Religious coping is differentially associated with physiological

Prévia do material em texto

Religious coping is differentially associated with physiological 
and subjective distress indicators: Comparing cortisol and self-
report patterns
Alison M. Haney1, Sean P. Lane2
1Department of Community Health and Health Behavior, School of Public Health and Health 
Professions, University at Buffalo, The State University of New York
2Department of Psychological Sciences, University of Missouri
Abstract
Use of religious coping in response to life stress is associated with improved mental and physical 
health outcomes. The aim of this study was to examine the influence of religious coping on 
conscious self-reported and non-conscious physiological stress responses to an acute, real-world 
stressor to better understand how this benefit may be conferred. This study examined the trajectory 
of subjective distress and cortisol patterns leading up to and following a stressful college exam 
using daily diary and ambulatory saliva samples, respectively (N students = 246). Religious coping 
was not significantly associated with subjective reports of distress. However, prior to the exam, 
greater use of religious coping was associated with an ostensibly more adaptive accelerated return 
to a cortisol baseline. This protective effect was no longer significant when the exam was over, 
suggesting that religious coping acts as a protective buffer against physiological stress responses 
rather than aiding in subjective recovery from stress.
Keywords
Coping; Daily Diary; Religion; Salivary Cortisol; Stress
Introduction
Involvement in religion is associated with enhanced positive psychological states, stress-
buffering, and protection against negative psychological states.1 Turning to religion as a 
form of distress tolerance is an adaptive strategy that may support overall well-being and 
buffer against maladaptive behaviors and mental health difficulties.2 Several mechanisms 
have been proposed to explain how religiosity may improve mental and physical health 
outcomes, including social support through involvement in a religious community, use 
of positive religious coping (e.g., turning to the divine for help) to manage distress, 
Corresponding author: Correspondence concerning the article should be addressed to Alison M. Haney amhaney@buffalo.edu Phone: 
(716) 829-6770, 323 Kimball Tower, Buffalo, New York 14214) or Sean P. Lane (lanesp@missouri.edu Phone: (573) 882-8065, 
Department of Psychological Sciences, McAlester Hall, Room 110, Columbia, MO 65203). 
Declarations
Competing interests: The authors declare that they have no conflict of interest.
HHS Public Access
Author manuscript
Behav Med. Author manuscript; available in PMC 2025 October 01.
Published in final edited form as:
Behav Med. 2024 ; 50(4): 312–320. doi:10.1080/08964289.2023.2277926.
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reduction in existential uncertainty, and participation in religious rituals that may activate 
self-monitoring and regulation.3–6 More recently, research has begun to examine health-
relevant physiological correlates of religiosity that may account for its influence.
Religion, as a buffer against psychological stress, has also been found to impact 
physiological indicators of stress, such as heart rate, blood pressure, and cortisol levels.1 
In a sample of individuals with HIV/AIDS, higher levels of religiosity, and a sense of 
peace from religion, and faith in God, specifically, was associated with lower levels of 
urinary cortisol and lower levels of psychological distress and mental health problems.7 
The association between religiosity and long-term survival in this sample was mediated by 
optimism, altruistic behaviors, and cortisol concentration.7
In addition to overall chronic and/or stable levels of cortisol, religiosity may be associated 
with more acute adaptive daily diurnal cortisol reactive changes. In a sample of women with 
fibromyalgia, a disorder marked by endocrine and psychological stress, those with higher 
reported intrinsic religiosity (e.g., internal thoughts of a personal connection to the divine) 
and non-organizational religiosity (e.g., private prayer) had steeper diurnal cortisol slopes, 
while those with lower reported religiosity showed a more flattened slope.8 Here, steeper 
slopes are considered to indicate a quicker return to homeostatic baseline, signifying more 
functional stress regulation.9 This pattern remained after statistically adjusting for social 
support. However, levels of intrinsic and non-organizational religiosity were not associated 
with a reduction in self-reported perceived stress.
Religious affiliation has been found to predict this steeper diurnal cortisol slope 10 years 
later, even when adjusting for general emotional coping and social support.10 Participation 
in specific religious activities also has been found to be associated with diurnal cortisol 
patterns consistent with adaptive regulation. One ethnographic study of indigenous Sahariya 
refugees in central India found that over a nine-day period of group religious rituals, the 
magnitude of difference between morning and evening cortisol levels increased, reflecting a 
more adaptive peak-deviation cortisol arousal response.11 This corresponded with increased 
subjective psychological well-being on group ritual days, particularly among those with 
higher levels of economic insecurity, suggesting that religious affiliation may buffer against 
other stressors that have documented stress-impairing consequences.11
Research on the connection between religion and cortisol has largely focused on chronic 
stressors such as illness, though there has been some examination of more acute stressors 
that impact individuals for a short duration but then may have both short- and long-term 
consequences, such as public speaking. For acute stress, the connection between religion 
and cortisol levels has been examined in the context of laboratory-based stress-induction 
tasks. One study found that low to moderate levels of baseline/pre-stress cortisol levels 
were associated with greater church attendance.12 However, religious participation was not 
associated with the trajectory of cortisol during the stress task when estimated alongside 
baseline cortisol and demographic variables in a regression model (none of the model 
variables reached statistical significance). The stress task used in this study (the Trier 
Social Stress Test) is designed to increase cortisol levels then return them to baseline 
over approximately 75 minutes. These results suggest that cortisol levels taken during an 
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acute stress task may not be significantly related to religious participation when considered 
alongside baseline cortisol and other demographic variables.
In another study with a laboratory stress task, religious participation (as measured by 
frequency of service attendance) alone did not predict cortisol responses.13 However, those 
with higher levels of religiously-motivated forgiveness and frequency of prayer showed 
significantly lower cortisol responses to the stress-inducing task.13 This suggests that 
dimensions other than frequency of service attendance, such as intrinsic religiosity, may 
be more strongly related to cortisol responses to acute stressors. The impact of religious 
coping on time-bound stressors that may exert influence over the course of a day or several 
weeks is still unclear.
This study seeks to examine the role of religious coping when dealing with short-term, 
real-life stressors. Specifically, the influence of religious coping is examined before and 
after a stressful, time-limited event, with stress measured both by a physiological indicator 
and a subjective indicator. Notably, the impact of the stressoris assessed over the course 
of continuous days, which examines a different timescale of both cortisol and self-report 
response profiles than the reviewed experimental paradigms that operate on the order of 
minutes to hours. By using this design, it is possible to determine whether religious coping 
differentially influences reactions to a non-chronic life stressor and begin to elucidate 
a possible physiological contribution of religiosity to ecologically valid subjective and 
physical well-being over time.
Methods
Participants
Participants were college students preparing for premedical midterm science examinations. 
Informed consent was obtained from each participant, and all procedures were approved 
by the New York University and Columbia University Institutional Review Boards. A 
total of 246 individuals were initially recruited to participate in a two-week diary study 
(see Table 1 for demographic information). The study included three components: a 
background questionnaire, diary reports, and cortisol assessments. Two hundred and thirty-
four individuals completed the background questionnaire, which contained demographic 
information, psychological functioning, coping style, and personality measures. The daily 
diary portion consisted of morning and evening reports of mood, health, and interpersonal 
functioning. We restrict our analyses to the 228 participants who completed at least one 
diary.
In addition to the diary protocol, an a priori random subset of participants (N = 81) were 
invited to also provide multiple saliva samples per day to estimate diurnal cortisol levels. In 
the daily diary study, participants were primarily women (70.1%), with an average age of 
20.1 years, and most identified their ethnicity as Asian (44.1%) or White (42.0%). The most 
commonly reported religious affiliations were Catholic (21.2%) and Protestant (16.0%), 
with 38.1% of the sample reporting that they did not belong to any religion. The cortisol 
subsample demographics were not significantly different than the whole sample in terms of 
demographics or other variables of interest.
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Daily Diary Procedure
Participants were randomly assigned to start the diary survey between 8 and 2 days before 
the selected midterm exam that they reported being the most stressful, only if they were 
enrolled in more than one qualifying premedical course. Regardless of the day participants 
started, each person completed a morning and an evening diary for at least 14 consecutive 
days, such that participants who started the daily diaries 2 days before the exam completed 
diaries until 11 days after the exam, and those that started 8 days before the exam completed 
diaries until 5 days after the exam. Morning diary surveys were completed online via an 
emailed web link using a smart phone or personal computer at the time the participant 
awoke, and evening diaries were completed via the same method before the participant went 
to bed. For additional details, refer to work by Shrout and colleagues.14
Cortisol Procedure
As part of an independent nested experimental study design, participants provided saliva 
samples for either, 1) 5 consecutive days before the exam and 5 consecutive days following 
the exam, starting 2 days after the exam day, or 2) 2 consecutive days before and after the 
exam with a gap of 5 days in between, starting either 5, 4, 3, or 2 days before the exam. 
Participants provided 4 samples per day: upon waking, 30-min post-waking, before lunch, 
and before bedtime. Saliva was obtained using salivette collection devices and cotton swabs 
(Sarstedt, Numbrecht, Germany). Participants received written instructions and color-coded 
and numbered salivettes and completed a written log at each collection time providing 
information about the exact time of the collection, sleeping patterns, eating behaviors, 
medication, caffeine, and alcohol use, and other adjustment variables (e.g., chewing gum 
or brushing teeth). Saliva samples were stored in individuals’ home refrigerators until they 
were returned to the principal investigators to store at −20°C until all samples were collected 
and shipped for processing.
Upon completion of the saliva sampling procedure, the salivettes were shipped to the 
MIDUS Biological Core at the University of Wisconsin, where they were stored at −60°C. 
For analysis, salivettes were thawed and centrifuged at 3000 rpm for 5 min, yielding a 
clear fluid with low viscosity. Cortisol concentrations were quantified with a commercially 
available luminescence immunoassay (IBL, Hamburg, Germany), with intra-assay and inter-
assay coefficient of variations below 5%.15 A random subset of 10% of all saliva samples 
were double-assayed to estimate measurement reliability, which was r = .99. While a 
number of factors can influence cortisol levels, in healthy adults, cortisol levels are typically 
10–27 μg/dL in the morning after waking and 2–4 μg/dL in the evening.16
Measures
Religious Coping—Religious coping was assessed at baseline using the “turning to 
religion” items on the COPE, an inventory of coping strategies.17 These items (e.g., “I seek 
God’s help”) were rated on a 4-point Likert scale from 0 (“I usually don’t do this at all”) 
to 3 (“I usually do this a lot”). To reduce participant burden, only two items that were 
consistently the highest loading in the original study and replications were administered. 
In this sample, the mean for the religious coping subscale was 0.76 (SD = 1.07). The 
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correlation between the two religious coping items on the COPE was r = 0.91 (pacross days 
(morning Rc = 0.80, evening Rc = 0.82).
Analytic Plan
Multilevel modeling (MLM) was used to examine the influence of religious coping on 
daily measures of cortisol and subjective distress, using SAS PROC MIXED (v9.4; SAS 
Institute).21 Our sample size was selected so that effect sizes of d = .23 would be 82% 
powered. In our first model with cortisol as the outcome, we utilized a 3-level model 
(moments nested within days, days within participants), as there were 4 collection times 
per day and 4/10 days of data collection per participant. In this 3-level model, cortisol 
estimates would be interpreted as the level of cortisol at a given time on a given day for 
a given individual. The model for cortisol included a time-coded variable to represent the 
morning cortisol response (“Peak”), data collection time adjusted for deviations in initial 
time at waking (“Time”), and collection time squared (“Time2”). Religious coping, the 
interaction of religious coping and cortisol peak, and the interaction of religious coping 
and time (and with time2) were included to determine the impact of religious coping on 
cortisol trajectories over the course of the day. Covariates included gender (0 = man, 1 
= woman), a dichotomous religion variable (0 = not religious, 1 = religious), and several 
cortisol-relevant variables to adjust for confounding influences (medication use, overall 
health, hours of sleep, consumption of sour food, chewing gum, brushing teeth, and time 
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of awakening; consistent with work by Stawski and colleagues).22 In order to examine 
differences between the pre- and post-exam period, interactions were included between each 
variable in the model and dichotomous variables representing whether a given measurement 
occasion was before (“pre”) or after the exam (“post”). Random intercepts for person and 
day were also included in the model. Random slopes were included for peak, time, time2, 
pre-, and post-exam to account for expected non-random variation by measurement time due 
to person-specific diurnal cortisol patterns.
Subjective distress was modeled using a 2-level mixed-effects design, with moments nested 
within participants. Therefore, subjective distress estimates are interpreted as the level of 
subjective distress at a given measurement occasion for a given individual. The model 
predicting subjective distress included the number of days before or after the exam (−8 to 
11; “Day”), whether the diary was completed on a weekday or weekend (0 = weekday, 
1 = weekend; “Weekend”), whether it was completed in the morning or the evening (1= 
morning, 0 = evening; “Time of Day”), and the same gender and dichotomous religion 
variables used in the cortisol model. The predictor of interest was religious coping, and 
interactions between religious coping and day, and religious coping and time of day were 
also included. As in the cortisol model, each variable was simultaneously estimated by 
pre- and post-exam. Finally, the model included a random intercept for person, along with 
random slopes for day, time of day, pre-, and post-exam.
Results
Cortisol
Table 2 presents fixed-effect estimates from the model predicting cortisol levels before 
and after the exam. Cortisol assessments displayed the well-established within-person/day 
pattern of acute elevation following waking (b = 4.54, t(76) = 5.99, pwas due to differences between individuals. At post-exam, the variance due to 
individual differences was 57.4%. This shift is the reverse of what was observed in pre- 
versus post-exam cortisol response variability, which may inform the veridicality, or at least 
the multidimensionality, of stress experiences as they are operationalized in psychological 
research.
Discussion
These findings indicate that the impact of religious coping on well-being varies both as 
a function of particular indicator (cortisol vs. subjective distress), and as a function of 
stress context. In this study, religious coping was associated with cortisol levels, in a 
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suggestively adaptive way, only during a period of acute stress, in the days leading up to 
an important exam; but it was not predictive of cortisol after the exam, when individuals 
would be recovering from a stressful period. While this might suggest that religious coping 
is not associated with cortisol levels outside of a stressful period, extant literature does not 
necessarily bear this out. Instead, these findings may indicate that religious coping is not a 
significant predictor of stress recovery from a time-limited stressor but rather pre-emptive 
stress-buffering, consistent with decades of theory but little direct evidence until now.23
The way that religion was associated with cortisol during the pre-exam period offers some 
insight into the nature of this association. Those who reported higher levels of religious 
coping also had higher overall cortisol levels (though they did not have higher daily peaks). 
Individuals often increase their use of religious coping in response to life stress, and prior 
research on cortisol and coping has similarly found that using more coping techniques than 
typical is associated with increased cortisol levels.3,24 It is important to note that simply 
identifying as religious was not associated with cortisol during this exam stress phase, 
suggesting that using religious coping is unique from religious affiliation more generally 
in predicting cortisol. Importantly, religious coping seems to be used effectively to manage 
cortisol, as those who endorsed higher levels of religious coping also had overall steeper 
declines and faster asymptotes in cortisol levels over the course of the day than those with 
lower levels of religious coping, regardless of mean cortisol level.
While religious coping was significantly associated with the physical stress response of 
individuals as they were approaching a significant stressor versus when they were recovering 
from it, religious coping was not associated with changes or differential trajectories 
in subjective reports of distress. These findings align with other literature identifying 
differences between physiological and subjective stress correlates of religious coping.8,13 
These results are also consistent with literature indicating that religion may primarily act as 
a buffer against negative mental health outcomes (e.g., depression), rather than improving 
general mental functioning and well-being.25,26
There are several limitations to the current study, including that only one dimension of 
religious coping was captured. These data did not capture negative religious coping, a 
form of religious coping that involves feelings of persecution and abandonment. While 
religious individuals may differ in whether they use negative religious coping concurrently 
with positive religious coping, extant research suggests the two forms of coping may 
interact in clinically meaningful ways.27 Future work should include multidimensional 
measures of religious faith in order to determine what aspects of religiosity may most 
influence these stress-relevant processes. Additionally, there may be some unique properties 
of performance-based stress that are being captured in this study. While there was variability 
between subjects in their reports of religious coping and cortisol levels, on average this 
sample endorsed using religious coping only occasionally and had cortisol levels within a 
healthy range.16 The average level of stress reported by the sample was relatively low, and it 
is possible that these associations may differ during higher-stress events.
This sample was primarily composed of young, mostly white students, and those who 
identified as religious primarily identified as Catholic or Protestant. This limits our ability 
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to generalize these findings to other sociocultural groups or religious traditions. Importantly, 
this study lacked adequate power to examine group-level differences in religious affiliation 
and ethnicity, which are two highly interwoven factors known to contribute to the 
association between religion and health.28 Further, more representative research is necessary 
in order to comprehensively map the manifold of associations linking religiosity and health 
outcomes, especially given disparities in healthcare access that have robust epidemiological 
correlations with ideological markers. The initial patterns identified in this study warrant 
additional consideration, as these factors may influence the degree to which religion reduces 
cortisol levels.
Conclusions
The current study uniquely examines the impact of religious coping on a real-life acute, 
not chronic, stressor. These findings suggest that even when an individual does not 
perceive changes in their mental state, religious coping is still significantly associated 
with and may play a regulatory role in reducing cortisol levels. Of clinical relevance, 
this protective influence may buffer against future mental and physical health problems, 
and healthcare providers may consider inquiring about positive religious coping as part 
of their overall stress assessment of an individual. Researchers seeking to understand 
how religion influences health should consider measuring both self-reported and relevant 
physiological indicators, as our findings demonstrate the potential for distinct patterns. 
Clarifying the association identified in this study may improve our understanding of how 
religion influences long-term physical and mental health outcomes.
Supplementary Material
Refer to Web version on PubMed Central for supplementary material.
Funding:
This research was supported by the National Institutes of Health research grants R01 AA017672 (Shrout), R01 
AA027264 (Lane/Hennes), and T32 AA013526 (McCarthy/Sher).
References
1. Hood RW, Hill PC, Spilka B. The Psychology of Religion: An Empirical Approach. 4th ed. Guilford 
Press; 2009.
2. Pargament KI, Smith BW, Koenig HG, Perez L. Patterns of positive and negative religious coping 
with major life stressors. Soc Sci Study Relig. 1998;37(4):710–724. doi:10.2307/1388152
3. Pargament KI, Koenig HG, Perez LM. The many methods of religious coping: Development 
and initial validation of the RCOPE. J Clin Psychol. 2000;56(4):519–543. doi:10.1002/
(SICI)1097-4679(200004)56:43.0.CO;2-1 [PubMed: 10775045] 
4. Pargament KI, Magyar-Russell GM, Murray-Swank NA. The sacred and the search for 
significance: Religion as a unique process. J Soc Issues. 2005;61(4):665–687. doi:10.1111/
j.1540-4560.2005.00426.x
5. McCullough ME, Willoughby BLB. Religion, self-regulation, and self-control: Associations, 
explanations, and implications. Psychol Bull. 2009;135(1):69–93. doi:10.1037/a0014213 [PubMed: 
19210054] 
Haney and Lane Page 9
Behav Med. Author manuscript; available in PMC 2025 October 01.
A
uthor M
anuscript
A
uthor M
anuscript
A
uthor M
anuscript
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uthor M
anuscript
6. Monteiro LM. Dharma and distress:Buddhist teachings that support the psychological principles 
in a mindfulness program. In: Shonin E, Van Gordon W, Singh NN, eds. Buddhist Foundations of 
Mindfulness. Springer International; 2015:181–215. doi:10.1007/978-3-319-18591-0_10
7. Ironson G, Solomon GF, Balbin EG, et al. The Ironson-Woods Spirituality/Religiousness Index 
is associated with long survival, health behaviors, less distress, and low cortisol in people with 
HIV/AIDS. Ann Behav Med. 2002;24(1):34–48. doi:10.1207/S15324796ABM2401_05 [PubMed: 
12008793] 
8. Dedert EA, Studts JL, Weissbecker I, Salmon PG, Banis PL, Sephton SE. Religiosity may 
help preserve the cortisol rhythm in women with stress-related illness. Int J Psychiatry Med. 
2004;34(1):61–77. doi:10.2190/2Y72-6H80-BW93-U0T6 [PubMed: 15242142] 
9. Lee DY, Kim E, Choi MH. Technical and clinical aspects of cortisol as a biochemical marker 
of chronic stress. BMB Rep. 2015;48(4):209–216. doi:10.5483/BMBRep.2015.48.4.275 [PubMed: 
25560699] 
10. Tobin ET, Slatcher RB. Religious participation predicts diurnal cortisol profiles 10 years later 
via lower levels of religious struggle. Health Psychol. 2016;35(12):1356–1363. doi:10.1037/
hea0000372 [PubMed: 27280366] 
11. Snodgrass JG, Most DE, Upadhyay C. Religious ritual is good medicine for indigenous Indian 
conservation refugees: Implications for global mental health. Curr Anthropol. 2017;58(2):257–
284. doi:10.1086/691212
12. French JA, Smith KB, Alford JR, Guck A, Birnie AK, Hibbing JR. Cortisol and politics: Variance 
in voting behavior is predicted by baseline cortisol levels. Physiol Behav. 2014;133:61–67. 
doi:10.1016/j.physbeh.2014.05.004 [PubMed: 24835544] 
13. Tartaro J, Luecken LJ, Gunn HE. Exploring heart and soul: Effects of religiosity/spirituality and 
gender on blood pressure and cortisol stress responses. J Health Psychol. 2005;10(6):753–766. 
doi:10.1177/1359105305057311 [PubMed: 16176954] 
14. Shrout PE, Stadler G, Lane SP, et al. Initial elevation bias in subjective reports. Proc Natl Acad Sci 
U S A. 2018;115(1):E15–E23. doi:10.1073/pnas.1712277115 [PubMed: 29255039] 
15. Dressendörfer RA, Kirschbaum C, Rohde W, Stahl F, Strasburger CJ. Synthesis of a cortisol-biotin 
conjugate and evaluation as a tracer in an immunoassay for salivary cortisol measurement. J 
Steroid Biochem Mol Biol. 1992;43(7):683–692. doi:10.1016/0960-0760(92)90294-s [PubMed: 
1472460] 
16. Laudat MH ,Cerdas S, Fournier C, Guiban D, Guilhaume B, Luton JP. Salivary cortisol 
measurement: a practical approach to assess pituitary-adrenal function. J Clin Endocrinol Metab. 
1988;66(2):343–348. doi:10.1210/jcem-66-2-343 [PubMed: 2828410] 
17. Zuckerman M, Gagne M. The COPE revised: Proposing a 5-factor model of coping strategies. J 
Res Personal. 2003;37:169–204. doi:10.1016/S0092-6566(02)00563-9
18. McNair DM, Lorr M, Droppleman LF. Manual for the Profile of Mood States. Educational and 
Industrial Testing Service; 1971.
19. Bolger N, Zuckerman A, Kessler RC. Invisible support and adjustment to stress. J Pers Soc 
Psychol. 2000;79(6):953–961. doi:10.1037/0022-3514.79.6.953 [PubMed: 11138764] 
20. Cranford JA, Shrout PE, Iida M, Rafaeli E, Yip T, Bolger N. A procedure for evaluating sensitivity 
to within-person change: Can mood measures in diary studies detect change reliably? Pers Soc 
Psychol Bull. 2006;32(7):917–929. doi:10.1177/0146167206287721 [PubMed: 16738025] 
21. Snijders TAB, Bosker RJ. Multilevel Analysis: An Introduction to Basic and Advanced Multilevel 
Modeling. 2nd ed. Sage Publications; 2012.
22. Stawski RS, Cichy KE, Piazza JR, Almeida DM. Associations among daily stressors and salivary 
cortisol: Findings from the National Study of Daily Experiences. Psychoneuroendocrinology. 
2013;38(11):2654–2665. doi:10.1016/j.psyneuen.2013.06.023 [PubMed: 23856186] 
23. Cohen S, Wills TA. Stress, social support, and the buffering hypothesis. Psychol Bull. 
1985;98(2):310–357. doi:10.1037/0033-2909.98.2.310 [PubMed: 3901065] 
24. Sladek MR, Doane LD, Luecken LJ, Eisenberg N. Perceived stress, coping, and cortisol reactivity 
in daily life: A study of adolescents during the first year of college. Biol Psychol. 2016;117:8–15. 
doi:10.1016/j.biopsycho.2016.02.003 [PubMed: 26876116] 
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25. Haney AM, Rollock D. A matter of faith: The role of religion, doubt, and personality in emerging 
adult mental health. Psychol Relig Spiritual. 2020;12(2):247–253. doi:10.1037/rel0000231
26. Soenke M, Landau MJ, Greenberg J. Sacred armor: Religion’s role as a buffer against the anxieties 
of life and the fear of death. In: Pargament KI, ed. APA Handbook of Psychology, Religion, 
and Spirituality (Vol 1): Context, Theory, and Research. American Psychological Association; 
2013:105–122. doi:10.1037/14045-005
27. O’Brien B, Shrestha S, Stanley MA, et al. Positive and negative religious coping as predictors 
of distress among minority older adults. Int J Geriatr Psychiatry. 2019;34(1):54–59. doi:10.1002/
gps.4983 [PubMed: 30375027] 
28. Sternthal MJ, Williams DR, Musick MA, Buck AC. Religious practices, beliefs, 
and mental health: Variations across ethnicity. Ethn Health. 2012;17(1–2):171–185. 
doi:10.1080/13557858.2012.655264 [PubMed: 22296590] 
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Figure 1. 
Pre- and Post-Exam Cortisol Trajectories By Religious Coping
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Figure 2. 
Religious coping and subjective distress: All participants and cortisol participants.
Note. Low, average, and high cortisol and religious coping scores defined as −1 SD, sample 
mean, and +1 SD respectively
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Table 1
Demographic Characteristics of Sample (Daily Diary) and Cortisol Sub-Sample
Daily Diary (N = 246) Cortisol (N = 81)
Mean SD Mean SD
 Age 20.1 2.0 20.0 2.2
 Ethnicity n % n %
Asian 102 44.16 41 51.25
White/European American 97 41.99 27 33.75
Other 27 11.69 10 12.50
Hispanic 29 12.72 9 11.25
Black/African American 19 8.23 6 7.50
American Indian or Alaska Native 6 2.60 3 3.75
Hawaiian/Pacific Islander 3 1.30 1 1.25
 Gender n % n %
Women 162 70.13 53 66.25
Men 69 29.87 27 33.75
 Religious Affiliation n % n %
None 88 38.10 31 38.75
Christian - Catholic 49 21.21 15 18.75
Christian - Protestant 37 16.02 15 18.75
Other 18 7.79 5 6.25
Jewish 14 6.06 4 5.00
Muslim 13 5.63 4 5.00
Hindu 12 5.19 6 7.50
Notes. SD = standard deviation; Daily diary and cortisol sub-sample did not significantly differ on any demographic variables (all ps > .05)
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Table 2
Fixed Effect Estimates of Cortisol Levels Simultaneously Estimated at Pre- and Post-Exam
Pre-Exam Post-Exam Pre/Post Difference
Effect b SE t b SE t b SE t
Intercept 15.61*** 1.65 9.46 12.32*** 2.01 6.13 3.29 2.60 1.27
Peak 4.54*** 0.76 5.99 4.67*** 0.79 5.91 −0.13 1.10 −0.12
Time −1.18*** 0.09 −13.3 −1.18*** 0.11 −10.5 −0.01 0.14 −0.04
Time2 0.04*** 0.00 8.00 0.04*** 0.01 6.44 −0.00 0.01 −0.34
RC 1.12** 0.42 2.66 0.85 0.50 1.71 0.27 0.65 0.41
Peak*RC 0.00 0.68 0.01 0.42 0.72 0.59 −0.42 0.99 −0.42
Time*RC −0.36*** 0.09 −3.87 −0.19 0.10 −1.87 −0.16 0.14 −1.18
Time2*RC 0.02*** 0.00 3.70 0.01 0.01 1.40 0.01 0.01 1.34
Gender 0.78 0.70 1.11 1.01 0.89 1.13−0.23 1.14 −0.20
Relig −0.55 0.81 −0.69 −1.24 1.02 −1.22 0.69 1.30 0.53
Meds 1.18 0.75 1.57 1.66 0.97 1.71 −0.47 1.23 −0.39
Health −1.13** 0.38 −3.01 −0.94 0.48 −1.94 −0.19 0.61 −0.32
Sleep 0.08 0.13 0.63 0.34 0.18 1.93 −0.26 0.22 −1.19
Food: Sour 0.53 1.87 0.28 4.96** 1.62 3.06 −4.43 2.48 −1.79
Food: Gum −0.34 0.51 −0.65 0.91 1.32 0.69 −1.24 1.41 −0.88
Brush 0.70 0.79 0.89 3.02*** 0.83 3.64 −2.32* 1.15 −2.03
WakeTime −0.35** 0.13 −2.78 −0.24 0.16 −1.54 −0.10 0.20 −0.52
Notes. RC = Religious Coping; Relig = Religious (0=No, 1=Yes); Brush = Brushed Teeth; WakeTime = Time Awake;
*
p