religious beliefs, social support, self-efficacy and adjustment to cancer

Psycho-OncologyPsycho-Oncology 18: 1069–1079 (2009)Published online 2 February 2009 in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/pon.1442

Religious beliefs, social support, self-efficacy andadjustment to cancer

Barbara A. Howsepian1 and Thomas V. Merluzzi2�1University of California San Francisco-Fresno Medical Education Program, Fresno, California, USA2University of Notre Dame, Notre Dame, IN, USA

Abstract

Purpose: Religious beliefs have received relatively little attention in research on coping with

cancer. In this study, the relationship of religious beliefs and perceived social support with

adjustment to cancer was studied in a coping model that included self-efficacy for coping as a

mediator. Of particular interest was the relationship between religious beliefs and social

support.

Method: Data were collected from 164 in-treatment cancer patients. They completed

measures of religious beliefs, social support, physical functioning, self-efficacy for coping, and

adjustment. A model comparison approach was used to assess the fit of models that included or

excluded the contribution of religious beliefs while testing the relationship between religious

beliefs and social support.

Results: Religious beliefs were more strongly connected to perceived social support than

with other constructs. Importantly, a coping model that included religious beliefs fit the data

significantly better than a model without paths related to religious beliefs. Self-efficacy

partially mediated the relation of age, physical functioning, and perceived support to

adjustment, but not religious beliefs.

Discussion: Religious beliefs may not directly affect self-efficacy and adjustment; however,

cancer patients who have religious beliefs may experience an enhanced sense of social support

from a community with whom they share those beliefs.

Copyright r 2009 John Wiley & Sons, Ltd.

Keywords: cancer; religious beliefs; social support; self-efficacy; adjustment

Polls in the United States indicate that approxi-mately 95% of adults believe in God [1]. Inaddition, many individuals who confront threatsof illness report turning to religion for solace andhelp with coping [2–4] and that religion has beeneffective in reducing negative psychosocial statesassociated with severe health-related stressors [5,6].Thus, religion plays a role in the lives of asignificant number of Americans who face severehealth-related stressors; moreover, health psychol-ogists have begun to explore systematically the roleof religion and spiritually in health and mortality[7–11].A number of studies have shown that religiosity/

spirituality is directly related to positive adjustmentamong cancer patients [4,12–18], however theeffects are not uniformly positive. In a criticalanalysis of 17 studies concerning the effects ofreligious coping on adjustment, the results weremixed with about half of the studies reportingsignificant effects [19]. The authors of that studypoint to a number of methodological problemswith the studies reviewed, especially with the

conceptualization and operationalization of reli-gious coping and the lack of inclusion or controlfor other variables such as illnesses, functioninglevel, and social support. Another weakness ofresearch on religiosity and coping with cancer isthat indirect effects of religious coping, which mayhelp articulate a more complex role for religion inhealth and illness, have not been examined. Finally,the review focused on religious coping, whereas fewstudies have looked at the effects of religiousbeliefs.

It has been proposed that religiosity/spiritualitymay indirectly relate to adjustment through vari-ables such as health practices, social support, orpsychosocial resources such as self-efficacy forcoping or that it may moderate the effects ofnegative life events on adjustment [7,16,20,21].Hence, religiosity may indirectly lead to betteradjustment by its association with other variablessuch as social support or by enhancing self-efficacyexpectations that, in turn, enhance adjustment.This effect is relatively easy to understand in thecontext of religious practices in the sense that there

* Correspondence to:Department of Psychology,University of Notre Dame,Notre Dame, IN 46556,USA. E-mail:[email protected]

Received: 30 March 2008

Revised: 30 July 2008

Accepted: 31 July 2008

Copyright r 2009 John Wiley & Sons, Ltd.

are others physically present to commune with andto provide encouragement and support yet it is lessclear how this indirect effect might operate withrespect to religious beliefs. The two-part definitionof religion suggested by Pargament [22], in whichreligion has both substance (e.g. beliefs) andfunction (e.g. how beliefs relate to our behaviorin everyday life), may help clarify the importanceof religious beliefs in the context of coping withcancer. Along those lines, this study was anattempt to investigate the function of religiousbeliefs by studying their relationship with othervariables, such as social support, self-efficacy forcoping, and psychosocial adjustment to cancer.This approach may remedy a problem in theliterature noted by Stefanek et al. [23] related tothe lack of specification of the mechanismsinvolved in the relationship between religiousbeliefs and cancer outcomes.Religious beliefs are an internal coping resource

that individuals may use to reduce stress andenhance adjustment [24]. These beliefs may affecthow individuals appraise stressful events andinterpret their meanings and implications [17].For example, Holland et al. [25] found thatendorsement of religious beliefs was related to anactive versus passive coping style. Thus, the beliefthat ‘With God’s help all problems are resolvable’,may foster confidence (self-efficacy) that one cancope with problems, which, in turn, fosters adjust-ment. Other evidence suggests that persons withcancer who espouse strong religious beliefs ‘wereless reliant on health professionals, had less needfor information, attached less importance to themaintenance of independence, and had less needfor help with feelings of guilt, with their sexuality,or with some practical matters than those who saidthey had no religious faith’ [26; p. 49]. Given that

religious beliefs are (a) portable, as the individualcarries them, (b) compatibility with models ofcoping, and (c) have the potential to foster coping,in this study religious beliefs were included in acoping model with coping self-efficacy as amediator. In addition, unlike most studies ofreligiosity and spirituality that focus, to a greatextent, on meaning making [27,28] this studyfocuses exclusively on religious beliefs. Moreover,in contrast to many religious beliefs studies that donot clearly distinguish religious practices fromreligious beliefs [15], this study addresses specifi-cally religious beliefs and not religious practices orspirituality as a broad concept.An important consideration is the notion that

religious beliefs, within the constraints of aparticular religious tradition, may be assumed tobe shared with others in the same religiouscommunity. This may lead to a perception ofsupport, which is beneficial to individuals instressful situations because it fosters beliefs thatthey are connected and have others on whom theycan depend [29]. These beliefs give individuals asense of reassurance that they can cope, that is, asense of self-efficacy. [30–32]. Social support is onemechanism that has been suggested, in associationwith religious beliefs, as enhancing coping andadjustment [7,22]. Consequently, shared beliefsmay afford an individual support for coping andadjustment by fostering thoughts or perceptions ofbeing part of a larger community of believers.The overall structure of this study follows

[33–35] Rowland’s suggestion that there are fourmain patient variables that affect an individual’sadjustment to cancer: (1) interpersonal resources,(2) intrapersonal resources, (3) developmentalstage, and (4) medical context of disease. Weextended Rowland’s model by proposing amechanism by which those four variables impactadjustment [31]. In this model self-efficacy forcoping mediates the relationship between intraper-sonal variables (e.g. religious beliefs), interpersonalvariables (e.g. perceived social support), develop-mental stage (e.g. age as a proxy), the medicalcontext of the disease (e.g. disease impact), andoutcomes such as psychosocial adjustment. Ourself-efficacy mediated coping model is consistentwith mediated models reviewed by George et al. [7]and utilized by Ironson et al. [27] in their work onHIV/AIDS. In addition, it meets the need forresearch on the effects of psychosocialresources (e.g. self-efficacy) that may function asmediators as indicated by George et al. [7].Moreover, because our model examines a self-efficacy-mediated relationship between religiousbeliefs and health outcomes, it addressesMiller and Thoresen’s [8] concern that, ‘Surpris-ingly few studies have included adequate measuresof potential mediators of the relationships betweenhealth and spiritual/religious factors’ (p. 31).

Figure 1. Full mediated model with all paths included(Table 3—Model A) �po0.01

Copyright r 2009 John Wiley & Sons, Ltd. Psycho-Oncology 18: 1069–1079 (2009)

DOI: 10.1002/pon

1070 B. A. Howsepian and T. V. Merluzzi

Because religiosity and, in the case of this study,religious beliefs seem to play an integral role inpeople’s lives when they face health threats, wehypothesized that a coping model that incorporatesreligious beliefs would better explain adjustmentamong cancer patients than one that excludedreligious beliefs.In sum, we tested a coping model (Figure 1)

in which religious beliefs, social support, age,and disease impact were independent variableswhose relationship with adjustment was mediatedby self-efficacy for coping. We were particularlyinterested in whether religious beliefs wouldfollow the same pattern as religious practicesin having a significant relationship with socialsupport. [7, 36–39]. Beliefs could merely be heldin the minds of believers and not involvesocial support, or beliefs could represent a connec-tion with a community of believers, real, orperceived that is related to perceived socialsupport.

Method

Participants

Participants were recruited from several outpatientoncology clinics in two moderate-sized cities innorthern California. Patients were excluded if theywere not in active medical treatment and if theywere suffering from other major medical orphysical illnesses. Study materials were given to388 potential participants; 146 of these peopleeither decided not to participate in the study or didnot return all of the questionnaire materials. Of the242 who chose to complete the materials, 55 whowere no longer in treatment and 23 who hadsignificant other physical or mental illnesses (e.g.advanced heart disease, terminal renal disease,thought disordered mental illness, etc.) wereexcluded. The exclusion criteria were based onthe goal of studying the coping model strictly in theexclusive context of active coping with cancer andits treatments rather than on post-treatment cancersurvivorship or on co-morbidity. Thus, 164 cancerpatients, who were in treatment, completed thequestionnaire booklet sufficiently enough for theirresponses to be analyzed. The participants andtheir medical information were treated in accor-dance with HIPPA regulations and the ethicalstandards of the American Psychological Associa-tion. There are no conflicts of interest in any aspectof this research including publishing. Informationwas not available on those who declined toparticipate. However, on the basis of medicalvariables, the sample was diverse with respect tosite and stage.The participants consisted of 103 women and 61

men who were between 25 and 84 years of age

(M5 59). They were predominantly married(70.1%), Caucasian (89.0%), Protestant (53.7%),middle class, and retired (35.4%), with, amongother sites, breast cancer (42.1%) and prostatecancer (14.6%). Complete demographic and dis-ease-related information is contained in Table 1.

Measures

In accordance with typical structural equationmodel (SEM) testing, multiple measures were usedto assess the constructs of disease impact andreligious beliefs. Owing to constraints of partici-pants’ willingness and ability to respond to lengthypackets of questionnaires, however, some measureswere randomly divided into parallel halves in orderto create two measures. That was the case for thefollowing constructs: perceived support, self-effi-cacy, and adjustment. This ‘parceling’ approachhas much research to support its use [40] in testingmodels using SEM. The parceling approach allowsfor a more thorough use of the SEM methodology,which cannot be achieved with a single measure.

Disease impact

The physical impact of cancer was measured withthe Sickness Impact Profile (SIP), which contains136 statements about health-related dysfunction[41,42]. The 88 items that constitute the physicaland independent scales were used in order to focuson the physical impact of cancer and its treatments;thus, the scales that deal with the psychological andsocial aspects were not included in this study. TheSIP is highly reliable and valid [41–43] and higherscores indicate greater cancer impact. The SIP wasoperationalized as a multiple indicator of cancerimpact by generating both an independence scale(Miscellaneous Dimension of the Sickness ImpactProfile, MSIP) and a physical scale (PhysicalDimension of the Sickness Impact Profile, PSIP)score for each participant. Internal consistency ofthe MSIP was 0.87 and 0.86 for the PSIP.

Perceived social support

Perceived social support was assessed with theInterpersonal Support Evaluation List (ISEL),which is a 40-item measure of perceptions of theavailability of social support [44]. Ten items on theISEL that related to self-esteem support wereeliminated because they assess an internal constructrather than an interpersonal one and because theymay over lap with psychosocial adjustment. Higherscores on the ISEL indicate greater perceived socialsupport. Research suggests that the ISEL has goodtest–retest reliability, good internal consistency,and validity [45]. For this study, the ISEL wasoperationalized as a multiple indicator of perceivedsocial support by randomly dividing it in half tocreate two parallel measures. Internal consistency

Religious beliefs and adjustment to cancer 1071


DOI: 10.1002/pon

Table 1. Demographic and disease-related information

Variable % Variable %

Sex of participants Age of participants

Male 37.2 25–39 5.5

Female 62.8 40–49 17.7

50–59 26.8

60–69 26.2

70–79 20.1

80–84 3.7

Marital status

Never married 2.4

Married 70.1

Divorced 17.1

Separated 1.8

Widowed 7.3

Other 1.2

Education level

Some grade school 0.6

Completed grade school 1.2

Some high school 4.3

Completed high school 21.3

Some college or vocational school 37.8

Completed college 9.8

Some graduate work 9.8

A graduate degree 14.6

Did not report 0.6

City of residence

Fresno 36.0

Visalia 26.4

Other cities 47.6

Employment status

Employed 37.2

Unemployed 4.9

Retired 35.4

Full-time Homemaker 9.8

On leave from 12.8

Employment

Religious preference

Catholic 25.6

Protestant 53.7

Orthodox Christian 1.8

Muslim 0.6

Mixed affiliations 2.4

No affiliation 8.5

Agnostic 1.8

Atheist 2.4

Other 1.8

Did not report 1.2

Household income level

o$15 000 12.8

$15 000–$24 999 17.7

$25 000–$40 000 23.8

4$40 000 44.5

Did not report 1.2

Race or ethnicity Recurrence of cancer

Hispanic 6.1 First time 70.7

White 89.0 Recurrence 29.3

Black 1.2

Asian/Pacific Islander 1.2

Surgery

67.7

Native American 0.6

Surgery

32.3

Other 1.8

No surgery

61.6Site of cancer

Breast 42.1

Chemotherapy

38.4

Lung 7.3

Chemotherapy

Prostate 14.6

No chemotherapy

84.8

Colorectal 4.3 15.2

Cervix 1.8

Radiation therapy

Lymphoma 8.5

Radiation therapy

6.1

Other 21.3

No radiation therapy

93.9

Other types of treatment

72.0

Other treatment

No other treatment

Time since diagnosis

o2 months ago 20.7

o6 months ago 41.5 15.2

o1 year ago 18.9 20.1

o2 years ago 6.7

42 years ago 12.2 1.8

Living arrangementa

1.8

Husband/wife

Alone

With children

With parents

With siblings

With friends

With grandchildren

With grandparent

Age of participant Years 4.9

Mean age 59.1 1.2

Minimum age 25.0 0.6

Maximum age 84.0

Cancer stage at time of diagnosis %

Stage I 23.8

Stage II 25.0

Stage III 19.5

Stage IV 12.8

Not staged 3.0

Other 11.0

Information not available 4.9

aParticipants were allowed to endorse more than one category on this question. Hence, the percentages add up to more than 100.



DOI: 10.1002/pon

for the first half was 0.89 and 0.86 for the secondhalf.

Religious beliefs

Three instruments were used to assess religiousbeliefs based on their overall psychometric quality.In all three instruments higher scores indicategreater religious belief. First, the 10-item subscaleof the Systems of Belief Inventory that focuses onbeliefs was used (SBI-15R; [46]). Items such as‘Religion is important to my day-to-day life’, and ‘Ibelieve that God will not give me a burden I cannotcarry’, were rated on a 4-point scale ranging from 0(strongly disagree) to 3 (strongly agree). The SBI-15R has good internal consistency, test–retestreliability, and validity [46]. The internal consis-tency of the beliefs subscale of the SBI-15R in thisstudy was 0.96.The 10-item Religious Belief Index (RBI) was

also used [18]. It includes items such as ‘I feel sureGod exists’, and ‘There is meaning and purpose ineveryone’s life, no matter what he or she is like orwhat he or she does’, that were rated on a 5-pointscale from 0 (disagree completely) to 4 (agreecompletely). Research has demonstrated that theRBI has adequate reliability and validity [18]. Inthis study, the internal consistency of the RBI was0.92. Finally, the Spiritual Belief Statement (SBS)is a single-item measure developed for this study toassess participants’ religious belief. It is based onPalmer’s [47] definition of religious belief withregards to ill-health and reads, ‘I believe becauseGod is with me in very difficult times; these difficulttimes will contribute to my well-being either in thislife or the after life’. Participants were asked toindicate how much this statement applies to them.This item was correlated with variables expected tobe closely related (SBI, r5 0.79; RBI, r5 0.79) andnot highly correlated with variables not expected tobe closely related (age, r5 0.07; PSIP, r5 0.03);thus, it appeared to be a valid construct in thecontext of this study.

Coping self-efficacy

Self-efficacy for coping was assessed with theCancer Behavior Inventory (CBI; [48,49]). Theversion of the CBI used in this study included 43coping behaviors that cancer patients engage inthroughout the course of their illness (e.g. ‘Main-taining independence’ and ‘Asking nurses ques-tions’). Patients rate their coping efficacy on a 9-point scale ranging from 1 (not all confident) to 9(totally confident). Because the CBI measurescoping self-efficacy or expectations, patients areable to respond to all the items even if they arecurrently not using a particular coping strategy.Higher scores indicate greater coping self-efficacy.Three of the 43 items were eliminated in this studybecause they comprise a social support factor that

could have been correlated with the social supportvariable. The CBI has high internal consistencyand adequate validity [48,49]. For this study, theCBI was operationalized as a multiple indicator ofself-efficacy by randomly dividing the CBI items inhalf to create two parallel measures. Internalconsistency for the first half was 0.86 and 0.86 forthe second half.

Adjustment

Adjustment to cancer was assessed by the Psycho-social Adjustment to Illness Scale, Self-Reportform (PAIS-SR; [50]). This 46-item instrumentevaluates the psychosocial adjustment of medicalpatients to illnesses. Participants rate their adjust-ment by choosing one of four responses that rangefrom low to high in terms of adjustment to illness.The four responses vary as a function of thecontent of each item. For example, one itempresents the participant with the following ques-tion: ‘Are you still as interested in your leisure timeactivities and hobbies as you were prior to yourillness?’ Response options include ‘same level ofinterest as previously’, ‘slightly less interest thanbefore’, significantly less interest than before’, and‘little or no interest remaining’. Higher scoresindicate better psychosocial adjustment. Researchon the PAIS-SR has revealed that it has goodinternal consistency and validity [50,51]. In thisstudy, the PAIS-SR was operationalized as amultiple indicator of psychological adjustment toillness by randomly dividing it in half to create twoparallel measures. Internal consistency for the firsthalf was 0.86 and 0.87 for the second half.

Demographic information

Demographic information was gathered from theparticipants in the questionnaire packet. Eachparticipant’s age in years was collected on thedemographic form and verified by informationfrom his or her medical chart.

Procedure

Participants, who assented, were contacted inoutpatient oncology clinics by either the firstauthor (B.A.H.) or staff from the respectiveinstitutions and given the study materials. In-formed consent, including consent to allow accessto participants’ medical charts for the purpose ofcollecting information about their diseases (e.g.stage at diagnosis, treatments, presence of meta-static disease) was obtained from all those whochose to participate. In addition to the informedconsent form, the materials included the measuresand demographic information sheets to completeduring their medical office visit. Participantsreturned their completed questionnaires, in sealedenvelopes, to the receptionist at each location. The



DOI: 10.1002/pon

entire questionnaire packet took about 60minutesto complete and patients were not compensated fortheir participation.

Power analyses

The MacCallum et al. [52] framework of not-close-fit was used to assess power. These authorsapproach the issue of model fit by reversing therole of the traditional null hypothesis of close fitthat employs the w2 likelihood ratio test. In thisperspective on power in SEM, the null hypothesisrepresents some value of the RMSEA where the fitof the model would be judged as unacceptable (i.e.the conclusion being that the model does not fit). Inthe present study we chose a Type I error rate of0.05 with the null value of the RMSEA specified tobe greater than or equal to 0.08, which generally isregarded as representing mediocre fit. In the not-close-fit framework the goal is to reject the nullvalue of the RMSEA (i.e. RMSEA45 0.08) andaccept the alternative hypothesis that the RMSEAis less than 0.08. The alternative hypothesiswe specified for power calculations wasRMSEA5 0.025, which is generally regarded asrepresenting a fit between good and excellent. Anacceptable value of the RMSEA is one whose 95%confidence interval does not include the value of0.08. We assessed power for each of the modelspresented in this study by employing the SASpower analysis routine developed by MacCallum etal. [52; p 148]. The analysis was set up to evaluatepower for the particular situation in whicha5 0.05, RMSEA_Null45 0.08, andRMSEA_A5 0.025. Power for each model, weinvestigated, is reported in Table 3. Values rangedfrom 0.95 to 0.98. These values signal adequatepower to reject the null hypothesis of not-close-fit(i.e. RMSEA540.08), when the alternative isspecified to be 0.025.

Results

Preliminary analyses

The coping models in this study were analyzedusing LISREL with the maximum likelihoodestimation procedure. For each of the constructsin the study (disease impact, social support,religious beliefs, self-efficacy, and adjustment)multiple measures were used, in accordance withstandard approaches to the use of LISREL andother SEM programs. As noted in the descriptionof the measures, for some variables multiplemeasures were formed by randomly dividing theexisting scale into two measures or ‘parcels’ [40].The reported path coefficients were derived from acorrelation matrix after the SIP, ISEL, SBI, RBI,and SBS were transformed using the natural logtransformation procedure [53]. Table 2 presents thecorrelation matrix and the means, medians, andstandard deviations for the variables in this study.

Measurement model

Before proceeding to test the coping (i.e. structural)model represented in Figure 1, a measurementmodel was established to determine (a) theadequacy of the measures that were used includingthe ones that were divided into parallel halves orparcels, and (b) the correlation between the sixmajor constructs (i.e. latent variables: age, diseaseimpact, social support, religious beliefs, self-effi-cacy, and adjustment). In order to test the latter,the measurement model was compared with a ‘null’model in which the constructs were assumed to beuncorrelated. The optimal outcome of this pre-liminary analysis is that (a) specific measures (i.e.manifest variables) relate significantly to specificconstructs (i.e. latent constructs), (b) the latentconstructs are related to each other, and (c) the

Table 2. Intercorrelations, means, and standard deviations of the variables used in model testing

Variables 1 2 3 4 5 6 7 8 9 10 11 12

1. AGE

2. MSIP �0.196�

3. PSIP �0.001 0.675��

4. ISELA �0.031 �0.228�� 0.262��

5. ISELB �0.045 �0.261�� 0.265�� 0.812��

6. SBI 0.004 0.120 0.089 0.100 0.239��

7. RBI 0.043 0.094 0.117 0.067 0.206�� 0.792��

8. SBS 0.067 0.084 0.029 0.075 0.198� 0.793�� 0.788��

9. CBIA 0.226�� 0.362�� 0.351�� 0.396�� 0.397�� 0.091 0.134 0.179�

10. CBIB 0.198� �0.339�� 0.347�� 0.469�� 0.446�� 0.077 0.141 0.145 0.906��

11. PAISA 0.287�� 0.652�� 0.589�� 0.356�� 0.385�� 0.010 0.020 0.096 0.613�� 0.571��

12. PAISB 0.243�� 0.614�� 0.595�� 0.395�� 0.426�� 0.034 0.034 0.135 0.603�� 0.574�� 0.920��

Mean 59.12 14.46 5.28 38.47 37.95 22.70 33.26 7.02 142.05 147.30 37.58 35.81

SD 12.67 13.29 7.57 6.85 6.54 8.26 8.39 2.55 19.01 19.25 9.54 9.01

Note: MSIP, Miscellaneous Dimension of the Sickness Impact Profile; PSIP, Physical Dimension of the Sickness Impact Profile; ISELA & ISELB, Interpersonal Support

Evaluation List, parallel halves; SBI, Systems of Belief Inventory; RBI, Religious Beliefs Index; SBS, Spiritual Belief Statement; CBIA & CBIB, Cancer Behavior Inventory,

parallel halves; PAISA & PAISB, Psychosocial Adjustment to Illness Scale, parallel halves.�po0.05,��po0.01.



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measurement model with the correlated constructsrepresents the actual data (i.e. correlations) betterthan the null model. Without these conditions, thehypothesized mediational model (Figure 1) cannotbe tested.First, a six-factor measurement model with 11

measures (two for each construct except age) wastested and compared with a null model using thesame six factors. The null model did not allow forany of the six constructs to be correlated. If themeasurement model was not different from the nullmodel, we could conclude that the constructs arenot related to each other and testing the copingmodel (Figure 1) should not proceed. Because therewas no reason to believe that the parallel measures(i.e. those randomly divided into two halves foreach construct: social support, self-efficacy, andadjustment) would be different from one another,the pathways between the construct and the twoparallel forms as well as the error terms for eachpair were constrained to be equal. The paths fromthe variable to the constructs were all positive andsignificant, indicating that the measures were goodindicators of their respective constructs. In addi-tion, the null model, in which all of the pathsrelating the constructs to each other were set atzero, provided a poor fit to the data (Table 3; notelarge w2 and low GFI and AGFI and large RMSRand RMSEA values). As anticipated, the proposedsix-factor measurement model fit the actual datawell [54]. Moreover, as evidenced by the w2

difference test (w2 Null Model [324.28] minus w2

Measurement Model [55.14]; df Null [64] minus dfMeasurement [49]; w2diff (df5 15, N5 164)5 269.14,po0.001, the measurement model fit the datasignificantly better than the null model.

Structural model

In line with Barron and Kenny [55], we first testedthe direct effects of the predictor variables (age,disease impact, social support, and religiousbeliefs) on adjustment. A model that allowed forcorrelations among the predictors revealed that thedirect effects were significant for age (0.198,po0.05), disease impact (�0.697, po0.01), per-ceived social support (0.203, po0.01), and religious

beliefs (0.110, po0.05). The significant directeffects allowed further testing of the mediatedmodel. First, because there was no basis for theassumption that the predictors would be fullymediated by coping self-efficacy, a model (ModelA) was tested that included all direct and indirectpaths for the predictors; then a second model(Model B) was tested based on the finding that forModel A, the direct effect of religious beliefs onadjustment was not significant, whereas the indirectpath to self-efficacy was nearly significant(po0.10). Finally, a third model (Model C) wastested in which all paths involving religious beliefswere excluded. These three models were thencompared to determine the importance of the roleof religious beliefs; first, Model A was comparedwith Model B to determine if the elimination of thedirect path between religious beliefs and adjust-ment improved the fit of the model to the data.Then, Models A and B were compared with ModelC, in which all effects of religious beliefs wereeliminated, to determine if the inclusion of religiousbeliefs improved the fit of the model. If so, then, itis presumed that while the contributions ofreligious beliefs may not be directly on adjustment,the effects of religious beliefs may be importantalthough more diffuse.The full model (Table 3—Model A) with all

paths was compared with the reduced model(Table 3—Model B). The full model consisted ofall paths, including both direct paths to adjustmentand indirect paths through self-efficacy as depictedin Figure 1. Because the direct path from religiousbeliefs to adjustment was not significant, a reducedmodel (Model B) was tested in which the directpath between religious belief and adjustment wasconstrained by being set equal to zero, thuseliminating this path from the model. Both the full(Model A) and the reduced (Model B) copingmodels fit the data equally well in that the indicesof fit were adequate in both models (Table 3).Results suggest that, while religious beliefs werenot directly related to adjustment, they nonethelesscontributed to the overall fit of the model and wererelated primarily to perceived social support, whichconfirms the hypothesized relationship betweenreligious beliefs and perceived social support.

Table 3. Fit indices and power estimates for all models tested

Model w2 df GFI AGFI RMSR RMSEA Power

Measurement model analysis

Null model 324.28� 64 0.74 0.69 0.27 0.16 0.98

Measurement model 55.14 49 0.95 0.91 0.04 0.03 0.95

Structural model analysis

A. Full model (Figure 1) (all paths included) 63.90 49 .94 .90 0.06 0.04 0.95

B. Reduced model (Figure 2) (without direct path between religious belief and adjustment) 65.59 50 .94 .90 0.06 0.04 0.95

C. Partial model (with paths involving religious belief set equal to zero) 76.64 54 0.93 0.90 0.08 0.05 0.95

Note: GFI, Goodness-of-Fit Index; AGFI, Adjusted Goodness-of-Fit Index; RMSR, root mean squared of the residuals; RMSEA, root mean square error of approximation.

Optimal fit, nonsignificant w2, GFI and AGFI40.90, and RMSR and RMSEAo0.05.�po0.05 (null model w2 is the only one that was statistically significant).



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In order to provide a stringent test to determinethe importance of inclusion of religious beliefs inthe coping model, two models were compared. Onemodel included all the paths involving religiousbeliefs (Table 3—Model A) and the second(Table 3—Model C) eliminated the religious beliefeffects by setting all of those paths equal to zero.The w2 difference test that compared the fits of thetwo models was significant, w2diff [C minus A:76.64–63.90]5 12.74 (df5 5; N5 164), po0.05.Thus, the results of the model with the religiousbeliefs paths included (Figure 2) were a superior fitcompared with the model in which those pathswere constrained to zero. An even more stringenttest of the importance of including religious beliefsin the coping model was the comparison of themodel (Model B) without a direct path fromreligious beliefs to adjustment (Figure 2) to themodel in which all paths involving religious beliefswere constrained to equal zero (Model C), thuseliminating the relationship between religiousbeliefs with any other variable in the model. Thew2 difference test that compared the two modelswas significant, w2diff [C minus B:76.64�65.59]5 11.05 (df5 4; N5 164), po0.05,which means that, once again, the model with thereligious beliefs paths included (in this case Figure2) was a superior fit to the model in which thosepaths were constrained to equal zero. Conse-quently, the models that included the relationshipsbetween religious belief and other constructsprovided a better representation of the actual dataand therefore modeled the coping process betterthan a model that did not. In addition, because ofthe significant relationship between religious beliefand social support, the salutatory effects ofreligious beliefs may operate primarily, thoughnot exclusively, through social support. In sum, the

inclusion of religious beliefs in the model enhancedthe fit of the model to the data.In terms of the other aspects of the coping

model, self-efficacy partially mediated the relation-ships of age and disease impact with adjustment. Inaddition, the relationship between self-efficacy andadjustment was significant and positive indicatingthat those with higher efficacy for coping are betteradjusted to cancer than those low in copingefficacy. Age was positively related to both self-efficacy and adjustment such that older patientswere more efficacious with respect to coping andmore generally well adjusted than younger patients.Along those same lines, disease impact had astrong negative relationship with self-efficacy andadjustment indicating that a high level of physicaldebilitation was associated with poorer coping andadjustment to cancer. Finally, perceived socialsupport was significantly related to self-efficacybut not to psychosocial adjustment, indicating thatthe relationship between perceived social supportand adjustment was fully mediated by self-efficacy.

Discussion

The overall aim of this research was to determinethe function of religious beliefs in coping withcancer. Results of the study indicated that religiousbeliefs were related to perceived social support.Moreover, there was statistical confirmation thatthe inclusion of the paths related to religious beliefsenhanced the fit of the coping model comparedwith a model in which those paths were removed(i.e. constrained to equal zero). Thus, while theeffects of religious beliefs are not direct onpsychosocial adjustment, they are important andmay operate through other variables, most notablysocial support.One interpretation of the findings regarding the

relationship of religious beliefs and social supportmay parallel findings on religious practices, that is,religious beliefs may affect cancer patients’ percep-tions of their ability to access help from others.Hence, greater strength of religious beliefs mayfoster the perception of the accessibility of socialsupport. In line with the findings of this study,these perceptions of the accessibility of help, inturn, may increase patients’ confidence that theycan manage cancer-related difficulties. Therefore,the impact of religious beliefs may be related tobelievers’ perceptions that they are part of alarger community of people who share their beliefs.The larger community may also include theirrelationship to or partnership with God or a higherpower [22].This interpretation of the relationship between

religious beliefs and social support also relates toSarason et al.’s [56] suggestion that even duringperiods of developmental and environmental

Figure 2. Reduced mediated model without a direct pathbetween religious belief and psychosocial adjustment (Table 3—Model B) ��po0.01



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change, perceived support remains stable. Sarasonet al. also stated that the sense of perceived supportdevelops within the individual beginning in earlychildhood and is based on the interactions that aperson has with his or her environment. Thus,religious beliefs may manifest in adulthood percep-tions that others, such as fellow believers or God,may be available in time of need. In that sense,beliefs may be a part of a general perception ofsupport that also might include more tangible orinstrumental support.Similar to previous research on other cancer

patient populations [48,49], disease impact relatedsignificantly and positively to psychosocial adjust-ment. This finding indicates that the more cancerimpacts physical functioning, the greater thedifficulty a patient has in adjusting to the disease.Additionally, age was positively related to psycho-social adjustment, the older the cancer patientswere (i.e. the more life experience they had) thebetter their adjustment.Self-efficacy played an important role as a partial

mediator of the effects of age, cancer impact, andperceived social support on adjustment. In thisstudy, self-efficacy mediated part of the effects ofage, cancer impact, and fully mediated perceivedsocial support on adjustment and, consequently,added to the prediction of adjustment. Thesemediated and partially mediated effects suggestthat it is not only the direct information from ageand impact of cancer that determines adjustmentbut also what cancer patients believe about theircapabilities regarding cancer-related coping (i.e.self-efficacy). Those efficacy expectations are influ-enced by age, cancer impact, and perceived socialsupport.Determining the relative function of religious

beliefs, disease impact, age, social support, self-efficacy, and psychosocial adjustment in cancerpatient populations can help health-care profes-sionals understand and address the needs of cancerpatients. It appears from this research that patientsin treatment for cancer may benefit from theirreligious beliefs by the resulting connection tosocial support. Thus, in exploring religious beliefs,for patients who are so inclined, health profes-sionals might include the exploration of how thosebeliefs foster religious support, which may includea sense of being loved by God, but also a sense ofsharing those beliefs with other people.The results also suggest that self-efficacy may be

the focal point for a portion of the effects of aging,physical debilitation, and perceived social support.It is clear that efficacy can be altered [57]. That is,self-efficacy for coping may involve a set ofexpectations that affects adjustment. In addition,because there are a wide variety of coping skills,interventions might target those areas in which thepatient has particularly low or high efficacy tomaximize the impact of the intervention. The focus

on areas in which there is high efficacy is tomaintain or bolster strengths in coping; whereas,the focus on areas of low coping efficacy wouldremedy problem areas. Interventions with anemphasis on enhancing self-efficacy might alsoinclude some remediation of the precursors ofefficacy such as social support and fosteringreligious beliefs if the patient endorses those beliefsas a coping resource. Thus, fostering religiousbeliefs, perceived support, and reducing the impactof symptoms are all paths to better coping andadjustment.The current study is the first to cast religious

beliefs in a comprehensive theoretically derivedcoping model; however, the study would need to bereplicated and extended to fully understand role ofreligious beliefs. Because the current study is crosssectional, future work might include a longitudinalanalysis to confirm the direction of the relation-ships among the variables in the model. Inaddition, it would be interesting to investigatemore homogeneous groups of cancer patientsaccording to site, time-since-diagnosis, or in- andoff-treatment versus the heterogeneous approach inthis study, which included all cancer patients whowere in treatment. The absence of a direct relation-ship between religious beliefs and adjustment doesnot obviate the effects of other aspects of religiositynot addressed in our study, such as religiouspractices, which in some studies relate to healthand adjustment outcomes. Thus, it might beinteresting to include both religious practices andreligious beliefs in the same model to assess therelative importance and independence of thoseaspects of religiosity. The current study is alsolimited in scope in that it focuses primarily ontraditional Judeo-Christian beliefs. It would beimportant to compare those beliefs with otherbelief systems that are somewhat different in focus(e.g. Buddhism). Moreover, it would also beimportant to account for more subtle variationsin the fundamental assumptions of those who holdthose beliefs and how believers use those beliefs toconceptualize the causes or reasons for illness.

Acknowledgements

Dr Howsepian wishes to thank the California Cancer Centerat Woodward Park, The Cancer Center at St. Agnes, theFresno Chapter of Reach to Recovery, and the KaweahDelta Cancer Care Center for their invaluable assistance andpatience with the implementation of this research study. Theauthors wish to thank Ken Kelley, Ph. D. for his statisticalconsultation. Preparation of this manuscript was supportedby a grant from the National Cancer Institute (CA200916).

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