GOING BEYOND POSITIVE AND NEGATIVE
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and may not exactly replicate the final, authoritative version of the article. Please
do not copy or cite without authors' permission. The final article will be available,
upon publication, via its DOI: 10.1037/rel0000310
GOING BEYOND POSITIVE AND NEGATIVE
Going Beyond Positive and Negative: Clarifying Relationships of Specific Religious Coping
Styles with Posttraumatic Outcomes
Curtis Lehmann and Emma Steele
Azusa Pacific University
GOING BEYOND POSITIVE AND NEGATIVE
Abstract
Religion and spirituality provide coping resources that are associated with outcomes
following a trauma, including posttraumatic stress and posttraumatic growth. Although religious
coping was initially conceptualized by Pargament (1997) as a set of 21 constructs, most
researchers have favored a brief assessment of the two higher order constructs, positive and
negative religious coping. This brief measure has popularized research on religious coping but
the tradeoff has been that findings are restricted to these higher-order constructs, rather than the
actual coping methods. As a result, findings are difficult to apply to clinical interventions, to
religious settings, and in refining theory. This research study was designed to help address this
shortcoming in the literature by modeling posttraumatic stress (PTS) symptoms and perceived
posttraumatic growth (PPTG). The study was composed of two samples of trauma-exposed
individuals: 286 participants from Amazon’s MTurk and 308 undergraduate students at a faith
based university. Participants completed measures of traumatic experiences, PTSD symptoms,
PPTG, and the full Religious Coping Inventory. Multiple penalized regressions were conducted
to develop models of religious coping methods that were strongly linked to PTSD symptoms and
posttraumatic growth. The models that were developed included variables both positively and
negatively associated with PTS and PPTG, identifying specific relationships between the
constructs, such as the negative association between active surrender and PTS. The results
provide guidance for researchers, therapists, and religious leaders who aim to minimize
posttraumatic stress responses and to facilitate posttraumatic growth.
Keywords: Spirituality, religious coping, posttraumatic stress, posttraumatic growth, trauma
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Introduction
Traumatic events have been found to be associated with a wide array of physiological,
psychological, and interpersonal consequences. Traumatic events have been found to be
associated with changes in hypothalamic-pituitary-adrenal axis functioning (Jones & Moller,
2011), world assumptions (Nygaard & Heir, 2012), personal identity (Bernsten & Rubin, 2007),
and relationship satisfaction (Goff, Crow, Reisbig, & Hamilton, 2007). Notably, posttraumatic
stress disorder can be an associated outcome of a trauma. Posttraumatic stress (PTS) has been
defined as a stress reaction to a traumatic event with symptoms of increased arousal, negative
cognitions and mood, intrusive thoughts, and avoidance (APA, 2013). An individual who
experiences clinically significant distress from these PTS symptoms may be diagnosed with
posttraumatic stress disorder (APA, 2013) but other serious mental disorders can emerge
following a severe adverse event (Allen, 2001).
Although research has focused primarily on these adverse outcomes, others have noted
that positive outcomes can occur following trauma, including improved psychological
adjustment (Joseph & Linley, 2008; Tedeschi & Calhoun, 1996). This research led to the
conceptual development of posttraumatic growth, defined as positive change as the result of a
traumatic experience (Tedeschi & Calhoun, 2004). The Posttraumatic Growth Inventory (PTGI,
Tedeschi & Calhoun, 1996) was a self-report scale developed to assess this construct.
Although widely utilized, some researchers have found limited evidence of the construct
validity of the PTGI - arguing instead that simple optimism or cognitive dissonance accounts for
the perception of growth following trauma (Blix, Hansen, Birkeland, Nissen, & Heir, 2013).
Other researchers have defended the PTGI by looking for corroboration of posttraumatic growth
from sources other than self-report. One such study asked the significant others of trauma
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survivors to report on whether their partner had developed virtues and strengths after
experiencing a traumatic event, and asked them to provide details of these developments
(Shakespeare-Finch & Barrington, 2012). This method was not only able to find evidence for
posttraumatic growth without utilizing self-report, but also found evidence in support of the self-
report nature of the PTGI (Shakespeare-Finch & Enders, 2008). Nevertheless, there continues to
be intense debate on the nature of posttraumatic growth and epistemological approaches to
assessing it (e.g., Blackie & Jayawickreme, 2014).
Regardless of how strongly perceived growth corresponds with actual growth, the
perception of growth following trauma is an important construct to study. This perceived
posttraumatic growth (PPTG) has been seen in many populations, such as cancer patients and
first responders (Park, Chmielewski, & Blank, 2009; Shakespeare-Finch, Smith, Gow, Embelton,
& Baird, 2003). PPTG can include an increased sense of personal strength, improved
relationships with others, a perceived increase in opportunities, an increased appreciation for life,
and a deepening of one’s faith or spirituality (Taku, Cann, Calhoun, & Tedeschi, 2008).
One important consideration is that PTS and PPTG are not mutually exclusive but are
actually two independent constructs with an intricate relationship (Shand, Cowlishaw, Brooker,
Burney, & Ricciardelli, 2015). For instance, studies have demonstrated that the relationship
between PTS and PPTG is curvilinear, with PTS and PPTG being positively associated at low to
moderate levels of PPTG but negatively associated at high levels of PPTG (Kleim & Ehlers,
2009; Thomas & Savoy, 2014). Given the complex relationships between these constructs and
the ethical imperative to promote beneficial outcomes and minimize psychological distress, it is
critical to study contributors to these outcomes.
The Role of Religious Coping
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One noteworthy factor for traumatic outcomes is religion. Surveys of the survivors of
disasters, such as 9/11 (Meisenhelder & Marcum, 2009), the 2004 Indian Ocean tsunami
(Hollifield et al., 2008), and Hurricane Katrina (Henslee et al., 2015), have consistently found
levels of reported religious coping to be as high as 97.1%. Religious resources, including beliefs,
values, practices, and ethical principles, can be a key resource for coping with trauma (Bryant-
Davis & Wong, 2013). For many individuals, religion played a role in the development of basic
assumptions about life, the world, and the self (Nygaard & Heir, 2012) and could be significant
in the re-evaluation, restructuring, or replacement of these assumptions (Shaw et al., 2005).
Given the prevalence of utilizing religious resources following a crisis and the potentially
significant impacts on psychological adjustment, it is critical to clarify the actual mechanisms
and outcomes of this type of religious coping (RC). One pioneer in the study of RC was Kenneth
Pargament, who developed what is known as the RCOPE – a measure of RC theoretically
developed to assess 21 different types of RC. Pargament further argued that each of these coping
methods had one of five specific functions, which is to provide either meaning, control, comfort,
intimacy, or life transformation (Gall & Guirguis-Younger, 2013).
Although Pargament highlighted the complexity of RC, most research on religious coping
has generally utilized the Brief RCOPE (Pargament et al., 2011). The Brief RCOPE is a
condensed version of the RCOPE, which divides religious coping methods into two subscales:
positive and negative religious coping (Pargament, Koenig, & Perez, 2000). Positive religious
coping consists of coping styles such as collaborative religious coping and benevolent religious
reappraisal, whereas negative religious coping includes coping styles such as punishing God
reappraisal, demonic reappraisal, and spiritual discontent. Research utilizing the Brief RCOPE
has demonstrated that positive religious coping generally leads to adaptive functioning, while
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negative religious coping typically correlates with greater symptomatology (Ano &
Vasconcelles, 2005; Gerber et al., 2011; Pargament et al., 2011).
When the Brief RCOPE has been utilized in studies on posttraumatic outcomes, positive
religious coping tended to be associated with posttraumatic growth and negative religious coping
with more posttraumatic stress symptoms (Ano & Vasconcelles, 2005; Gerber, Boals, &
Schuettler, 2011; Pargament, Feuille, & Burdzy, 2011). However, these patterns have been
inconsistent in certain populations (Currier, Smith, & Kuhlman, 2017; Park et al., 2017), which
has made interpretation of findings perplexing. Nevertheless, the finding that different forms of
RC have different effects on posttraumatic outcomes suggests that RC is an important
contributor to posttraumatic outcomes.
The Brief RCOPE has been of great utility to researchers interested in RC due to its
brevity and simplicity, but it also has several drawbacks. The Brief RCOPE clusters RC styles
into very broad categories, and has reduced diverse religious coping styles into just two general
forms of coping. This imprecision limits the ability to differentiate RC styles that relate more
strongly to each traumatic outcome, which in turn hinders applications to clinical interventions
and theoretical development. The potential salubrious or deleterious effects of RC methods
makes clear the importance of researching the various types of RC to evaluate their role in
adjustment to the cognitive, emotional, interpersonal, and behavioral after-effects of trauma.
For the current study, we administered the full RCOPE measure, rather than the brief
RCOPE. This approach allowed us to test the outcome of each individual coping style on
posttraumatic outcomes, while simultaneously controlling for the other coping styles. Due to the
current scarcity of research that has been conducted utilizing the full RCOPE in relation to
posttraumatic outcomes, our study was exploratory in nature. The guiding research question was:
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what RC styles are pertinent to PTS and PPTG? The aim was to develop models of PTS and
PPTG that effectively predicted these outcomes.
Although the Full RCOPE has rarely been used in research (Pargament, Feuille, Burdzy,
2011), several studies have utilized subscales and are informative for the current study. Gall
(2006) utilized eight RC subscales to predict anxious, angry, and depressed mood among
survivors of childhood sexual abuse. Some of the findings in that study were anticipated, such as
that forgiveness and spiritual support were related to less distress, but other findings were
surprising, such as that passive deferral was associated with less anxiety. Another study found
benevolent religious reappraisals, a specific type of religious coping, were associated with PPTG
among medical rehabilitation inpatients (Magyar-Russell, Pargament, Trevino, & Sherman,
2013). Although not utilizing the Full RCOPE, a study of Muslim trauma survivors in United
Kingdom and Iraq found that Negative Islamic appraisals were associated with more PTS, while
positive Islamic appraisals were associated with less PTS (Brezengi, Berzenji, Kadim, Mustafa,
& Jobson, 2017). Each of these studies provides a more specific understanding of the role of
religious coping than has been provided when the Brief RCOPE was utilized.
In the current study, comprehensive hypotheses were not formed as the study was
designed to be exploratory in nature. However, the research discussed above suggested that RC
styles categorized as “positive” would be correlated with increased PPTG and decreased PTS
symptoms, whereas “negative” RC styles would have the inverse trend. A few specific
hypotheses were tentatively formed. In regards to PTS, it seemed likely that spiritual discontent
and punishing God reappraisal would be positively associated, as the negative religious coping
scale was largely composed of items addressing these constructs. In regards to PPTG, we
expected benevolent religious reappraisals and religious direction or conversion would likely be
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positively associated, given past findings. The overall expectation was that there would be some
variability in the strength and direction of the association of the religious coping styles with
posttraumatic outcomes, but it was difficult to formulate further specific hypotheses with limited
empirical evidence on the specific religious coping styles.
Method
Participants
In order to increase the generalizability of the results, we sampled two populations. The
first sample was retrieved from Amazon Mechanical Turk (MTurk), an online platform on which
individuals can participate in research for a small monetary compensation. MTurk tends to be
fairly representative of the population of the United States (Huff & Tingley, 2015). The second
sample included students enrolled in a lower level psychology course at an evangelical Christian
university, who received course credit for participating. A total of 737 participants were sampled,
370 from MTurk and 367 undergraduates. Participants who did not report a personal or work
experience of trauma (MTurk n = 50, undergraduate n = 59) were excluded from analyses. Those
who identified as atheist were also excluded, due to the difficulty interpreting and applying
findings with this population, leaving 286 MTurk participants (41.3% male, 58.7% female) and
308 undergraduate participants (22.7% male, 77.3% female).
The mean age of the participants from the Amazon Mechanical Turk platform was 37.51
years old (SD = 11.64) ranging from 21 to 70 years of age. Participants from this sample were
limited to United States residents, and the resulting sample’s ethnic diversity was relatively
representative, with the majority of participants identifying as Caucasian (71.0%), and other
ethnicities represented included African American (9.1%), Asian-American (7.7%), Latino
(7.3%), multiracial (3.5%), Native American (1.0%), and other (0.3%). The sample of
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undergraduate students had a mean age of 19.52, (SD = 1.64), but was more ethnically diverse
with 40.3% Caucasian, 25.3% Latino, 15.9% Asian-American, 8.4% Multiracial, 7.5% African
American, 1.3% Native American, and 1.3% Other ethnicities represented.
A wide range of religious identities were reported in the MTurk sample, including
Protestant (31.5%), Catholic (21.7%), Agnostic (20.3%), other (10.1%), no preference (9.8%),
Buddhist (3.5%), Muslim (2.1%), Jewish (0.7%), and Mormon (0.4%). Religious affiliations
represented in the undergraduate data included Protestant (63.0%), Catholic (17.9%), other
(11.4%), no preference (4.9%), and Agnostic (2.9%). The lack of religious diversity among the
undergraduate sample was not surprising given that the university is Christian faith-based.
Measures
The Life Events Checklist (LEC-5). The LEC-5 is a 17-item questionnaire that
measures the number of traumatic events that an individual has experienced directly or indirectly
in a checklist format (Gray, Litz, Hsu, & Lombardo, 2004; Weathers, Litz, & Keane, 2013). The
scale asks participants to specify whether they experienced it directly, witnessed it, learned about
it, it is part of their job, they are not sure, or it doesn’t apply to them. Representative items
include a “sudden accidental death” and a “fire or explosion” (Weathers et al., 2013). The LEC-5
is a minor revision of the prior LEC, which had adequate kappa values ranging from .52 to .84
for personally experienced traumas at one week re-test and was moderately correlated (r = .43)
with posttraumatic stress symptoms (Gray et al., 2003). The MTurk sample reported a higher
mean number of personally experienced traumas (M = 3.02, SD = 2.13) than the undergraduate
sample (M = 2.71, SD = 1.66). Experiences of work trauma were similarly higher among the
MTurk sample (M = 0.63, SD = 1.90) than the undergraduate sample was (M = 0.24, SD = 1.19).
The Posttraumatic Stress Checklist for DSM-5 (PCL-5). The PCL-5 is a 20-item
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questionnaire assessing symptoms experienced after a “very stressful event” using a 5-point scale
from 0 to 4. This scale matches DSM-5 diagnostic criteria for PTSD and recognizes four
symptom clusters, including re-experiencing, avoidance, negative thoughts and mood, and
hyperarousal (Blevins et al., 2016). It was previously found to have good internal consistency (α
= .91), as well as 72% sensitivity and 92% specificity for PTSD (Ghazali & Chen, 2018).
The Posttraumatic Growth Inventory (PTGI). The PTGI is a 21-item questionnaire
that measures the extent to which one has experienced perceived growth following a traumatic
event using a 6-point rating scale from 0 to 5 (Tedeschi & Calhoun, 1996). Participants
responded to items based on “the crisis/disaster” and thus it was not clear if participants were
responding to the same trauma as in the PCL-5. Data were analyzed with two items that deal
exclusively with religious and spiritual growth excluded from the PTGI scale score due to
concern about confounding (Joseph, 2011). Past research has demonstrated very good reliability
(α = .95) for the total scale among breast cancer survivors (Brunet, McDonough, Hadd, &
Sabiston, 2010). PTGI predicts psychological adjustment, such as gratitude, life satisfaction, and
positive relations, but the relationship is much stronger when the event is central to the person’s
identity (Johnson & Boals, 2015). Qualitative research with trauma survivors and significant
others has provided additional evidence of validity (Shakespeare-Finch & Enders, 2010).
The Religious Coping Inventory (Full RCOPE). The Full RCOPE is a 105 item scale
that measures the extent to which individuals engage in various RC methods using a 4-point
scale (Pargament et al., 2000). To assess the religious coping styles utilized for the trauma,
participants were asked to report “what you did to cope with this negative event.”
One challenge of utilizing the Full RCOPE has been that the scales have not been fully
validated. In fact, some studies have employed the theoretically developed scales, rather than the
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empirically validated scales (e.g., Gall, 2006, Magyar-Russell et al., 2013). In the validation
study, Pargament and colleagues (2000) performed an exploratory factor analysis (EFA) with a
college student sample and a confirmatory factor analysis (CFA) with a hospital sample.
However, validation was complicated by the decision to give the college sample the full 105-
item RCOPE while the hospital sample was given a 63-item scale – administered concurrently to
data collection of the college sample. The EFA revealed a 17 factor structure, which was
supported partially by the CFA. The current study opted to calculate scale scores based upon the
EFA results, as they demonstrated good reliability in the validation study. Thus, 17 subscales
were computed as the sum of three to ten items. Research has demonstrated the RCOPE was able
to predict physical and mental health outcomes among elderly patients who had been
hospitalized (Pargament et al., 2000).
Procedures
Prior to data collection, the study was approved by the Institutional Review Board at the
authors’ university. Participants received a link to the survey and were asked to provide informed
consent. Participants responded to basic demographic questions, the Life Events Checklist for
DSM-5, the Posttraumatic Stress Checklist for DSM-5, and the Posttraumatic Growth Inventory,
in that order. The survey then asked their religious preference, after which participants
completed the Full Religious Coping Inventory, with the items presented in a randomized order.
Upon completion of the study, participants from the Amazon Mechanical Turk sample received
$0.70, while participants in the sample of undergraduate students received course credit.
Plan of Analysis
The primary aim of the analysis was to identify RC variables that are most related to the
outcome variables. However, data analysis was hindered by intercorrelations of the RC scales
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ranging from -.37 to .83, with a median of .43. This multicollinearity affects the consistency of
regression coefficients by inflating the variance of beta weights. Thus, the analytic approach
needed to mitigate this multicollinearity, while also parsimoniously identifying RC strategies that
may have potential clinical implications.
Traditional methods, such as stepwise and forward regression can achieve simplicity, but
they tend to have low prediction accuracy for correlated data (Gunes, 2015). To improve upon
both variable selection and prediction accuracy, a penalized regression method was utilized. This
method is similar to multiple regression but places constraints that limit the coefficient estimates.
As a result, coefficient estimates are biased but less variable, which results in models that have
more optimal predictive performance. Although there are several types of penalized regression
methods, this study utilized the elastic net method, which avoids the limitations of other methods
when there are groups of correlated variables (Zou & Hastie, 2005). Moreover, this analysis
utilized a double pass approach which involved carrying out the analysis once with all predictors
and then again with only the predictors selected from the first pass, which separates the impact of
variable selection and shrinkage (Barker, 2013).
Data analyses were conducted in JMP, a software package from SAS. This software
package can conduct a generalized regression with adaptive elastic net, selecting the optimal
model based upon minimal AICc with Early Stopping. The use of AICc, or the Akaike
Information Criterion Correction, balances goodness-of-fit with parsimony of predictors, and has
shown to be asymptotically optimal for converging on the model with the least mean squared
error (Yang, 2005). Moreover, the use of Early Stopping helps to avoid overfitting that can result
in non-reproducible findings.
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Analysis was conducted separately with the MTurk and undergraduate samples. The
analytic approach involved first identifying appropriate control variables. The control variables
included in the model differed depending on the outcome variable and the population. The
control variables investigated included gender, age, number of personal experiences of trauma,
and number of work traumas. This step was important to eliminate variables that might mask or
amplify associations between the RC and outcome variables. The control variables were tested
separately for both samples with PTS and PPTG as outcomes. In each case, a double pass
penalized regression with adaptive elastic net was conducted.
The analyses then proceeded to test models of both PTS and PPTG with the religious
coping variables, utilizing these control variables. There were three models being tested:
Religious Coping subscales (Model 1), Religious Coping subscales along with Positive and
Negative Religious Coping scales (Model 2), and Positive and Negative Religious Coping scales
only (Model 3). Model 1 was being tested to investigate RC subscales that might have a greater
impact on the outcomes variables with the assumption that these variables would be candidates
for interventions in further research. Model 2 was being tested to determine whether the positive
and negative RC scales could contribute to the prediction of PTS and PPTG, after controlling for
the subscales. It should be noted that Positive and Negative RC were composed from items that
were concurrently utilized in the RC subscales. Thus, this model was utilized for comparison
with Model 1 and Model 3 only, rather than as a basis for interpretation of findings given the
difficulty in teasing apart the effects. Lastly, Model 3 was being tested to investigate the
predictive power of the positive and negative RC variables alone and to compare this model with
Model 1. This model comparison approach provided evidence on whether using RC subscales
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produced superior models to the positive and negative RC scales. These procedures were utilized
in all analyses below.
Results (link to table online?)
Descriptive statistics, alpha reliabilities, bivariate and partial correlations of RC variables
with PTS and PPTG were calculated separately for each sample and are presented in Table 1.
The analysis followed the procedures detailed in the Plan of Analysis section, above. The
double-pass adaptive elastic net penalized regression analysis proceeded according to AICc and
selected variables to include in each model separately for MTurk and undergraduate samples for
both PTS and PPTG.
The analyses predicting PTS are presented in Tables 3 and 4 for the MTurk and
undergraduate samples, respectively. Utilizing a model comparison approach, the findings
demonstrated that the RC subscales predicted PTS more optimally, based upon both R2 and
AICc, than the higher order scales. The model composed of both RC subscales and higher order
scales (i.e., Model 2) included significant subscale predictors for both MTurk and undergraduate
samples. In fact, Table 4 showed that the higher order RC scales were not significant predictors
when included with subscales in the undergraduate sample. The subscale model predicted 37.5%
of the variance in PTS for the MTurk sample and 34.9% of the variance for the undergraduate
sample, as compared to 34.1% and 27.7%, respectively, for the higher order RC models.
Additional analyses investigated whether the models developed with each sample were
interchangeable. When utilizing the RC subscale model developed from the MTurk sample (i.e.,
Model 1 variables in Table 3) on the undergraduate sample, this model slightly outperformed the
higher order model (i.e., Model 3 in Table 4), with R2 = .277 and AICc = 703.283. All variables
were selected through the first pass of penalized regression, except Reappraisal of God’s Powers.
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Similarly, the RC subscale model developed from the MTurk sample (i.e., Model 1 in Table 4)
also outperformed the higher order model (i.e., Model 3 in Table 3) in variance explained and
information criterion, with R2 = .357 and AICc = 666.351. For this model, only four subscale
variables were selected from the model, Active Surrender, Passive Religious Deferral, Spiritual
Discontent, and Religious Direction/Conversion. Thus, in both cases, the models developed
based upon the other sample were still able to outperform the higher order models.
Tables 5 and 6 display results of the analyses predicting PPTG with the MTurk and
undergraduate samples, respectively. In both samples, the selected RC subscales (i.e., Model 1)
were more strongly predictive of PPTG than the higher order RC scales (i.e., Model 3), based
upon both R2 and AICc. Moreover, Model 2 shows that the higher order scales did not add
additional variance above the subscales in predicting PPTG in either sample. As the RC subscale
models only differed in the inclusion of a single variable, testing whether the models were
interchangeable between MTurk and undergraduate samples was not necessary.
Discussion
This study results indicated that, in zero-order correlations, all but one of the RC sub-
scales were positively correlated with both PTS and PPTG. This pattern of associations was
unexpected, given that past research has found that positive religious coping was unrelated with
PTS and negative religious coping was unrelated to PPTG (Ano & Vasconcelles, 2005). The raw
correlations with PTS are particularly surprising, given that religiousness typically has a
beneficial effect on mental health. There are several possible explanations of the positive
associations between RC styles and PTS. Certainly, one must consider that RC might be
ineffective at reducing or, more provocatively, might exacerbate stress responses among
individuals. Another possibility is that the true associations may be masked by a lurking variable,
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such as religious motivation or acquiescence bias, which is related to both PTS and increased use
of RC. The intercorrelations of the RC styles could thus be due to this lurking variable, which
would explain the consistently positive associations.
Despite removing items that potentially conflated PPTG with religiousness, as suggested
by Joseph (2011), this study still found that all RC subscales were positively correlated with
PPTG. These consistently positive raw correlations were similarly unexpected, given that the
content of some RC styles, such as Passive Deferral, appeared essentially opposed to PPTG.
The data were analyzed using a method that accounts for multicollinearity, penalized
regression analysis, in order to identify a multivariate model that could predict posttraumatic
outcomes. The predictors of PPTG included in this model were positively associated both in
bivariate and multivariate associations. However, some of the RC styles reversed in direction of
association with PTS. We argue that the findings based on multivariate analysis better reflect the
actual relationships of the RC subscales than the bivariate relationships, particularly for Active
Surrender. The basis for this argument is three-fold: first, several of the resulting negative
associations with PTS were statistically significant in the model; second, the negative
associations with Active Surrender were consistent across both samples; third, Active Surrender
made theoretical sense given that it has been discussed extensively as a positive resource for
coping (see Cole & Pargament,1999; Wong-McDonald & Gorsuch, 2000). Thus, the effect of
Active Surrender, and possibly Religious Helping, on PTS may have been masked by lurking
variable that was indirectly accounted for in multivariate analyses.
The possibility that the intercorrelations of the RC styles mask the effects of individual
coping styles poses a challenge to measurement and research on RC and posttraumatic outcomes.
Research that incorporates only a subset of the RC styles identified in this study, rather than a
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more comprehensive model, may result in findings that misrepresent the relationship of that RC
style with posttraumatic outcomes. Consequently, the findings support the major premise of the
study: the role of RC in posttraumatic outcomes would be better understood with a more nuanced
and comprehensive approach to assessment of RC.
Associations with Posttraumatic Stress
The findings provide suggestive evidence for theory development and clinical
applications, although the generalization to clinical populations should be made tentatively given
the findings were from a non-clinical sample. The most prominent religious coping scale in the
analyses was Active Surrender, which was associated with decreased PTS in multivariate
analyses. In contrast to Passive Deferral, Active Surrender involves an individual taking
responsibility for certain actions in their lives, while turning the situations that are outside of
one’s control over to God. This approach to problem solving may have some unique advantages
for negotiating the negative effects of trauma. Clarifying whether this association might be due
to general acceptance or specifically to one’s relationship with God would be helpful.
Nevertheless, bivariate correlations between surrender and PTS were modestly positive, so
cautious interpretation of Active Surrender’s effect on PTS is appropriate.
Moreover, the findings could justify a narrowed focus from the broader negative religious
coping to the specific effects of Passive Religious Deferral and Spiritual Discontent with PTS.
The positive association between Passive Religious Deferral and PTS intersects with past
research that passive approaches to dealing with trauma are generally unhelpful (Goldenberg &
Matheson, 2005). Spiritual Discontent may be the result of schemas that the self is flawed and
unworthy of God’s love or rather that God is fickle and unjust in the way he treats people. Thus,
these coping styles might reflect an underlying pathological view of the self or, alternatively,
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they might reflect a negative view of God. Of course, these explanations could be
interconnected, given that relationship with God may reflect attachment styles that are embedded
with beliefs about self and others (Kirkpatrick, 1998; Beck, 2006). It may be beneficial to alter
these thought patterns using therapies that address attachment injuries or that change cognitions
about self and others, which may in turn reduce symptoms of PTS.
Lastly, the positive associations of Religious Purification/Forgiveness and Religious
Direction/Conversion with PTS in the undergraduate sample were surprising. Past research has
found that forgiveness is associated with decreased PTS (Reed & Enright, 2006). However, the
current finding should not be interpreted as contradictory of such research. The scale items
include mention of anger, resentment, and bitterness that the person is seeking to reduce, which
suggests that the individual may be undergoing increased difficulty with forgiveness and
rumination that could exacerbate symptoms of PTS. Religious Direction/Conversion similarly
might reflect a difficulty with meaning-making that might contribute to the stress reaction.
Moreover, these associations may be unique to the developmental stage of college students.
Associations with Posttraumatic Growth
The RC styles that were included in the models with PPTG similarly provide insight into
the role of religiousness and spirituality in PPTG. Religious Direction/Conversion, where an
individual asks God for a new purpose in life, was found to be positively correlated with PPTG.
It is important to note that this construct was assessed with items addressing the process of
seeking direction or conversion, rather than having achieved it. Thus, the findings suggest that
those who express engaging in an ongoing process of conversion or direction seeking are also
likely to report experiencing posttraumatic growth. Note that this variable was found to be
positively correlated with both PTS and PPTG. Perhaps this is because, in the short term, efforts
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to find new meaning or a new religious trajectory might initially cause an individual increased
distress but, in the long run, may be beneficial for producing growth. Longitudinal research on
this coping style could look at these relationships more closely.
Another interesting RC style was Spiritual Connection, which was positively correlated
with PPTG in the MTurk sample. This variable includes seeing one’s life as part of the spiritual
domain and making efforts to deepen one’s spirituality, while remaining actively attuned with
reality. None of the three items composing this scale explicitly address relationship with God,
though one item does involve efforts to build a relationship with a higher power. This suggests
that viewing one’s self as being within a spiritual system may promote posttraumatic growth.
Moving from Broad to Subscale Approaches
In comparing the utilization of the RC sub-scales with the broader positive and RC styles,
it is important to consider predictive power, clinical utility, and theoretical grounding, along with
parsimony. It is important to consider all these factors in determining the merits of a model based
on subscales, rather than higher-order constructs.
In regards to predictive power, the religious coping subscale model predicted more
variance in PTS than the higher order model in both the MTurk (37.5% vs. 34.1%) and the
undergraduate (34.9% vs. 27.4%) samples. The results were similar for PPTG, where the
subscale model explained more variance than the higher order scales for the MTurk sample
(20.6% vs. 15.1%) and the undergraduate sample (20.4% vs. 17.9%). In each case, this
difference was not due solely to increased number of predictors, as AICc was lower for the
subscale model, indicating better model fit even when penalized for number of parameters. This
supports the hypothesis that RC subscale models were superior to broad RC models.
GOING BEYOND POSITIVE AND NEGATIVE
Although these models need to be validated with clinical samples, the RC subscale
models also potentially have advantages in regards to clinical utility, as the precise constructs
underlying the relationships could be identified. Although negative RC involves demonic
reappraisal and reappraisal of God’s powers, this approach highlighted spiritual discontent as
having been more strongly associated with PTS. Thus, clinical work could focus on ameliorating
spiritual discontent. Similarly, this approach demonstrates that religious direction/conversion and
spiritual connection are particularly strongly related to PPTG, whereas other positive religious
coping styles, such as religious focusing, are less strongly associated. This suggests that
facilitating religious change or spiritual connection might be important in promoting the
perception of posttraumatic growth.
The last advantage of the subscale model of PTS is the potential for theoretical advances.
Positive and negative religious coping are such broad constructs, that it is difficult to explain the
associations from a theoretical perspective. The specific constructs could aid in theory
development and refinement because they clarify specific mechanisms that may be at play.
Relevant theories that could provide context to these findings include social problem solving
(Sutherland & Bryant, 2008) and meaning-making (Park, 2013).
The three major drawbacks of the subscale approach, at least with PTS, are the
complexity of the models, the variability across populations, and the length of the assessment.
Certainly, the broad constructs provide simple and elegant accounts of the role of RC in
posttraumatic outcomes. This simplicity makes communication of the findings more
straightforward. Moreover, although the religious coping subscale models had modest
consistency between MTurk and undergraduate samples, it is unclear if these models will apply
to other diverse samples. Lastly, researchers may find it difficult to include assessment of the
GOING BEYOND POSITIVE AND NEGATIVE
diverse RC subscales in their research designs, where space is at a premium. For instance, the
undergraduate RC subscale model of PTS was composed of 55 items. It is apparent that more
refinement could be made to clarify these relationships, narrow the models, and identify possible
causal relations. Despite these challenges, advances in understanding the role of religious coping
in PTS and PPTG may only be possible with a more nuanced approach.
Limitations and Future Directions
The primary limitation of this study is its cross-sectional design. As a result, no causal
conclusions should be drawn from this research, even as the study highlights some potential
causal mechanisms to explore in future research. Moreover, this research was conducted using a
non-clinical sample, which limits our ability to generalize the findings of this study to those who
have been diagnosed with PTSD. Additionally, the use of online surveys may have evoked a
response set that contributed to the positive links between the variables. Nevertheless, the
widespread prevalence of trauma suggests these findings might still provide guidance for
therapists, clergy, and mental health providers.
Future research might also utilize a longitudinal research design, which might better
reveal the effects of RC methods on posttraumatic outcomes. Researchers could also test the
relationship of RC styles on theoretical mechanisms, such as cognitive schemas of self,
difficulties with forgiveness, and willingness to engage in exposure processes.
One major focus of future research could also be to investigate the effectiveness of RC
styles in clinical interventions. Based on research that negative religious coping was related with
increased symptoms of PTS, Harris et al. (2011) created an intervention known as Building
Spiritual Strength designed to reduce negative religious coping, and subsequently, decrease
symptoms of PTS. The results of the current study suggest the Building Spiritual Strength
GOING BEYOND POSITIVE AND NEGATIVE
intervention might consider some minor adaptations, including a review of theological
justifications for forgiveness, encouraging surrender to God, and minimizing passive deferral to
God. Future research could investigate the effects of interventions based on these particular
religious coping styles.
GOING BEYOND POSITIVE AND NEGATIVE
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29Running head: GOING BEYOND POSITIVE AND NEGATIVE
Table 1
Mean, SD, Alpha Reliability, and Raw Correlations of Religious Coping Variables with Posttraumatic Stress Symptoms and
Posttraumatic Growth for MTurk Participants.
Variable# of
itemsRaw r Partial r b
Mean SD α PTS PPTG PTS PPTGPositive Religious Coping 7 0.97 0.92 .93 .18 .39 -.04 .35Negative Religious Coping 7 0.52 0.70 .90 .48 .18 .45 .00Benevolent Religious Reappraisal 9 1.06 0.93 .96 .17 .41 -.05 .07Punishing God Reappraisal 5 0.48 0.72 .91 .44 .15 .07 -.05Demonic Reappraisal 5 0.51 0.75 .92 .36 .22 .07 -.01Reappraisal of God's Powers 4 0.71 0.82 .83 .39 .21 .09 .13Collaborative Religious Coping 8 2.94 0.67 .73 -.15 .17 -.02 .07Active Surrender 5 1.04 1.01 .95 .13 .33 -.12 -.07Passive Religious Deferral 5 0.55 0.76 .91 .32 .23 .01 -.10Pleading for Direct Intercession 5 0.95 0.88 .87 .33 .30 .12 .00Religious Focus 5 0.84 0.88 .90 .24 .35 -.03 -.13Religious Purification/Forgiveness 10 0.87 0.87 .96 .27 .37 .01 -.00Spiritual Connection 3 1.12 0.97 .86 .21 .43 .08 .11Spiritual Discontent 6 0.60 0.81 .94 .46 .12 .08 -.05Marking Religious Boundaries 4 0.77 0.75 .71 .26 .32 .05 .09Seek Support from Clergy/Members 5 0.65 0.85 .92 .23 .32 .00 .07Religious Helping 6 0.93 0.88 .92 .19 .38 -.07 .00Interpersonal Religious Discontent 5 0.49 0.74 .87 .35 .19 .01 .05Religious Direction/Conversion 10 0.85 0.86 .95 .30 .43 .06 .16Posttraumatic Stress 20 1.11 0.94 .96 - .18 - -Perceived Posttraumatic Growtha 19 2.37 1.25 .95 - - - -
a Posttraumatic Growth was calculated without two items that address religious and spiritual growth specifically. N = 286.
GOING BEYOND POSITIVE AND NEGATIVE
b Partial correlations were calculated separately for the set of religious subscales and for Positive Religious Coping and Negative Religious Coping, due to item overlap.
31GOING BEYOND POSITIVE AND NEGATIVE
Table 2
Mean, SD, Alpha Reliability, Raw and Partial Correlations of Religious Coping Variables with Posttraumatic Stress Symptoms and
Posttraumatic Growth for Undergraduate Participants.
Variable# of
itemsRaw r Partial r b
Mean SD α PTS PPTG PTS PPTGPositive Religious Coping 7 1.58 0.80 .88 .13 .34 .06 .32Negative Religious Coping 7 0.72 0.68 .84 .41 .23 .40 .18Benevolent Religious Reappraisal 9 1.71 0.80 .94 .04 .31 -.07 .02Punishing God Reappraisal 5 0.76 0.80 .89 .40 .22 .10 .03Demonic Reappraisal 5 0.81 0.78 .89 .33 .19 .06 -.07Reappraisal of God's Powers 4 0.75 0.75 .79 .22 .20 -.00 .07Collaborative Religious Coping 8 3.10 0.62 .75 -.24 -.04 -.05 -.12Active Surrender 5 1.51 0.86 .89 .05 .27 -.06 .03Passive Religious Deferral 5 0.73 0.67 .82 .19 .13 .08 -.06Pleading for Direct Intercession 5 1.28 0.79 .80 .24 .28 .00 -.03Religious Focus 5 1.14 0.77 .84 .15 .32 -.02 .00Religious Purification/Forgiveness 10 1.49 0.83 .93 .24 .34 .11 .00Spiritual Connection 3 1.45 0.87 .76 .17 .36 -.01 .08Spiritual Discontent 6 0.85 0.83 .93 .36 .20 .06 .00Marking Religious Boundaries 4 1.07 0.67 .65 .11 .25 .00 -.01Seek Support from Clergy/Members 5 0.90 0.74 .83 .14 .29 .01 .08Religious Helping 6 1.44 0.86 .91 .04 .30 -.10 .02Interpersonal Religious Discontent 5 0.54 0.69 .86 .29 .17 -.02 -.07Religious Direction/Conversion 10 1.18 0.83 .93 .34 .43 .19 .18Posttraumatic Stress 20 1.14 0.87 .95 - .26 - -Perceived Posttraumatic Growtha 19 2.51 1.29 .95 - - - -
a Posttraumatic Growth was calculated without two items that address religious and spiritual growth specifically. N = 308.
32GOING BEYOND POSITIVE AND NEGATIVEb Partial correlations were calculated separately for the set of religious subscales and for Positive Religious Coping and Negative Religious Coping, due to item overlap.Table 3
Parameter Estimates of Posttraumatic Stress Symptom Models from Penalized Regression Among MTurk Participants.
VariableControls Model 1 Model 2 Model 3
b SE b SE b SE b SEAge -0.023c 0.004 -0.015c 0.004 -0.015c 0.004 -0.016c 0.004Personal Experience Trauma 0.149c 0.023 0.139c 0.022 0.136c 0.022 0.130c 0.022Work Trauma 0.120b 0.043 0.082b 0.025 0.076b 0.026 0.067a 0.030Reappraisal of God’s Powers 0.111 0.075 0.127 0.073Active Surrender -0.207b 0.080 -Passive Religious Deferral 0.144 0.088 -Plead for Direct Intercession 0.213a 0.091 0.240b 0.091Spiritual Connection 0.087 0.069 -Spiritual Discontent 0.198a 0.084 -Positive Religious Coping -0.148 0.078 -Negative Religious Coping 0.320b 0.097 0.510c 0.073AICc 714.866 662.608 661.576 667.438R2 .216 .375 .368 .341
Note: N = 286. p-value was based on Wald Chi-square statistic. a p < .05, b p < .01, c p <.001. Each model was determined by
penalized regression with adaptive elastic net, determined by minimal AICc with Early Stopping. Controls fit determined the
covariates for inclusion. Model 1 fit was tested with 17 religious coping variables, along with identified covariates. Model 2 fit was a
test to determine whether effects of positive and negative religious coping would be fully mediated by Model 1. Model 3 fit was a test
of only positive and negative religious coping variables, along with the covariates.
33GOING BEYOND POSITIVE AND NEGATIVE
Table 4
Parameter Estimates of Posttraumatic Stress Symptom Models from Penalized Regression Among Undergraduate Participants.
VariableControls Model 1 Model 2 Model 3
b SE b SE b SE b SEPersonal Experience Trauma 0.217c 0.027 0.165c 0.024 0.165c 0.024 0.174c 0.026Punishing God Reappraisal 0.107 0.087 0.107 0.087Demonic Reappraisal 0.068 0.067 0.068 0.067Active Surrender -0.156a 0.067 -0.156a 0.067Passive Religious Deferral 0.093 0.062 0.093 0.062Rel. Purification/Forgiveness 0.192a 0.084 0.192a 0.084Spiritual Connection -0.087 0.091 -0.087 0.091Spiritual Discontent 0.115 0.078 0.115 0.078Religious Helping -0.155a 0.071 -0.155a 0.071Relig. Direction/Conversion 0.282c 0.082 0.282c 0.082Positive Religious Coping - 0.086 0.058Negative Religious Coping - 0.392c 0.070AICc 734.982 679.687 679.687 716.800R2 .171 .349 .349 .274
Note: N = 308. p-value was based on Wald Chi-square statistic. a p < .05, b p < .01, c p <.001. Each model was determined by
penalized regression with adaptive elastic net, determined by minimal AICc with Early Stopping. Controls fit determined the
covariates for inclusion. Model 1 fit was tested with 17 religious coping variables, along with identified covariates. Model 2 fit was a
test to determine whether effects of positive and negative religious coping would be fully mediated by Model 1. Model 3 fit was a test
of only positive and negative religious coping variables, along with the covariates.
34GOING BEYOND POSITIVE AND NEGATIVE
Table 5
Parameter Estimates of Posttraumatic Growth Models from Penalized Regression Among MTurk Participants.
VariableControls Model 1 Model 2 Model 3
b SE b SE b SE b SEWork Trauma 0.070 0.045 - - -Spiritual Connection 0.329b 0.111 0.329b 0.111Religious Direction/Conversion 0.324b 0.119 0.324b 0.119Positive Religious Coping - 0.530c 0.073Negative Religious Coping - -AICc 941.368 880.856 880.856 897.797R2 .011 .206 .206 .151
Note: N = 286. p-value was based on Wald Chi-square statistic. a p < .05, b **p < .01, c p <.001. Each model was determined by
penalized regression with adaptive elastic net, determined by minimal AICc with Early Stopping. Controls fit determined the
covariates for inclusion. Model 1 fit was tested with 17 religious coping variables, along with identified covariates. Model 2 fit was a
test to determine whether effects of positive and negative religious coping would be fully mediated by Model 1. Model 3 fit was a test
of only positive and negative religious coping variables, along with the covariates.
35GOING BEYOND POSITIVE AND NEGATIVE
Table 6
Parameter Estimates of Posttraumatic Growth Models from Penalized Regression Among Undergraduate Participants.
VariableControls Model 1 Model 2 Model 3
b SE b SE b SE b SEPersonal Experience Trauma 0.165c 0.041 0.118b 0.040 0.118b 0.040 0.143c 0.040Religious Direction/Conversion 0.622c 0.080 0.622c 0.080Positive Religious Coping - 0.522c 0.094Negative Religious Coping - 0.227b 0.102AICc 1019.623 965.655 965.655 977.262R2 .045 .204 .204 .179Note: N = 308. p-value was based on Wald Chi-square statistic. a p < .05, b p < .01, c p <.001. Each model was determined by penalized regression with adaptive elastic net, determined by minimal AICc with Early Stopping. Controls fit determined the covariates for inclusion. Model 1 fit was tested with 17 religious coping variables, along with identified covariates. Model 2 fit was a test to determine whether effects of positive and negative religious coping would be fully mediated by Model 1. Model 3 fit was a test of only positive and negative religious coping variables, along with the covariates.