A Systematic Review of the Self-Medication Hypothesis in the Context of Posttraumatic Stress Disorder and Comorbid Problematic Alcohol Use

Method

Results

Discussion

The present systematic review aimed to provide a critical synthesis of the existing literature on the drinking-to-cope self-medication hypothesis with regard to comorbid PTSD and alcohol use, specifically, and to use the findings to inform future directions in the field. Overall, the literature provides support for the self-medication hypothesis across a variety of methodological approaches such that drinking-related coping motives and tension-reduction expectancies were broadly found to influence the association between PTSD and alcohol use. However, it should be noted that a majority of the included studies reported positive findings, which could potentially support the presence of a “file drawer” effect, which suggests that studies that did not produce significant findings (i.e., did not find support for the self-medication hypothesis) were less likely to be published than those that did.

By and large, the included studies assessed a range of generalized drinking motives, tension-reduction strategies, or alcohol expectancies to infer trauma-specific drinking-to-cope rather than to assess trauma-related drinking-to-cope specifically; this demonstrates a notable lack of measures that explicitly assess trauma- or PTSD–specific drinking-to-cope motives. Moreover, we found methodological inconsistencies across studies that we believe may have implications for the self-medication literature as a whole. Each of these topics is discussed in turn.

Despite its popularity, a systematic review of the literature revealed a lack of rigorous empirical evidence in support of the self-medication model, which is likely due to several important methodological considerations. Such considerations, deduced from this systematic review, include the lack of specific operationalization of trauma-specific drinking-to-cope, lack of longitudinal study designs and mediational analyses to account for the temporal and causal assumptions underlying the self-medication model, heterogeneity in alcohol assessment, and failure to account for potential confounding variables, such as sample selection (e.g., sex, race/ethnicity), trauma type and timing, and other commonly comorbid internalizing disorders, such as depression and anxiety.

With the exception of the PTSD-Alcohol Expectancies Questionnaire (P-AEQ), which assesses expectations of the effects of alcohol on PTSD symptoms and was only used in two of the 24 included studies, the present systematic review of the literature revealed that the self-medication model is frequently postulated to explain PTSD–AUD comorbidity in the absence of any explicit validated measure of trauma-specific drinking-to-cope. The prolific use of measures assessing general drinking-to-cope motives (e.g., the Coping subscale of the Drinking Motives Questionnaire [DMQ-Cope]) to infer trauma-related drinking creates an illusion in the literature that drinking-to-cope motives are synonymous with drinking to cope with PTSD symptoms specifically; however, in practice, drinking to cope is assessed with regard to negative internal experiences more generally. For example, a sample item on the DMQ-Cope asks respondents if they use alcohol “to cheer you up when you’re in a bad mood” (Cooper, 1994). To date, it appears that no studies have explicitly examined the extent, in terms of frequency and quantity, that drinking-to-cope relates to PTSD symptoms specifically, making this a critical void to fill.

In addition to this critical lack of assessment of drinking to cope with trauma-specific symptoms, only a few longitudinal published longitudinal studies have investigated the temporal precedence of PTSD before AUD, a basic assumption of the self-medication model. If alcohol use among individuals with PTSD represents attempts at self-medication of PTSD symptoms, then it stands that problematic alcohol use should develop following trauma exposure and the emergence of PTSD symptoms (Stewart et al., 1998). Thus, to truly test the theory that PTSD increases the subsequent risk for AUD (i.e., self-medication), longitudinal research designs are warranted. However, according to a recent review published by Langdon and colleagues (2017), and confirmed through the present systematic review, only three studies to date have prospectively examined the effects of trauma exposure and PTSD on subsequent alcohol use (Breslau, Davis, & Schultz, 2003; Read et al., 2012; Testa, Livingston, & Hoffman, 2007). Notably, none of these studies met the inclusion criteria for the present systematic review because they did not include any assessment of drinking-to-cope. Of the 24 studies that did meet the current review’s eligibility criteria, only one was longitudinal in design (Beseler et al., 2011). However, because preliminary analyses failed to show an association between PTSD and alcohol-related outcomes, Beseler and colleagues (2011) did not include any measure of PTSD or traumatic stress in their final analyses.

Although the results of the systematic review revealed only one longitudinal study, two included studies (Simpson et al., 2014; Taylor, 2011) applied daily time-series analyses, each collecting daily monitoring assessments over the span of 7 days. Time-series analyses are similar to longitudinal analyses in that variables are examined at multiple times; however, whereas longitudinal data typically examine changes in variables over long periods of time (e.g., months or years) between multiple individuals, time-series information is a collection of observations for a single individual at multiple short and evenly spaced time intervals (e.g., every 24 hr for 7 days), and, typically, these observations are modeled as time-dependent in study analyses (Kazdin, 2003). It is interesting to note that the two studies that used time-series analyses reported conflicting results: One study provided support for the self-medication model (Simpson et al., 2014), whereas the other failed to demonstrate support for the self-medication model (Taylor, 2011). The stark contrast between these findings could likely be explained by a number of factors, including the use of disparate samples and methodology, the implications of which are discussed in more detail in the following sections.

The present systematic review revealed additional notable methodological concerns and inconsistencies that likely contribute to the current lack of substantiality of the self-medication model. For instance, provided that the self-medication model is inherently mediational by design, it would follow that the use of mediational analyses to test its validity is imperative. Surprisingly, however, of the 24 studies included in the systematic review, fewer than half included mediational analyses as part of their data analytic plan, and, when they did, it was not always with alcohol as the outcome and drinking to cope as the mediator, as the self-medication hypothesis would suggest.

Another notable threat to the internal validity of the self-medication model is the failure to standardize the operationalization of alcohol use as an outcome. This is a difficult feat given the vast heterogeneity of AUD, which presents symptoms on a continuum of severity that ranges from occasional binge drinking to chronic heavy drinking (Litten et al., 2015). In attempts to capture AUD heterogeneity, numerous validated measures have been created to reliably capture these various presentations and neurobiological research that are used to inform heuristic frameworks for personalized treatment. The inclusion of a plethora of alcohol phenotypes may potentially result in the increased credibility of the self-medication model but does pose a challenge with regard to synthesis of the literature. For example, the studies included in this review operationalized alcohol outcomes in several different ways. The frequency and/or quantity of alcohol consumption was the most commonly used assessment of alcohol use, with 41.6% (k = 10) of the included studies assessing the frequency or quantity of use within a specified time period, which ranged from drinks per day to drinks over a 3-month period. Alcohol use disorders and alcohol abuse symptoms were the second most commonly used method for assessing alcohol-related outcomes (37.5%; k = 9). However, the studies varied concerning which edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM) was used for diagnostic criteria, creating further complications in that diagnostic criteria evolves with each version of the DSM. Finally, 20.8% (k = 5) of the included studies assessed alcohol use by measuring various negative consequences and problems related to drinking, such as issues of an interpersonal, occupational, and/or physical nature. In many ways, this variability in measurement is a notable strength of the self-medication literature as it helps capture the heterogeneity of alcohol use and AUD. However, the lack of standardization between studies that claim to support the self-medication model makes the empirical certainty of the self-medication model difficult to determine.

A review of the literature also calls for consideration of the variation between sample selection criteria and subsequent sample descriptive characteristics, as these differences hold a number of methodological implications. The broad variation between studies with regard to ascertainment and sample constitution has both empirical strengths and weaknesses. For instance, the extension of this literature beyond common convenience samples (e.g., undergraduate populations) to more distinct populations, particularly those at an increased risk for both PTSD and AUD (e.g., veteran populations), is a strength of the current PTSD–AUD self-medication literature such that it increases external validity, or the extent to which the results of an investigation can be generalized, beyond the conditions of the experiment, to other populations, settings, and circumstances (Kazdin, 2003). The examination of these associations among community, college, veteran, inpatient, epidemiologic, and domestic violence populations allows for inferences to be made for a wider breadth of individuals and, consequently, may lead to more broad-reaching dissemination of prevention and intervention programs. The same strength could be said for the variability among other important factors, such as sex and race/ethnicity. However, as is commonly seen across various literature, the studies that used undergraduate samples were composed of disproportionately more female than male participants. Additionally, multiple studies (k = 8) used exclusively female samples. In some instances, this was likely because the assessed trauma exposure was sexual in nature, whereas in other instances, the choice to analyze an all-female sample was unexplained. This failure to examine both sexes equally is likely problematic given that the existence of significant sex differences regarding both PTSD and alcohol is well established in both the PTSD and alcohol literature (Goldstein, Dawson, Chou, & Grant, 2012; Koenen et al., 2018). Important sex discrepancies highlight the need for consideration of sex in both sample ascertainment and data analytic plans.

Further complicating a systematic comparison of results across studies that claim support for the PTSD–AUD self-medication model is the well-known and substantiated variability in outcomes related to trauma type and timing. Certainly, there is great variability between study designs in the PTSD–AUD self-medication literature, including differences in timing between trauma exposure and assessment of alcohol and PTSD. Traumas that are experienced during childhood, for example, have been consistently shown to result in more severe PTSD irrespective of cumulative trauma load and trauma-specific characteristics, such as trauma type and subjective perception of the event (Ogle, Rubin, & Siegler, 2013). Additionally, trauma type has been shown to influence the likelihood that an individual will develop PTSD such that interpersonal traumas, such as sexual and physical assault, are more likely to result in PTSD than accidental traumas or natural disaster–related traumas (Brewin, Andrews, & Valentine, 2000).

It is important to note that measures of trauma exposure can be highly variable, with assessments differing both across and within trauma types. This heterogeneity is both necessary and unavoidable as it provides a representative picture of the multiplex nature of trauma exposure and PTSD, but it limits standardization in general. Despite substantiated effects of trauma type and timing on PTSD outcomes, only about one-third (k = 8) of the 24 studies identified for inclusion in the present review accounted for one or both of these potential confounds, let alone assessed for these considerations in their study design. Indeed, obtaining information about trauma type and timing history is time-intensive and arguably burdensome on the participant. However, trauma type and timing have considerable effects on PTSD and, most likely, alcohol use and are, therefore, crucial to consider when attempting to investigate the veracity of the self-medication model.

Finally, given the common comorbidity between PTSD and other internalizing disorders, such as anxiety and depression (Brown, Campbell, Lehman, Grisham, & Mancill, 2001), as well as the notion that the drinking-to-cope self-medication model postulates that individuals may develop problematic drinking behaviors due to a tendency to drink to cope with negative internal experiences (Khantzian, 1997), it is plausible that individuals with PTSD may be drinking to cope with more than PTSD symptoms, making the frequent lack of consideration of these potential confounding variables noteworthy. As discussed, the field as a whole is prone to relying on the assumption that individuals with PTSD are using substances or alcohol to cope with their PTSD symptoms; however, individuals with PTSD may be drinking to cope with other internalizing phenotypes characterized by negative internal experiences, such as depression and anxiety. Indeed, like PTSD, both depression and anxiety commonly co-occur with AUD (Kessler, Chiu, Demier, Merikangas, & Walters, 2005). This comorbidity highlights the need for consideration of other phenotypes commonly comorbid with PTSD for which drinking may alleviate negative internal experiences, consistent with the self-medication model.

Given that the basic premise of the self-medication model is that PTSD influences the development of AUD via drinking to cope with unpleasant symptoms of PTSD, failure to explicitly test trauma-specific drinking-to-cope is an irrefutable gap in the current literature. Because trauma-specific drinking-to-cope may likely help explain the common co-occurrence between PTSD and AUD, further work is needed to create a gold standard measure for self-reported trauma-specific drinking-to-cope, which would serve not only to improve methodology by generating reliability and validity but would also improve treatment and prevention efforts by increasing the ability to target individuals with PTSD who may be at an increased risk for developing problematic alcohol use and AUD.

In addition to operationalizing trauma-specific drinking-to-cope, another methodological suggestion that would significantly increase the veracity of the commonly assumed self-medication model would be to increase the amount of longitudinal research investigating this model. Given the basic causal premise of the self-medication model, the use of longitudinal data to conduct mediational analyses would increase understanding with regard to if and how much variance in the association between PTSD and AUD is explained by trauma-specific drinking to cope, which would ultimately provide validated, empirical support for the model. Correlated mediation models, specifically, could allow for the examination of indirect effects of trauma-specific drinking-to-cope while accounting for more generalized drinking-to-cope measures, such as the DMQ (e.g., Hawn et al., 2020). Moreover, the inclusion of drinking-to-cope motives and alcohol expectancies into daily diary and EMA study designs would enable the assessment of daily patterns of drinking-to-cope with symptoms of PTSD in real time. It is notable that only two of the 24 included studies used EMA or daily diary approaches, thereby excluding studies that have added meaningfully to the self-medication literature by assessing daily PTSD–alcohol use patterns, but not coping motives, from our review (e.g., Possemato et al., 2015).

Additionally, the inclusion of relevant factors, such as race, ethnicity, trauma type, and trauma timing would substantially improve the PTSD–AUD self-medication literature and likely result in more consistent findings across studies. One explanation for the inconsistency of the current literature is that these crucial confounding variables are scarcely accounted for, resulting in skewed findings. This is exemplified by the commonly supported finding that only a percentage of individuals go on to develop problematic alcohol use following PTSD onset (Kilpatrick et al., 2003), indicating that there is likely an array of confounding risk factors necessary to explain the existence of alcohol abuse in association with PTSD. This restates the need for this association to be understood in the context of a multifactorial model. To that end, studies should extend additional risk factors to include other psychiatric conditions, particularly given that alcohol abuse is associated with other psychiatric disorders, such as depression and anxiety (Brown et al., 2001). Moreover, given evidence for a moderate overlap in genetic variance between PTSD and AUD (Sartor et al., 2011; Xian et al., 2000), genetically informed research regarding the self-medication model is warranted. Investigations into the shared genetic risk and biological underpinnings of comorbid PTSD and AUD would help to further elucidate common etiological pathways underlying PTSD, AUD, and intermediate trauma-specific drinking-to-cope, which is imperative to the development of effective prevention and treatment programs.

Despite the high prevalence of comorbid PTSD and AUD, there is an unsettling sparsity in empirically based treatment for comorbid PTSD–AUD. In fact, the results of a systematic review and meta-analysis of psychological interventions for comorbid PTSD and SUD in general demonstrated that the quality of evidence found in the extant literature is low and that high attrition rates exist across most treatment interventions (Roberts, Roberts, Jones, & Bisson, 2015). Similarly, a Veterans Affairs (VA) consensus panel (Department of Veterans Affairs, 2009) concluded that there is currently no “gold standard” treatment for comorbid PTSD–AUD, imploring that further research into and development of alternative approaches for treating these comorbid conditions be undertaken. In addition to informing much-needed evidence-based treatment modalities, increased understanding of the underlying mechanisms between PTSD and AUD (i.e., trauma-specific drinking-to-cope) would allow for early screening and identification of trauma-exposed individuals who are at risk for developing comorbid PTSD–AUD and, hopefully, help to ameliorate the current public health crisis.

Both high prevalence estimates (Grant et al., 2015; Koenen et al., 2018) and associated negative sequelae of comorbid PTSD–AUD (Blanco et al., 2013; Ipser et al., 2015; Read, Brown, & Kahler, 2004; Shorter et al., 2015) highlight the need for a better understanding of the PTSD–AUD comorbidity. To the best of our knowledge, this was the first systematic review of the self-medication model in relation to PTSD. The results of the systematic review suggest that the literature to date does, overall, provide evidence for the self-medication hypothesis but that empirically rigorous investigation of the hypothesis is lacking due to numerous methodological limitations, as discussed previously. Future research that seeks to provide sound evidence for the self-medication hypothesis should focus on incorporating a measure to assess drinking to cope with trauma-specific symptoms, testing mediational hypotheses using longitudinal data, and comprehensively assessing and including key covariates in their analyses.

Supplementary Material