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. Author manuscript; available in PMC: 2021 Feb 5.
Published in final edited form as: Exp Clin Psychopharmacol. 2019 Aug 5;28(3):265–270. doi: 10.1037/pha0000318

Behavioral economics and coping-related drinking motives in trauma exposed drinkers: Implications for the self-medication hypothesis

Matthew T Luciano a, Samuel F Acuff a, Meghan E McDevitt-Murphy a, James G Murphy a,*
PMCID: PMC7000292  NIHMSID: NIHMS1038274  PMID: 31380693

Abstract

Behavioral economic theory can help researchers understand complex behavior by considering the availability and economic value associated with an individual’s choices. This study explored how behavioral economic constructs relate to alcohol consumption and alcohol problems in a sample of trauma-exposed young adults. We further explored whether these behavioral economic constructs explained unique variance in alcohol outcomes beyond coping-related drinking motives. Participants were 91 trauma-exposed young adults who reported recent alcohol consumption (Mage = 26.53, Female = 36.26%, Non-White = 41.75%). Participants were recruited through Amazon Mechanical Turk. Questionnaires measured alcohol consumption, problems, and motives for use, as well as alcohol demand, delayed reward discounting, future orientation, and access to environmental reward. Future orientation (ΔR2 = .05 p = .03) and delay discounting (ΔR2 = .04, p = .05) explained unique variance in alcohol problems after controlling for coping-related drinking motives. Further, alcohol demand indices (ΔR2 = .04−.10, p = .00−.05) explained unique variance in alcohol consumption after controlling for coping-related drinking. Both coping motives and behavioral economic variables contribute to alcohol consumption and alcohol-related consequences among trauma-exposed young adults. Findings suggest that, beyond coping motives, behavioral economics may play a meaningful role in understanding alcohol misuse.

Keywords: Alcohol, trauma, behavioral economics, coping, self-medication

Alcohol misuse in the aftermath of a traumatic event is associated with a number of psychosocial problems. Research shows that individuals with posttraumatic stress disorder (PTSD) endorse higher levels of coping-related drinking motives when compared to trauma- exposed individuals without PTSD (McDevitt-Murphy, Fields, Monahan, & Bracken, 2015). This suggests that alcohol use may be negatively reinforced by momentary reductions in distress. Coping-related drinking has also been shown to partially explain the relationship between psychological distress in the wake of trauma and later alcohol misuse (Kaysen, Dillworth, Simpson, Waldrop, Larimer, & Resick, 2007; Grayson & Nolen-Hoeksema, 2005). This is reflected in the self-medication hypothesis, which posits that alcohol is used as an avoidant coping mechanism when faced with psychological symptoms or other subjective states of distress (Khantzian, 1997). However, several limitations to the self-medication hypothesis warrant an exploration into additional factors that may further help to explain variance in alcohol misuse following trauma (Lembke, 2012). For example, self-medication does not consider how trauma may reduce the availability of alcohol-free reinforcers in one’s environment, change the economic value of alcohol, or increase the extent to which individuals devalue the future when making decisions about whether and how much to drink versus engaging in other activities.

One alternative approach is to view this co-occurrence through the lens of behavioral economic theory, which has been useful in explaining variability in alcohol misuse. Behavioral economics combines operant psychology with aspects of microeconomic theory to explain complex human decision making. Through this lens, alcohol misuse is considered a reinforcer pathology that develops as a result of a persistently high valuation for alcohol, a strong relative preference for immediate rather than delayed rewards, and a deficit in substance-free activities available in the environment (Bickel, Johnson, Koffarnus, MacKillop, & Murphy, 2014). Research supports an association between these constructs and alcohol misuse (Acuff, Dennhardt, Correia, & Murphy, 2019; Acuff, Soltis, Dennhardt, Berlin, & Murphy, 2018; Joyner, Pickover, Soltis, Dennhardt, Martens, & Murphy, 2016; McKay, Percy, & Cole, 2013; MacKillop et al., 2010), but there is a need for more research that integrates comorbidity within a reinforcer pathology framework.

Behavioral economic concepts account for environmental context (i.e., substance-free reinforcement), the value of alcohol, and the effect of reward delay on decision-making; therefore, it may be informative to examine these variables among trauma-exposed individuals with some form of psychopathology (for whom self-medication has been the prevailing model to explain substance use). For example, heavy drinkers with symptoms of stress, depression, or PTSD report greater alcohol demand (i.e., economic valuation of alcohol), and this has been shown to mediate the association between PTSD symptoms and alcohol problems (Murphy, Yurasek, Dennhardt, Skidmore, McDevitt-Murphy, MacKillop, J., & Martens, 2013; Tripp, Meshesha, Pickover, Teeters, McDevitt-Murphy, & Murphy, 2015). Access to environmental rewards has also been shown to mediate the relationship between PTSD severity and alcohol craving as well as PTSD and alcohol problems (Acuff, Luciano, Soltis, Joyner, McDevitt-Murphy, & Murphy, 2018), while low levels of reward availability are associated with greater alcohol use disorder (AUD) symptoms and alcohol problems after controlling for depressive symptomatology (Joyner et al., 2016). Similarly, future orientation has been shown to mediate the relation between depression and alcohol problems, as well as the relation between stress severity and alcohol problems (Soltis, McDevitt-Murphy, & Murphy, 2017). Finally, individuals with comorbid mood and substance use disorders are more likely to undervalue (discount) delayed rewards when compared to substance users without comorbid psychopathology (Moody, Franck, & Bickel, 2016).

One study found that coping-related drinking motives may partially explain the relation between alcohol demand and alcohol consumption/problems (Yurasek, Murphy, Dennhardt, Skidmore, Buscemi, McCausland, & Martins, 2011). However, no research has examined whether similar behavioral economic constructs explain unique variance in alcohol misuse beyond coping-related drinking motives, which is the primary mechanism of action considered in the self-medication hypothesis. The goals of this investigation were to (a) explore how behavioral economic constructs (including access to environmental reward, delayed reward discounting, consideration of future consequences, and alcohol demand) are related to alcohol problems in a sample of trauma-exposed adults and (b) evaluate if these constructs can explain additional variance in alcohol problems above and beyond coping-related drinking motives.

Methods

Participants

This project originally sampled 313 participants. Of these, we included 91 participants who (a) reported consuming alcohol on at least one occasion in the past month, (b) experienced a traumatic event over the course of their lifetime, (c) responded appropriately to 4 out of 5 questions designed to measure attentiveness to the survey (e.g., “please select ‘moderately’ for the question”; Meade & Craig, 2012), and (d) reported being between 21 and 30 years of age. Fifty-seven participants were removed because of survey inattentiveness and 153 were removed because they denied drinking or experiencing a traumatic event. Twelve more were removed for being older than 30. The remaining 91 participants included 33 women (36.26%) and 58 men (63.74%) with an average age of 26.53 years (SD = 2.69, Range = 21–30). Participants identified as Caucasian (n = 55, 60.4%), Black (n = 8, 8.8%), Asian (n = 24, 26.4%), and Other (n = 6, 6.6%).

Procedure

A university Institutional Review Board approved all study procedures. The study was posted on Amazon’s Mechanical Turk (Mturk), an international, online community of individuals willing to participate in research. Research has shown Mturk to be an effective method for recruiting a sample exposed to potentially traumatic events (van Stolk-Cooke, Brown, Maheux, Parent, Forehand, & Price, 2018) and those who are using substances (Strickland & Stoops, 2019), with participants who perform better on attention checks than those in a university subject pool (Hauser, & Schwarz, 2016). Further, percentages of clinically relevant drug abuse and trauma exposure appear to be consistent with percentages found in the general population (Shapiro, Chandler, & Mueller, 2013). Worker qualifications included a Human Intelligence Test (HIT) approval rating greater than 85%. Further, participants were required to reside in the United States and be 21 years of age or older. Potential participants gave informed consent before completing measures. Participants were only allowed to complete the survey once and were paid $4 for their time.

Measures

The Life Events Checklist for the DSM-5 (LEC-5; Weathers, Blake, Schnurr, Kaloupek, Marx, & Keane, 2013) assessed exposure to 17 potential trauma experiences. Participants were selected for this study if they reported witnessing a traumatic event or having an event happen to them directly. To better describe our sample, we included measures of psychological distress that are common in the aftermath of a trauma. The PTSD Checklist-5 (PCL-5; Blevins, Weathers, Davis, Witte, & Domino, 2015) is a 20-item measure of PTSD symptom severity based on DSM-5. Participants indicate the extent that each symptom has bothered them in the past month using a scale ranging from 0 (not at all) to 4 (extremely). The severity score is calculated by adding together all items from the measure (Cronbach’s alpha = .98). Only individuals who experienced a LEC traumatic event were presented with the PCL-5, which instructed them to complete the measures with their most distressing trauma in mind. We also included the Depression, Anxiety, and Stress Scale (DASS; Antony, Bieling, Cox, Enns, & Swinson, 1998) which included subscales measuring depression (Cronbach’s alpha = .93) and anxiety (Cronbach’s alpha = .92). Participants were asked to rate each question in the measure as it relates to their own experience in the past week. The seven items for each scale were summed and multiplied by two to match the original 42-item DASS.

The Daily Drinking Questionnaire (DDQ; Collins, Parks, & Marlatt, 1985) assessed alcohol consumption by having participants report the number of standard drinks consumed on each day of a typical week in the past month. Values for each day were added to derive a sum score reflecting typical drinks per week.

The Young Adult Alcohol Consequences Questionnaire (YAACQ; Read, Kahler, Strong, & Colder, 2006) is a 48-item measure assessing alcohol problems associated with drinking. Participants reported dichotomously whether they had experienced each consequence over the past month. All 48 items are summed to create a total alcohol problems score (Cronbach’s alpha = .94).

The Drinking Motives Questionnaire Revised (DMQ-R; Cooper, 1994) is a 20-item measure assessing different motives for drinking. Participants report the degree to which they agree with each item on a four-point scale from 1 (almost never/never) to 5 (almost always/always). For the purpose of the current study, we used the 5-item coping motives subscale that combines items assessing drinking-to-cope with anxiety and depressive feelings (e.g., “I drink to forget my worries”). Items are summed to reflect the degree to which a person drinks to cope (Cronbach’s alpha = .73).

The Delayed Discounting Task (DDT; Gray, Amlung, Acker, Sweet, & MacKillop, 2014) is an 8-item measure assessing monetary intertemporal choice. Participants choose between hypothetical smaller rewards that are available sooner, or larger rewards that are available later (e.g., “Would you rather have $14 today or $25 in 19 days”). Discounting function is ascertained by creating a ratio of immediate choices to delayed choices. A greater number indicates a greater discounting of delayed rewards.

The Consideration of Future Consequences Scale (CFCS; Strathman, Gleicher, Boninger, & Edwards, 1994) is a 12-item scale assessing the degree to which future outcomes are considered during present decision making. Participants report how much they agree with 12 statements on a 5-point scale. A total score was calculated by adding together the 12 items (higher scores = greater future orientation; Cronbach’s alpha = .83). Although the CFCS does not use a behavioral economic choice based approach, it does measure the construct of future valuation which is central to behavioral economic theory and conceptually related to delayed reward discounting.

The Reward Probability Index (RPI; Carvalho et al., 2011) is a 20-item measure with a subscale assessing access to reward (environmental suppressors subscale; Cronbach’s alpha = .84). Participants indicate agreement for each statement on a four-point rating scale. Although the RPI does not use a behavioral economic choice based approach, the RPI environmental suppressor subscale measures access to environmental reward, which is central to behavioral economic models of addiction.

The Alcohol Purchase Task (APT; Murphy & MacKillop, 2006) was used to measure alcohol demand, an index of motivation for alcohol. Participants estimate the number of drinks that they would consume at escalating prices. The Stein macro identified six cases that were nonsystematic (trend, detection limit for ΔQ = .025; bounce, detection limit for B = .10; reversal from zero, detection limit number for reversals = 0) and removed from further analysis (Stein, Koffarnus, Snider, Quisenberry, & Bickel, 2015). From this data, three observed demand indices were calculated: 1) intensity (consumption when drinks are free), breakpoint (the price at which an individual would stop consuming alcohol), and Omax (maximum expenditure). We also calculated elasticity (the rate at which consumption changes as a function of price). This was done using a modified, exponentiated version of the exponential equation (Hursh & Silberberg, 2008; Koffarnus, Franck, Stein, & Bickel, 2015). Elasticity was calculated in the Demand Curve Analyzer program (Gilroy, Kaplan, Reed, Koffarnus, & Hantula, 2018) using a shared k (1.80); zeros were included in analyses due to the use of the exponentiated equation. Two additional cases were excluded from the elasticity analyses because they reported no variation in price across the task.

Data Analytic Plan

All variables were checked for normality and corrected for outliers using recommendations from Tabachnick and Fidell (2013). Typical drinks per week, Intensity, and Omax were all successfully square root transformed due to skewness and kurtosis that exceed limitations (±2). We first calculated bivariate correlations to explore relationships among all study variables. Next, individual regression analyses evaluated the incremental utility of behavioral economic variables in predicting alcohol problems and consumption after accounting for variance associated with demographic variables and coping motives.

Results

On average, participants reported drinking 10.64 (SD=10.31) standard drinks per week, with a mean of 6.26 (SD=6.49) alcohol problems over the last month. In our sample, 42.9% and 52.7% of participants endorsed “moderate” to “extremely severe” levels of depressive and anxiety symptoms, respectfully. Using the recommended cut-off of 33 on the PCL-5, 36.3% (n=33) of participants screened positive for PTSD with participants reporting an average of 8.46 traumatic events (range 1–17) on the Life Events Checklist. Correlations are reported in Table 1.

Table 1.

Correlations: Behavioral economic indices, coping-related drinking motives, and alcohol variables

Variable M (SD) Range 1 2 3 4 5 6 7 8 9
1. Drinks per week 10.64 (10.31) 1–42 -
2. Alcohol Problems 6.26 (6.49) 0–22 .38** -
3. Drinking to Cope 15.15 (5.00) 5–29 .45** .38** -
4. Access to Reward 23.50 (5.13) 13–36 −.21 −.25* −.34** -
5. Delayed Discounting .54 (.27) 0–1 .11 .24* .14 −.26* -
6. CFC 40.98 (7.70) 23–56 −.15 −.33** −.14 .34** −.33** -
7. Breakpoint 8.90 (5.53) .25–22 .29** .22* .26** −.01 .01 −.21 -
8. Intensity 4.93 (3.08) 1–20 .50** .16 .33** −.21 .08 −.12 .06 -
9. Omax 12.81 (12.11) 0–75 .30** .12 .22* .04 −.13 −.09 .85** .19 -
10. Elasticity .02 (.03) 0–.10 −.30* −.03 −.25* −.05 .17 .05 −.75** −.26* −.86**
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CFC=Consideration of future consequences; Delay discounting = ratio of choice for immediate v. delayed rewards on the 8-item delay discounting measure; Access to reward = environmental suppressors subscale of the RPI; Breakpoint = price when consumption is 0; intensity = consumption at minimum price; Omax = maximum expenditure; Elasticity = slope of the demand curve

*

p ≤ .05

**

p ≤ .005.

Alcohol Consumption

In step 1, neither gender nor age explained unique variance in alcohol consumption (ΔR2 = .01). Coping-related drinking motives predicted alcohol consumption (ΔR2 = .18, p < .001). In models accounting for coping motives (as well as gender and age), breakpoint (ΔR2 = .04, p = .05), intensity (ΔR2 = .15, p < .001), and Omax (ΔR2 = .05, p = .03) each explained unique variance in the number of drinks consumed over a typical week. No other variable contributed significant variance to these models beyond coping (see Table 2).

Table 2.

Hierarchical regressions: Coping-related drinking motives and behavioral economic indices predicting alcohol problems and consumption

Alcohol Problems Alcohol Consumption
Variable Beta (S.E.) β t p ΔR2 Beta (S.E.) β t p ΔR2
Step 1
Gender −1.14 (1.44) −.09 −.79 .43 .14 −.31 (.33) −.10 −.93 .36 .01
Age −.19 (.27) −.07 −.68 .50 -- .03 (.06) .05 .42 .68
Alcohol Consumption 1.54 (.47) .47 .35 .00* -- -- -- -- --
Step 2
Coping Motives .38 (.15) .29 2.45 .02* .06 .12 (.03) .43 4.21 .00 .18
Step 3 (separate)
Access to Reward −.18 (.14) −.14 −1.32 .19 .02 −.02 (.03) −.07 −.63 .53 .00
DD 4.77 (2.40) .20 1.99 .05 .04* .21 (.54) .04 .38 .71 .00
CFC −.20 (.09) −.23 −2.23 .03 .05* −.01 (.02) −.07 −.67 .51 .00
Breakpoint .05 (.13) .04 .38 .71 .00 .05 (.03) .21 1.97 .05 .04*
Intensity −1.35 (1.37) −.12 −.98 .33 .01 1.01 (.24) .43 4.21 .00 .15**
Omax −.18 (.46) −.04 −.39 .69 .00 .2(.10) .23 2.26 .03 .05*
Elasticity 12.65 (10.26) .13 1.23 .22 .02 −3.88 (2.24) −.19 −1.73 .09 .03
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Note. CFC=Consideration of future consequences; Delay discounting = ratio of choice for immediate v. delayed rewards on the 8-item delay discounting measure; Access to reward = environmental suppressors subscale of the RPI; Breakpoint = price when consumption is 0; intensity = consumption at minimum price; Omax = maximum expenditure; Elasticity = slope of the demand curve

*

p ≤ .05

**

p ≤ .005., S.E. = Standard Error.

Alcohol Problems

In step 1, typical drinks per week explained significant variance in alcohol problems (ΔR2 = .14, p < .001) although gender and age did not. Coping-related drinking motives also predicted alcohol problems (ΔR2 = .06, p = .02). In models accounting for coping motives (as well as drinking level and demographic factors), CFC (ΔR2 = .05, p = .03) and delay discounting (ΔR2 = .04, p = .05) each explained unique variance in YAACQ score. No other variable contributed significant variance to these models beyond coping and drinking level. Detailed results are presented in Table 2.

Discussion

The self-medication conceptualization of substance misuse in the context of PTSD, mood, and anxiety disorders has received some criticism in recent years due to an overly broad mechanism of action (Lembke, 2012; Kaysen, Bedard-Gilligan, & Stappenbeck, 2017) that does not fully consider other variables that may contribute to excessive motivation for alcohol. In response, this study examined constructs derived from the behavioral economic framework that may help to further explain variability in alcohol consumption and alcohol problems for individuals who have experienced trauma and may be using alcohol to cope with depression, anxiety, and/or PTSD.

Our results suggest that consideration of future consequences and delayed discounting can predict drinking problems after accounting for demographic variables, alcohol consumption, and drinking-to-cope. Thus, individuals with a trauma history may experience alcohol problems, in part, because they tend to be more focused on the present and devalue future outcomes. This may be due to changes in an individual’s belief system, which often accompanies traumatic events. For example, distorted beliefs about safety may lead an individual to engage in more impulsive decision-making while strong negative beliefs of worthlessness may lead individuals to devalue the future.

We also found that aspects of demand (breakpoint, intensity, Omax) predicted alcohol consumption after controlling for demographic variables and drinking-to-cope motives. These findings suggest that there is reinforcement value associated with alcohol use, beyond symptom reduction, and may also suggest that positive reinforcement models of alcohol use should also be considered when conceptualizing consumption in the aftermath of a trauma.

Although coping-related drinking motives have been shown to predict alcohol misuse among trauma-exposed populations with or without PTSD (Dixon, Leen-Feldner, Ham, Feldner, & Lewis, 2009), this study offers alternative pathways that should be examined further. Findings from this study suggest that drinking-to-cope is an important consideration in understanding why trauma-exposed individuals often develop harmful patterns of alcohol use, and that behavioral economics may shed additional light on this problem. In fact, regression analyses demonstrate that behavioral economic indices often explained roughly the same amount of variance in alcohol misuse as coping-related drinking motives.

Whereas the self-medication model highlights the negatively reinforcing aspects of alcohol, which temporarily alleviates negative affect, our results support both positive reinforcement models (e.g., the role of alcohol demand) and negative reinforcement models (e.g., coping), as well as individual-level self-regulatory deficits (e.g., ability to delay reward). Individuals experiencing depression, posttraumatic stress, and general distress in the aftermath of a trauma often develop patterns of avoidant coping (Littleton, Horsley, John, & Nelson, 2007) and anhedonic behavior (Nawijn, van Zuiden, Frijling, Koch, Veltman, & Olff, 2015). These patterns of behavior may effectively reduce the availability of substance-free rewarding stimuli and may shift the perceived relative value of activities. Thus, these individuals are at risk of experiencing less overall reward from prosocial alternatives that require engagement with the environment and instead lead them to engage in impulsive behaviors aimed at reducing negative affect. Alcohol is an immediate and potent reinforcer, which could fill a reward void among these individuals.

Several limitations of this study warrant further discussion. First, our use of cross-sectional retrospective data introduces error and precludes an analysis of the directionality of the observed associations. Second, interpretation of our analyses could be strengthened if our sample included only those who were trauma exposed and were also experiencing some form of depression, anxiety, or post-trauma symptoms. In other words, our interpretation of findings could be stronger if we had more assurance that all the individuals in our sample had symptoms that they could potentially use alcohol to cope with. Mturk samples also tend to deviate slightly from population-based demographics of trauma-exposed and alcohol-using populations. This study is no exception and it may be important to consider these factors in future studies. Finally, the data gathered in this study relied on self-report measures that used unstandardized time frames. Thus, our data are subject to a degree of response error.

Future research should examine these variables prospectively in samples with trauma- related pathology in order to better understand how the experience of trauma changes negative affect, drinking patterns, reasons for drinking, and classic behavioral economic variables. Furthermore, given the unique role that different traumatic events play in shaping cognitions, emotions, and behavior, it may be worth examining these findings in populations with specific trauma experiences. Still, the finding that demand and discounting are meaningful in explaining alcohol outcomes in a general trauma-exposed sample underscores the importance of developing a more inclusive etiological framework of co-occurring trauma and substance use that includes both coping and behavioral economic concepts.

Public Health Significance:

Models of etiology and treatment for alcohol misuse among individuals who have experienced a trauma should focus on coping-related drinking as well as discounting of the future and alcohol reward value.

Acknowledgements

This research was conducted with support from National Institute of Health Grant F31 AA026174–01A1 (PI: Matthew T. Luciano) and Grant R01 AA020829 (PI: James G. Murphy). These funding sources had no involvement other than financial support.

Footnotes

Disclosures

None of the authors have conflicts of interest to declare.

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