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Journal of Studies on Alcohol and Drugs logoLink to Journal of Studies on Alcohol and Drugs
. 2022 Jan 19;83(1):106–114. doi: 10.15288/jsad.2022.83.106

The Influences of Posttraumatic Stress Disorder and Distress Tolerance on Trauma and Alcohol Cue Reactivity in a Sample of Trauma-Exposed College Students

Katherine C Paltell a, Erin C Berenz a,*
PMCID: PMC8819898  PMID: 35040766

Abstract

Objective:

Models of comorbid posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) often emphasize negative reinforcement drinking (i.e., drinking to reduce negative affect) as a key etiological and maintenance factor. However, potential risk factors related to negative reinforcement drinking in PTSD–AUD are less understood. Distress tolerance exhibits theoretical and empirical promise as one possible, malleable, risk factor. The current study used a trauma and alcohol cue reactivity paradigm to elucidate the role of perceived (i.e., self-reported) distress tolerance in trauma-related alcohol risk.

Method:

Participants were 185 university students (50.3% female) endorsing lifetime interpersonal trauma exposure and current weekly alcohol consumption. Subjective craving for alcohol was assessed in response to four combinations of audio narrative (personalized trauma vs. neutral) and beverage (alcohol vs. water) cues. Forward-fitting linear mixed-effects models were used to evaluate study hypotheses.

Results:

Perceived distress tolerance significantly interacted with beverage cue in relation to craving (β = -.293, p = .011), such that individuals low, as compared with high, in perceived distress tolerance reported greater craving for alcohol in response to the alcohol, but not water, beverage cue. Although low perceived distress tolerance was associated with greater alcohol coping motives and alcohol use problems at baseline, there were no main effects of perceived distress tolerance in relation to craving, and perceived distress tolerance did not significantly interact with trauma cues to predict craving (ps > .05).

Conclusions:

Among trauma-exposed young adult drinkers, low perceived distress tolerance may influence alternative processes of AUD risk, such as susceptibility to conditioned craving responses to alcohol.

Posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD) are highly comorbid (Blanco et al., 2013; Kessler et al., 2005; Pietrzak et al, 2011), which poses significant challenges in treatment settings (Foa & Williams, 2010; Roberts et al., 2015). For example, individuals with PTSD–AUD, compared with those with AUD alone, are more likely to relapse following AUD treatment (Brown et al., 1999; Norman et al., 2007). However, efforts to improve abstinence rates in PTSD–AUD by addressing PTSD have demonstrated little improvement in drinking outcomes compared with standard AUD treatment alone, in spite of successful amelioration of PTSD (Coffey et al., 2016; Ruglass et al., 2017). Therefore, understanding which individuals are most likely to develop chronic PTSD–AUD and identifying potential prevention targets is important.

Models of PTSD–AUD comorbidity often emphasize negative reinforcement drinking (i.e., drinking to reduce negative affect) as a key etiological and maintenance factor (Khantzian, 1999; O’Hare & Sherrer, 2011). Individuals with PTSD report coping-orientated drinking more often than those without PTSD (Filipas & Ullman, 2006; Waldrop et al., 2007), and coping-oriented alcohol use partially mediates the association between PTSD and alcohol use problems (O’Hare & Sherrer, 2011). Laboratory experimental designs such as the trauma and alcohol cue reactivity paradigm have been particularly useful in furthering understanding of the role of negative reinforcement drinking in PTSD–AUD risk. In this paradigm, craving for alcohol is measured in response to four combinations of narrative (trauma vs. neutral) and beverage (alcohol vs. water) cues. Prior research using the paradigm has found that individuals with comorbid PTSD–AUD display craving in response to trauma memories even when no alcohol is present (Coffey et al., 2002, 2006) and that cue-elicited craving for alcohol decreases following PTSD remission (Nosen et al., 2014). These findings indicate that there may be a learned association between trauma reminders and alcohol use.

Although the utility of trauma and alcohol cue reactivity paradigms as a means of assessing PTSD–AUD risk is well established, few studies have evaluated potential risk factors associated with laboratory craving in trauma-exposed drinkers, particularly in non–treatment-seeking samples where theoretical models of etiology may be especially relevant. For example, college students are at heightened risk for problem drinking (Jackson & Sartor, 2016; Kessler et al., 2005), and early adulthood is also a developmentally sensitive time for the onset of AUD (Slutske, 2005). Further, studies have shown that trauma-exposed college students are at especially high risk for drinking problems (Overstreet et al., 2017; Read et al., 2012). Therefore, trauma-exposed college student drinkers are an ideal population for evaluating PTSD–AUD risk factors.

One potential risk factor is distress tolerance, defined as the perceived capacity to withstand negative emotional and/or other aversive states (e.g., physical discomfort, pain, frustration; Howell et al., 2010). Distress tolerance, which has been conceptualized as a distinct construct that overlaps with other transdiagnostic cognitive-affective vulnerability factors (e.g., anxiety sensitivity [the fear of anxiety and related consequences]; Keough et al., 2010), exhibits theoretical and empirical promise as a possible risk factor related to negative reinforcement drinking in PTSD–AUD. Distress tolerance is appealing as a construct of study, given that it is malleable to clinical intervention (Bornovalova et al., 2012; Lotan et al., 2013). Therefore, extensive research has examined the role of unique distress tolerance in vulnerability for, and resilience to, psychopathology, with both low and high levels of distress tolerance implicated in maladaptive and adaptive behavioral health outcomes (Anestis et al., 2012; Leyro et al., 2010).

Prior research has determined that measures of distress tolerance differ as a function of distress type (e.g., physical vs. emotional), and even more so as a function of assessment modality (i.e., self-report vs. behavioral measures). Self-report and behavioral measures of distress tolerance often do not correlate (Marshall-Berenz et al., 2010; McHugh et al., 2011), and it has been suggested that these constructs could be referred to as “perceived distress tolerance” (i.e., assessed via self-report) and “behavioral distress tolerance” (i.e., assessed via behavioral tasks; Marshall-Berenz et al., 2010; McHugh et al., 2011). Studies in trauma-exposed samples with PTSD symptoms have found the most support for the relevance of perceived distress tolerance to emotional distress (Marshall-Berenz et al., 2011). Individuals with low perceived distress tolerance believe that they are unable to cope with the experience of negative affect and tend to engage in various emotional avoidance behaviors, including coping-oriented alcohol use (Marshall-Berenz et al., 2011; Simons & Gaher, 2005) and problem drinking (Buckner et al., 2007).

In trauma-exposed samples, low perceived distress tolerance has been identified as a partial mediator of the association between PTSD symptoms and alcohol use coping motives (Vujanovic et al., 2011), and elevated alcohol consumption has been reported by adults with low perceived distress tolerance and PTSD symptoms (Duranceau et al., 2014). Taken together, trauma-exposed individuals with lower perceived capacities to withstand emotional distress may use alcohol as a means to cope with the negative affect elicited by their trauma reminders. However, the majority of work exploring relationships among PTSD, perceived distress tolerance, and coping motives for alcohol has relied on cross-sectional survey methods as opposed to laboratory designs, such as the trauma and alcohol cue reactivity paradigm. Elucidating the role of perceived distress tolerance in trauma-related alcohol risk could inform etiological models of alcohol craving as a function of negative affect in high-risk trauma-exposed drinkers.

The current study examined the role of perceived distress tolerance in trauma and alcohol cue reactivity (i.e., self-reported alcohol craving) in a sample of college students endorsing lifetime interpersonal trauma exposure and current, weekly alcohol use. It was hypothesized that (a) perceived distress tolerance would interact with trauma cues to predict elevated craving, such that individuals low in perceived distress tolerance would exhibit greater subjective responses to trauma cues than those high in perceived distress tolerance. We also evaluated an alternative hypothesis, that (b) perceived distress tolerance would moderate an association between alcohol cues and craving, although insufficient research has been conducted to inform a role of perceived distress tolerance in conditioned craving to alcohol cues.

Method

Study overview

The current study uses secondary data from a laboratory investigation of trauma and alcohol cue reactivity (Berenz et al., 2021). Data were collected from 2015 to 2019 and at two universities; a “site” variable was created (0 = a university in the mid-Atlantic, 1 = an urban university in the Midwest) and included as a covariate in analyses. The Institutional Review Boards at each university approved all study procedures.

Participants

A total of 223 participants were enrolled in the main study. Of these, 24 were not scheduled for the laboratory session of the study because of ineligibility at baseline, 6 had missing data on one or more primary assessments, and 8 completed the laboratory session but had data excluded from analyses because of issues identified during the laboratory procedure. Ultimately, 185 participants (50.3% women) were included in the current analyses.

Participants were college students ages 18–25, recruited from paper flyers and online advertisements. Advertisements highlighted that the research team was seeking individuals who had experienced or witnessed “one or more stressful life events” and who “use alcohol regularly.” Interested individuals contacted the lab and completed screening procedures (see below). Inclusion criteria were a history of one or more interpersonal potentially traumatic events, current weekly alcohol use, and the ability to complete study procedures in English. Exclusion criteria were current use of craving-reducing medications or medications that interfere with cue-elicited craving, current or past participation in exposure-based therapy for PTSD, and participation in any substance use treatment program in the past 6 months.

Measures

Baseline session (Session 1).

(A) TIMELINE FOLLOWBACK (TLFB): The TLFB (Sobell & Sobell, 1992) assessed the presence and quantity of alcohol use for each of the 30 days before the participant's baseline session. Individuals who did not endorse regular alcohol use in the 30 days before Session 1 were excluded from participation in Session 2. The TLFB exhibits good reliability (Sobell et al., 1996) and concurrent validity with other alcohol consumption measures (Grant et al., 1995). The TLFB was used to assess past-30-day alcohol use frequency (i.e., number of drinking days in the past 30 days) and quantity (i.e., average number of drinks consumed per drinking day). Alcohol use frequency was included as a covariate in the primary models to account for the number of recent “learning trials” an individual has had (i.e., opportunities to pair alcohol cues with the acute effects of alcohol).

(B) DISTRESS TOLERANCE SCALE (DTS): The DTS (Simons & Gahr, 2005) is a 15-item self-report instrument designed to measure the extent to which individuals can withstand distressing affective states. Participants responded to questions (e.g., “I’ll do anything to stop feeling distressed or upset”) using a Likert scale ranging from 1 (strongly agree) to 5 (strongly disagree). The DTS demonstrates good test–retest reliability, convergent validity, and discriminant validity with established measures of mood (Simons & Gaher, 2005). The current study used the total DTS score as an index of perceived distress tolerance.

(C) TRAUMATIC LIFE EVENTS QUESTIONNAIRE (TLEQ): Interpersonal trauma history was assessed using the TLEQ (Kubany et al., 2000), a 23-item self-report measure that queries various potentially traumatic events. The TLEQ assessed the event frequency and severity and was used to identify interpersonal potentially traumatic events warranting additional assessment via clinical interview (below). The TLEQ demonstrates good test–retest reliability and convergent validity with trauma interview assessments. In the current study, the number of lifetime trauma categories endorsed by each participant was summed as an index of cumulative trauma. Cumulative trauma was included as a covariate in the primary models to account for differences in lifetime trauma exposure across participants.

(D) DRINKING MOTIVES QUESTIONNAIRE-REVISED (DMQ-R): Drinking motives were assessed using the DMQ-R (Cooper, 1994), a 20-item self-report measure designed to assess reasons (i.e., Social, Coping, Enhancement, and Conformity) people might be motivated to drink alcohol. Participants rated on a 5-point Likert-style scale how frequently each of the listed reasons motivated them to drink alcohol. The DMQ-R exhibits good psychometric properties, including good criterion validity and high internal consistency (Cooper, 1994; MacLean & Lecci, 2000). The current study used the DMQ-R Coping subscale as an index of frequency of drinking to cope with negative affect, for the purpose of baseline correlation analyses.

(E) CLINICIAN-ADMINISTERED PTSD SCALE FOR DSM-5 (CAPS-5): The CAPS-5 (Weathers et al., 2018), a diagnostic interview for current and lifetime PTSD symptoms uses the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5;American Psychiatric Association, 2013), diagnostic criteria to establish a past-30-day continuous PTSD symptom severity score (i.e., CAPS-5 total score) and diagnostic label (i.e., present vs. absent) for each participant. The CAPS-5 was completed with regard to all interpersonal potentially traumatic events meeting Criterion A for PTSD that were endorsed on the TLEQ. In the current analyses, the CAPS-5 total score was the principal measure of PTSD symptom severity and included as a covariate in primary models.

(F) MINI-INTERNATIONAL NEUROPSYCHIATRIC INTERVIEW (MINI; SHEEHAN ET AL., 1998): The MINI, a semi-structured clinical interview, was used to assess DSM-5 diagnostic criteria for anxiety and mood disorders, substance use disorders, eating disorders, and psychotic symptoms. Information obtained through this interview was used to determine whether participants met DSM-5 criteria for AUD, as well as the associated severity (i.e., mild, moderate, severe) of the AUD diagnosis. The current study used AUD diagnostic status, as measured by the MINI, for the purposes of sample descriptives.

Laboratory session (Session 2).

(A) THREE-ITEM ALCOHOL CRAVING SCALE: Craving for alcohol was assessed via three questions on a 0–10 Likert-type scale: “I crave a drink right now”; “I want a drink right now”; and “I have a desire for a drink right now” (Kozlowski et al., 1996). Participants rated their craving for alcohol following each of the four cue reactivity trials. In the current study, craving ratings were used as a primary outcome measure.

(B) SUBJECTIVE UNITS OF DISTRESS SCALE (SUDS): The SUDS (Wolpe, 1958) was used to measure participant's emotional distress on a 0–100 point scale (0 = totally relaxed and 100 = highest distress you have ever felt). Participants were asked to rate their SUDS level following the completion of each of the four cue reactivity trials. For the current study, SUDS ratings were evaluated for manipulation checks, to ensure trauma cues elicited greater distress than neutral cues.

Procedure

Screening. Interested individuals who initiated contact via telephone or email were scheduled for a phone screen that assessed eligibility, comprising their age, education status, frequency of alcohol use, lifetime interpersonal trauma exposure, current medication use, and history of PTSD or substance use treatment. Eligible individuals were scheduled for Session 1.

Session 1 (baseline). Informed consent was obtained, and participants completed the Session 1 self-report questionnaires, TLFB, and diagnostic interviews, which were administered by a trained Masters-level or doctoral student. The experimenter also obtained a detailed, written narrative of the participant's self-identified worst interpersonal traumatic event meeting Criterion A for PTSD (based on the CAPS-5). Specifically, the participant described, in detail, the traumatic experience, and the experimenter prompted for sensory details (e.g., sights, sounds), thoughts, emotions, and physical feelings as needed to ensure the vividness of the imagery. After Session 1 was completed, the narrative was edited for length, and a 60-second audio recording was created to serve as the trauma narrative cue in Session 2. The experimenter queried participants’ most frequently consumed alcohol beverage to use as an in vivo cue in Session 2. Participants who met inclusion criteria for Session 2 were compensated $25 and scheduled for Session 2 within 2 weeks from their Session 1 date. Participants were instructed to abstain from alcohol for 24 hours before Session 2. Participants who did not meet study criteria following the full baseline assessment received compensation but were not scheduled for Session 2.

Session 2 (laboratory session). Cue reactivity procedures were identical to those of Coffey et al. (2002), the gold-standard of assessment. First, a breath alcohol analysis test verified participants’ acute abstinence from alcohol. Participants were then seated in a comfortable chair with an adjustable-height table for cue presentation, and monitored through a nonrecording video camera behind a room partition. Each cue reactivity assessment consisted of the following procedures: (a) The participant closed their eyes and listened to a 60-second audio narrative (i.e., personalized trauma narrative or standard neutral narrative) over headphones. (b) The participant actively imagined the narrative scene for 2 minutes while viewing an in vivo beverage cue (i.e., personalized alcohol cue or water) that had been placed on the table in front of them. (c) The participant completed the self-report measures (i.e., craving scale, SUDS). A practice trial using the neutral-neutral cue combination was followed by the four experimental trials, which comprised the four possible cue combinations: trauma-alcohol (TA), trauma-neutral (TN), neutral-alcohol (NA), and neutral-neutral (NN). The order of cue presentations was counterbalanced between and within subjects by gender. Participants were compensated $50 for their participation in Session 2.

Data analytic plan

Analyses were conducted in R (Version 4.1.0, R Core Team, 2021). The tidyr 1.1.1 (Wickham & Henry, 2019) and dplyr 1.0.2 (Wickham et al., 2020) packages were used to organize, reshape, and summarize data. Results were visually displayed using the effects (4.2; Fox & Weisberg, 2019) and ggplot2 (3.3.2; Wickham, 2016) packages. Descriptive statistics were evaluated for key study variables, including evaluation of associations between distress tolerance and self-report measures of PTSD–AUD risk (e.g., PTSD symptom severity, alcohol use frequency, coping motives for alcohol use). Manipulation checks, conducted via a within-subjects analysis of variance, verified that trauma cues elicited greater emotional distress (i.e., higher mean SUDS rating) than neutral cues, and that alcohol cues elicited greater craving for alcohol (i.e., higher mean craving rating) than water cues.

Study hypotheses were evaluated using linear mixed-effects (LME) models, which required the lme4 1.1-23 R package (Bates et al., 2015b), with Satterthwaite degrees of freedom and subsequent p values for the parameters in the lmerTest package (3.1-3; Kuznetsova et al., 2017). Consistent with LME modeling recommendations (Bates et al., 2015b; Matuschek et al., 2017), random effects comprised the intercept and slopes of the repeated factors narrative cue (0:neutral, 1:trauma) and beverage cue (0:water, 1:alcohol). Random intercepts and slopes allow for the control of the mean response per individual and repeated measures slopes (i.e., random slopes) per individual. Random structure was checked for parsimony (Bates et al., 2015a; Matuschek et al., 2017) with the RePsychLing 0.0.4 package (Baayen et al., 2015), with random correlations blocked. Tables were reported using the texreg package (Leifeld, 2013). Covariates were previously selected on both theoretical and statistical bases; specifically, a number of theoretically meaningful covariates had been evaluated previously using forward-fitted LME models with these data, with the best-fitting model serving as the “covariate model” for the current study (Berenz et al., 2021). The covariates of cumulative trauma, data collection site, alcohol use frequency, PTSD symptom severity, and a PTSD × Narrative Cue interaction were included for all craving models.

To evaluate the interactions between perceived distress tolerance and narrative and beverage cue in relation to craving, forward-fitting models with -2 log likelihood ratio test were conducted to determine the best-fitting model to be carried forward at each step (Singer & Willet, 2003). Standardized beta coefficients of decomposed interactions were derived using the effectsize 0.4.5 package (Ben-Shachar et al., 2020). Three craving models were analyzed to evaluate (a) a distress tolerance main effect, (b) a Distress Tolerance × Narrative Cue interaction, and (c) a Distress Tolerance × Beverage Cue interaction, above and beyond the respective covariate model (i.e., Model 1). Interaction terms were only retained in the final model in the instance of improved model fit, per results of ratio testing.

Results

Sample characteristics and descriptive statistics

On average, participants (50.3% female; 53.5% White) endorsed exposure to six different types of traumatic events. The most frequently endorsed interpersonal traumas included witnessing family violence (43.2%), witnessing physical assault by a stranger (42.2%), and sexual assault as an adult (41.1%). In total, 49.2% of participants met criteria for a past-month diagnosis of PTSD (CAPS-5), and 82.7% met criteria for current AUD (MINI). Of those participants with current AUD, 30.7% and 32.7% met criteria for moderate and severe AUD, respectively. Assessment of past-30-day alcohol use revealed that, on average, participants used alcohol 10 days of the month, consumed 4 drinks per drinking episode, and engaged in 5 monthly binge drinking episodes.

Zero-order (bivariate) correlations

Correlations among the primary study variables are presented in Table 1. Distress tolerance (DTS total score) was significantly inversely associated with all continuous variables except for alcohol use frequency, with the strongest association observed between perceived distress tolerance and coping motives.

Table 1.

Zero-order (bivariate) correlations

graphic file with name jsad.2022.83.106tbl1.jpg

Variable 1. 2. 3. 4. 5. 6. M (SD)
1. Data collection site − −
2. Cumulative trauma 29** − 6.59 (3.32)
3. Alcohol use frequency .20** .18* − 10.37 (4.89)
4. CAPS-5 total score .08 .51** .12 − 15.04 (11.30)
5. DTS total score −.04 −2.5** −.12 −.48** − 44.41 (11.70)
6. DMQ coping motives .25** .33** .21** .41** −.53** − 12.49 (5.31)
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Notes: Data collection site = a university in the mid-Atlantic (0) or an urban university in the Midwest (1); cumulative trauma = number of lifetime trauma types assessed via TLEQ (Traumatic Life Events Questionnaire); alcohol use frequency = number of drinking days in past 30 days; total posttraumatic stress disorder (PTSD) symptom severity assessed via CAPS-5 (Clinician Administered PTSD Scale for DSM-5); DTS Total score = Distress Tolerance Scale. DMQ coping motives = Drinking Motives Questionnaire–Revised, Coping Motives subscale total score.

*

p < .05;

**

p < .01.

Perceived distress tolerance and craving for alcohol

A significant Distress Tolerance × Beverage Cue interaction was detected (Model 1c; β = -.293, p = .011) that significantly improved fit over the covariate model, χ2(2) = 9.46, p = .009. Examination of the interaction (Figure 1) indicated that individuals low, compared with high, in perceived distress tolerance reported greater craving for alcohol in response to the alcohol, β = -.23, t(204.42) = -2.83, p = .005, but not water, β = -.10, t(190.85) = -1.37, p = .171, cue. The main effect of perceived distress tolerance in relation to craving was not statistically significant (Model 1a; β = -.281, p = .074), and contrary to prediction, perceived distress tolerance did not significantly interact with narrative cue to predict craving (Model 1b; β = .189, p = .184). Neither Model 1a nor 1b improved fit over the covariate model, Model 1a, χ2(1) = 3.06, p = .080; Model 1b, χ2(2) = 4.76, p = .092. See Table 2 for model parameters.

Figure 1.

Figure 1.

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Association between beverage cues (i.e., water vs. alcohol) and subjective craving for alcohol at high and low levels of distress tolerance. “High” = 1 SD above sample mean; “Low” = 1 SD below sample mean; DTS = Distress Tolerance Scale total score; craving = self-reported craving for alcohol (on scale of 0–10). Error bars denote standard error. Asterisk (*) denotes significantly different comparison (p < .05).

Table 2.

Estimates, standard error, and model parameters for craving

graphic file with name jsad.2022.83.106tbl2.jpg

Variable Model 1 (Covariate model) Model 1a (DT Main Effect) Model 1b (DT x Narrative Cue) Model 1c (DT x Beverage Cue)
(Intercept) 1.48***(0.20) 1 48*** (0.20) 1.48***(0.20) 1.48***(0.20)
Narrative Cue: Trauma 1.06***(0.12) 1.06***(0.12) 1.06***(0.12) 1.06***(0.12)
Beverage Cue: Alcohol 1 40***(0.12) 1 40***(0.12) 1.40***(0.12) 1.41***(0.11)
Cumulative Trauma 0.11 (0.16) 0.13 (0.16) 0.13 (0.16) 0.13 (0.16)
Data Collection Site 0.69*(0.28) 0.68*(0.28) 0.68*(0.28) 0.68*(0.28)
Alcohol Use Frequency 0.45**(0.14) 0.42**(0.14) 0.42**(0.14) 0.42**(0.14)
PTSD Symptoms 0.76***(0.16) 0.62***(0.18) 0.59**(0.18) 0.61***(0.18)
PTSD Symptoms × Narrative Cue 0.45***(0.12) 0.45***(0.12) 0.54***(0.14) 0.47***(0.12)
DT −0.28(0.16) −0.34*(0.16) −0.22(0.16)
DT × Narrative Cue 0.19(0.14)
DT × Beverage Cue −0.29*(0.11)
AIC 3,112.18 3,111.11 3,111.41 3,106.72
BIC 3,181.60 3,185.16 3,190.09 3,185.40
Log likelihood −1,541.09 −1,539.56 −1,538.71 −1,536.36
Num. obs. 756 756 756 756
N 185 185 185 185
Var: ID (Intercept) 2.68 2.64 2.65 2.64
Var: ID Narrative Cue: Trauma 1.26 1.26 1.25 1.26
Var: ID Beverage Cue:
Alcohol 1.01 1.01 1.01 0.93
Cov: ID (Intercept) Narrative Cue: Trauma −0.16 −0.13 −0.14 −0.14
Cov: ID (Intercept) Beverage Cue: Alcohol 0.18 0.11 0.09 0.12
Cov: ID Narrative Cue:
Trauma Beverage Cue:
Alcohol 0.35 0.35 0.40 0.38
Var: Residual 1.51 1.51 1.51 1.51
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Notes: Cumulative trauma = number of lifetime trauma types assessed via TLEQ (Traumatic Life Events Questionnaire); data collection site = a university in the mid-Atlantic (0) or an urban university in the Midwest (1); alcohol use frequency = number of drinking days in past 30 days; Total posttraumatic stress disorder (PTSD) symptom severity assessed via CAPS-5 (Clinician Administered PTSD Scale for DSM-5); DT = Distress Tolerance Scale total score; AIC = Akaike information criterion; BIC = Bayesian information criterion; num. obs. = number of observed data points; var = variance (random effects); ID = subject; cov = covariance.

*

p < .05;

**

p < .01;

***

p < .001.

Discussion

The present study examined the effects of perceived distress tolerance on trauma and alcohol cue-elicited craving in a sample of college students endorsing lifetime interpersonal trauma exposure and weekly alcohol use. A significant interaction between perceived distress tolerance and beverage cue was observed, such that individuals low in perceived distress tolerance reported significantly greater craving in response to alcohol cues, compared with those high in perceived distress tolerance. Given that alcohol use frequency was included as a covariate, this suggests that there may be an association between perceived distress tolerance and conditioned craving for alcohol that exists above and beyond the frequency with which these individuals are drinking (i.e., opportunities to pair alcohol cues with the acute effects of alcohol).

There are various possible explanations for this effect that are not mutually exclusive. It could be the case that individuals low and high in perceived distress tolerance differ in their experience of the subjective effects of alcohol (Ray et al., 2010). For example, low perceived distress tolerance individuals may be more likely to experience acute effects of drinking that are reinforcing (e.g., elevated mood), thereby increasing the likelihood that these individuals would endorse a craving response in the presence of a drinking cue. The association may also reflect familial risk (genetic factors, shared environment) common to both distress tolerance and AUD (Pagan et al., 2006; Xian et al., 2000). Additional research using longitudinal methods, alcohol administration paradigms, and genetically informed designs would be useful for understanding this finding.

Given that prior cue reactivity research has found that subjective laboratory craving predicts subsequent alcohol consumption (Cooney et al., 1997; Papachristou et al., 2014), understanding the association between perceived distress tolerance and alcohol cue-elicited craving in young adult drinkers is of clinical importance. Perceived distress tolerance is malleable to clinical intervention (Lotan et al., 2013) and could enhance efforts to prevent chronic alcohol misuse in high-risk young adult drinkers. Additional research is needed to evaluate whether distress tolerance intervention could dampen alcohol cue reactivity, such as studies evaluating alcohol cue-elicited craving pre- and post-distress tolerance intervention.

Contrary to hypothesis, perceived distress tolerance did not interact with trauma cues to predict elevated subjective craving for alcohol. Specifically, low perceived distress tolerance did not predict stronger alcohol craving in response to personalized trauma memories, in spite of the trauma narrative eliciting elevations in anxious arousal. Therefore, even though perceived distress tolerance shows associations with self-reported alcohol coping motives in prior literature (Marshall-Berenz et al., 2011; Simons & Gaher, 2005) as well as the current analyses, perceived distress tolerance is likely not related to trauma-related negative reinforcement drinking in high-risk young adult drinkers. This finding does accord with one peripheral substance cue reactivity study in a treatment-seeking sample of individuals with a range of substance use (Vujanovic et al., 2018). It may be that self-reported coping motives, which capture a range of emotions falling under negative affect, do not correspond well to how individuals react to trauma-specific alterations in negative affect. Therefore, future research examining trauma-specific measures of coping motives for alcohol use may be valuable. Alternatively, it is possible that individuals are not reporting accurately on their reasons for drinking, perhaps because of low self-awareness of how they are using alcohol.

These findings should be interpreted in the context of study limitations. First, the current sample comprised young adult college students endorsing exposure to interpersonal trauma and regular alcohol use and may not generalize to other samples. However, the specificity of this sample was important, as it captured a developmentally sensitive period. Indeed, this sample endorsed high rates of both PTSD and AUD, which were comparable to those of similar college samples (Berenz et al., 2016) and in line with expectation, considering the recruitment focus of high-severity trauma and the low symptom count required for mild AUD. Second, because of the present study's cross-sectional design, conclusions regarding causation and temporality among study variables cannot be made, and future investigations using longitudinal methods are warranted. Ecological momentary assessment or similar methods (Veilleux et al., 2018) may be particularly useful for understanding the role of perceived distress tolerance in trauma-exposed individuals’ experiences of alcohol craving in the real world. Third, this study only used a self-report measure of distress tolerance. Given that self-report and behavioral measures of distress tolerance perform differently in studies of trauma and substance use (Vujanovic et al., 2018), the present study should be replicated using a behavioral distress tolerance task.

To conclude, despite a robust body of cross-sectional survey literature highlighting associations among trauma, perceived distress tolerance, and alcohol use outcomes, the present study is the first known investigation of perceived distress tolerance in the context of a laboratory trauma and alcohol cue reactivity paradigm. These preliminary findings offer important insight into alcohol risk among vulnerable young adult populations. Nonetheless, future studies using ecological momentary assessment and longitudinal methods are needed to further elucidate the nature of AUD risk among trauma-exposed individuals with differing capacities to withstand negative emotional states.

Footnotes

This research was supported by National Institute on Alcohol Abuse and Alcoholism Grant R00AA022385 (awarded to Erin Berenz).

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