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. Author manuscript; available in PMC: 2020 Oct 1.
Published in final edited form as: J Dual Diagn. 2019 Jul 14;15(4):233–242. doi: 10.1080/15504263.2019.1637039

PTSD symptom clusters and craving differs by primary drug of choice

Vanessa C Somohano a, Kristoffer L Rehder a, Tyree Dingle a, Taylor Shank a, Sarah Bowen a
PMCID: PMC6901023  NIHMSID: NIHMS1542806  PMID: 31304887

Abstract

Objective:

Research has demonstrated a cyclical relationship between posttraumatic stress disorder (PTSD) and substance use disorder (SUD). Identifying factors that link PTSD symptom clusters and SUD may illuminate mechanisms underlying the PTSD-SUD relationship, better informing interventions that target this comorbidity. The current study of individuals enrolled in an outpatient aftercare chemical dependency program in King County, Washington assessed whether overall PTSD symptoms, and specific PTSD symptom clusters predicted craving depending on individuals identified primary drug of choice (DOC).

Methods:

Participants eligible for the parent study were at least 18 years of age, fluent in English, medically cleared from substance withdrawal, able to participate in treatment sessions, and agreed to random assignment. Random assignment to either a mindfulness-based relapse prevention group, a standard relapse prevention group, or a treatment as usual group was conducted on a computer randomization program. A secondary analysis of baseline data was employed in the current study to determine which of the PTSD symptom clusters (avoidance, hyperarousal, and intrusion) predicted substance craving.

Results:

Co-varying for severity of dependence, results suggest that overall PTSD scores predicted craving in participants who identified alcohol, stimulants, and opiates as their primary DOC. Further, avoidance-related PTSD symptoms alone predicted a significant proportion of the variability in craving in stimulant users, and hyperarousal symptoms alone predicted a significant proportion of the variability in craving in alcohol users. No specific PTSD cluster significantly predicted a proportion of the variability in craving in marijuana or opiates users.

Conclusions:

Findings suggest craving may play a role in maintaining the relationship between specific PTSD symptom clusters and SUD, and the nature of this relationship may differ by primary DOC. The clinical trial on which this secondary analysis of data was conducted is registered as , at www.clinicaltrials.gov.

Keywords: Substance Use Disorder, Posttraumatic Stress Disorder, PTSD symptom clusters, craving, dual diagnosis, self-medication hypothesis

Introduction

Posttraumatic stress disorder (PTSD) is characterized by symptoms appearing after exposure to actual or threatened death, traumatic injury, or sexual assault, with symptoms categorized into four distinct clusters: Intrusion, Avoidance, Negative Alterations in Cognition and Mood, and Alterations in Arousal and Reactivity (American Psychiatric Association, 2013). In the general population, past-year prevalence rate of PTSD is approximately 4.7%, while lifetime prevalence rate is 6.1% (Goldstein et al., 2016). However, prevalence rates vary by population, type of trauma, and gender (Kilpatrick et al., 2013).

PTSD frequently co-occurs with substance use disorder (SUD; Grant et al., 2016). For example, among persons enrolled in inpatient SUD treatment, approximately 14% had a current diagnosis of PTSD (Chen et al., 2011). Similarly, a Dutch study of 423 patients in SUD treatment found that almost 37% met diagnostic criteria for current PTSD (Gielen, Havermans, Tekelenburg, & Jansen, 2012). The National Epidemiologic Survey on Alcohol and Related Conditions (N = 34,653) estimated 47% of persons with PTSD in the U.S. met criteria for SUD (Pietrzak, Goldstein, Southwick, & Grant, 2011) , and a Australian National Survey of Mental Health indicated nearly 35% of persons who met criteria for PTSD also met criteria for SUD (Mill, Teeson, Ross, & Peters, 2006). Rates of comorbid PTSD and SUD have been reported higher in some populations, such as combat veterans (Seal, Cohen, Waldrop, Cohen, Maguen, & Ren, 2011) and incarcerated women (Wolff, Frueh, Shi, Gerardi, Fabrikant, & Schumann, 2011).

A significant body of research supports the relationship between PTSD symptom severity and SUD severity (see reviews by Leeies, Pagura, Sareen, & Bolton, 2010; Conrad & Stewart, 2003; Jacobsen et al., 2001). It is essential to improve our understanding of this relationship, as persons with both disorders present with worse psychological functioning and greater psychiatric problems than persons with SUD alone (Flanagan, Korte, Killeen, & Back, 2016). Patients in residential SUD treatment with PTSD report greater overall emotion dysregulation and difficulty controlling impulsive behavior when distressed compared to patients without PTSD (Weiss, Tull, Anestis, & Gratz, 2012). Similarly, patients in SUD treatment who report higher PTSD scores also report higher scores on craving, depression, anxiety and stress (Wieferink, de Haan, Dijkstra, Fledderus, & Kok, 2017). Further, persons in SUD treatment with co-occurring PTSD have worse treatment outcomes than those with SUD only, including treatment noncompliance and shorter time to relapse (see review by Najt, Fusar-Poli, & Brambilla, 2011). Remission of PTSD symptoms, however, is predictive of abstinence from substance use up to five years following SUD treatment (Coffey, Schumacher, Brady, & Dansky Cotton, 2007; Hein et al., 2010), pointing to the interconnected nature of these disorders.

The relationship between PTSD and SUD is important to understand as persons who have experienced trauma, but do not meet diagnostic criteria for PTSD, still are at elevated risk for negative mental health outcomes. For example, persons with subthreshold PTSD symptoms report greater psychological impairment compared to trauma exposed persons without PTSD (Mylle & Maes, 2004), and subthreshold PTSD symptoms are consistently related to elevated risk for psychiatric conditions (Grubaugh, et al., 2005; Mota, et al., 2016). In addition, trauma exposed persons with subthreshold PTSD have greater risk for binge drinking compared to trauma exposed persons without PTSD (Boscarino, & Adams, 2009). There seem to be population-specific patterns, such as subthreshold PTSD as a risk factor for substance misuse in college students (Borsari, Read, & Campbell, 2008, 2009), and association of lifetime subthreshold PTSD with greater likelihood of lifetime SUD in military veterans (Mota, Tsai, Sareen, Marx, Wiscco, et al., 2016).

Although several models have been offered to explain co-occurring PTSD-SUD, the self-medication hypothesis (Khantzian, 1985) stands as the most accepted (Kramer, Polusny, Arbisi, & Krueger, 2014). This hypothesis posits that individuals use, and eventually become addicted to, substances as a way to cope with distressing PTSD symptoms acquired prior to use. This has been supported by numerous studies (Dworkin, Wanklyn, Stasjewicz, & Coffey, 2018; Ertl, Saile, Neuner, & Catani, 2016; Garland, Pettus-Davis, & Howard, 2013; Shadur, Hussong, & Haroon, 2015; Simpson et al., 2012), including studies showing that fluctuations in PTSD and SUD symptoms occur simultaneously. One study found fluctuations in weekly PTSD symptom severity were associated with concurrent fluctuations in alcohol and cocaine dependence severity, and opiate dependence severity the following week (Ouimette, Read, Wade, & Tirone, 2010). Similarly, Kaysen and colleagues (2014) found greater daily fluctuations in PTSD symptom severity predicted greater urges to drink in a sample of college women who experienced sexual assault, specifically when they experienced intrusion and avoidance symptoms. Additionally, using ecological momentary assessment, Possemato et al. (2015) found a higher incidence of PTSD symptoms was associated with heavier drinking within a 3-hour block of time, but no increases in alcohol use were observed in subsequent time blocks.

Alongside studies of co-occurring PTSD-SUD are investigations of specific PTSD symptom clusters and substance use (Debell et al, 2015; Dworkin et al, 2017, 2018). Results from these studies vary, however. Increased hyperarousal and avoidance/numbing symptoms have been found in persons with cocaine, alcohol, opioid, cannabis, and amphetamine use disorders (Dworkin et al., 2018; Khoury, Tang, Bradley, Cubells, & Ressler, 2010; Afful, Strickland, Cottler, & Bierut, 2010; Smith et al., 2010; Smith et al., 2016), and increased intrusion symptoms have been found in persons with cocaine, alcohol, cannabis, and sedative use disorders (Avant, Davis, & Cranston, 2011; Khoury et al., 2010). Inconsistent findings highlight the need for further investigations to clarify these relationships.

The link between affective discomfort, craving and substance use may shed light on the substrates of the PTSD-SUD relationship. While there are multiple predictors of substance use, (e.g., negative affect; Slofstra et al., 2018; Witkiewitz & Bowen, 2010) and impulsivity (see review by Loree, Lundahl, & Ledgerwood, 2015), craving has consistently been shown to be a primary predictor in SUD populations (Weiss, 2005). The aversive and seemingly uncontrollable nature of PTSD symptoms may lead to craving in individuals with SUD, as research indicates negative affect and craving are positively correlated (Schlauch, Gwynn-Shapiro, Stasiewicz, Molnar, & Lang, 2013). Saladin et al. (2003) found that, among individuals with co-occurring PTSD-SUD, PTSD symptom severity, elicited by reading a trauma script, predicted substance craving regardless of whether substance cues were present. Further, substance cues only elicited craving when the trauma script preceded substance cues, suggesting that trauma cues elicit substance craving over substance use cues alone (Saladin et al., 2003). Moreover, management of craving appears to have a positive effect on substance use severity following treatment (Mo & Deane, 2016).

Isolating predictors of relapse, such as craving, could help identify specific factors underlying use in relation to PTSD (Bradizza, Stasiewicz, & Paas, 2006), and further enhance treatments for individuals with SUDs experiencing trauma-related symptoms. Interventions that target craving in individuals experiencing specific PTSD symptoms may decrease the likelihood of relapse. Further, investigating PTSD cluster-craving relationships within various drugs of choice (DOCs) may inform more individualized treatment approaches, and may enhance treatment gains.

While studies have demonstrated relationships between PTSD severity, craving, and substance use, there is limited understanding of links within these relationships for different DOCs. Studies demonstrate associations between specific SUDs and PTSD clusters (Dworkin, Wanklyn, Stasiewicz, & Coffey, 2018; Khoury et al., 2010; Afful et al., 2010; Smith et al., 2010, 2016; Avant, Davis, & Cranston, 2011; Khoury, Tang, Bradley, Cubells, & Ressler, 2010); however, no locatable literature examines whether specific PTSD symptom clusters differentially predict craving depending on DOC. Such an understanding may reveal patterns of attempting to self-medicate certain symptoms through a substance that provides specific effects. As craving is a primary predictor of relapse (Fatseas, Serre, Alexandre, Debrabant, Auriacombe, & Swendsen, 2015; Serre, Fatseas, Swendsen, & Auriacombe, 2015), it may provide a more nuanced understanding of which PTSD clusters predict craving for different DOCs.

The current study was a secondary analysis of baseline data collected from adults in SUD treatment (Bowen et al., 2014), and assessed which specific PTSD symptom clusters predicted craving among individuals stratified by primary DOC. Specifically, we hypothesized that overall PTSD symptom severity would predict craving for all primary DOC categories, and that specific symptom clusters would differentially predict craving for each DOC. In line with the self-medication hypothesis (Khantzian, 1985), we expected high levels of hyperarousal and/or avoidance symptoms would be associated with craving for substances such as marijuana, alcohol or opiates, versus stimulants. We also hypothesized that high levels of re-experiencing symptoms would predict craving for stimulants, as stimulant use often results in physical activity (NIDA, 2013), which may serve as a distraction from intrusive thoughts.

Methods

2.1. Participants

Data for the current study are drawn from the baseline assessment (N = 257) of an IRB approved, randomized-controlled trial conducted in a community-based outpatient aftercare program (Bowen, et al., 2014). Prior to aftercare, participants in the parent study had attended either inpatient or intensive outpatient SUD treatment. Oral and written informed consent was obtained. Eligible participants were fluent in English, medically cleared to attend aftercare, able to participate in treatment sessions, and agreed to random assignment. Participants were not required to meet criteria for a dual diagnosis in order to be included. Individuals were excluded from the original study if they had a current diagnosis of dementia or a psychotic disorder, were experiencing suicidality, were an imminent danger to others, or had participated in previous MBRP trials. Information regarding co-occurring mental health diagnoses was not reported. See Table 1 for participant demographics.

Table 1:

Sample Demographic Characteristics

Demographic Factors (N = 257)
Age M (SD)
38.51 (11.03)
Gender n (%)
Male 182 (70.8)
Female 70 (27.2)
Other 1 (.4)
Race/Ethnicity
White 128 (49.8)
Black 53 (20.2)
Hispanic 22 (8.6)
Asian 2 (.8)
Native American 16 (6.2)
Mixed 26 (10.3)
Other 9 (3.5)
Education
≤ GED 82 (31.6)
≥ High School 174 (68.0)
Household Annual Income
0-$4,999 151 (58.8)
$5,000-$9,999 25 (9.7)
> $10,000 43 (16.7)
Unknown 34 (13.2)
Primary drug of choice
Alcohol 131 (51.0)
Stimulants 66 (25.7)
Opiates 36 (14.0)
Marijuana 24 (9.3)
Prescribed medication-assisted treatment
36 (14.2)
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Note. GED = general education development.

2.2. Measures

Paper-and-pencil self-report questionnaires were administered in the original study (Bowen et al., 2014), including information regarding SUD diagnosis and drug of choice. Measures included in the current study are listed below.

PTSD Checklist – Civilian version (PCL-C; Weathers et al., 1994).

The PCL-C is a 17-item Likert scale assessing Diagnostic and Statistical Manual for Mental Health Disorders-IV-Text Revision (DSM-IV-TR; APA, 2000) symptoms for PTSD over the past 30 days. Items can be totaled for overall symptom severity, or calculated for symptom cluster subscale scores. The PCL-C has shown good test–retest reliability and internal consistency (Blanchard et al., 1996; Ruggiero et al., 2003). Items range from 1 (not at all) to 5 (extremely). In the current study, internal consistency of total PCL-C was excellent (α = .93). Internal consistency for the re-experiencing and avoidance clusters were good (α = .86 and α = .85, respectively), and poor for hyperarousal (α = .67). The PCL-C, versus the PCL-5, was used because at the time of the original trial, the DSM-5 (APA, 2013), and thus PCL-5, was not yet available.

Penn Alcohol Craving Scale (PACS; Flannery, Volpicelli, & Pettinati, 1999).

The PACS is a 5-item Likert scale assessing intensity, duration, and frequency of substance cravings (Flannery, Volpicelli, & Pettinati, 1999). Items range from 0 (never/least severe) to 6 (always/most severe). The PACS was adapted to include craving for any substance of choice versus only alcohol (Bowen, Chawla, Collins, Witkiewitz, Hsu, Grow, et al. 2009). In the current study, internal consistency was good (α = .88).

Severity of Dependence Scale (SDS; Gossop et al., 1995).

The SDS is a 5-item Likert-type scale assessing degree of substance dependence. Items are rated from 0 (never/almost never) to 3 (always/nearly always). In the current study, internal consistency was good (α = .86).

2.3. Procedure

For the current study, data were split into four primary DOC categories: alcohol, stimulants (cocaine, and methamphetamine), opioids (heroin and prescription opioids) and marijuana. SPSS V.25 was used for all analyses.

2.4. Statistical Analyses

Data were checked for normality, and assumptions were met for multiple regression analyses. Two multiple regression analyses were run for each primary DOC group to determine whether PCL-C overall scores and which PCL-C subscale scores significantly predicted substance craving. Since severity of substance dependence is correlated with craving in the current study (r = .228; p <.000), SDS scores were added as covariates in the model. Gender (r = −.007, p = .458) and medication assisted treatment (r = −.057, p = .181) were not correlated with substance craving, and were not included in the model. Mean imputation was used for item-level missing data for participants with > 80% complete data, and excluded from analyses if they had < 80% missing item-level data (n = 8). For the first regression, SDS total was entered into step 1, and PCL-C overall score was entered in step 2. In the second regression, SDS total was entered into step 1, and PCL-C subscale scores were entered simultaneously into step 2. Clusters were entered simultaneously to assess which of the three clusters predicted substance craving when assessed together.

Results

Descriptive statistics and correlations between SDS, PCL-C and PACS can be found in Table 2.

Table 2.

Means and Correlations of PTSD Symptom Severity, Craving, and Severity of Dependence.

Primary DOC M (SD) 1 2 3 4 5 6
Alcohol n = 131
1. PTSD Symptom Severity 35.83 (12.93) -
2. Hyperarousal 9.40 (3.40) .869** -
3. Avoidance 2.28 (0.85) .942** .731** -
4. Re-experiencing 2.19 (0.80) .874** .660** .717** -
5. Craving 6.56 (5.10) .424** .429** .396** .359** -
6. Severity of Dependence 8.97 (4.11) .319** .328** .309** .273** .142* -
Stimulants n = 66
1. PTSD Symptom Score 34.48 (12.06) -
2. Hyperarousal 8.67 (3.44) .869** -
3. Avoidance 2.23 (0.82) .953** .793** -
4. Re-experiencing 2.11 (0.80) .874** .660** .772** -
5. Craving 5.23 (4.17) .363** .334** .405** .233* -
6. Severity of Dependence 9.61 (3.86) .248* .206* .201* .300** .245* -
Opiates n = 36
1. PTSD Symptom Score 34.08 (10.28) -
2. Hyperarousal 8.92 (2.98) .830** -
3. Avoidance 2.18 (0.79) .934** .686** -
4. Re-experiencing 2.01 (0.66) .799** .544** .607** -
5. Craving 9.05 (5.47) .350* .287* .305* .322* -
6. Severity of Dependence 12.28 (2.68) −.207 −.244* −.272 .003 .163 -
Marijuana n = 24
1. PTSD Symptom Score 33.62 (11.49) -
2. Hyperarousal 9.00 (3.32) .844** -
3. Avoidance 2.14 (0.86) .869** .582** -
4. Re-experiencing 2.00 (0.85) .844** .636** .596** -
5. Craving 6.16 (4.98) .356* .446** .229 .180 -
6. Severity of Dependence 5.46 (3.89) .424* .390* .241 .474** .379* -
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Note. PTSD = posttraumatic stress disorder; DOC = drug of choice.

*

p < .05.

**

p < .001.

For participants who identified alcohol as primary DOC (n = 131), PCL-C overall score predicted 18% of the variability in craving, F(2, 128) = 14.061, p < .001, R2 = .180. When mean PCL-C cluster scores were entered as separate variables, the model was still significant, F(4, 126) = 7.958, p < .001, R2 = .202; PTSD-related hyperarousal predicted a significant portion of variance in alcohol craving, t(126) = 2.283, p = .024, R2 =.033.

For participants identifying stimulants as primary DOC (n = 66), PCL-C overall score predicted 15.7% of the variability in craving, F(2, 63) = 5.886, p = .005, R2 = .157. When mean PCL-C cluster scores were entered as separate variables, the model was still significant, F(4, 61) = 4.334, p = .004, R2 = .221; PTSD-related avoidance predicted a significant portion of variance in stimulant craving, t(61) = 2.445, p = .017, R2 =.076.

For participants who identified opiates as primary DOC (n = 36), mean PCL-C overall score predicted 18.5% of the variability in craving, F(2, 33) = 3.751, p = .034, R2 = .185. When PCL-C cluster scores were entered into the model as separate variables, no one cluster alone significantly contributed to variance accounted for in opiate craving, F(4, 31) = 1.732, p = .168, R2 = .183.

For participants who identified marijuana as primary DOC (n = 24), PCL-C overall score did not significantly predict craving, F(2, 21) = 2.290, p = .126 R2 = .179. When PCL-C cluster scores were entered into the model separately, no one cluster significantly predicted craving F(4, 18) = 2.014, p = .113, R2 = .298; however, trauma-related hyperarousal accounted for 12.4% of the variability in craving, t(19) = 1.834, p = .080, R2 =.124. (see Table 3).

Table 3.

Multiple Regression Analyses Predicting Substance Craving by PTSD Symptom Severity and by Trauma Symptom Clusters while Covarying Severity of Dependence.

Primary Drug of Choice
Predictor Alcohol Stimulants Opiates Marijuana
F R2 ΔR2 β t F R2 ΔR2 β t F R2 ΔR2 β t F R2 ΔR2 β t
PTSD Overall Severity 14.016*** .180 .160 .422 4.997*** 5.886** .157 .097 .322 2.695** 3.751* .185 .159 .407 2.536* 2.290 .179 .035 .207 .948
Clusters 7.958*** .202 .161 - - 4.334** .221 .161 - - 1.732 .183 .156 - - 2.014 .298 .154 - -
Avoidance .007 .141 1.071 .076 .542 2.445* .017 .200 .804 .002 .055 .218
Hyperarousal .033 .281 2.283* .001 .044 .237 .011 .147 .634 .124 .490 1.834
Re-experiencing .003 .076 .640 .029 −.278 −1.512 .008 .120 .556 .047 −.320 −1.129
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Note. Craving as measured by the Penn Alcohol Craving Scale (PACS), modified for substance craving. PTSD = posttraumatic stress disorder.

*

p < .05.

**

p < .01.

***

p < .001.

Discussion

The current study examined relationships between PTSD clusters, SUD craving, and DOC among substance users attending SUD outpatient aftercare programs. Specifically, we assessed which PTSD symptom clusters predicted craving for different primary DOC. It was hypothesized that overall PTSD symptom severity would predict craving for all DOCs, and only specific PTSD clusters would predict craving based on identified DOC. Results suggested that, after controlling for severity of dependence, overall PTSD symptom severity significantly predicted craving for those who identified alcohol, stimulants, and opiates as primary DOC; however, it did not predict craving for those who identified marijuana as primary DOC. Thus, our first hypothesis, that overall PTSD symptom severity would predict craving for all primary DOC categories, was only partially confirmed. Results suggest use of alcohol, stimulants, and opiates may have been negatively reinforced, (i.e., individuals repeatedly used a specific substance to alleviate PTSD-related distress), which then increased the probability of future use and/or craving. This supports the self-medication hypothesis (Khantzian, 1985), and aligns with previous studies in which PTSD symptom severity significantly predicted craving among persons with co-occurring PTSD-SUD (Simpson et al., 2012).

Our second hypothesis posited that only specific PTSD symptom clusters would predict craving depending on primary DOC. Indeed, individuals endorsing marijuana as primary did not show a significant relationship between overall levels of PTSD, symptom clusters, and craving. To check whether non-significant results were due to lack of statistical power, a post hoc power analyses was conducted using G*Power (Faul, Erdfelder, Lang, & Buchner, 2007) with power (1 – β) set at 0.80 and α = .05, two-tailed. The power analysis indicated the sample size of n = 77 would be needed to detect a medium sized effect (0.15). The power of the current study sample size to detect medium effect size in those who identify marijuana as primary was 0.42. Thus, lack of significant findings may be due to limited number of participants identifying marijuana as primary DOC. Additionally, 91.0% of the sample who identified marijuana as primary DOC identified alcohol (58.3%), stimulants (20.8%) and opiates (4.2%) as secondary DOC; thus, marijuana may be used to counterbalance effects of the secondary DOC (e.g., alcohol withdrawal), and may therefore be unrelated to PTSD symptoms.

Results supporting our second hypothesis demonstrated that hyperarousal significantly predicted craving for those who identified alcohol as the primary DOC. This finding aligns with results from a study by Simpson, Stappenbeck, Varra, Moore, and Kaysen (2012), in which symptoms of hyperarousal, particularly startle response, anger, and irritability, predicted same-day craving for alcohol; the effect was stronger for women versus men. They also found symptoms of sleep disturbance and hypervigilance predicted next-day craving for alcohol, with no difference between genders. Given that alcohol is a CNS depressant, it may alleviate arousal and reactivity in individuals experiencing PTSD-related hyperarousal symptoms. Consequently, the anxiolytic properties of alcohol may negatively reinforce continued use. This is supported by studies suggesting alcohol use, AUD diagnosis, and longitudinal consequences of alcohol use are predicted by hyperarousal symptoms (Read, Colder, Merrill, Ouimette, White, & Swartout, 2012).

While our hypothesis that re-experiencing-related PTSD symptoms would predict craving for stimulants was not supported, results indicated avoidance-related PTSD symptoms significantly predicted craving for self-identified stimulant users, suggesting stimulant drugs may be used to avoid/escape PTSD-related distress. Previous studies found that PTSD symptom severity predicted craving among cocaine-dependent individuals in response to trauma cues (Khantzian, 1985; Saladin et al., 2003). Stimulant use increases motor activity for long periods of time (SAMHSA, 1999), and therefore may be used to initiate engagement in activities that distract from trauma cues. Additionally, initial euphoric effects of stimulants may shift focus from aversive PTSD symptoms to hedonic stimuli, providing temporary escape from distress.

No one specific PTSD symptom cluster predicted craving for persons who identified opioids as their primary DOC. Total PCL-C score predicted craving in the first regression analysis. However, when symptom clusters were entered as individual predictors, results were non-significant, indicating no one specific PTSD symptom cluster predicted craving. To assess whether non-significant results were due to lack of statistical power, a post hoc power analyses was set at 0.80 and α = .05, two-tailed. Results indicated sample size would have to increase up to n = 85 to detect a significant medium sized effect. Power in the current study to detect medium effect size in those who identify opiates as primary DOC was 0.37.

Limitations of this study should be noted. First, a large proportion (81.3%) of participants endorsed polysubstance use, and identified alcohol as secondary DOC (21.8%); therefore, there may be confounding effects of use of multiple substances on craving. While this is a common challenge in substance use research, literature suggests polysubstance use profiles can vary based on primary substance of use (Connor, Gullo, White, & Kelly, 2014). Thus, examining whether PTSD symptoms predict craving for the primary substance in polysubstance users is warranted. Second, only 24 participants identified marijuana as primary DOC, and 36 endorsed opiates, which limited power to detect which individual clusters predicted craving in this subset. Third, the PCL-C was used to measure these data because, during the time of the original study, the PCL-5 was yet not available. The DSM-5, and subsequently the PCL-5, includes a fourth PTSD symptom cluster of negative alteration in mood and cognition. Variability in craving due to this cluster is thus not represented the PCL-C three-cluster model. Fifth, variables such as co-morbid psychiatric diagnoses and amount of time in treatment prior to aftercare are factors that impact craving, and were not assessed in the parent study. Finally, assessment of trauma exposure was not collected during the parent trial, thus elevated ratings of trauma symptom severity via the PCL-C may actually reflect symptoms of general distress or negative affect. While the PCL-C demonstrates good discriminant validity between related constructs (i.e., depression, anxiety, hostility, physical and emotional functioning; see review by Wilkins, Lang, & Norman, 2011), future studies should include a standardized assessment of trauma exposure in addition to PCL-C scores to better distinguish trauma symptoms from other psychological symptoms.

Findings from the current study further inform our understanding of the PTSD-SUD relationship. Specifically, craving elicited by PTSD symptoms may differ between individuals with different DOCs, shaped by a history of attempts to alleviate specific symptoms with specific effects of different substances. A more nuanced understanding of factors that underlie and perpetuate PTSD-SUD comorbidity can offer specificity to current treatments targeting dually-diagnosed individuals.

Acknowledgements

The authors wish to thank all who contributed to the completion of the original randomized-controlled trial in 2014.

Funding

Funding for the original study was provided by NIDA 5 R01 DA025764-02. NIDA had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

The original trial from which data for this study was drawn was supported by the National Institutes of Health [NIH/NIDA 5 R01 DA025764-02].

Footnotes

Disclosures

All authors declare that they have no conflicts of interest.

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