sector services. On reflection, these assumptions were based on my own knowledge of the discourses that surround the current NHS. Discourses that suggest it is a source of national
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pride (I recall watching the opening ceremony of the London 2012 Olympics with my own pride) but also discourses expressing great threat, of underfunding, overworked staff and the associated uncompromising positions frontline staff may be put in that compromise care. Nurses are often at the forefront of such narratives with long working hours, patient contact time and the amount of nursing staff needed to care for patients effectively. I recognized that these narratives were all ones that I, to one degree or another, had been influenced by as a member of British society, as a trainee clinical psychologist, and as a person. I found myself in a position where, although not a nurse, I do empathize with their plight. Yet equally, I experience my own growing concern about the impact of such organizational pressures on patient care, for whom advocacy is a role I hold dear within my own professional context. As such, I have needed to hold awareness of and be transparent about the fact that I am also situated within the same cultural context even though my role might be different. I have needed to be aware of this possible bias in both interpreting the data by assuming similarity between the participants and myself but also in assuming difference. The input of two additional researchers both of whom have accessed the data and one of whom who has provided a second perspective allowing for debate and critique about the thematic development has enabled me to be aware of and manage my own position within the research as well as possible. Additionally, these reflections influenced my recruitment process as I made the decision to include all UK nurses, rather than just NHS ones to ensure my own bias about what it might mean to be an NHS nurse did not bias the results through exclusion of those working in other organizations. Finally, acknowledging my own assumptions in this way meant that when initially familiarizing myself with the data, cross checking responses with whether the individual did indeed work within the NHS context before making assumptions about what statements such as being ‘overworked’ might mean was an important part of interpretation.
2) The change from content to thematic analysis My inclusion of one open ended question with an unlimited character free text box was to enable the collection of data that was less constrained than that collected by the likert scale survey design characteristic of the quantitative element of this study. My choice of content analysis reflected my belief that the exploration of themes identified through these means would support the interpretation of the quantitative data with the frequency of themes being synonymous with their importance. However, my own journey within the context of this research has lead me to move from a research position that prioritizes quantitative, objective, measurable and reliable data to one that realizes that real life information can not and should not always be reduced to numbers. To do so by way of the gross categorization typical of content analysis would be to loose the subtly, the complexity and richness of language as well as the potential, where necessary, to understand its function. My realization of this materialized from familiarizing myself with the data and recognizing the complexity of the language, breadth and detailed information provided by participants. Discussing this with my supervisors and challenging my assumptions about
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what it means to ‘know’ something (discussed below) lead me to switch to using a more flexible thematic analysis.3) My own research orientation As I have insinuated above, my own research orientation has shifted not only during, but also because of, my commitment to immersion with this research. I have certainly had to acknowledge my own personal preference for phenomena to be reduced in complexity to a level that I can make sense of it, thus perhaps my own preference for quantitative research approaches. My research in to the critical social psychology perspective has opened my eyes to what it really means to ‘know’ something and has raised questions to me in this regard that my original position has struggled to answer. In holding in mind critical approaches to my understanding of attitudes within this research I have learned to embrace the uncertainty that not having one concrete answer inevitably brings. This development in my position as a researcher has shifted in part through my engagement with my own research data (as described above) but it also comes from my clinical practice. Working with clients over the last few years has lead me to appreciate more post structural forms of therapy (such as narrative approaches) as I begin to understand that as a clinician, the expert position often taken (although not always acknowledged) within modernist therapies, can limit us and our clients in accessing different types of knowledge and actively co-constructing knowledge, in a way that may not be helpful. These developments in my own work did influence the decision to move from a content analysis to a thematic analysis and are likely to influence the type of research methodologies I may indeed use within attitudes research in the future. In the context of this research, these reflections allowed me the flexibility in my own mind to consider something ‘bigger’ than an attitude. It allowed me to engage with critical approaches to attitudes wholly and genuinely in way that I may not have been able to do so before. As such, I have been able to integrate the perspectives of traditional and critical social psychology in to my work, an important stepping-stone in moving forward within a field that has typically been dichotomous.
Appendix 16 – Yardley’s principles of credibility
Establishing guidelines to assess the quality of qualitative research has notably been more difficult than in the traditions of quantitative research (Yardley, 2000). However, there is still a need to show that qualitative research is of good quality and credibility and thus in the context of this research, Yardley’s (2000) four characteristics of good qualitative research were drawn upon to illustrate this as discussed below.
1) Sensitivity to context This research explored weight bias in nurses and as such prior to the study commencing immersion with prior research relevant to this field was paramount. In order to fully understand the context in which previous literature on weight bias in nurses had been developed a range of research areas were drawn upon. This was largely due to the many fields that have
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influenced the development of the weight bias literature. These included broadly reviewing ‘attitudes literature’ generally along with the associated critique, the literature on prejudice and discrimination, as well as the literature exploring weight bias exhibited to and by different populations. Exploring the context in this way also lead to the exploration of a range of different methodologies employed to ‘measure’ attitudes and a range of underpinning theories used to understand weight bias but also attitudes more generally. Contextualizing the current research project within wider research and theory was important but given the predominantly inductive approach undertaken here, staying sensitive to the data in order to allow data driven themes to emerge was also necessary and achieved through supervision. A summary of attitudes research and its wider critique can be found in appendix 12. Additionally, the socio-cultural context of the current study was also considered. Although the study recruited all UK nurses, thus incorporating those in NHS, private and third sectors, the majority of participants were nurses working within the context of the NHS. The NHS is a often a forum within there are many competing viewpoints and discourses surrounding it all fighting for ascendency which are likely to influence the participants of this study. Although I am not a nurse, I am employed by the NHS and thus my awareness of the influences that has on my interpretation of the data was considered. My reflections on these contextual components can be found in appendix 15.
2) Commitment and rigor Commitment to process was adhered to through the immersion of the researcher within the data. Data was read and re-read regularly and over a period of several months. Data was referred back to regularly throughout the analysis and theme development. Researcher competence in the chosen analysis was developed through supervision, post-doctoral teaching, analysis of prior research using thematic analysis and reflective practice. Given the large participant sample size, saturation within the data was easily reached.
3) Transparency and coherence Transparency about the research process was achieved through the use of regular supervision and open conversations amongst researchers. Appendices 17, 18, & 19 document the process of theme development alongside reflections of how the researchers own position may impact on interpretation. Examples of each theme are provided within the results section to aid transparency. The fit between the qualitative method chosen (thematic analysis) and its function within the wider research are coherent as it enabled a richer perspective of the participants than the quantitative analysis could illustrate alone.
4) Impact and importance The importance of this research is addressed in the introduction and the discussion sections. Primarily, the importance of understanding weight related bias lies within the clinical and psychological implications it may have for the person who experiences that bias. Given the fragmented literature within this field, this is an important part of not only understanding weight bias but also changing the discourses associated with it in western cultures that are not helpful to the person concerned.
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Appendix 17 – Thematic map examples and discussion
Initial thematic map
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Appendix 17 – Thematic map examples and discussion (continued)
Developed thematic map
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Appendix 17 – Thematic map examples and discussion (continued)
Final thematic map
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Appendix 17 – Thematic map examples and discussion (continued)
Key changes during the development of the thematic maps discussion
Initial thematic map Initially every code that appeared in the text more than once was included in this map to ensure no potential themes were eliminated too quickly. There were some themes that appeared to overlap (for example the ‘NHS context’ theme within the pragmatics of caring theme and the ‘moral discourses’ in the culture theme). However, these were left separate at this stage until further evidence for each subtheme could be examined and reworked if appropriate. Themes were developed largely semantically but themes did emerge on an interpretative level as well. These appeared strongly evidenced within the text, and thus were also included in the analysis.
Developed thematic map This map was developed through re-reading the data and matching each code with each theme and sub theme. Where there was not sufficient evidence to support a theme or sub theme, it was removed. On re-reading the data and matching data with themes it was noted between researchers that there were several subthemes within the map that were well evidenced but did not fit well within their current category. Through drawing these out of the map, these sub themes appeared to serve a common purpose, that of ‘protecting’ the nurses identity in some way. For example, de-identifying with their nursing identity and aligning with their identity as a person when they voiced negative attitudes, distancing themselves from the obese patient, commenting on attitudes within others but not themselves or denying their negative attitudes impacted on the level of care the person received. As such, these were re grouped in to a theme of ‘identity management’.
Final thematic map This map was the final version and a product of comparing definitions between themes and subthemes to look for distinctiveness. At this stage, several subthemes were integrated either where by definition they were too similar or within the data they were used frequently within the context of each other (for example responsibility and choice/control). In addition to this, subthemes were also integrated depending on whether they added anything to the theme in the context of the overall research. For example, knowing that nurses who acknowledge a wide range of factors in their appraisal of what it means to be obese appear to hold more positive attitudes seemed equally as useful as differentiating between what each of those factors might be. The terms of themes were also examined in the context of the data that supported them and where needed, themes were re-defined to be more inclusive. For example, ‘culture’ was renamed ‘cultural context’ and attitudes
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seen in others became stake inoculation to highlight the idea that nurses appeared to have a stake in these attitudes but could not own them themselves. Some themes were also renamed to be more specific; for example, identity management became identity management strategies.
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Appendix 18- Example data and coding
174
Appendix 18- Example data and coding
175
Appendix 18- Example data and coding
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Appendix 19– Final coding categories
Theme Sub theme Coding categories included
Identity
Nursing identity Nurses non-judgmental, understanding, equality, compassionate, listening & to educate
Personal identity As with nursing identity but in the context of ‘being a human’
Weight related identity
Positive attitudes -increases empathy, compassion and understanding.
Negative attitudes- increases frustration if have experienced own successful weight loss.
Acknowledgement of wider factors
Social factors, education, finance, medical conditions, adverse experiences, inequality
Pragmatics of caring
Complications in caring
Risk of injury to HCP, difficulty in manual handling and mobilizing, increased and more complex interventions, difficulty with personal care, increased medical risk, co-morbidities
Lack of resources Lack of time, resources, funding, staff and equipment needed to care effectively
BlameResponsibility For losing weight, for
managing health conditions or following advice
Preventability Preventing associated health conditions or obesity itself
Deservingness Deservingness of healthcare, services and funding
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Appendix 19– Final coding categories (continued)
Theme Sub theme Coding categories included
Culture
Media Media (TV, newspaper)Social media
Wider society Society generallyWestern populations
NHS moral discourse
Acknowledgement of NHS as ‘underfunded, resourced or staffed’ NHS in ‘crisis’, NHS staff overworked.
Identity management strategies
Stake inoculation Attitudes expressed through others (blame, characteristics, general opinions).
De-identification Identifying with identity as a person over a nurse
Denying impact of attitudes on care
Denying the impact of negative attitudes on empathy, compassion, practical care and equal treatment
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Appendix 20 – Full data screening analysis
Four of the questionnaires (ATOP, RSE, PSS and MBI) had more
than 5% missing data (see missing data summary table Appendix 2) and
thus Little’s MCAR test (Little, 1988) was undertaken. This resulted in a
statistically significant result (p < .05), indicating that the missing data from
each questionnaire was not missing at random (see table 1).
Table 1. Little’s MCAR Test Results
Little’s MCAR Test ResultsScale Chi Squared (X ²) Significance Value (p)ATOP 158.774 p < .01RSE .000 p < .01PSS 27.705 p < .01MBI 174.724 p < .01
The presentation order appeared to have an effect, with those
questionnaires presented later, being more likely to have missing data. As
such all 218 participants completed every item on the first scale presented,
the AFA, whilst the last presented scale, the MBI, had between 10-18%
responses missing for each item. Participants with declining responses were
initially removed from the analysis and Little’s MCAR Test (Little, 1988)
repeated; but this still resulted in a statistically significant result (p< .05)
suggesting that the missing data remained not missing at random (see table
2).
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Appendix 20 – Full data screening (continued)Table 2.
Little’s MCAR test for non ‘trail off data’
Little’s MCAR Test ResultsScale Chi Squared (X ²) Significance Value (p)ATOP 33.419 p < .05PSS 27.623 p < .01MBI 202.326 p < .01Note: RSE missing data analysis was not computed as once the ‘trail off’ data was removed there were no missing values.
In response to the Little’s MCAR test results, Chi Squared tests were
conducted on the missing and non-missing data in relation to qualification
status, age, BMI, gender and number of hours spent with patients in order to
assess whether the missing data within each questionnaire related to
particular demographic variables. Missing data was associated with the
largest age category (ages 22-30) for qualified nurses, (p<. 05); (see
appendix 21) which may relate to nursing managers’ comments during
recruitment about concerns that qualified nurses may not have time to
complete the survey.
Given that there was no missing data for the AFA, the scale required
for research question one which needed an equal number of undergraduate
and qualified nurses, missing data for the remaining scales was excluded
using the ‘exclude pairwise’ option to enable full sets of data to be used
where appropriate ant thus a large enough sample size for each remaining
questionnaire to reach statistical power.
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Appendix 20 – Full data screening (continued)
In relation to research question one a number of Chi Squared tests
were conducted to assess the pattern of responses between demographic
variables and qualification status for the AFA scores. No patterns were
detected between gender, BMI, and number of patient hours in
undergraduate or qualified nurses (p>.05). However, patterns were detected
between age and qualification status, X² (5, N=218) = 66.754, p< .01 with
undergraduate nurses being significantly younger than qualified nurses
(appendix 22).
A series of Mann Whitney U tests were conducted to assess for
significant differences in the results of each scale between the undergraduate
and the qualified nurses due to the proposed analysis of these groups
together for research question 2,3,4 and 5. There were no significant
differences between the overall scores on the ATOP (U=4110.000, p >.05)
or the RSE (U=4787.500, p >.05) but undergraduate nurses scores were
significantly higher than qualified nurses (U=3550.500, p>.05) on the PSS.
There was no significant difference on the MBI between the
depersonalization average scores for undergraduate and qualified nurses
(U=3264.000, p >.05) or for the emotional exhaustion subscale
(U=3967.000, p>.05). However, for the personal accomplishment subscale,
undergraduate nurses scored significantly higher than qualified nurses did
(3374.500, p< .05).
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Appendix 20 – Full data screening (continued)
Homogeneity of variance
A Levenes test of variance was conducted on the AFA scale, required
prior to the comparison of its two qualification groups which indicated equal
variances between both groups for the dislike subscale (F=1.645, p>.05), the
fear of fat subscale (F=2.779, p>.05) and the willpower subscale (F=1.400,
p>.238).
Tests of normality
The Kolmogorov Smirnov (K.S.) tests (table 3) of normality
conducted for the ATOP and the PSS were both non significant (p>.05)
suggesting that both questionnaires were normally distributed. The RSE
scale, the MBI subscales and the AFA subscales were all significant (p<.05)
suggesting non normal distributions (see appendix 23).
Table 3.
Tests of normality
Scale Subscale Skewness Kurtosis K.SSE SE p
AFA Dislike -2.122 .165 4.912 .328 .209 .000**Fear .400 .165 -876 .328 .094 .000**Willpower .199 .165 -.757 .328 .071 .010*
ATOP -.090 .174 -.621 .346 .058 .200RSE .221 .173 -.523 .344 .067 .032*PSS .142 .174 .173 .346 .053 .200MBI DP 1.305 .182 1.920 .361 .164 .000**
PA -1.191 .174 2.303 .346 .121 .000**EE .078 .174 -.331 .346 .078 .006**
Note: DP = depersonalization, PA = personal accomplishment, EE=emotional exhaustion * p < .05, ** p <.01
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Appendix 20 – Full data screening (continued)
In relation to research question one, K.S tests were also run for both
qualification groups separately for the AFA. The subscales ‘dislike’ and
‘fear’ remained non normally distributed (p<.01) although the third subscale
‘willpower’ became normally distributed for both groups (table 4).
Table 4.
Normality tests for the AFA split by undergraduate and qualified nursing
groups.
Subscale Q-S Skewness Kurtosis K.SSE SE p
Dislike U -2.093 .228 4.119 .453 .221 .000Q -1.973 .235 5.241 .465 .192 .000
Fear U .522 .228 -.931 .453 .129 .000Q .297 .235 -.715 .465 .118 .001
Willpower U .034 .228 -.793 .453 .061 .200*Q .380 .235 -.612 .465 .080 .091*
Note: Q-S=qualification status, U=undergraduate, Q= qualified
* = Significant at the 0.5 level
Outliers
Outliers were detected on the dislike scale of the AFA, the PSS and on the
depersonalization and personal accomplishment subscales of the MBI
(appendix 24). The raw data was checked for errors and the trimmed means
examined for each scale which remained close in proximity to the means
(table 5). The assumptions of normality were retested for each scale with
outliers removed but the scales remained non-normally distributed and as
the trimmed mean suggested they were not distorting the results of each
scale in deviating from the mean, the outliers remained.
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Appendix 20 – Full data screening (continued)
Table 5.
Mean (S.E.) and Trimmed means for scale scores.Scale Subscale Mean score (S.E.) Trimmed meanAFA Dislike
FearWillpower
7.4734 (.13976)3.7929 (.21257)4.3116 (.16402)
7.71333.71534.2885
ATOP 71.5385 (1.12065) 71.7268RSE 26.2012(.43825) 20.0270PSS 19.3373 (.38451) 19.2761MBI DP
PAEE
.9053 (.05909)3.9830 (0.5416)2.9034 (.07574)
2.8864
Transformations
In light of the non-normally distributed data, transformations were
conducted based on whether the scale was positively or negatively skewed.
However, the range of transformations performed did not aid the data in
meeting the assumptions required of parametric data (appendix 25). The
reliability estimates for the items of each scale were examined and the most
unreliable item from each scale removed. However, this also did not
improve the distribution of scores and equally did not reduce the overall
reliability of the scale so the items remained.
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Appendix 21 – Chi Squared analysis for missing data and demographic variables
Note: The Pearson’s Chi squared statistic is reported except in the 2x2 designs where the continuity correction was reported or where a test yielded a count of less than five when a Fisher’s Exact statistic was reported instead. Regardless the statistic is reported as ‘chi squared’ within each table.
Attitudes Toward Obese Persons Scale (ATOP)
Table 1: Chi Squared for ATOP missing data and qualified status
Table 2: Chi Squared for ATOP missing data and gender
p <.05 significant
Chi Squared for ATOP missing data and qualified statusQualification status
Missing data
S.R Non missing data
S.R Chi Squared
P value
Undergraduate 0 -3.1 112 .9 28.081 .000Qualified 18 3.2 86 -1Total 22 196
Chi Squared for ATOP missing data and genderGender Missing
data S.R Non missing
data S.R Chi
Squared P value
Male 1 -.5 16 .2 .412 .706Female 21 .2 180 -.1Total 22 196
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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Table 3: Chi Squared for ATOP missing data and BMI
Chi Squared for ATOP missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P value<18.5 0 -.8 7 .3
1.170 .74018.5-24.9 10 -.2 95 .125-29.9 7 -.1 65 .030 plus 5 .8 29 -.3Total 22 196
Table 4: Chi Squared for ATOP missing data and number of hours spend with patients
p <.05 significant
Chi Squared for ATOP missing data and number of hours spend with patientsNo of patient hrs
Missing data S.R. Non missing data S.R. Chi Squared P Value
0-20 7 -.7 84 .2
8.893 .08621-40 13 .1 111 .041-60 1 1.8 1 -.660 plus 1 2.8 0 -.9Total 22 196
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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Table 5: Chi Squared for ATOP missing data and age categories
Rosenburg Self Esteem Scale (RSE)
Table 6: Chi Squared for RSE missing data and qualified statusChi Squared for RSE missing data and qualified status
Qualification status Missing data S.R Non missing data S.R Chi Squared P value Undergraduate 0 -3.2 112 -1.0 21.057 .000Qualified 20 3.3 86 -1.0Total 20 198
p <.05 significant
Chi Squared for ATOP missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.9 52 .6 9.781 .09122-30 11 1.9 51 -.631-40 4 -.4 45 .141-50 3 -.1 28 .051-60 3 .5 19 -.260 plus 0 -.3 1 .1Total 22 196
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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Table 7: Chi Squared for RSE missing data and gender
Table 8: Chi Squared for RSE missing data and BMI
Chi Squared for RSE missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 .1 7 .3 .625
.929
.18.5-24.9 10 .1 95 .025-29.9 1 -.2 66 .130 plus 4 .5 30 -.2Total 20 198
p <.05 significant
Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Chi Squared for RSE missing data and genderGender Missing data S.R Non missing data S.R Chi Squared P value Male 1 -.4 16 .1 .003 .958Female 19 .1 182 .0Total 20 198
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Table 9: Chi Squared for RSE missing data and number of hours spend with patients
Table 10: Chi Squared for RSE missing data and age categories
p <.05 significant
Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Chi Squared for RSE missing data and number of hours spend with patientsNo of patient hrs
Missing data S.R. Non missing data S.R. Chi Squared P Value
0-20 6 -.8 85 .35.271 .21121-40 13 .5 111 -.2
41-60 1 1.9 1 -.660 plus 0 -.3 1 .1Total 20 198
Chi Squared for RSE missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.8 52 .6
11.093 .04022-30 11 2.2 51 -.731-40 4 -.2 45 .141-50 1 -1.1 30 .351-60 3 .7 19 -.260 plus 0 -.3 1 .1Total 20 198
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Perceived Stress Scale (PSS)
Table 11: Chi Squared for PSS missing data and qualified status
Chi Squared for PSS missing data and genderGender Missing data S.R Non missing data S.R Chi Squared P Value Male 2 .2 15 -.1 .000 1Female 21 .0 180 .0Total 23 195
Table 12: Chi Squared for PSS missing data and gender
p <.05 significant
Chi Squared for PSS missing data and qualified statusQualification status Missing data S.R Non missing data S.R Chi Squared P Value Undergraduate 0 -3.4 112 1.2 24.918 .000Qualified 23 3.5 83 -1.2Total 23 195
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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Table 13: Chi Squared for PSS missing data and BMI
Table 14: Chi Squared for PSS missing data and number of hours spend with patients
p <.05 significant
Chi Squared for PSS missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 -.9 7 .3
2.009 .66818.5-24.9 10 -.3 95 .125-29.9 9 -.3 95 .130 plus 4 .5 63 -.2Total 23 195
Chi Squared for PSS missing data and number of hours spend with patientsNo of patient hrs Missing data S.R. Non missing data S.R. Chi Squared P Value 0-20 7 -.8 84 .3
4.935.20921-40 15 .5 109 -.2
41-60 1 1.7 1 -.660 plus 0 -.3 1 .1Total 23 195
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Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Table 15: Chi Squared for PSS missing data and age categories
Table 16: Chi Squared for MBI missing data and qualified statusChi Squared for MBI missing data and qualified status
Qualification status Missing data S.R Non missing data S.R Chi Squared P Value Undergraduate 1 -4.3 111 2.0 44.481 .000Qualified 39 4.4 67 -2.1Total 40 178
p <.05 significant
Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)
Chi Squared for PSS missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 1 -1.9 52 .7
12.355 .022
22-30 12 2.1 50 -.731-40 6 .4 43 -.141-50 1 -1.3 30 .451-60 3 .4 19 -.260 plus 0 -.3 1 .1Total 23 195
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Table 17: Chi Squared for MBI missing data and gender
Table 18: Chi Squared for MBI missing data and BMI
Chi Squared for MBI missing data and BMIBMI Missing data S.R. Non missing data S.R. Chi Squared P Value<18.5 0 -1.1 7 .5
1.898 .57818.5-24.9 18 -.3 87 .125-29.9 14 .2 58 -.130 plus 8 .7 26 -.3Total 40 178
p <.05 significant
Appendix 21 – Chi Squared analysis for missing data and demographic variables (continued)Table 19: Chi Squared for MBI missing data and number of hours spend with patients
Chi Squared for MBI missing data and genderGender Missing data S.R. Non missing data S.R. Chi Squared P Value Male 3 -.1 14 .0 .000 1.000Female 37 .0 164 .0Total 40 178
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Table 20: Chi Squared for MBI missing data and age categories
p <.05 significant
Appendix 22 – Chi Squared analysis between demographic variables and qualification status
Chi Squared for MBI missing data and number of hours spend with patientsNo of patient hrs
Missing data S.R. Non missing data S.R. Chi Squared P Value
0-20 17 .1 74 .02.282
.53921-40 22 -.2 102 .1
41-60 1 1 1 -.560 plus 0 -.4 1 .2Total 40 178
Chi Squared for MBI missing data and age categoriesAge categories Missing data S.R. Non missing data S.R. Chi Squared P Value 18-21 2 -2.5 51 1.2
17.547 .00222-30 14 .8 48 -.431-40 8 -.3 41 .241-50 7 .6 24 -.351-60 9 2.5 13 -1.260 plus 0 -.4 1 .2Total 40 178
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Note: The Pearson’s Chi squared statistic is reported except in the 2x2 designs where the continuity correction was reported or where a test yielded a count of less than five when a Fisher’s Exact statistic was reported instead. Regardless the statistic is reported as ‘chi squared’ within each table.
Table 1: Chi Squared for qualification status and gender AFA questionnaire
Table 2: Chi Squared for qualification status and age categories
Qualification status
Age category (number of participants) Chi Squared P Value18-21 22-30 31-40 41-50 51-60 60+
Undergraduate 49 30 22 9 2 0 66.754 .000Qualified 4 32 27 22 20 1
Table 3: Chi Squared for qualification status and BMI categories
Qualification status
BMI category (number of participants) Chi Squared P Value<18.5 18.5-24.9 25-29.9 30+
Undergraduate 5 62 32 13 7.335 .062Qualified 2 43 40 21
p <.05 significant
Qualification Status
Gender (number of) Chi Squared P ValueMale Female
Undergraduate 7 105 .389 .453Qualified 10 96
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Appendix 22 – Chi Squared analysis between demographic variables and qualification status (continued)
Table 4: Chi Squared test for qualification status and number of hours spent with patients per weekQualification status
Patient hours (number of participants) Chi Squared P Value0-20 21-40 41-60 60+
Undergraduate 51 60 1 1 2.468 .620Qualified 40 64 64 1
p <.05
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Appendix 23 – Normality distribution histograms
Figure 1: AFA Dislike Subscale
Figure 2: AFA Fear
197
Appendix 23 – Normality distribution histograms (continued)
Figure 3: AFA Willpower Subscale
AFA subscale histograms split by qualification status
Figure 4: AFA Dislike Subscale undergraduate nurses only
198
Appendix 23 – Normality distribution histograms (continued)
Figure 5: AFA Dislike Subscale qualified nurses only
Figure 6: AFA Fear Subscale undergraduate nurses only
199
Appendix 23 – Normality distribution histograms (continued)
Figure 7: AFA Fear Subscale qualified nurses only
Figure 8: AFA Willpower Subscale undergraduate nurses only
200
Appendix 23 – Normality distribution histograms (continued)
Figure 9: AFA Willpower Subscale qualified nurses only
Figure 10: ATOP
201
Appendix 23 – Normality distribution histograms (continued)
Figure 11: RSE
Figure 12: PSS
202
Appendix 23 – Normality distribution histograms (continued)
Figure 13: MBI Depersonalization Subscale
Figure 14: MBI Personal Accomplishment Subscale
203
Appendix 23 – Normality distribution histograms (continued)
Figure 15: MBI Willpower Subscale
204
Appendix 24 -Correlation analysis with AFA dislike and MBI Depersonalization outliers removed
** significant at the .01 level
AFA dislike MBI DPAFA dislike Spearman’s rho 1 -.292**
Sig. (2-tailed) .000N 208 166
MBI DP Spearman’s rho -.292** 1Sig. (2-tailed) .000N 166 170
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Appendix 25 – Normality tests post transformations
Table 1: Anti-Fat Attitudes Scale (AFA) tests of normality on raw data and transformationsTest performed
AFA subscale
No transformation Log10-Reflect SQRT-Reflect Reciprocal= Reflectp p p p
K S Test (p) Dislike .209 .000 .125 .000 .153 .000 .088 .000Fear .094 .000 .169 .000 .142 .000 .279 .000Willpower .071 .010 .119 .000 .094 .000 .225 .000
Skewness Dislike -2.12 1.043 1.378 .302Fear .4 -1.100 -.829 2.387Willpower .199 -.909 -.625 2.528
Kurtosis Dislike 4.912 .683 1.788 -.847Fear -.8 .265 -.267 5.121Willpower -.757 .252 -.275 7.599
p <.05 significant
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Appendix 25 – Normality tests post transformations (continued)Table 2: AFA tests of normality on raw data and transformations split by qualification status Test performed
AFA subscale
Log10-Reflect SQRT-ReflectUndergraduate p Qualified p Undergraduate p Qualified p
Kolmogorov Smirnoff
Dislike .146 .000 .150 .000 .173 .000 .159 .000Fear .175 .000 .180 .000 .138 .000 .158 .000Willpower .102 .006 .146 .000 .083 .057 .119 .001
Skewness Dislike 1.136 -920 1.466 1.202Fear -1.137 -1.090 -.900 -.784Willpower -.786 -1.055 -.485 -.784
Kurtosis Dislike .886 .242 1.852 1.288Fear .173 .484 -.319 -.100Willpower .090 .528 -.396 -.040
Test performed
AFA subscale
Reciprocal ReflectUndergraduate p Qualified p
Kolmogorov Smirnoff
Dislike .073 .188 .104 .007Fear .301 .000 .277 .000Willpower .214 .000 .248 .000
Skewness Dislike .390 .171Fear 2.81 2.535Willpower 2.281 2.535
Kurtosis Dislike -.491 -1.117Fear 4.453 6.215Willpower 7.320 6.869
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Appendix 25 – Normality tests post transformations (continued)Table 3: Attitudes Toward Obese Persons Scale (ATOP) tests of normality on raw data and transformationsTest performed
No transformation p Log10-Reflect p SQRT-Reflect p Reciprocal= Reflect p
K S Test (p) .058 .200 .119 .000 .062 .062 .334 .000Skewness -.090 -1.657 -.511 10.471Kurtosis -.621 4.899 -.075 128.792Test performed
Log10 p SQRT p Reciprocal p
K S Test (p) .087 .001 .073 .012 .113 .000Skewness -.594 -.324 1.354Kurtosis .217 -.350 3.237
p <.05 significant
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Appendix 25 – Normality tests post transformations (continued)
Table 4: Rosenberg Self Esteem Scale (RSE) tests of normality on raw data and transformations
Test performed
No transformation
p Log10 p SQRT p Reciprocal p
K S Test (p) .067 0.32 0.87 .001 .060 .082 .136 .000Skewness .221 -.397 -.082 1.050Kurtosis -523 -.355 -.550 .729
Table 5: Perceived Stress Scale (PSS) tests of normality on raw data and transformations
Test performed
No transformation p Log10 p SQRT p Reciprocal p
K S Test (p) 0.60 2.00 0.92 .000 0.68 .030 .147 .000Skewness .142 -.653 -.243 1.634Kurtosis .173 -.761 -.208 .4.259
p <.05 significant
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Appendix 25 – Normality tests post transformations (continued)
Table 6: MBI tests of normality on raw data and transformationsTest performed Subscale10 No transformation Log10-Reflect SQRT-Reflect Reciprocal= ReflectK S Test (p) DP
PAEE
.164 .000 .089 .001 .181 .000 .136 .000
.121 .000 .089 .001 .100 .000 .060 .083
.078 .006 .196 .000 0.85 .002 .231 .000Skewness DP
PAEE
1.305 -.648 -1.675 1.436-1.191 .460 .804 .198.078 -2.269 -.350 4.139
Kurtosis DPPAEE
1.920 .358 3.974 3.6502.303 .242 .954 .319-.331 7.831 -.182 27.836
Test performed Log10 SQRT ReciprocalK S Test (p) DP
PAEE
.086 .002 .126 .000 .124 .000
.168 .000 .144 .000 .252 .000
.088 .001 .064 .051 .136 .000Skewness DP
PAEE
.346 .789 .356-3.101 -1.909 6.742-1.009 -.350 3.703
Kurtosis DPPAEE
-.583 .240 -.92416.041 6.542 55.4372.966 .415 23.215
10 Note: DP=depersonalization, PA= Personal Accomplishment, EE=Emotional Accomplishment
210
Appendix 26 – Scatterplots for correlation analyses
Figure 1: Scatter plot for the correlation between the AFA dislike subscale and BMI
Figure 2: Scatter plot for the correlation between the AFA fear of fat subscale and
BMI
211
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 3: Scatter plot for the correlation between the AFA willpower subscale and BMI
Figure 4: Scatter plot for the correlation between the AFA dislike subscale and the RSE
212
Appendix 26 – Scatterplots for correlation analyses (continued)Figure 5: Scatter plot for the correlation between the AFA fear of fat subscale and the RSE
Figure 6: Scatter plot for the correlation between the AFA fear of fat subscale and the RSE
213
Appendix 26 – Scatterplots for correlation analyses (continued)Figure 7: Scatter plot for the correlation between the ATOP and RSE
Figure 8: Scatter plot for the correlation between the AFA dislike subscale and the PSS
214
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 9: Scatter plot for the correlation between the AFA fear of fat subscale and the PSS
Figure 10: Scatter plot for the correlation between the AFA willpower subscale and the PSS
215
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 11: Scatter plot for the correlation between the ATOP and the PSS
Figure 12: Scatter plot for the correlation between the AFA dislike subscale and the MBI DP subscale
216
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 13: Scatter plot for the correlation between the AFA dislike subscale and the MBI PA subscale
Figure 14: Scatter plot for the correlation between the AFA dislike subscale and the MBI EE subscale
217
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 15: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI DP subscale
Figure 16: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI PA subscale
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 17: Scatter plot for the correlation between the AFA fear of fat subscale and the MBI EE subscale
218
Figure 18: Scatter plot for the correlation between the AFA willpower subscale and the MBI DP subscale
219
Appendix 26 – Scatterplots for correlation analyses (continued)
Figure 19: Scatter plot for the correlation between the AFA willpower subscale and the MBI PA subscale
Figure 20: Scatter plot for the correlation between the AFA willpower subscale and the MBI EE subscale
220
Part 3: Summary of clinical experience
Over the course of three years on the PsychD Clinical Psychology programme I
have completed five clinical placements across the lifespan and within a variety of
specialties. This section of the portfolio outlines a description of each placement
alongside the experiences and opportunities I gained from each.
In year one I completed a 10 month placement in a community adult mental
health recovery and support service. I worked across both adult community and
inpatient settings providing comprehensive psychological assessment, formulation,
intervention and consultation. My main therapeutic model was CBT although the
majority of my work was also informed by attachment and systemic theory. I co-
facilitated a psychoeducation group for managing bipolar disorder and a cognitive
based mindfulness therapy group for people with complex depression and anxiety. I
held responsibilities for risk assessment and clinical governance for my clients
alongside the wider MDT and enjoyed engaging with teaching opportunities with the
team to help develop psychological thinking.
In year two, my first six-month placement was in a community learning
disability service. Adapting evidence based therapies in flexible ways enabled me to
make psychological therapy accessible for people with learning disabilities and
mental health difficulties. I worked on a consultancy basis with behaviours that
challenge from a Positive Behavioural Support standpoint, infiltrating systemic and
attachment ideas. I conducted a range of assessments including eligibility, sexual
knowledge, dementia and autism. I also taught on the learning disabilities module of a
clinical psychology masters programme. This placement enabled me to hone my
verbal and written communication skills to meet the needs of this client group.
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The second six-month placement in my second year was in a child and
adolescent mental health team. I was part of the reflecting team within the systemic
family therapy service for young people with eating disorders and was lead therapist
for one family. I worked with young people using either CBT or narrative practice,
although again being informed by attachment and systemic theory. I worked within
the neurodevelopment pathway to conduct neuropsychological assessments for
children with possible autism and/or ADHD. I learned to work creatively and
adaptively according to the developmental stage of the clients.
In my first placement of my third year I worked within an older adult
community mental health team. Here I worked predominantly within a narrative
therapeutic framework whilst working with clients individually. I worked within a
Positive Behavioural Support framework to provide consultancy other services where
there were difficulties caring for clients diagnosed with dementia and the associated
behaviours that staff found challenging. I conducted a range of neuropsychological
investigations to aid the assessment of dementia.
My last six-month placement was my specialist option. I worked within the
personality disorder pathway within a community mental health team and also within
an Early Intervention Service for people with psychosis. I worked with people with a
diagnosis of personality disorder in a group context (STEPPS group) and individually
highlighting the impact of early attachment difficulties and trauma on the
development of severe mental health difficulties.
Through working within the Early Intervention Service for psychosis I have
worked within the CBT-P model for clients with psychosis, developing skills in
therapeutic engagement and developing collaborative understandings of the person’s
difficulties. I have conducted assessments and interventions using the Compassion
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Focused Therapy model and I have also co-facilitated a compassion focused resilience
group and an Acceptance and Commitment Group for this client group.
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Part 4PSYCHD CLINICAL PROGAMME
TABLE OF ASSESSMENTS COMPLETED DURING TRAINING
Year I AssessmentsASSESSMENT TITLE
WAIS WAIS Interpretation (online assessment)Practice Report of Clinical Activity
CBT assessment and formulation of Lucy, a female in her 40’s experiencing agoraphobia (without panic)
Audio Recording of Clinical Activity with Critical Appraisal
Audio recording of clinical activity and critical appraisal
Report of Clinical Activity N=1
Report of clinical activity, N=1 analysis. Mary a female in her 30’s with a diagnosis of bipolar disorder
Major Research Project Literature Survey
A literature survey investigating the factors associated with weight related bias in healthcare professionals towards obese patients
Major Research Project Proposal
A research proposal exploring the variables associated with weight related bias in healthcare professionals towards obese patients
Service-Related Project Evaluating a service user and carer based initiative at one UK Clinical Psychology Doctorate Training Course
Year II AssessmentsASSESSMENT TITLE
Report of Clinical Activity Formal Assessment
A learning disability assessment for Mel, a female in her late teenage years.
PPLD Process Account PPLDG Process Account
Year III Assessments ASSESSMENT TITLE
Presentation of Clinical Activity
A 9 year old girl experiencing intrusive thoughts and anxiety; who loves cats and playing teachers
Major Research Project Literature Review
Personal factors associated with the attitudes of UK nurses toward patients with obesity: A literature review
Major Research Project Empirical Paper
A mixed methods study exploring weight related bias in undergraduate and qualified nurses
Report of Clinical Activity
A story of a woman in her late 60’s and her experiences of distress: A Narrative informed approach.
Final Reflective Account
On becoming a clinical psychologist: A retrospective, developmental, reflective account of the experience of training
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