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GOING BEYOND POSITIVE AND NEGATIVE

© 2020, American Psychological Association. This paper is not the copy of record

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: Clarifying Relationships of Specific Religious Coping

Styles with Posttraumatic Outcomes

Curtis Lehmann and Emma Steele

Azusa Pacific University


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


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


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


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


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:


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


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


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


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


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


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.


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


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.


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,


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


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,


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


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.


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


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


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.


References

American Psychiatric Association. (2013). Diagnostic and Statistical Manual of Mental

Disorders (5th Edition). Arlington, VA: American Psychiatric Publishing, Inc.

Ano, G. G., & Vasconcelles, E. B. (2005). Religious coping and psychological adjustment to

stress: A meta-analysis. Journal of Clinical Psychology, 61(4), 461–480.

https://doi.org/10.1002/jclp.20049

Barker, C. (2013). Variable selection made easy using GENREG in JMP Pro. SAS Institute.

https://community.jmp.com/kvoqx44227/attachments/kvoqx44227/discovery-2016-

content/11/1/genregTutorialSHORT.pdf

Beck, R. (2006). God as a secure base: Attachment to God and theological exploration. Journal

of Psychology and Theology, 34(2), 125-132.

Berntsen, D., & Rubin, D. C. (2007). When a trauma becomes a key to identity: Enhanced

integration of trauma memories predicts posttraumatic stress disorder symptoms. Applied

Cognitive Psychology, 21(4), 417-431.

Berzengi, A., Berzenji, L., Kadim, A., Mustafa, F., & Jobson, L. (2017). Role of Islamic

appraisals, trauma-related appraisals, and religious coping in the posttraumatic

adjustment of Muslim trauma survivors. Psychological Trauma: Theory, Research,

Practice, and Policy, 9(2), 189–197. https://doi.org/10.1037/tra0000179.supp

Blackie, L. E., & Jayawickreme, E. (2014). Promoting change in posttraumatic growth research:

Response to commentaries. European Journal of Personality, 28(4), 351-361.

Blix, I., Hansen, M. B., Birkeland, M. S., Nissen, A., & Heir, T. (2013). Posttraumatic growth,

posttraumatic stress and psychological adjustment in the aftermath of the 2011 Oslo

bombing attack. Health and Quality of Life Outcomes, 11(160), 1–6.


Brunet, J., McDonough, M. H., Hadd, V., Crocker, P. R., & Sabiston, C. M. (2010). The

Posttraumatic Growth Inventory: An examination of the factor structure and invariance

among breast cancer survivors. Psycho‐Oncology, 19(8), 830-838.

Bryant-Davis, T., & Wong, E. (2013). Faith to move mountains: Religious coping, spirituality,

and interpersonal trauma recovery. American Psychologist, 2, 675–684.

https://doi.org/10.1037/a0022040

Currier, J. M., Smith, P. N., & Kuhlman, S. (2017). Assessing the unique role of religious coping

in suicidal behavior among U. S. Iraq and Afghanistan veterans. Psychology of Religion

and Spirituality, 9(1), 118–123.

Gall, T. L., & Guirguis-Younger, M. (2013). Religious and spiritual coping: Current theory and

research. In K. I. Pargament (Ed. in Chief), J. J. Exline, & J. W. Jones (Associate Eds.),

APA Handbook of Psychology, Religion, and Spirituality (Vol. 1: Context, theory, and

research, pp. 459 – 475). Washington, DC: American Psychological Association.

doi:10.1037/14045-019

Gerber, M. M., Boals, A., & Schuettler, D. (2011). The unique contributions of positive and

negative religious coping to posttraumatic growth and PTSD. Psychology of Religion and

Spirituality, 3(4), 298–307. https://doi.org/10.1037/a0023016

Ghazali, S. R., & Chen, Y. Y. (2018). Reliability, concurrent validity, and cutoff score of PTSD

Checklist (PCL-5) for the Diagnostic and Statistical Manual of Mental Disorders, Fifth

Edition among Malaysian adolescents. Traumatology, 24(4), 280.

Goldenberg, I., & Matheson, K. (2005). Inner representations, coping, and posttraumatic stress

symptomatology in a community sample of trauma survivors. Basic and Applied Social

Psychology, 27(4), 361–369. https://doi.org/10.1207/s15324834basp2704_9


Gray, M., Litz, B., Hsu, J., & Lombardo, T. (2004). Psychometric properties of the Life Events

Checklist. Assessment, 11, 330–341.

Gunes, F. (2015). Penalized regression methods for linear models in SAS/STAT®. In

Proceedings of the SAS Global Forum 2015 Conference. Cary, NC: SAS Institute Inc.

http://support. sas. com/rnd/app/stat/papers/2015/PenalizedRegression_LinearModels.pdf.

Harris, J. I., Erbes, C. R., Engdahl, B. E., Olson, R. H. A., & Winskowski, A. M. (2008).

Christian religious functioning and trauma outcomes. Journal of Clinical Psychology,

64(1), 17–29. https://doi.org/10.1002/jclp

Harris, J. I., Erbes, C. R., Engdahl, B. E., Thuras, P., Murray-Swank, N., Grace, D., Ogden, H.,

Olson, R. H. A., Winskowski, A. M., Bacon, R., Malec, C., Campion, K., & Tuvan, L.

(2011). The effectiveness of a trauma-focused spiritually integrated intervention for

veterans exposed to trauma. Journal of Clinical Psychology, 67(4), 425-438.

https://doi.org/10.1002/jclp.20777

Henslee, A. M., Coffey, S. F., Schumacher, J. A., Tracy, M., Norris, F. H., & Galea, S. (2015).

Religious coping and psychological and behavioral adjustment after Hurricane Katrina.

Journal of Psychology: Interdisciplinary and Applied, 149(6), 630–642.

https://doi.org/10.1080/00223980.2014.953441

Hollifield, M., Hewage, C., Gunawardena, C. N., Kodituwakku, P., Bopagoda, K., &

Weerarathnege, K. (2008). Symptoms and coping in Sri Lanka 20-21 months after the

2004 tsunami. British Journal of Psychiatry, 192(1), 39–44.

Huff, C., & Tingley D. (2015). Who are these people? Evaluating the demographic

characteristics and political preferences of MTurk survey respondents. Research and

Politics, 2(3), 1-12.


Johnson, S. F., & Boals, A. (2015). Refining our ability to measure posttraumatic

growth. Psychological Trauma: Theory, Research, Practice, and Policy, 7(5), 422-429.

Jones, T., & Moller, M. D. (2011). Implications of hypothalamic–pituitary–adrenal axis

functioning in posttraumatic stress disorder. Journal of the American Psychiatric Nurses

Association, 17(6), 393-403.

Joseph, S. (2011). Religiosity and posttraumatic growth: A note concerning the problems of

confounding in their measurement and the inclusion of religiosity within the definition of

posttraumatic growth. Mental Health, Religion & Culture, 14(8), 843–845.

https://doi.org/10.1080/13674676.2011.609162

Joseph, S., & Linley, P. A. (Eds.). (2008). Trauma, Recovery, and Growth: Positive

Psychological Perspectives on Posttraumatic Stress. John Wiley & Sons.

Kirkpatrick, L. A. (1998). God as a substitute attachment figure: A longitudinal study of adult

attachment style and religious change in college students. Personality and Social

Psychology Bulletin, 24(9), 961-973.

Kleim, B., & Ehlers, A. (2009). Evidence for a curvilinear relationship between posttraumatic

growth and posttrauma depression and PTSD in assault survivors. Journal of Traumatic

Stress, 22(1), 45–52. https://doi.org/10.1002/jts.

Meisenhelder, J. B., & Marcum, J. P. (2009). Terrorism, post-traumatic stress, coping strategies,

and spiritual outcomes. Journal of Religion and Health, 48(1), 46–57.

https://doi.org/10.1007/s10943-008-9192-z

Nygaard, E., & Heir, T. (2012). World assumptions, posttraumatic stress and quality of life after

a natural disaster: A longitudinal study. Health and Quality of Life Outcomes, 10(1). 76–

83. https://doi.org/10.1186/1477-7525-10-76


Pargament, K., Feuille, M., & Burdzy, D. (2011). The Brief RCOPE: Current psychometric

status of a short measure of religious coping. Religions, 2(4), 51–76.

https://doi.org/10.3390/rel2010051

Pargament, K. I., Koenig, H. G., & Perez, L. M. (2000). The many methods of religious coping:

Development and initial validation of the RCOPE. Journal of Clinical Psychology, 56(4),

519–543.

Park, C. L., Chmielewski, J., & Blank, T. O. (2010). Post-traumatic growth: Finding positive

meaning in cancer survivorship moderates the impact of intrusive thoughts on adjustment

in younger adults. Psycho-Oncology, 19(11), 1139–1147.

https://doi.org/10.1002/pon.1680.

Park, C. L., Smith, P. H., Lee, S. Y., Mazure, C. M., Mckee, S. A., & Hoff, R. (2017). Positive

and negative religious / spiritual coping and combat exposure as predictors of

posttraumatic stress and perceived growth in Iraq and Afghanistan veterans. Psychology

of Religion and Spirituality, 9(1), 13–20.

Shakespeare-Finch, J., & Barrington, A. J. (2012). Behavioural changes add validity to the

construct of posttraumatic growth. Journal of Traumatic Stress, 25(4), 433–439.

https://doi.org/10.1002/jts.

Shakespeare-Finch, J., & Enders, T. (2008). Corroborating evidence of posttraumatic growth.

Journal of Traumatic Stress, 21(4), 421–424. https://doi.org/10.1002/jts.20347

Shakespeare-Finch, J., Smith, S., Gow, K., Embelton, G., & Baird, L. (2003). The prevalence of

post-traumatic growth in emergency ambulance personnel. Traumatology, 9(1), 58–71.

Shand, L. K., Cowlishaw, S., Brooker, J. E., Burney, S., & Ricciardelli, L. A. (2015). Correlates

of post-traumatic stress symptoms and growth in cancer patients: A systematic review


and meta-analysis. Psycho-Oncology, 24(6), 624–634.

Shaw, A., Joseph, S., Linley, P. A. (2005). Religion, spirituality, and posttraumatic growth: A

systematic review. Mental Health, Religion & Culture, 8(1), 1-11.

Sutherland, K., & Bryant, R. A. (2008). Social problem solving and autobiographical memory in

posttraumatic stress disorder. Behaviour Research and Therapy, 46(1), 154-161.

Taku, K., Cann, A., Calhoun, L. G., & Tedeschi, R. G. (2008). The factor structure of the

Posttraumatic Growth Inventory: A comparison of five models using confirmatory factor

analysis. Journal of Traumatic Stress: Official Publication of The International Society

for Traumatic Stress Studies, 21(2), 158-164.

Tedeschi, R., & Calhoun, L. (1996). The Posttraumatic Growth Inventory: Measuring the

positive legacy of trauma. Journal of Traumatic Stress, 9, 455–471.

Tedeschi, R. G., & Calhoun, L. G. (2004). Posttraumatic growth: Conceptual foundations and

empirical evidence of North Carolina Charlotte circumstances. Psychological Inquiry,

15(1), 1–18.

Thomas, E., & Savoy, S. (2014). Relationships Between Traumatic Events , Religious coping

style, and posttraumatic outcomes. Traumatology: An International Journal, 20(2), 84–90.

Weathers, F., Litz, B., & Keane, T. (2013). The PTSD Checklist for DSM-5.

Yang, Y. (2005). Can the strengths of AIC and BIC be shared? A conflict between model

indentification and regression estimation. Biometrika, 92(4), 937-950. Retrieved from

http://www.jstor.org/stable/20441246

Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of

the Royal Statistical Society: Series B (Statistical Methodology, 67(2), 301-320.

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.


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.


Table 4

Parameter Estimates of Posttraumatic Stress Symptom Models from Penalized Regression Among Undergraduate Participants.


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






Table 5

Parameter Estimates of Posttraumatic Growth Models from Penalized Regression Among MTurk Participants.


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






Table 6

Parameter Estimates of Posttraumatic Growth Models from Penalized Regression Among Undergraduate Participants.


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.

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