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1 23
Journal of Religion and Health
ISSN 0022-4197
J Relig Health
DOI 10.1007/s10943-015-0129-z
Effect of a Faith-Based Education Program
on Self-Assessed Physical, Mental and
Spiritual (Religious) Health Parameters
Frans J.Cronjé, Levenda S.Sommers,
James K.Faulkner, W.A.J.Meintjes,
Charles H.Van Wijk & Robert P.Turner
1 23
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ORIGINAL PAPER
Effect of a Faith-Based Education Program on
Self-Assessed Physical, Mental and Spiritual
(Religious) Health Parameters
Frans J. Cronje
´
1,3
•
Levenda S. Sommers
2
•
James K. Faulkner
2
•
W. A. J. Meintjes
1,3
•
Charles H. Van Wijk
4
•
Robert P. Turner
5
Springer Science+Business Media New York 2015
Abstract The aim of the study was to determine the effect of attending a faith-based
education program (FBEP) on self-assessed physical, mental and spiritual health param-
eters. The study was designed as a prospective, observational, cohort study of individuals
attending a 5-day FBEP. Out of 2650 sequential online registrants, those previously
unexposed to the FBEP received automated invitations to complete 5 sequential Self-
Assessment Questionnaire’s (SAQ’s) containing: (1) Duke University Religion Index
(DUREL); (2) Negative Religious Coping (N-RCOPE); (3) Perceived Stress Scale (PSS);
(4) Center for Epidemiology and Statistics-Depression Scale (CES-D); (5) Brief Illness
Perception Questionnaire (BIPQ); and the (6) State Trait Anxiety Inventory (STAI). Pre-
attendance SAQ (S1) was repeated immediately post-FBEP (S2), at 30 days (S3), 90 days
(S4) and after 1 year (S5). Of 655 invited, 274 (42 %) succeeded, 242 (37 %) failed and
139 (21 %) declined to complete S1. Of the 274, 37 (14 %) were excluded at on-site
interview; 26 (9 %) never attended the FBEP (i.e., controls: 5#;21$; 27–76 years); and
211 (77 %) participated (i.e., cases: 105#; 106$; 18–84 years) and were analyzed over
time: 211 (S1); 192 (S2); 99 (S3); 52 (S4); 51 (S5). IRB approval was via the Human
Research Ethics Committee of Stellenbosch University. DUREL showed significant,
& Frans J. Cronje
´
fransc@sun.ac.za
& W. A. J. Meintjes
wajm@sun.ac.za
1
Department of Interdisciplinary Health Sciences, Faculty of Health Sciences, University of
Stellenbosch, Parow, South Africa
2
Be in Health Inc, Thomaston, GA, USA
3
Division of Community Health, Faculty of Medicine, University of Stellenbosch, Room 0073
(Baromedical Facility); Education Building, Francie van Zijl Drive, Tygerberg Campus,
Parow 7500, South Africa
4
South African Military Health Service, Institute for Maritime Medicine, Simon’s Town,
South Africa
5
Division of Biostatistics and Epidemiology, MUSC, Charleston, SC, USA
123
J Relig Health
DOI 10.1007/s10943-015-0129-z
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sustained changes in Intrinsic Religiosity. N-RCOPE showed significant, lasting
improvement. In others, median values dropped significantly immediately after the FBEP
(S1:S2) for STAI-State p \ 0.0001; PSS p \ 0.0001; BIPQ p \ 0.0001; and CES-D
p \ 0.0001; and at 1 month (S1:S3) for STAI-Trait p \ 0.001; all changes were sustained
(S3 through S5). This FBEP produced statistically and clinically significant changes; these
lasted in those followed up [1 year.
Keywords Religion Mental health Spirituality Religion and Medicine Religion and
Psychology
Introduction
Faith, religiosity and spirituality (F–R–S) play a significant role in the perception, pre-
vention and treatment of disease (Stanley et al. 2011). Collectively, they have indirect
effects by influencing people’s understanding of the nature and etiology of disease; by
favoring or prohibiting particular methods of disease management; by influencing uti-
lization of healthcare resources; by affecting patient compliance and satisfaction; and by
supporting or impairing recovery (Borras et al. 2007; Grossoehme et al. 2008; Kemppainen
et al. 2008; Koenig 2007; Kremer et al. 2009; Lyon et al. 2011; Mellins et al. 2009; Parsons
et al. 2006; Stewart and Yuen 2011). They may also have direct effects by being con-
stituent parts of the therapeutic process, e.g., prayer. As a result, F–R–S and health research
tends to fall into two broad categories: (1) correlation studies that typically explore psy-
chosocial and behavioral elements of faith and attempt to identify potential mediators,
factors and physiological mechanisms through which the positive or negative health effects
may be explained; and (2) intervention studies that examine the effect of a specific F–R–S
variable and an associated objective health outcome.
This study examined both of these components: In this first paper, we report the out-
come of an intervention—a standardized faith-based education program (FBEP)—on a set
of outcome measures. In a subsequent paper, we will examine the outcome data as cor-
relates of morbidity and mortality. Therefore, the chosen outcome measures were all
previously validated Self-Assessment Questionnaires (SAQ’s), some of which have
extensive normative data for comparison.
Justification for the study lay in the present paucity of scientific outcome data on health-
oriented faith-based instruction on physical, mental and spiritual (religious) health
parameters. While many faith-based organizations address health issues at some level, few
offer standardized interventions that would permit the analysis of outcomes. Even fewer
consider the durability of the results or the possible detrimental effects. Therefore, the
objective of this paper was to report the outcomes of a standardized FBEP intervention:
Were there effects; were they positive or negative; and did they last?
The FBEP intervention is a 5-day program called For My Life
TM
(4ML), presented by Be
in Health Inc (BiH), an international, NFP Christian ministry specializing in faith-based
teaching on spiritual, psychological and physical health issues. BiH has developed a wide
range of Biblically based educational materials, ministry approaches and training programs
aimed specifically at bio-psycho-socio-spiritual health and disease prevention. The 40-h 4ML
program offers the initial, intensive, systematic teaching and ministry components and
introduces a framework for ongoing discipleship from a Christian, Biblical perspective. It is
estimated that approximately 30,000 people have attended the 4ML program since its
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inception. A central part of the program is the so-called 8 R’s, also called ‘‘the walk-out’’
which includes recognition, responsibility, repentance, renunciation, removal, resistance,
rejoicing and restoring in response to negative life experiences, thoughts and emotions. There
is a significant amount—approximately 20 h—of Biblically referenced teaching on sickness
and health; pathways of disease and ‘‘spiritual roots’’ of disease; as well as the importance of
forgiveness, resolving negative religious coping and becoming reconciled with God, others
and themselves. Great emphasis is also placed on the effects of fear, stress and anxiety on
health. Various opportunities for relational restoration and reconciliation with God, self and
others are offered throughout the program—in the form of collective prayers of confession
and repentance—to facilitate resolving unforgiveness and receiving God’s love. The program
concludes with a final 30-min individual ‘‘wrap-up’’ ministry session at the end to deal with
any residual or outstanding issues. Negative Religious Coping and disempowerment issues
are dealt with specifically throughout the program. Negative spiritual and emotional influ-
ences are externalized and objectified for the purpose of ensuring a functional internal locus of
control in partnership with God and self. The negative influences and thoughts are categorized
by means of descriptive names, like ‘bitterness’, ‘accusation’, ‘envy & jealousy’, ‘rejection’,
‘unloving’, and ‘fear’, to allow the participants to more readily identify them; to take
authority over their impact on their lives and relationships; and to constructively pursue and
manifest positive emotions, behavior and relational skills in return (analogous to Cognitive
Behavioral Training). The emphasis is on empowering individuals to accept responsibility for
their lives and to realize that reconciliation with God and others is the primary objective. This,
in turn, will facilitate removal of existing barriers to spiritual, mental and physical health
recovery. The goal, therefore, is not primarily healing but relational restoration; healing is
presented as the by-product of restored relationships.
Methods
Study Design
The study was designed as a prospective, observational, cohort study of individuals
attending a 5-day FBEP called ‘‘For My Life
TM
’’ (4ML) with IRB approval. The FBEP
was presented by Be in Health Inc (www.beinhealth.com), a 501(c)3 organization in
Thomaston, GA. During FBEP online registration, all individuals who indicated their age
as C18 years and had no prior exposure to the FBEP (or its associated materials) received
Fig. 1 Subject enrollment over 21-month study period and 63 consecutive FBEPs
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an automated online invitation to participate in the study; no other methods of solicitation
were employed, and no other subjects were recruited. The only incentive to participate was
a complimentary book related to the program material; there were no other benefits to
participating. Sample size calculations were performed using Stata/IC 10.1 for Windows
(StataCorp LP, 4905 Lakeway Drive, College Station, TX 77845, USA). The study
required 44 cases for a power of 0.9 and an alpha of 0.05. To allow for on-site exclusion
and attrition over time, a target of 250 subjects was selected. Enrollment was from
February 1, 2011, to November 21, 2012 (21 months). Between 1 and 9 subjects (out of a
class of 16–95 attendees; average 41) enrolled over 63 consecutive 4ML programs (see
Fig. 1).
The FBEP director and teachers were blinded to who the subjects were. Apart from the
initial, brief on-site eligibility interview with the on-site research coordinator, contact with
subjects was limited to e-mailed instructions to complete the follow-up SAQ’s. Long-term
follow-up continued until January 15, 2014. The 91-item SAQ was offered online via
Survey Monkey (www.surveymonkey) using a personal e-mailed link. All data were
entered directly into the survey. The results were de-identified and exported for analysis
with subject numbers allocated to permit collation. No alterations were made to the data
entries. All incomplete surveys were excluded from analysis. Scoring and reverse scoring
configurations were verified meticulously to assure validity of the SAQ results. The SAQ
was completed once before and four times after the FBEP: SAQ 1 (S1) was taken during
FBEP online registration; SAQ 2 (S2) was immediately after the FBEP (with a 7-day cutoff
period); SAQ 3 (S3) was at 30 days after S2; SAQ 4 (S4) was at 60 days after S3; and SAQ
5 (S5) was taken at the end of the study period, more than 1 year after S1. Participants
received two e-mail prompts, 7 days apart, to complete SAQ’s S2, S3, S4. If they failed to
respond within 7 days of the second e-mail, they were excluded from further surveys other
than S5, which all subjects (cases and controls) were again invited to complete. See Fig. 2.
A brief telephone interview was performed within 30 days of S4 to determine whether the
participants had participated in any alternative interventions and to obtain qualitative
Fig. 2 Study timeline for cases and controls
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information about their experiences during and following the program. The S5 question-
naire was also accompanied by an introductory set of questions to determine whether
participants had received any interventions between S4 and S5. No participants reported
any additional interventions other than routine religious involvement and medical care.
Participants
Out of 2650 sequential online registrants during the enrollment period, 655 indicated they
were of eligible age and had no prior exposure; these were invited to participate. Of these,
274 (42 %) were successful in submitting S1; 242 (37 %) were unsuccessful; and 139
(21 %) were unwilling to participate. Of the 274, 26 never attended the FBEP (i.e., con-
trols: 5#;21$; 27–76 years); 211 met the eligibility criteria (i.e., cases: 105#; 106$;
18–84 years); and 37 were excluded during the on-site interview. Reasons for exclusion
were: age \18 years; any prior exposure to the program or its material before the first day
of the FBEP; not personally completing the SAQ’s; and lack of English and basic computer
proficiency for proper comprehension of the FBEP material and valid completion of the
questionnaires. The derivation of the study sample is depicted in Fig. 3.
Age and gender distribution are shown in Fig. 4 in 5-year intervals. All the participants
were US citizens, thereby permitting comparison to US normative data.
Research Instruments
The 91-item SAQ was made up of 6 components: (1) Duke University Religion Index
(DUREL); (2) Negative Religious Coping (N-RCOPE); (3) Perceived Stress Scale (PSS);
(4) Center for Epidemiology and Statistics-Depression Scale (CES-D); (5) Brief Illness
Perception Questionnaire (BIPQ); and (6) State Trait Anxiety Inventory (STAI).
The DUREL is a 5-item questionnaire that measures Organizational and Non-Organi-
zational Religious Activity (i.e., ORA and NORA—also classified collectively as Extrinsic
Religiosity); and private or Intrinsic Religiosity (IR) (Harold G. Koenig and Bu
¨
ssing
2010). The higher the score the greater the involvement in religious activities. The
Fig. 3 Derivation of the study sample
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questionnaire has been used extensively in regression analyses linking religious activity
and health outcomes. It has good test–retest reliability (Koenig and Bu
¨
ssing 2010; Storch
et al. 2004).
The N-RCOPE is a 7-item questionnaire. It assesses spiritual discontent, perceived
spiritual punishment and harmful spiritual influences related to illness (Pargament et al.
2000). Scores are from 0 to 21. The higher the score the greater the ability to cope in a
positive religious way to life’s stressors. The questionnaire has good test–retest reliability
and identifies important negative religious factors that have been associated with poor
mental and physical health outcomes (Pargament et al. 2011).
The PSS is a 10-item questionnaire that assesses perceived stress (Cohen 1983; Cohen
et al. 1995). Scores range from 0 to 40. It measures the extent to which a person perceives
that life’s demands exceed their ability to cope. The higher the number the greater per-
ceived stress in the individual’s life. The PSS has established associations with physical
symptoms and abnormal health parameters (Burns et al. 2002; Carpenter et al. 2004; Cohen
et al. 1993; Cruess et al. 1999; Culhane et al. 2001; Ebrecht et al. 2004; Epel et al. 2004;
Holzel et al. 2010; Kramer et al. 2000; Leon et al. 2007; Malarkey et al. 1995; McAlonan
et al. 2007; Stone et al. 1999).
The CES-D is a 20-item questionnaire that assesses depressive symptoms in the past
week (Radloff 1977). It is well recognized in depression research for a general population
(Choi et al. 2014; Radloff 1977; Schein and Koenig 1997). Scores range from 0 to 60. The
higher the score the more depression there is. It also correlates with abnormal EEG findings
associated with depression (Diego et al. 2001).
The BIPQ is an 8-item questionnaire that offers high-yield information on perception of
an individual’s illness as a threat (Broadbent et al. 2006; Leventhal 1984). Scores range
from 0 to 80. A higher score indicates a more threatening view of illness. It has been
validated over a large spectrum of illnesses relevant to the study population (Broadbent
et al. 2008).
Fig. 4 Age and gender distribution of subjects—in 5-year increments
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Table 1 Comparison of mean scores of the study population and general population norms for PSS, CES-D and STAI over time
Scale Norms S1 S2 S3 S4 S5
M
(SD)
M
(SD)
MD p M
(SD)
MD p M (SD) MD p M (SD) MD p M
(SD)
MD p
PSS (women) (Cohen and
Janicki-Deverts 2012)
16.14
(7.56)
25.07
(8.16)
?8.9 \0.001* 16.56
(9.29)
?0.4 0.89 13.80 (6.27) -2.3 \0.01
#
14.30 (6.44) -1.8 0.14 15.87
(8.84)
-0.3 0.61
PSS (men) (Cohen and
Janicki-Deverts 2012)
15.52
(7.44)
20.87
(8.57)
?5.4 \0.001* 14.16
(8.60)
-1.4 0.06 10.22 (6.31) -5.3 \0.001
#
10.28 (5.93) -5.2 \0.001
#
13.82
(9.15)
-1.7 0.10
CES-D (Crawford et al.
2011)
10.24
(9.67)
23.87
(15.95)
?13.6 \0.001* 12.54
(11.89)
?2.3 0.79 8.91 (8.31) -1.3 \0.01
#
9.13 (10.98) -1.1 \0.05
#
9.80
(12.86)
-0.4 0.14
CES-D (Radloff 1977) 9.25
(8.58)
23.87
(15.95)
?14.6 \0.001* 12.54
(11.89)
?3.3 0.11 8.91 (8.31) -0.3 0.07 9.13 (10.98) -0.1 0.09 9.80
(12.86)
?0.6 0.26
STAI-S (women)
(Spielberger 1983)
35.20
(10.61)
50.79
(16.29)
?15.6 \0.001* 31.31
(11.24)
-3.9 \0.001
#
33.61 (10.22) -1.6 0.13 34.48 (14.89) -0.7 0.26 35.96
(17.26)
?0.8 0.43
STAI-S (men) (Spielberger
1983)
35.72
(10.40)
44.53
(16.62)
?8.8 \0.001* 32.75
(13.85)
-3.0 \0.01
#
29.52 (11.29) -6.2 \0.001
#
28.72 (10.79) -7.0 \0.01
#
32.57
(13.07)
-3.2 0.08
STAI-T (women)
(Spielberger 1983)
34.79
(9.22)
51.77
(15.02)
?17.0 \0.001* 39.94
(13.17)
?5.2 \0.001* 37.12 (10.81) ?2.3 0.19 38.26 (13.75) ?3.5 0.48 37.52
(16.91)
?2.7 0.98
STAI-T (men) (Spielberger
1983)
34.89
(9.19)
46.77
(15.25)
?11.88 \0.001* 37.35
(13.14)
?2.5 \0.01* 31.60 (11.35) -3.3 \0.001
#
31.17 (11.71) -3.7 \0.01
#
34.29
(13.01)
-0.6 0.08
* Significantly higher than population mean
#
Significantly lower than population mean
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The STAI has 40 items and is made up of 2 parts (Bergua et al. 2012; Kvaal et al. 2005;
Oei et al. 1990; Tenenbaum et al. 1985): Part One (State Anxiety or STAI-S) has 20 items
measuring current anxiety; the higher the number the more anxious the individual feels
right now (Spielberger 1983). Part Two (Trait Anxiety or STAI-T) has 20 items measuring
long-term anxiety; the higher the number the more anxious the person feels generally
(Spielberger 1983). Both parts have scores ranging from 20 to 80.
At the conclusion of the study period, all valid SAQ’s were analyzed: (1) cases S1: 211;
S2: 192; S3: 99; S4: 52; and S5: 51; (2) controls S1: 26; S5: 6 (female only). Twenty cases
completed all 5 SAQ’s; then, to increase the number of S5
0
s a second invitation was sent to
the remaining 218 participants. Cases who did not complete all 5 surveys were categorized
as lost to follow-up (LTFU) as opposed to those cases who completed (CMPL) all of them;
these two groups were compared at baseline (S1) and immediately after the FBEP (S2) to
assess bias and possible predictors of attrition (Fewtrell et al. 2008)—see Table 2.
Biostatistics
Statistical analyses were performed using STATGRAPHICS
Sigma Express for Micro-
soft Excel
(Statpoint Technologies, Inc, USA; www.statgraphics.com). Wilcoxon rank-
sum tests were performed to determine the level of significance between the means of the
subscales of the respective SAQ’s. Kruskal–Wallis rank tests were used for determining
differences in medians. The reference groups were derived from the original scale publi-
cations or from the most appropriate recent population data available online (Cohen and
Janicki-Deverts 2012; Crawford et al. 2011; Radloff 1977; Spielberger 1983); p-values in
Table 1 were obtained using the Wilcoxon signed-rank test; and for Table 2. Fischer’s
exact test was used after confirming equal variances.
Table 2 Attrition analysis—comparison between those completing all 5 surveys (completers or CMPL;
n = 30) and those with less than 5 surveys (lost to follow-up or LTFU; n = 181)
Metrics LTFU (n = 181) CMPL (n = 30) p value
Comparison at baseline (S1)—mean (±SD)
Age 43.0 (±14.1) 43.8 (±13.1) 0.767
Gender (male/female) 88/93 17/13 0.4373
N-RCOPE 16.42 (±4.18) 17.33 (±4.32) 0.258
BIPQ 41.91 (±17.39) 44.43 (±15.67) 0.457
PSS 23.24 (±8.56) 21.4 (±8.90) 0.28
CES-D 24.05 (±15.66) 22.8 (±17.82) 0.692
STAI-S 47.94 (±16.66) 46.1 (±17.27) 0.578
STAI-T 49.67 (±15.16) 46.93 (±16.24) 0.365
Comparison of changes S1 vs. S2 [mean (SD)]
N-RCOPE 0.975 (±3.61) 0.3 (±3.075) 0.337
BIPQ -13.37 (±17.0) -23.767 (±17.9) 0.003*
PSS -7.05 (±8.5) -8.6 (±10.3) 0.376
CES-D -10.66 (±10.7) -12.87 (±12.64) 0.414
STAI-S -14.31 (±15.8) -19.83 (±16.6) 0.082
STAI-T -9.82 (±
5.1) -13.133 (±14.10) 0.266
* Significantly greater improvement in CMPL
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Results
Of the 211 cases, 190 (90 %) attended the FBEP within 1 month and 134 (64 %) attended
within 2 weeks (range 1–213 days), of completing S1. Compliance with the time-sensitive
points for S2, S3 and S4 was excellent (see Fig. 5) with minor variability due to response
time to the e-mail prompts. Personal qualitative telephone interviews were scheduled
within 30 days of completing S4; none of the participants reported receiving any additional
interventions of a medical, psychiatric, counseling or faith-based nature, other than routine
follow-up and religious activities since attending the FBEP. Responses to specific intro-
ductory questions on S5 confirmed no additional interventions between S4 and S5.
Changes in the DUREL scale are depicted in Fig. 6: Because the FBEP included ORA,
NORA and IR activities, changes between S1 and S2 would be expected to reflect the
content of the FBEP program relative to the individual’s baseline religiosity: There was no
statistically significant change between median ORA scores at S1 vs. S4 (p = 0.06) or S1
vs. S5 (p = 0.09). Median and mean NORA scores did increase statistically between S1 vs.
S3, S4 and S5 (p \ 0.001 for each, respectively), whereas S3, S4 and S5 did not differ
statistically. Median and mean IR scores also increased significantly between S1 vs. S3, S4
and S5 (p \ 0.001, respectively) without statistically significant differences between S3,
S4 and S5.
The median N-RCOPE scores improved after the FBEP (see Fig. 7); differences
between S1 vs. S2, S3, S4 were all significant (p \ 0.0001, respectively); S3 was also
statistically higher than S2 (p \ 0.001), whereas S3, S4 and S5 did not differ statistically
from each other. Confidence intervals did not overlap between S1 and S2 and narrowed
over 3 years, with homogenization of the group.
The CES-D changes are depicted in Fig. 8. The initial values showed a wide distribution
from S2 onwards, with an homogenization of values; the changes were preserved over the
remainder of the study period. The median and 95 % confidence intervals of S2, S3, S4 and
S5 did not overlap with S1.
Based on epidemiological studies, CES-D scores were grouped as follows: low (\15);
mild-to-moderate depression (16–21); and possible major depressive illness ([21) (Radloff
1977; Schein and Koenig 1997; Stansbury et al. 2006). Using these criteria, there was a
significant redistribution of the possible major toward low-grade depression (see Fig. 9)
Fig. 5 Period between FBEP and time-sensitive SAQ’s (S2, S3 and S4)
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Fig. 6 DUREL score changes over time. a Organizational Religious Activity (ORA). b Non-Organizational
Religious Activity (NORA). c Intrinsic Religiosity (IR). In these figures, the embedded tables show the
application of a multiple comparison procedure to determine which means are significantly different from
which others. The output shows the estimated difference between each pair of means. The asterisk indicates
statistically significant differences at the 95.0 % confidence level
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(p \ 0.0001). The ratio between low-grade and major depression continued to improve
between S1 vs. S3 (p \ 0.0001), and the relative proportions were maintained through S5.
The BIPQ scores dropped significantly after the FBEP with a decrease in median and
mean values between S1 vs. S2 (p \ 0.0001); a gradual homogenization of the population;
and no statistically significant difference between S2, S3, S4 and S5. See Fig. 10.
Median and mean PSS scores also dropped with statistical significance between S1 vs.
S2 (p \ 0.0001) and S2 vs. S3 (p \ 0.001) with no further significant changes from S3
through S5. See Fig. 11.
State Anxiety (STAI-S) median and mean scores showed a prompt drop at S2
(p \ 0.0001) and no further significant changes between S2 through S5—see Fig. 12.
Fig. 7 Negative RCOPE changes over time
Fig. 8 CES-D changes over time. In this figure, the embedded table shows the application of a multiple
comparison procedure to determine which means are significantly different from which others. The output
shows the estimated difference between each pair of means. The asterisk indicates statistically significant
differences at the 95.0 % confidence level
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Lastly, as would be expected, STAI-T dropped more slowly than STAI-S; as such,
significant statistical differences were recorded between median and mean values for S1 vs.
S2 and between S2 and S3 (p \ 0.002). There was no statistical difference between S3, S4
and S5—see Fig. 13a. The box and whisker plot shows a homogenization of the popula-
tion—Fig. 13b.
Discussion
The vast majority (90 %) of the subjects attended the FBEP within a month of online
registration. As such, the changes immediately following the program are more likely to be
the result of the FBEP than a time-based deviation towards the mean. This is also sup-
ported by the fact that the measures did not revert to the baseline values over time.
Fig. 9 CES-D changes over
time—by category. The bar
graph shows the CES-D scores
for all cases grouped as low
(\15); mild to moderate (15–21);
and possibly major ([21)
depression
Fig. 10 BIPQ changes over time. In this figure, the embedded table shows the application of a multiple
comparison procedure to determine which means are significantly different from which others. The output
shows the estimated difference between each pair of means. The asterisk indicates statistically significant
differences at the 95.0 % confidence level
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To reflect the changes in more absolute terms, the CES-D, PSS and STAI data from the
sample were compared to population norms (see Table 1). The study population scored
significantly higher at baseline (S1): PSS women & 1 SD, PSS men & 1.5 SD; CES-
D & 1.5 SD; STAI-S women & 1.5 SD; STAI-S men & 1 SD; STAI-T women & 2 SD;
and STAI-T men & 1 SD. This suggests poorer mental health on entry into the study
(Cohen and Janicki-Deverts 2012; Radloff 1977; Spielberger 1983). Immediately after the
FBEP program, S2 scores were reduced by C1 SD on all scales. PSS and CES-D scores
were now comparable with population means, whereas STAI-S scores were significantly
below population means. STAI-T also underwent a highly significant change at S2, relative
to S1, but was still significantly above population norms. By 90 days (S3) the STAI-T for
males approached population norms; for women it was still slightly above normal mean
scores.
The attrition analysis is shown in Table 2. When comparing those completing less than
5 surveys (lost to follow-up [LFTU]) vs. all 5 surveys (completers [CMPL]), no significant
differences were found for age (p = 0.767), gender (p = 0.437), N-RCOPE (p = 0.258),
BIPQ (p = 0.258), PSS (p = 0.28), CES-D (p = 0.692), STAI-S (p = 0.578) or STAI-T
(p = 0.365).
Similarly, when comparing LTFU and CMPL according to recorded changes in scores
between S1 and S2 (excluding DUREL—as explained previously), only the BIPQ changes
were significantly different between the groups; this suggests that cases who experienced
positive changes in BIPQ may have been more likely to complete all 5 surveys, whereas
changes in the other measures were not significantly associated with attrition.
In general, the FBEP had a remarkably prompt, statistically and clinically significant
‘normalizing’ and homogenizing effect on the respective parameters by S2. Interestingly,
by 30 days (S3), most of the scores were still decreasing from the S2 values with PSS,
CES-D and STAI (men) reaching levels significantly below population means. The
observed changes were largely maintained by 90 days (S4), with STAI (women) now
approaching population means. After a year (S5), all mean scores had returned to popu-
lation means which, as noted previously, were significantly different from S1 scores: For
Fig. 11 PSS changes over time. In this figure, the embedded table shows the application of a multiple
comparison procedure to determine which means are significantly different from which others. The output
shows the estimated difference between each pair of means. The asterisk indicates statistically significant
differences at the 95.0 % confidence level
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each index, the difference was &1 SD below the baseline scores and on par with the
general population. Thus, the FBEP appeared to improve the study population’s mental
health parameters (as measured by these scales and compared to population norms), and
this continued to improve in the period of follow-up after the program and was maintained
for [1 year.
It is important to state that not everybody benefited equally from program. However:
When reviewing the 211 individual scores, some individuals experienced an initial increase
in scores (i.e., defined as any increase in score, irrespective of magnitude) between S1 and
S2 for N-RCOPE (n = 81; 38 %); BIPQ (n = 34; 16 %); PSS (n = 34; 16 %); CES-D
(n = 33; 16 %); STAI-S (n = 24; 11 %) and STAI-T (n = 40; 19 %). However, the vast
Fig. 12 a STAI-S changes over time. In this figure, the embedded table shows the application of a multiple
comparison procedure to determine which means are significantly different from which others. The output
shows the estimated difference between each pair of means. The asterisk indicates statistically significant
differences at the 95.0 % confidence level. b STAI-S changes over time
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majority of these were minor increases. The majority of the participants followed the
general trend of significantly lowered scores or improved significantly by S3.
The FBEP improved N-RCOPE scores significantly, suggesting a more constructive
religious perspective on the circumstances or the condition that brought participants to the
FBEP. The DUREL Extrinsic Religiosity scores were not affected over time, whereas IR
scores—which correlate more closely with better health outcomes—did show a significant
increase from baseline.
Fig. 13 a STAI-T changes over time. In this figure, the embedded table shows the application of a multiple
comparison procedure to determine which means are significantly different from which others. The output
shows the estimated difference between each pair of means. The asterisk indicates statistically significant
differences at the 95.0 % confidence level. b STAI-T changes over time
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Limitations
As is not unusual for these studies, there was a 75 % attrition over the full study period.
With 92 % completing S2, however, the evidence supporting the initial impact of the
FBEP is strong. The evidence for enduring effects is weakened by the attrition over time,
although those who completed all 5 surveys (CMPL) did show lasting changes. The
attrition analysis did show that, with the exception of BIPQ changes from S1 to S2, the
LTFU and CMPL groups did not differ significantly from each other (Table 2). However, it
is obviously impossible to determine whether the LFTU group (n = 181) retained the
recorded changes through to S5, even though some did complete S3 (n = 69; 38 %) and
S4 (n = 22; 12 %), respectively, and changes in their respective scores were maintained
until their last completed survey.
It is unfortunate that the small number of female-only controls at S5 did not allow for a
meaningful case–control analysis. Comparisons between cases and controls at S1 did not
show any significant differences, however.
In addition, all the general strengths and weaknesses inherent to SAQ’s in assessing
health status apply to this study (Smith and Goldman 2011) and specifically for each of the
respective SAQ scales employed (Bergua et al. 2012; Broadbent et al. 2006; Choi et al.
2014; Cohen 1983; Cohen et al. 1995; Koenig and Bu
¨
ssing 2010; Kvaal et al. 2005;
Leventhal 1984; Oei et al. 1990; Pargament et al. 2000, 2011; Radloff 1977; Schein and
Koenig 1997; Tenenbaum et al. 1985).
The following potential biases were also identified, assessed and mitigated where
possible. Volunteer bias: For various reasons, persons who chose to enroll for the FBEP
may have differed from general population, thereby limiting the extent to which the data
can be extrapolated. Reassuringly, baseline SAQ data showed significant heterogeneity,
whereas demographic data analysis reflected a near-normal distribution by age and gender.
Self-selection bias: Persons opting to complete the survey may have differed from those
who chose not to. However, after the a priori exclusion of underage and previously
exposed individuals, only 21 % opted out of the study. As such, the study was able to
capture 79 % of the eligible participants during the study period. Computer-literacy bias:
Thirty-seven percent of the subjects enrolling for the study failed to complete and submit
the first SAQ successfully. Recent polls state that more than 50 % of US citizens above the
age of 65 years use the internet regularly, whereas more than 75 % under 65 years do.
Moreover, it is normative for approximately 97 % of all regular program registrations for
the FBEP to be received online. We were therefore surprised by the relatively high
‘‘failure’’ rate; a bias toward higher levels of computer literacy cannot be excluded.
Language bias: For practical reasons, and to ensure validity of the SAQ’s, the study was
limited to subjects with English language proficiency. As such, the results cannot be
generalized to non-English-speaking subjects. Vested interest bias: The primary investi-
gator, co-investigator and two of the co-authors have no organizational affiliations to Be in
Health Inc. nor any specific vested interest in the outcome of the study. However, two of
the researchers are current employees of Be in Health Inc. As such, every effort was made
to minimize vested interest bias by limiting personal interactions with subjects to the
initial, brief and carefully scripted on-site interview by the Research Coordinator and by
providing online access for direct entry of data by subjects. Further measures included:
blinding of the teachers and staff of the FBEP to avoid any differential attention being
given to the study participants; limiting all communication to generic, electronic and
merely instructional media; and forwarding any program-related enquiries from the
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participants directly to the Program Director without any interaction or revealing their
participation in the study. Religious bias: The FBEP is explicitly Christian in its religious
orientation. Gallup polls indicate that 77 % of US citizens identify as Christian (Newport
2012). Nevertheless, the program is more likely to attract individuals with higher levels of
F–R–S, and this probability is supported by the participants’ high DUREL scores.
Accordingly, the response to the program should not be extrapolated to individuals with
low levels of religiosity or to other persuasions of faith.
Conclusion
This study is important because it is a prospective intervention study. Conceptually, the
FBEP represents, as a standardized, short-term, intensive exposure, what might otherwise
be addressed within a conventional Faith-Based Community context by means of delib-
erate and specific emphasis on health and disease, emotional awareness and well-being,
relational competence, social support, and trauma- and health-oriented counseling and
prayer.
The findings of this study support the conclusion that attendance of this FBEP is
associated with prompt, mostly positive, and statistically and clinically significant changes
on the assessed spiritual, mental and physical health parameters, within a self-selected
group of participants, who were eligible, able and willing to complete all the surveys. For
them the changes also appeared to last over the full study period; only limited conclusions
are possible for those who did not.
Further analyses are planned to evaluate the differential impact on the various SAQ
parameters; to perform projected calculations of lowered morbidity and mortality as a
result of the observed changes; and to explore mechanisms for the observed changes. The
findings also support the conclusion that self-selected individuals attending the FBEP are
more likely to benefit than to be harmed by doing so.
The authors hope that this work will encourage more intervention studies of this nature.
Source of funding None. However, two co-authors are employees of Be in Health Inc. Thomaston, GA,
USA.
References
Bergua, V., Meillon, C., Potvin, O., Bouisson, J., Le Goff, M., Rouaud, O., & Amieva, H. (2012). The STAI-
Y trait scale: Psychometric properties and normative data from a large population-based study of
elderly people. International Psychogeriatrics, 24(7), 1163–1171. doi:10.1017/S1041610212000300.
Borras, L., Mohr, S., Brandt, P. Y., Gillieron, C., Eytan, A., & Huguelet, P. (2007). Religious beliefs in
schizophrenia: Their relevance for adherence to treatment. Schizophrenia Bulletin, 33(5), 1238–1246.
doi:10.1093/schbul/sbl070.
Broadbent, E., Kydd, R., Sanders, D., & Vanderpyl, J. (2008). Unmet needs and treatment seeking in high
users of mental health services: Role of illness perceptions. Australian and New Zealand Journal of
Psychiatry, 42(2), 147–153. doi:10.1080/00048670701787503.
Broadbent, E., Petrie, K. J., Main, J., & Weinman, J. (2006). The brief illness perception questionnaire.
Journal of Psychosomatic Research, 60(6), 631–637. doi:10.1016/j.jpsychores.2005.10.020.
Burns, V. E., Drayson, M., Ring, C., & Carroll, D. (2002). Perceived stress and psychological well-being are
associated with antibody status after meningitis C conjugate vaccination. Psychosomatic Medicine,
64(6), 963–970. Retrieved from http://www.hubmed.org/display.cgi?uids=12461201
Carpenter, L. L., Tyrka, A. R., McDougle, C. J., Malison, R. T., Owens, M. J., Nemeroff, C. B., & Price, L.
H. (2004). Cerebrospinal fluid corticotropin-releasing factor and perceived early-life stress in
J Relig Health
123
Author's personal copy
depressed patients and healthy control subjects. Neuropsychopharmacology, 29(4), 777–784. Retrieved
from http://www.hubmed.org/display.cgi?uids=14702025, http://www.nature.com/npp/journal/v29/n4/
pdf/1300375a.pdf
Choi, S. W., Schalet, B., Cook, K. F., & Cella, D. (2014). Establishing a common metric for depressive
symptoms: Linking the BDI-II, CES-D, and PHQ-9 to PROMIS depression. Psychological Assessment,
26(2), 513–527. doi:10.1037/a0035768.
Cohen, S. (1983). A global measure of perceived stress. Journal of Health and Social Behavior, 24, 385.
Cohen, S., & Janicki-Deverts, D. (2012). Who’s stressed? Distributions of psychological stress in the United
States in probability samples from 1983, 2006 and 2009. Journal of Applied Social Psychology, 42(6),
1320–1334.
Cohen, S., Kessler, R. C., & Underwood, L. G. (1995). Measuring stress: A guide for health and social
scientists. New York: Oxford University Press.
Cohen, S., Tyrrell, D. A., Russell, M. A., Jarvis, M. J., & Smith, A. P. (1993). Smoking, alcohol con-
sumption, and susceptibility to the common cold. The American Journal of Public Health, 83(9),
1277–1283. Retrieved from http://www.hubmed.org/display.cgi?uids=8363004, http://www.ncbi.nlm.
nih.gov/pmc/articles/PMC1694990/pdf/amjph00533-0087.pdf
Crawford, J., Cayley, C., Lovibond, P., Wilson, P., & Hartley, C. (2011). Percentile norms and accompa-
nying interval estimates from an Australian general adult population sample for self-report mood
scales. Australian Psychologist, 46, 3–14.
Cruess, D. G., Antoni, M. H., Kumar, M., Ironson, G., McCabe, P., Fernandez, J. B., … Schneiderman, N.
(1999). Cognitive-behavioral stress management buffers decreases in dehydroepiandrosterone sulfate
(DHEA-S) and increases in the cortisol/DHEA-S ratio and reduces mood disturbance and perceived
stress among HIV-seropositive men. Psychoneuroendocrinology, 24(5), 537–549. Retrieved from
http://www.hubmed.org/display.cgi?uids=10378240, http://www.psyneuen-journal.com/article/S0306-
4530(99)00010-4/abstract
Culhane, J. F., Rauh, V., McCollum, K. F., Hogan, V. K., Agnew, K., & Wadhwa, P. D. (2001). Maternal
stress is associated with bacterial vaginosis in human pregnancy. Maternal and Child Health Journal,
5(2), 127–134. Retrieved from http://www.hubmed.org/display.cgi?uids=11573838
Diego, M. A., Field, T., & Hernandez-Reif, M. (2001). CES-D depression scores are correlated with frontal
EEG alpha asymmetry. Depress Anxiety, 13(1), 32–37. Retrieved from http://www.ncbi.nlm.nih.gov/
pubmed/11233458, http://onlinelibrary.wiley.com/doi/10.1002/1520-6394(2001)13:1\32::AID-DA5[
3.0.CO;2-G/abstract
Ebrecht, M., Hextall, J., Kirtley, L.-G., Taylor, A., Dyson, M., & Weinman, J. (2004). Perceived stress and
cortisol levels predict speed of wound healing in healthy male adults. Psychoneuroendocrinology,
29(6), 798–809. Retrieved from http://www.hubmed.org/display.cgi?uids=15110929, http://www.
psyneuen-journal.com/article/S0306-4530(03)00144-6/abstract
Epel, E. S., Blackburn, E. H., Lin, J., Dhabhar, F. S., Adler, N. E., Morrow, J. D., & Cawthon, R. M. (2004).
Accelerated telomere shortening in response to life stress. Proceedings of National Academy of Sci-
ences USA, 101(49), 17312–17315. Retrieved from http://www.hubmed.org/display.cgi?uids=
15574496, http://www.pnas.org/content/101/49/17312.full.pdf
Fewtrell, M. S., Kennedy, K., Singhal, A., Martin, R. M., Ness, A., Hadders-Algra, M., … Lucas, A. (2008).
How much loss to follow-up is acceptable in long-term randomised trials and prospective studies?
Archives Disease in Childhood, 93(6), 458–461. doi:10.1136/adc.2007.127316
Grossoehme, D. H., VanDyke, R., & Seid, M. (2008). Spirituality’s role in chronic disease self-management:
Sanctification of the body in families dealing with cystic fibrosis. J Health Care Chaplain, 15(2),
149–158. doi:10.1080/08854720903163312.
Holzel, B. K., Carmody, J., Evans, K. C., Hoge, E. A., Dusek, J. A., Morgan, L., … Lazar, S. W. (2010).
Stress reduction correlates with structural changes in the amygdala. Social Cognitive and Affective
Neuroscience, 5(1), 11–17. Retrieved from http://www.hubmed.org/display.cgi?uids=19776221, http://
www.ncbi.nlm.nih.gov/pmc/articles/PMC2840837/pdf/nsp034.pdf
Kemppainen, J., Kim-Godwin, Y. S., Reynolds, N. R., & Spencer, V. S. (2008). Beliefs about HIV disease
and medication adherence in persons living with HIV/AIDS in rural southeastern North Carolina.
Journal of the Association of Nurses in AIDS Care, 19(2), 127–136. doi:10.1016/j.jana.2007.08.006.
Koenig, H. G. (2007). Physician’s role in addressing spiritual needs. The Southern Medical Journal, 100(9),
932–933. Retrieved from http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&
dopt=Citation&list_uids=17902307
Koenig, H. G., & Bu
¨
ssing, A. (2010). The Duke University Religion Index (DUREL): A five-item measure
for use in epidemological studies. Religions, 1(1), 78–85. Retrieved from http://www.mdpi.com/2077-
1444/1/1/78
J Relig Health
123
Author's personal copy
Kramer, J. R., Ledolter, J., Manos, G. N., & Bayless, M. L. (2000). Stress and metabolic control in diabetes
mellitus: methodological issues and an illustrative analysis. Annals of Behavioral Medicine, 22(1),
17–28. Retrieved from http://www.hubmed.org/display.cgi?uids=10892525
Kremer, H., Ironson, G., & Porr, M. (2009). Spiritual and mind-body beliefs as barriers and motivators to
HIV-treatment decision-making and medication adherence? A qualitative study. AIDS Patient Care
STDS, 23(2), 127–134. doi:10.1089/apc.2008.0131.
Kvaal, K., Ulstein, I., Nordhus, I. H., & Engedal, K. (2005). The Spielberger State-Trait Anxiety Inventory
(STAI): the state scale in detecting mental disorders in geriatric patients. International Journal of
Geriatric Psychiatry, 20(7), 629–634. doi:10.1002/gps.1330.
Leon, K. A., Hyre, A. D., Ompad, D., Desalvo, K. B., & Muntner, P. (2007). Perceived stress among a
workforce 6 months following hurricane Katrina. Social Psychiatry and Psychiatric Epidemiology,
42(12), 1005–1011. Retrieved from http://www.hubmed.org/display.cgi?uids=17932611, http://link.
springer.com/article/10.1007%2Fs00127-007-0260-6
Leventhal, E. A. (1984). Aging and the perception of illness. Research Aging, 6(1), 119–135. Retrieved from
http://www.ncbi.nlm.nih.gov/pubmed/6544973
Lyon, M. E., Garvie, P. A., Kao, E., Briggs, L., He, J., Malow, R., … McCarter, R. (2011). Spirituality in
HIV-infected adolescents and their families: FAmily CEntered (FACE) advance care planning and
medication adherence. Journal of Adolescent Health, 48(6), 633–636. doi:10.1016/j.jadohealth.2010.
09.006
Malarkey, W. B., Pearl, D. K., Demers, L. M., Kiecolt-Glaser, J. K., & Glaser, R. (1995). Influence of
academic stress and season on 24-h mean concentrations of ACTH, cortisol, and beta-endorphin.
Psychoneuroendocrinology, 20(5), 499–508. Retrieved from http://www.hubmed.org/display.
cgi?uids=7675934, http://www.psyneuen-journal.com/article/0306-4530(94)00077-N/abstract
McAlonan, G. M., Lee, A. M., Cheung, V., Cheung, C., Tsang, K. W. T., Sham, P. C., … Wong, J. G. W. S.
(2007). Immediate and sustained psychological impact of an emerging infectious disease outbreak on
health care workers. The Canadian Journal of Psychiatry, 52(4), 241–247. Retrieved from http://www.
hubmed.org/display.cgi?uids=17500305
Mellins, C. A., Havens, J. F., McDonnell, C., Lichtenstein, C., Uldall, K., Chesney, M., & Bell, J. (2009).
Adherence to antiretroviral medications and medical care in HIV-infected adults diagnosed with
mental and substance abuse disorders. AIDS Care, 21(2), 168–177. doi:10.1080/09540120802001705.
Newport, F. (2012). In US, 77 % Identify as Christian. Retrieved from http://www.gallup.com/poll/159548/
identify-christian.aspx from Gallup, Inc. http://www.gallup.com/poll/159548/identify-christian.aspx
Oei, T. P., Evans, L., & Crook, G. M. (1990). Utility and validity of the STAI with anxiety disorder patients.
British Journal of Clinical Psychology, 29(Pt 4), 429–432. Retrieved from http://www.ncbi.nlm.nih.
gov/pubmed/2289078
Pargament, K., Feuille, M., & Burdzy, D. (2011). The brief RCOPE: Current psychometric status of a short
measure of religious coping. Religions, 2(1), 51–76. Retrieved from http://www.mdpi.com/2077-1444/
2/1/51
Pargament, K. I., Koenig, H. G., & Perez, L. M. (2000). The many methods of religious coping: Devel-
opment and initial validation of the RCOPE. Journal of Clinical Psychology, 56(4), 519–543. doi:10.
1002/(SICI)1097-4679(200004)56:4\519:AID-JCLP6[3.0.CO;2-1.
Parsons, S. K., Cruise, P. L., Davenport, W. M., & Jones, V. (2006). Religious beliefs, practices and
treatment adherence among individuals with HIV in the southern United States. AIDS Patient Care
STDS, 20(2), 97–111. doi:10.1089/apc.2006.20.97.
Radloff, L. S. (1977). The CES-D scale: A self-report depression scale for research in the general popu-
lation.
Applied Psychological Measurement, 1, 385–401.
Schein, R. L., & Koenig, H. G. (1997). The Center for Epidemiological Studies-Depression (CES-D) Scale:
Assessment of depression in the medically ill elderly. International Journal of Geriatric Psychiatry,
12(4), 436–446. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/9178047, http://onlinelibrary.
wiley.com/doi/10.1002/(SICI)1099-1166(199704)12:4\436::AID-GPS499[3.0.CO;2-M/abstract
Smith, K. V., & Goldman, N. (2011). Measuring health status: Self-, interviewer, and physician reports of
overall health. Journal of Aging and Health, 23(2), 242–266. doi:10.1177/0898264310383421.
Spielberger, C. D. (1983). Manual for the State-Trait Anxiety Inventory. Palo Alto, CA: Consulting Psy-
chologists Press.
Stanley, M. A., Bush, A. L., Camp, M. E., Jameson, J. P., Phillips, L. L., Barber, C. R., & Cully, J. A.
(2011). Older adults’ preferences for religion/spirituality in treatment for anxiety and depression. Aging
and Mental Health, 15(3), 334–343. doi:10.1080/13607863.2010.519326.
Stansbury, J. P., Ried, L. D., & Velozo, C. A. (2006). Unidimensionality and bandwidth in the Center for
Epidemiologic Studies Depression (CES-D) Scale. Journal of Personality Assessment, 86(1), 10–22.
doi:10.1207/s15327752jpa8601_03.
J Relig Health
123
Author's personal copy
Stewart, D. E., & Yuen, T. (2011). A systematic review of resilience in the physically ill. Psychosomatics,
52(3), 199–209. doi:10.1016/j.psym.2011.01.036.
Stone, A. A., Mezzacappa, E. S., Donatone, B. A., & Gonder, M. (1999). Psychosocial stress and social
support are associated with prostate-specific antigen levels in men: Results from a community
screening program. Health Psychology, 18(5), 482–486. Retrieved from http://www.hubmed.org/
display.cgi?uids=10519464, http://psycnet.apa.org/journals/hea/18/5/482/
Storch, E. A., Strawser, M. S., & Storch, J. B. (2004). Two-week test-retest reliability of the Duke Religion
Index. Psychological Reports, 94(3 Pt 1), 993–994. Retrieved from http://www.hubmed.org/display.
cgi?uids=15217062
Tenenbaum, G., Furst, D., & Weingarten, G. (1985). A statistical reevaluation of the STAI anxiety ques-
tionnaire. Journal of Clinical Psychology, 41(2), 239–244. Retrieved from http://www.ncbi.nlm.nih.
gov/pubmed/3980747
J Relig Health
123
Author's personal copy
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