Distress tolerance in social versus solitary college student drinkers

    Distress tolerance in social versus solitary college student drinkers Catherine L. Williams, Peter W. Vik, Maria M. Wong PII: DOI: Reference:

S0306-4603(15)00213-0 doi: 10.1016/j.addbeh.2015.06.025 AB 4588

To appear in:

Addictive Behaviors

Please cite this article as: Williams, C.L., Vik, P.W. & Wong, M.M., Distress tolerance in social versus solitary college student drinkers, Addictive Behaviors (2015), doi: 10.1016/j.addbeh.2015.06.025

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ACCEPTED MANUSCRIPT DISTRESS TOLERANCE IN SOLITARY AND SOCIAL DRINKING

Distress tolerance in social versus solitary college student drinkers

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Catherine L. Williams, M.S.

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Peter W. Vik, Ph.D

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Idaho State University

Pacific University

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Maria M. Wong, Ph.D

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Idaho State University

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Abstract

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Low distress tolerance has been an inconsistent predictor of alcohol-related consequences in college students, but its relationships to depression and coping motives for alcohol have

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received stronger support. Research on college students who drink heavily in isolation suggests

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that this population is more likely to have a greater number and severity of alcohol-related problems, depression, and coping motives. Solitary heavy drinkers were therefore hypothesized to have lower distress tolerance than other drinkers. This study examined differences in self-

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reported and behavioral distress tolerance across two groups of university students: those who endorsed heavy solitary drinking (20.1%) versus those who endorsed other types of drinking.

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Students completed a self-report measure (Distress Intolerance Self-Report, or DISR) and behavioral measure of distress tolerance (Paced Auditory Serial Addition Test, or PASAT).

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Students who reported drinking heavily in isolation differed from other students on the DISR,

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F(1, 132) = 4.645, p = .033, η2 = .034, but not the PASAT, F(1, 132) = 0.056, p = .813. These students also endorsed more coping motives for alcohol. Distress tolerance did not predict

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drinking consequences directly, yet a mediation model linking distress tolerance to consequences through coping motives supports previous findings of distress tolerance as a distal, indirect predictor of drinking problems. The unique characteristics of solitary binge drinkers and the significance of distress tolerance as an indirect predictor of alcohol-related consequences are discussed.

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1. Introduction

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1.1 Distress Tolerance, Coping, and Alcohol-Related Problems

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Despite years of research, college student drinking continues to present a major health

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problem within the United States. Full-time college students are more likely to drink and drink heavily compared to same-age peers not in college (SAMHSA, 2014), and approximately 1 in 4 students experience consequences as a result of drinking as some point during their time in

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college (Wechsler et al., 1998). Previous research suggests that certain subsets of students may be especially at risk of serious drinking consequences, and it is therefore important to better

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identify such students so that more effective steps can be taken to prevent such consequences. Young adults who report that they drink to manage negative affect may be at greater risk

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for problematic drinking consequences than those who drink for other reasons. Research has

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demonstrated that motivation to drink as a means to cope with negative affect tends to predict more problematic drinking than do enhancement and social drinking motives (Cooper, 1994;

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Cooper, Russell, Skinner, & Windle, 1992; Holyfield et al., 1995; Kuntsche, Knibbe, Gmel, & Engels, 2005; Rafnsson, Jonsson, & Windle, 2006). Distress tolerance is one factor that is likely to influence coping with negative affect. It reflects a person’s likelihood of enduring, attending to, and alleviating perceived emotional discomfort (Simons & Gaher, 2005), and it has predicted a variety of adverse consequences that are purportedly regulated by self-control, such as substance abuse (Grant & Chamberlain, 2014; Zvolensky & Hogan, 2013). The ability to tolerate distress likely acts on the mechanism of negative urgency (Kaiser, Milich, Lynam, & Charnigo, 2012). Negative urgency – commonly conceptualized as a component of impulsivity – refers to the tendency to act rashly when experiencing adverse emotions such as sadness (Wray, Simons, Dvorak, & Gaher, 2012). Therefore, in a model that predicts substance abuse, negative affect is likely to be experienced as more aversive in people with low distress tolerance who then behave impulsively and engage in risky drinking behaviors due to a sense of negative urgency (Kaiser et al., 2012). Wray and colleagues (2012) found more support for this model than a direct relationship between distress tolerance and risky drinking behaviors. This model also helps to explain the plethora of indirect relationships that have been

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suggested between distress tolerance and alcohol abuse, such as evidence from Marshall-Berenz, Vujanovic, and MacPherson (2011), who found that distress tolerance partially mediated the

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relationship between impulsivity and coping motives among people with PTSD, and evidence from Buckner, Keough, and Schmidt (2007), who found that distress tolerance mediated the

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relationship between depression and problems with alcohol and cannabis.

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The relationship between distress tolerance and negative affectivity is made even more intriguing when it is examined in the context of the motivation to cope with negative affect. Because distress tolerance is related to drinking to cope (Howell et al., 2010; Marshall-Berenz et

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al., 2011) and coping motives strongly predict alcohol-related problems in college students (Cooper et al., 1992; Kuntsche et al., 2005), the relationship between distress tolerance and

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alcohol-related problems may be best captured in a mediational model rather than through direct effects (Martens et al., 2008). In addition to assessing differences in distress tolerance across

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groups of college student drinkers, this study proposes to assess the validity of distress tolerance

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1.2 Solitary Heavy Drinkers

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measures in predicting alcohol-related consequences via coping motives.

Although the majority of college students who drink do not experience many severe negative consequences, the subset of students who drink to cope appear to be at a higher risk of engaging in risky behaviors (e.g., driving while intoxicated) and experiencing negative consequences (e.g., arrests for driving while intoxicated; Wray et al., 2012). Therefore, it is important to identify the characteristics of the students who engage in this pattern of drinking. One such group may be college students who drink heavily in isolation. Previous research has demonstrated that these students are at greater risk for experiencing more and more severe drinking consequences than their social-drinking peers (Chrisitansen, Vik, & Jarchow, 2002). Compared to social drinkers, solitary heavy drinkers endorse more coping motives, experience more serious consequences such as increased suicidal ideation (Gonzales, Collins, & Bradizza, 2009), and have greater difficulty regulating negative mood (Gonzales & Skewes, 2013). For these individuals, distress tolerance might exert a greater influence on their alcohol consumption and alcohol-related consequences through negative urgency and coping mechanisms. Therefore,

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it is likely that college students who drink heavily alone also have lower levels of distress tolerance than students who engage in other patterns of drinking. This study proposes to

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examine those group differences in distress tolerance.

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1.3 Measuring Distress Tolerance

There are many means by which researchers have been studying distress tolerance over the past decade, using either self-report questionnaires that assess one’s perceived ability to

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withstand distress or measures that capture the behaviorally demonstrated capacity to tolerate distress (Leyro, Zvolensky, & Bernstein, 2010). While both types of measures have been linked

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to alcohol-related problems (Daughters et al., 2005a; Simons & Gaher, 2005), the literature is mixed on their efficacy at predicting problems directly (Howell et al., 2010). As was suggested

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above, distress tolerance appears to impact alcohol use and alcohol-related problems indirectly,

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via mechanisms such as negative urgency and coping motives. The relationship between distress tolerance and alcohol-related problems is made especially problematic by the myriad of ways in

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which tolerance is assessed, as well as the types of distress captured by such measures. For example, although self-report measures of distress tolerance correlate well with one another and behavioral measures of distress tolerance correlate well with one another (Anestis et al., 2012), these different modalities do not always hang together and, indeed, may be addressing different aspects of distress (e.g., perceptions of how one will respond to distress versus behavioral responses during physiological discomfort; McHugh et al., 2011). The question then becomes which of these two types of measures are better at measuring the component of distress that best predicts alcohol-related problems. Comprehensive reviews of the utility of distress tolerance measures to predict specific psychopathology, such as alcohol abuse, are lacking (Anestis et al., 2012). Simons and Gaher (2005), Wray and colleagues (2012), and Buckner and colleagues (2007) reported evidence between low self-reported distress tolerance and more alcohol problems, but Howell and colleagues (2010) did not find a significant, direct relationship between low distress tolerance and a greater number of problems. With respect to behavioral measures, one study found evidence that low distress tolerance can predict subsequent dropout from a substance abuse

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treatment program (Daughters et al., 2005a) and another linked low distress tolerance to failed attempts to stop smoking (Brown et al., 2005). Other studies have found evidence of an indirect

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relationship between behavioral measures of distress tolerance and problematic alcohol use (Daughters et al., 2009; Gorka, Ali, & Daughters, 2012). However, to our knowledge, there has

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not yet been evidence to suggest a direct relationship between any behavioral measure of distress

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tolerance and alcohol-related problems per se.

Even so, there is a robust theoretical argument for a relationship between behavioral distress tolerance and alcohol-related problems. For example, Anestis and colleagues (2012)

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found support for the predictive validity of self-report and behavioral measures of distress tolerance (e.g., the Distress Tolerance Scale and Distress Tolerance Test, respectively) for

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impulsive behaviors, which are important to the realm of alcohol consumption because facets of impulsivity (e.g., negative urgency) have been shown to predict maladaptive alcohol

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consumption and alcohol-related problems (Kaiser et al., 2012; Shin, Hong, & Jeon, 2012). The

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conflicting results span different types of distress tolerance measures, and the evidence suggesting that both may be useful in predicting alcohol-related consequences highlights the

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importance of a multimodal assessment of distress tolerance. In an attempt to address these concerns, this study compared solitary and social drinkers across a self-report measure and a behavioral measure of distress tolerance. The first measure, the distress intolerance self-report (DISR) scale, is brief measure of distress tolerance that includes ten items from four established measures of distress and anxiety tolerance (i.e., Anxiety Sensitivity Index, Discomfort Intolerance Scale, Distress Tolerance Scale, and Frustration Discomfort Scale). In a recent study, these ten questions were shown to have the highest factor loadings for a single “distress intolerance” factor in both clinical and nonclinical samples (McHugh & Otto, 2012). This finding was important because the succinct assessment of distress tolerance is very useful given the lack of a gold standard for self-reported distress tolerance among the variety of measures available (McHugh & Otto, 2012; McHugh et al., 2011). Although the DISR has not yet been used to predict alcohol-related problems, the Discomfort Intolerance Scale (DIS) and Distress Tolerance Scale (DTS) have been independently linked to alcohol-related problems (Howell et al., 2010; Simons & Gaher, 2005). The Anxiety Sensitivity Index (ASI) and The Frustration Discomfort Scale (FDS) have not yet been used to predict

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alcohol-related problems, but the ASI has predicted coping motives for alcohol use (Stewart & Zeitlin, 1995), and the FDS was shown to be related to similar constructs such as “internet

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addiction” and problems with self-control (Harrington, 2005; Ko et al., 2008). Although we know of no published studies that have examined the relationship between

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behaviorally demonstrated distress tolerance and alcohol-related problems, there are a few

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studies that have used behavioral distress tolerance measures to examine the relationship between distress tolerance and alcohol use. The Paced Auditory Serial Addition Test, or PASAT, has typically been the measure used in such studies. For example, Gorka and

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colleagues (2012) reported using the PASAT to predict early termination from a drug and alcohol treatment facility. These authors found that subjects with lower distress tolerance (as

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indicated by premature termination of the PASAT) were more likely to leave treatment early than individuals with greater distress tolerance. Daughters and colleagues (2009) found a

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relationship between early PASAT termination and greater amounts of alcohol use among

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Caucasian (but not ethnic minority) youths aged 9-13 (Daughters et al., 2009). As mentioned above, the PASAT has not yet been used to predict drinking consequences

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in a college student population; in fact, to our knowledge there are no published studies that have attempted to link any behavioral measure of distress tolerance to alcohol-related problems per se. The aforementioned evidence suggests that the PASAT, though previously untested, is perhaps the behavioral measure of distress tolerance that has the greatest likelihood of predicting alcoholrelated problems, and therefore it may be the behavioral measure that best reflects differences in distress tolerance across solitary and social college student drinkers.

1.4 Summary and Hypotheses

In summary, college students who drink heavily in isolation seem to be at greater risk of experiencing more and more severe alcohol-related consequences. There is also literature to suggest that they have higher rates of depressive symptoms and more motives to drink to cope with negative affect. Despite the fact that distress tolerance has been linked to negative affect, coping motives, and alcohol-related problems, differences in distress tolerance have not been compared across groups of solitary heavy drinkers and other drinkers. Therefore, this study

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hypothesizes that distress tolerance – assessed via a self-report and a behavioral measure – will vary across groups of college student drinkers, such that individuals who drink heavily alone will

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have greater levels of distress tolerance than college students who endorse other drinking patterns.

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A second set of analyses will examine the ability of both distress tolerance measures to

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predict alcohol-related consequences in college students. Although there is some evidence that both self-report and behavioral measures of distress tolerance can predict amount of alcohol use, there is less evidence for a direct relationship between such measures and alcohol-related

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consequences. Furthermore, much of the research seems to suggest an indirect relationship between distress tolerance and alcohol-related consequences, as previous studies have shown that

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low distress tolerance is related to greater incidence of depression and coping motives, which subsequently predict more drinking consequences. Therefore, specific predictions about a direct

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relationship between distress tolerance and alcohol-related consequences are tenuous, whereas a

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mediation model linking distress tolerance, coping motives, and alcohol-related problems is likely to be more robust. This set of analyses will test the hypothesis that greater coping motives

problems.

2. Method

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will significantly mediate the relationship between low distress tolerance and alcohol-related

2.1 Participants

The sample included 134 undergraduates (67.9% women) with an average age of 23.31 (SD = 5.94, range 18-43) from a midsized Western university. Most were Caucasian (74.6%) or Latino/Latina (15.7%). The rest were African-American (N = 5), Asian-American (N=2), Native American (N = 1), or “other” (N = 5). Two-thirds (68.7%) were single, 28.4% were either married or living in a committed relationship, and four individuals were divorced or separated.

2.2 Procedures

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College students were recruited from lower-division psychology classes via an online (SONA System) research volunteer managing system. Eligibility was restricted to students aged

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18 and older, and the study advertisement requested only students who acknowledged drinking alcohol at least once during the past year. As compensation, participants received research credit

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for psychology courses. Upon the participant’s arrival at the research lab, a research team

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member explained the study, reviewed the informed consent, and answered any questions. Participants who consented to participate were randomly assigned to begin with either the Paced Auditory Serial Addition Test (PASAT; see below) or a questionnaire packet containing the self-

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report measures listed below. The order of these two measures was counterbalanced across participants. The entire process of informed consent and questionnaire packet completion was

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approximately twenty-five minutes. Participants were debriefed at the conclusion of the study.

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2.3 Measures

2.3.1 Background and Drinking Questionnaire.

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This self-report measure comprised three basic components: demographics, alcohol consumption, and alcohol-related consequences. First, basic demographic data (e.g., age, race, ethnicity, and place of residence) were collected. Certain items from the Customary Drinking and Drug Use Record (CDDR; Brown, Creamer, & Stetson, 1987) were modified for self-report format in earlier studies (Vik, Carrello, & Nathan, 1999; Vik, Carrello, Tate, & Field, 2000; Vik, Tate, & Carrello, 2000) to estimate the quantity and frequency of alcohol use during the previous three months. The values provided to two questions (i.e., “On how many days of the past three months did you consume alcohol?” and “On the days that you drank, what was the average number of drinks that you had?”) were multiplied to estimate quantity of alcohol consumed in the past three months, and this resulting variable was used to control for quantity of alcohol consumption while predicting alcohol-related consequences. Means, standard deviations, and ranges for the two drinking groups are reported in Table 1. (see Table 1 for more information). The CDDR has demonstrated reliability and validity (Brown et al., 1998) and psychometric strength with respect to internal consistency (Cronbach alphas range from .80 to .90, with replications ranging from .74 to .92), one-week test-retest reliability (coefficients

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ranged from .70 to .92), and inter-rater reliability. When completing the questions from the CDDR, students checked a box to indicate whether or not they had engaged in or experienced a

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certain consequence due to alcohol use in the past year; the consequences ranged from relatively minor (e.g., “Missed a Class”) to risky or reckless (e.g., “Engaged in Unplanned Sexual

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Activity”). Additional questions asked students whether or not they had ever experienced any of

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the seven DSM-IV criteria for alcohol dependence. Finally, the questionnaire assessed alcoholuse consequences experienced during the prior 12 months. The list of consequences was compiled from seminal studies of alcohol-use problems by Berkowitz and Perkins (1986) and

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Wechsler and colleagues (Wechsler, et al., 1994; Wechsler Dowdall, Davenport, & Castillo. 1995). This list of problems has been used in prior studies by Vik and colleagues (Christiansen

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et al., 2002; Vik et al., 2000a; Vik et al., 2003; Vik et al., 2000b) to reveal conceptual clusters

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and progressive severity of consequences.

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2.3.2. Distress Intolerance Self-Report (DISR). The Distress Intolerance Self-Report scale (DISR; McHugh & Otto, 2012) is a relatively

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novel, 10-item measure of distress tolerance that incorporates questions from four previously established self-report measures of anxiety and distress tolerance: the Anxiety Sensitivity Index (Peterson & Reiss, 1992), the Distress Tolerance Scale (Simons & Gather, 2005), the Discomfort Intolerance Scale (Schmidt, Richey, & Fitzpatrick., 2006), and the Frustration Discomfort Scale (Harrington, 2005). The items drawn from these measures had the highest factor loadings for a unifying construct of distress tolerance (McHugh & Otto, 2012). Participants were asked to rate the extent to which they agreed or disagreed with the distress tolerance items (e.g., “It scares me when I am nervous,” “I can’t handle feeling distressed or upset” and “I can’t stand situations where I might feel upset”) on a Likert-type scale that ranged from Strongly Disagree to Strongly Agree. Therefore, higher scores on the DISR reflect lower distress tolerance. In the current sample, Cronbach’s alpha was .92.

2.3.3 Paced Auditory Serial Addition Test. A computerized version of the Paced Auditory Serial Addition Test (Gronwall & Sampson, 1974; PASAT-C) was used in this study. During the PASAT, participants hear a

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series of numbers, and they are instructed to add the number immediately presented to them to the number just previously presented, providing what they believe to be the correct sum of the

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two numbers before they are exposed to the next number in the series. For example, if the participant heard “2, 5,” then she or he would answer “7.” If the next number presented was 4,

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then the participant would respond “9.” The numbers are presented at consistent intervals (e.g.,

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3 seconds) until a trial is completed. In this study, participants were presented with three PASAT trials that increased in difficulty by (a) decreasing the interval latency between numbers (i.e., 3 seconds, 2 seconds, 1 second) and (b) extending the length of the trials (i.e., 3, 5, and 10

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minutes respectively). PASAT has been shown to generate anxiety and frustration in participants (Tombaugh, 2006), and as such it has previously been used to estimate distress tolerance by

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assessing the point at which respondents choose to stop participating in the task: the sooner the individual “gives up,” the lower his or her distress tolerance.

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While receiving information relevant to the informed consent, all participants were told

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that they could terminate the PASAT by informing the experimenter that they wanted to stop. They were also informed that early termination of the PASAT would not prevent them from

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receiving full research credit in their courses. Prior to initiating the final trial of the PASAT, participants were again reminded that they could terminate the PASAT early with the following verbal instruction: “You’re about to begin the third and final trial of the PASAT. This trial is going to be much faster than the previous two, and many people find it tedious and frustrating. If you decide to stop at any point, just let me know. You will still receive the full research credit.” All participants who chose to quit (35%) gave up very early in the third trial, resulting in a severe positive skew. As such, the PASAT was treated as a binary variable (i.e., “quitters” versus “non-quitters”). This procedure has also been used in previous studies due to significant skew (Daughters et al., 2005a; 2009).

2.4 Analyses Solitary drinking was defined as a dichotomous variable. Participants had the option of indicating that they had either consumed 4 or more (if women) or 5 or more (if men) drinks alone, in a social situation, or in a social situation where they were the only one drinking in the past 3 months. The “alone” and “only one drinking” options were combined into a single

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category (with a total N of 27), because while they are not the same, both situations suggest a social disconnect that may result from maladaptive coping strategies or social skills, both of

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which could contribute to drinking problems in college students. In addition, as the total number

groups added incremental power to subsequent analyses.

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of students who admitted to binge drinking in isolation was fairly small (N = 20) combining both

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As quantity of alcohol consumption is frequently related to alcohol problems, zero-order correlations were calculated between alcohol problems and the estimated amount of drinks consumed in the past three months (Table 2). Estimated number of drinks was submitted to an

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inverse transformation to account for substantial positive skewness within the variable, and this transformed variable was subsequently included as a covariate in predictions of alcohol

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problems. Preliminary analyses also revealed that DISR scores had a moderate positive skew, so a square root transformation was performed on the DISR. Drinking consequences were based on

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the total number of problems that students reported experiencing within the past year. Total consequences consisted of careless consequences, risky/reckless problems, and problems with

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authority (Vik et al., 2000a), with acceptable internal consistency (α = .74).

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Zero-order correlations were also conducted to determine if age and gender were related to alcohol-related consequences, as previous research suggests that these variables may differentially predict drinking consequences. Only age (Pearson’s r = -.177, p < .05) was significantly related to drinking consequences in this sample. Thus, both age and quantity of alcohol consumption were included as covariates in the prediction of drinking consequences. A series of one-way ANOVAs were conducted to determine if there were a significant difference in DISR scores, coping motives, and total number of drinking days across solitary binge drinkers and social drinkers. A chi-square analysis was then run to test for significant differences in PASAT performance (i.e., Quit Early versus No Quit) across drinking groups. Next, two sequential regression equations were conducted using DISR scores and PASAT performance to predict drinking consequences, after controlling for age and amount of alcohol consumed in the past three months. As PASAT performance did not appear to be a significantly related to either solitary binge drinking or alcohol related-consequences (see below), it was dropped from the final analysis. Consequently, only one mediation model utilizing a product of coefficients test (MacKinnon et al., 2002; Sobel, 1982) was run to determine whether or not

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coping motives significantly mediated the relationship between DISR scores and alcohol-related

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problems.

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3. Results

3.1 Differences across Solitary and Social Drinkers

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Students’ average distress tolerance scores, number of drinking consequences, estimated amount of drinks consumed in the past three months, and coping motives scores are listed in

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Table 1. Of the 134 students sampled, 27 (20.1%) endorsed either binge drinking (i.e., 4 or more drinks for women, 5 or more drinks for men) of alcohol either by themselves in a social situation

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or alone in the past three months. One-way ANOVA revealed a significant difference between solitary and social drinkers with respect to DISR scores, F(1, 132) = 4.645, p = .033, η2 = .034. 1

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On average, solitary drinkers tended to score nearly 3 points higher on the DISR than social

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drinkers (i.e., M = 19.1 for social drinkers vs. M = 21.9 for solitary drinkers). Higher scores suggest a poorer ability to tolerate distress. (That is, scores reflect the extent to which an

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individual is disturbed by and intolerant of distress). Because the PASAT was divided into two groups (i.e., Quit Early vs. No Quit), chisquare analysis was used to determine if there were significant differences in PASAT performance across drinking groups. There was insufficient evidence to support a relationship between these two variables, χ2(1, N = 134) = .057, p = .811. Means and standard deviations by drinking group are reported in Table 1. Additional one-way ANOVAs revealed significant differences in endorsed coping motives between solitary and social drinking groups, such that solitary drinkers endorsed more coping motives than social drinkers, F(1, 132) = 5.021, p = .027, η2 = .037. However, independent samples t-test revealed no significant differences across groups on estimated number of drinks consumed in the past three months, t(129) = 1.355, p = .178. Group

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Given the unequal distribution of sample size, Levene’s test of homoscedasticity was requested for this analysis. Levene statistic for prediction of DISR scores was .848, p = .359, suggesting that variance did not differ significantly across groups.

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comparisons of coping motives, distress tolerance scores, and amount of drinks consumed are

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listed in Table 1.2

3.2 Distress Tolerance and the Prediction of Drinking Consequences

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A sequential regression model predicting alcohol consequences was run by entering age

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and estimated number of drinks into the first step and DISR scores into the second step. The overall model accounted for a significant portion of the variance of alcohol consequences, F(3, 127) = 6.355, p < .001, R2 = .131, but only age and number of drinks were significant predictors

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in the model. DISR scores did not contribute significantly to that prediction. A second sequential regression model was run similar to the one above, although PASAT

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performance was used in place of DISR scores. Again, the overall model accounted for a significant portion of the variance of alcohol consequences, F(3, 127) = 6.721, p < .001, R2 =

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.137, but once again only age and number of drinks were significant predictors in the model.

3.3 Coping Motives as Mediator between Distress Tolerance and Drinking Consequences

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Sobel’s test of mediation was conducted using three standard regression equations. First, DISR scores were shown to significantly predict coping motives, F(1, 132) = 12.338, p = .001. Then, coping motives were used to predict drinking consequences, F(1, 132) = 14.373, p < .001. The unstandardized beta values and their respective standard errors from equations one and two were used to calculate a Sobel test (Fig. 1). The mediation model was significant (z = 2.58, p = .01). MacKinnon’s asymmetric confidence interval (PRODCLIN; MacKinnon, Fritz, Williams, & Lockwood, 2007) program was run to supplement these analyses, as the program attempts to correct for coefficient products that are not normally distributed. The asymmetric confidence interval program also supported a significant mediation (UL = 0.600; LL = 0.113), as is demonstrated in Figure 1.

4. Discussion Previous research has demonstrated that young adults who drink to cope with negative affect and who drink heavily alone are more likely than their peers to experience negative 2

Again, Levene’s test for the analyses of coping motives and number of alcoholic drinks were not significant.

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drinking consequences (Kuntsche et al., 2005; Christiansen et al., 2002). In addition, distress tolerance has been used to predict negative drinking consequences in college students for nearly

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a decade, although primarily through indirect means such as coping motives (Howell et al., 2010; Simons & Gaher, 2005). In order to investigate how distress tolerance may appear in a

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particularly vulnerable population of students, this study administered a self-report and

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behavioral measure of distress tolerance across different groups of student drinkers. Significant differences were found across the self-report measure but not across performance on the PASAT,

tolerance than their social-drinking peers.

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such that students who reported engaging in solitary binge drinking endorsed lower distress

After controlling for age and amount of drinking days, neither the self-report nor the

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behavioral measure of distress tolerance predicted drinking consequences. However, a model in which coping motives mediated the relationship between distress tolerance and alcohol-related

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problems was supported with a Sobel product of coefficients test and MacKinnon’s asymmetric

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confidence interval approach (MacKinnon et al., 2007). These findings have several implications, especially given that a direct effect between self-reported distress tolerance and

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alcohol-related problems was not established. The higher rates of distress intolerance in solitary drinkers likely interacts with negative affect, which is more prevalent in this group of students (Gonzales & Skewes, 2013), and students are subsequently more likely to drink to avoid uncomfortable emotions. This pattern of discomfort and avoidance likely precede heavy or risky drinking (Gonzales et al., 2009), which may lead to alcohol problems and other serious consequences.

That PASAT performance did not differ across groups of students (and, furthermore, did not predict alcohol-related consequences) suggests that the PASAT does not directly assess the type of distress that precedes problematic drinking. Although Daughters et al. (2005a) found that substance-abusing populations who prematurely terminated distress-persistence tasks (i.e., PASAT) were more likely to leave treatment early and presumably have more alcohol-related problems, perhaps PASAT was not as distressing to a college student population because college students are more practiced with tasks that utilize working memory capacity (e.g., listening to lectures while note-taking, or taking math tests). Therefore, it may be that in a college student sample, a sustained, rapid math test was not as psychologically stressful as it was in a sample of

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outpatient substance abusers. Students’ reasons for terminating the PASAT may have been closer to boredom than distress.

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In summary, this study found support for an indirect model of distress tolerance on problematic drinking consequences in college students. Students who endorsed drinking heavily

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alone were more likely to have higher distress intolerance scores and more coping motives than

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their social-drinking peers, but they were not significantly more likely to have alcohol-related problems than purely social heavy drinkers. A relationship between distress tolerance and drinking consequences was only supported indirectly via coping motives. As PASAT

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performance did not vary across drinking group nor successfully predict drinking consequences, future research on behavioral measures of distress tolerance should more closely consider the

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application of specific assessment tools within the populations under study. Just as individuals differ in their preferences and irritants, so may a particular test be more or less distressing

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4.1 Limitations and strengths

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depending on the unique experiences of the individual in question.

These findings are limited by the cross-sectional nature of the design. While it is very likely that distress tolerance could act on coping motives and negative urgency to result in alcohol-related problems, it is also possible that alcohol-related problems could create such significant distress in a student’s life that they impair the student’s ability to tolerate distress. Estimated alcohol use was also retrospective, and as such it could have been contaminated by errors in memory. A relatively small number of students reported engaging in solitary binge drinking, which may have limited power to detect all but the most robust between group differences. Despite these limitations, this study demonstrated a strength in its use of a multimodal assessment of distress tolerance, a complex and multi-faceted construct.

5. Role of funding sources This research was supported by Idaho State University (ISU). ISU had no role in the collection, analysis, or interpretation of these data, writing the manuscript, or the decision to submit the paper for publication.

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Contributors

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Ms. Williams and Dr. Vik designed the study, conducted statistical analyses, and wrote the manuscript. Ms. Williams collected the data with the help of a research assistant. Dr. Wong

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supervised the final analyses of this data.

Conflict of Interest

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All authors declare that they have no conflicts of interest.

Acknowledgements

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The authors wish to thank Troy Savary for his assistance in data collection. IRB approval

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was through Idaho State University’s Human Subjects Committee.

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DISTRESS TOLERANCE IN SOLITARY AND SOCIAL DRINKING

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Table 1. Descriptives for study variables. Values for estimated number of drinks and DISR scores are prior to inverse and square

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root transformations, respectively.

19.07

5.89

Min.

Max.

Possible

Reported

Reported

Range

10

36

26

34.6

PASAT

22.39

5.38

18

Estimated

33.5

50.3

0

4

21.89

SD

6.70

Min.

Max.

Possible

Reported

Reported

Range

10

34

26

37.0

43

--

26.93

6.72

19

42

--

240

240

53.87

77.0

0

324

324

9

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Number of Drinks

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Consumed in Past 3 Months DMQ

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(% quit) Age

Mean

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DISR

SD

Solitary Drinkers

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Mean

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Social Drinkers

8.26

3.04

5

19

20

9.74

3.15

5

15

20

2.55

2.49

0

10

18

2.26

2.36

0

9

18

Coping Alcohol Related Problems

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Table 2. Correlation matrix between study variables. Number of drinking days was submitted

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* = p < .05; ** = p ≤ .01

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.319**

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-.069

3 4 5 -.050 .069 -.293** -.010 .015 .032 1 .091 .284** .091 1 -.051 .284** -.051 1 .051 -.114 .309**

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2 .055 1 -.010 .015 .032 -.171

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1. NUMBER OF DRINKS 2. AGE 3. DISR 4. PASAT 5. DMQ COPING 6. ALCOHOL PROBLEMS 7. SOLITARY DRINKING

1 1 .055 -.050 .069 -.293** -.326**

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to an inverse transformation.

.161

.018

.170*

6 -.326** -.171 .051 -.114 .309** 1

7 -.069 .319** .161 .018 .170* -.062

-.062

1

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Coping Motives b = .234* sb = .101

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a = 1.306* sα = .372

Drinking Consequences

c = .055; c’ = -.040

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DISR scores

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Figure 1. Unstandardized beta coefficients and their respective standard errors for paths a and b, which were used for a mediation model between DISR scores and drinking consequences. Both

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pathways were significant at p ≤ .001. The standardized betas for paths c and c’ are listed for

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reference, although neither were significant at p < .05.

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Highlights  Reported differences in distress tolerance across types of college student drinkers.

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Students varied by self-report but not behavioral distress tolerance measures. Solitary binge drinkers had more coping motives than other drinkers. Coping mediated the relationship between distress tolerance and alcohol problems.

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  