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. Author manuscript; available in PMC: 2022 Mar 1.
Published in final edited form as: Psychol Addict Behav. 2020 Jul 13;35(2):148–159. doi: 10.1037/adb0000653

Putting Things in Context: Longitudinal Relations Between Drinking Contexts, Drinking Motives, and Negative Alcohol Consequences

Jack T Waddell 1, William R Corbin 1, Shane D Marohnic 1
PMCID: PMC7855250  NIHMSID: NIHMS1606470  PMID: 32658492

Abstract

Objective:

Recent studies suggest that solitary (but not social) drinking may confer risk for negative alcohol consequences via beliefs about alcohol’s ability to reduce tension, and explicit motivations to drink to cope with negative mood states. However, because prior studies are largely cross-sectional, it is unclear if tension reduction expectancies and drinking to cope are antecedents or consequences of solitary drinking. The current study aimed to address this gap in the literature using prospective data (three waves across 12 months) from a sample of moderate to heavy drinking young adults.

Method:

Data were drawn from a larger investigation of contextual influences on subjective alcohol response. Participants (N=448) reported on alcohol use in multiple drinking contexts and tension reduction expectancies at baseline (T1), drinking motives at a 6-month follow-up (T2), and past-month negative alcohol consequences at a 12-month follow-up (T3). We examined potential indirect effects of drinking contexts on negative consequences operating through alcohol expectancies and drinking motives.

Results:

Solitary drinking was indirectly associated with later negative consequences through stronger coping motives, although tension reduction expectancies did not serve as a significant mediator. Social drinking was not directly or indirectly related to later alcohol consequences.

Conclusions:

Results suggest that solitary drinking contexts confer risk for negative consequences through coping motives, and that these effects are invariant across sex, race, and ethnicity. These findings have important clinical implications as they suggest that targeting solitary drinkers for skills-based coping interventions may reduce risk for a developmental trajectory toward negative alcohol consequences.

Keywords: Solitary Drinking, Coping Motives, Tension Reduction, Alcohol Consequences

Introduction

Alcohol misuse, defined as excessive daily and weekly alcohol consumption (CDC, 2008), is a serious and growing public health concern, as it is common (Grant et al., 2015), and on the rise since the early 2000s (Grant et al., 2017). Alcohol misuse is associated with negative consequences such as alcohol-impaired driving, risky sexual behavior, and death (e.g., Mokdad et al., 2004; NIAAA, 2017; Perkins, 2002; Wechsler et al., 2004; 2005), as well as risk for Alcohol Use Disorders (AUDs), which are most prevalent in young adults (Grant et al., 2017; SAMHSA, 2015). Although many young adults mature out of heavy drinking patterns, a substantial minority continue risky drinking patterns (Lee & Sher, 2016; O’Malley, 2004), increasing their likelihood of developing an AUD. As such, delineating prospective risk factors for negative alcohol consequences in young adulthood has clear implications for public health and prevention programming.

The context in which one drinks is one potentially important risk factor for young adult negative alcohol consequences. Since most young adults endorse drinking with others (e.g., Johnston et al., 2006; Mohr et al., 2001), typically with the intent of socializing (e.g., Bradley et al., 1991; Kuntsche et al., 2005), early theorists conceptualized solitary drinking as a culturally deviant and abnormal behavior (Akerlind & Hornquist, 1992; Jellinek, 1946). However, research suggests that a sizable portion of adolescents and young adults (12–25%) drink alone (Christiansen et al., 2002; Gonzalez et al., 2009; Neff, 1997), highlighting the importance of research on the effects of drinking in a solitary context.

Several studies have found that solitary drinking is related to both high-risk alcohol use and alcohol-related problems (e.g., Bilevicious et al., 2018; Bourgault & Demers, 1997; Christiansen et al., 2002; Creswell et al., 2014; Gonzalez et al., 2009; Holyfield et al., 1995; Keough et al., 2015; Keough et al., 2016; Keough et al., 2018; Skryzynski et al., 2018). More recent studies have used comprehensive designs to more clearly isolate solitary drinking as a risk factor. For example, Creswell et al. (2014) found that solitary drinking was prospectively associated with AUD symptoms at age 25 above and beyond focal predictors of negative consequences, such as drinking quantity/frequency, demographics, and past AUD symptoms. Additionally, Bilevicious et al. (2018) found that solitary drinking (compared to social drinking) had the largest effect size when predicting hazardous alcohol use, and Keough et al. (2018) found that solitary but not social drinking was indirectly associated with young adult negative consequences through hazardous drinking. Taken together, these studies suggest that solitary drinking may represent a critical risk factor for a shift toward more problematic use of alcohol and/or development of AUD.

In an effort to better understand associations between solitary drinking and risk for later alcohol-related problems, several studies have examined relations between solitary drinking and other known risk factors including depression, anxiety, and/or loneliness. For example, Keough et al. (2015) and Buckner & Terlecki (2016) found that solitary drinking mediated the effect of depressive and anxiety symptoms, respectively, on alcohol-related problems, and Bilevicius et al. (2018) found that solitary drinking mediated the effect of negative affect on alcohol-related problems. Additionally, Akerlind & Hornquist (1992) suggest that individuals may drink in solitary settings because they lack social support to drink in a group, and Gonzalez et al. (2009) found that suicidal ideation was associated with more frequent solitary drinking. Collectively, these studies support important links between negative affective states and solitary drinking.

There is also accumulating empirical evidence to support links between solitary drinking and drinking to cope (e.g., Armeli et al., 2014; Blevins et al., 2018; Cooper et al., 1992; Gonzalez et al., 2009; O’Hara et al., 2014; 2015; Skyrzynski et al., 2018). The majority of past research suggests that coping motivation is an antecedent to solitary drinking, given the lack of socialization/planning required and the availability of alcohol in one’s home/place of residence. In concert with this reasoning, individuals high in negative affect tend to seek coping mechanisms that do not require a lot of physical or social energy (Denollet & de Vries, 2006). However, such an argument implicitly argues that a coping-motivated drinker decides to drink in a solitary setting due to the expectation that alcohol will facilitate tension reduction. Thus, an alternate explanation places solitary drinking as the antecedent, as persistent solitary drinking may sensitize one to the negatively reinforcing effects of alcohol, leading to expectations of tension reduction and coping motivation for use (Corbin et al., 2020). Consistent with decades of research on drinking motivation, this alternative model suggests that global drinking motivation is a malleable construct that can be affected by past learning (e.g., Cooper et al., 1995; Kuntsche et al., 2005; Madden & Clapp, 2019). In summary, the direction of effects between solitary drinking and coping motives is unclear due to the cross-sectional nature of most prior studies. Individuals who drink to cope may select solitary settings to facilitate these effects, or, drinking in solitary settings may serve to sensitize individuals to alcohol’s negatively reinforcing effects. It is also possible that solitary drinking and coping motives are reciprocally related across time.

Although either direction of effects is plausible, Social Learning Theory (SLT; Bandura, 1977, Maisto et al., 1999) might suggest that the selection of a solitary context by coping-motivated drinkers is proceeded by past learning and expectations that solitary contexts facilitate negatively reinforcing effects. SLT posits that cognitive factors, particularly alcohol outcome expectancies and drinking motives, are focal and proximal predictors of drinking behavior that may serve to mediate more distal risk factors. Drinking motives are logically proceeded by alcohol expectancies (beliefs about potential alcohol reward), with motives serving as a final common pathway to drinking behavior and related consequences. In addition, motivational models of alcohol use suggest that environmental factors related to drinking (e.g., solitary versus social settings) lead to past reinforcement from drinking (e.g., alleviating negative affect), which indirectly predict coping motivation through alcohol expectancies (Cox & Klinger, 1988). Consistent with this causal sequence, Cooper et al. (1995) found that expectations for stress relief and tension reduction (Brown et al., 1985) were associated with coping motives, which were, in turn, associated with drinking and alcohol-related problems. Kuntsche et al. (2007) also found that tension reduction expectancies predicted drinking indirectly through coping motives.

Different drinking contexts may also serve to strengthen particular alcohol expectancies. Past research suggests that solitary/family contexts are associated with expectancies for negatively reinforcing alcohol effects, whereas social contexts are associated with expectancies for positively reinforcing alcohol effects (Brown et al., 1985; Christiansen et al., 2002). Thus, solitary drinking is likely to take place in less stimulating environments (e.g., at home), which may be more conducive to feeling tension reducing effects. On the contrary, more stimulating environments, such as bars or parties, may be more conductive to experiencing rewarding effects of alcohol. Consistent with this notion, Corbin et al. (2015) found that low arousal positive effects (e.g., relaxed, calm) were endorsed more strongly in a low arousal lab setting (chairs, computer, desks) than in a high arousal simulated bar setting (neon lights, alcohol paraphernalia).

The literature reviewed thus far is consistent with a model in which solitary drinking leads to tension reduction expectancies, which indirectly contribute to negative alcohol consequences through coping motives. Importantly, coping motives are a well-established predictor of negative alcohol consequences (e.g., Merrill et al., 2010; 2014). One cross-sectional study (Corbin et al., 2020) tested this conceptual model and found that solitary drinking predicted alcohol consequences indirectly through tension reduction expectancies and coping motives, though the indirect effect through coping motives (and not tension reduction expectancies) was stronger. Unfortunately, given the cross-sectional nature of the data, this study was not able to demonstrate temporal precedence of the variables in this potential causal sequence. Although this study also demonstrated invariance of the model by sex and race/ethnicity, the sample size (n = 157) did not permit strong tests of invariance.

Therefore, the present study sought to provide a more rigorous test of indirect effects of solitary drinking on negative alcohol consequences through both tension reduction expectancies and coping motives using a larger sample and prospective data. The larger sample size allows for a stronger test of model invariance by sex and race/ethnicity. In addition, the present study was able to test a competing model, in line with the summation of past research, where solitary drinking serves as the mediator and coping motives serve as the distal predictor. Consistent with Corbin et al. (2020), we hypothesized that solitary drinking at baseline (T1) would be indirectly related to negative alcohol consequences one year later (T3) through tension reduction expectancies (T1) and coping motives six months later (T2). We chose to measure the distal (drinking context) and outcome variable (consequences) one year apart, in line with other prospective studies (e.g., Merrill et al., 2014). In addition, we chose to measure the mediating variable of drinking motives at a 6-month follow up to allow for a rigorous test of temporal precedence between the mediator and outcome. We also anticipated an indirect effect of solitary drinking on negative alcohol consequences directly through coping motives.

In the competing model, we reversed the direction of effects such that solitary drinking was the proposed mediator of the relation between coping motives and negative alcohol consequences. Tension reduction expectancies were not included in this model as they are conceptually distal to coping motives and therefore of less relevance in the causal sequence. We anticipated that the prospective relation between coping motives and solitary drinking would be weaker than the prospective relation between solitary drinking and coping motives.

Methods:

Participants

The current study utilized data from a larger investigation of contextual influences on subjective alcohol response. Participants were recruited via flyers around Arizona State University and the surrounding community, as well as through online advertisements and listservs (e.g., Craigslist, Facebook). Participants completed an initial phone screen, and 547 individuals who met preliminary eligibility criteria came to the lab for a baseline session. To be eligible, participants had to endorse binge drinking (4+ drinks on one drinking occasion for women, 5+ for men) at least once in the past month and be between the ages of 21–25. Exclusion criteria included serious mental illness or medical conditions, use of psychotropic or pain medicine, negative reactions to alcohol (e.g., flushing response), use of illicit drugs other than marijuana, daily marijuana use, past treatment seeking for alcohol problems, and pregnancy/nursing. Participants who met these criteria were brought in for a baseline session and administered a clinical interview. Participants were further excluded if they endorsed alcohol dependence or a past-month mood/anxiety disorder. A total of 448 moderate to heavy drinking young adults who met full eligibility requirements returned to the lab for an alcohol challenge session. For a more detailed explanation of the lab protocol, see Hartman et al., 2019 and Richner et al., 2018. Of the 448 participants who completed the lab session (and were therefore eligible for follow-up surveys), the mean age was 22.27 (SD = 1.25) and roughly half were male (253; 56.5%). Participants were predominately Caucasian (66.1%) and Non-Hispanic (71.7%), with overall racial/ethnic composition representative of the local population (See Table 1 for demographics).

Table 1:

Demographics

Variable N Mean (SD)
Age 448 22.27
(1.25)
Sex 448
 Male 253 (56.5%)
 Female 194 (43.3%)
 Missing 1 (.2%)
Race 448
 White/Caucasian 296(66.1%)
 Black/African-American 34 (7.6%)
 Asian 43 (9.6%)
 American Indian/Native 7(1.6%)
 Other 65 (14.5%)
 Missing 3 (.7%)
Ethnicity 448
 Hispanic/Latinx 113(25.2%)
 Non-Hispanic/Latinx 321 (71.7%)
 Missing 14(3.1%)
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Procedure

All procedures were approved by the Human Subjects committee at the institution where the research was conducted (Protocol #1210008481). If participants met eligibility criteria via an initial phone screen, they were brought into the lab for the baseline session. Participants were administered the Alcohol Use Disorders and Associated Disabilities Interview Schedule-IV (AUDADIS-IV; Grant et al., 2003) and a battery of questionnaires/assessments. Participants who remained eligible after the baseline session were scheduled to come back to the lab for a placebo-controlled alcohol challenge. After the alcohol challenge, participants were followed up at 6 and 12 months. To obtain follow-up data, participants were sent a confidential, personalized Qualtrics link to complete an online survey. Participants were then directed to a secure website where they filled out a web-based calendar of alcohol use patterns. After each follow-up, participants were thanked for their time and compensated. Participants were paid $12 an hour for the baseline session (and alcohol challenge) and an addition $5 dollars per session (2 sessions) if they attended at their originally scheduled time. Participants were paid $20 at the 6-month follow-up, and $30 at the 12-month follow-up. Data from the second lab session (alcohol challenge) were not included in the present analyses, as all variables of interest were measured during the first lab session and the longitudinal follow-ups.

Measures

Demographics.

Age, sex, race, and ethnicity were all assessed at the baseline session.

Alcohol Use.

Participant alcohol use was assessed via the Timeline Follow-Back (TLFB; Sobell & Sobell, 1992). Participants were asked to report the number of drinks consumed on each day in the past month and the amount of time spent drinking each day. Participants were provided standard drink charts to facilitate accurate reporting and were encouraged to reference text messages, social media, and other personal data that could aid in remembering specific drinking episodes. The TLFB was administered in person by a Research Assistant at baseline and via web-based calendars at follow-up assessments. Past research suggests that the TLFB has good test-retest reliability (Carey et al., 2004). Additionally, the TLFB provides more comprehensive data than other quantity and frequency measures, which may over- or under-estimate drinking patterns comparatively (Stevens et al., 2019). In the current study, drinks per drinking day was included in the analytic models. This was calculated by summing all reported drinks consumed in the 30-day period and dividing by the number of drinking days reported.

Drinking Contexts.

Typical drinking contexts were assessed by asking participants to indicate how frequently they drink in a variety of different situations. Responses ranged from “never drink in this context” (1) to “always drink in this context” (7). A single item assessed drinking “alone,” which we defined as solitary drinking. Seven different contexts that included other people (e.g., “at a tailgate or sporting event,” “at a large house party,” “at a bar”) were averaged to create a social drinking variable. The social drinking variable had good internal consistency (α = .79).

Expectancies.

Alcohol Outcome Expectancies were assessed via the Comprehensive Effects of Alcohol (CEOA; Fromme et al., 1993). The CEOA is a 38-item measure that assesses anticipated alcohol effects in a variety of different domains. Subscales include Tension Reduction (e.g., “I would feel calm”), Sexuality (e.g., “I would be a better lover”), Liquid Courage (e.g., I would be more likely to be courageous”), Sociability (e.g., I would be more likely to act sociable), Self-Perception (e.g., “I would be more likely to feel moody), Cognitive and Behavioral Impairment (e.g., “I would be more likely to be clumsy”), and Risk/Aggression (e.g., I would be more likely to act aggressively). All items were rated on a 1 to 4 scale ranging from disagree (1) to agree (4). For the present analyses, only the Tension Reduction subscale was used based on the theoretical model. Past research suggests that the CEOA has good internal consistency in college-aged samples (Hatzenbeuhler et al., 2008; Zamboanga et al., 2010), and internal consistency for the Tension Reduction subscale was adequate in the current sample (α = .75).

Drinking Motives.

Specific drinking motives were assessed via the Drinking Motives Questionnaire-Revised (DMQ-R; Cooper, 1994; Cooper et al., 1995), which includes 20-items assessing motivations for alcohol use. Drinking motives are divided into coping (e.g., “to forget your worries”), conformity (e.g., “so that others won’t kid you about not drinking”), social (e.g., “to be sociable”), and enhancement (e.g., “because it’s exciting”) motives. Each motive was assessed on a 6-point scale with responses ranging from never (1) to almost always (6). Internal consistency in the current sample was good for all subscales (α = .81-.84).

Negative Consequences.

Negative alcohol consequences were assessed via the Young Adult Alcohol Consequences Questionnaire (YAACQ; Kahler et al., 2005; Read et al., 2006). The YAACQ includes 48 items assessing a range of consequences (1= yes, 0 = no) from alcohol use in the past month. Subscales include social/interpersonal (e.g., “I have become very rude, obnoxious, or insulting after drinking”), academic/occupational (e.g., “I have neglected my obligations to family, work, or school because of my drinking”), risky behavior (e.g., ‘I have taken foolish risks when I have been drinking”), impaired control (e.g., “I often drank more than I originally had planned”), poor self-care (e.g., “I have been less physically active because of drinking”), diminished self-perception (e.g., “I have felt badly about myself because of my drinking”), blackout drinking (e.g., “I have awakened the day after drinking and found that I could not remember a part of the evening before”), and physiological dependence (e.g., “I have felt anxious, agitated, or restless after stopping or cutting down on drinking”). All subscales were added together as a total “negative consequences” score, which had excellent internal consistency at baseline and follow-up (a = .92-.94).

Data Analytic Plan.

Before conducting the primary analyses, all variable distributions were evaluated for assumptions of normality. If significant outliers were identified, they were winsorized by replacing values more than 3 standard deviations away from the mean with a value of one higher than the highest value within the distribution (Tabachnick & Fidell, 2007). To address any remaining non-normality, bootstrapping was used.

Longitudinal path analyses were conducted using Mplus Version 7.7 (Muthen & Muthen, 2017). Evidence of adequate model fit was based on guidelines outlined in Hu & Bentler (1999) including Root Mean Square Error of Estimate (RMSEA) values close to .06, Standardized Root Mean Square Residual (SRMR) values close to .08, and both Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) values close to .95. The conceptual model (Figure 1) included predictor variables from baseline assessments (T1), mediators from baseline assessments and 6-month follow-up (T2), and outcome measures (negative alcohol consequences) from baseline (T1) and 12-month follow-up (T3).

Figure 1:

Figure 1:

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Hypothesized Path Model

Solitary drinking, social drinking, and drinks per drinking day at baseline were included as predictors of T3 negative alcohol consequences, controlling for drinking consequences at baseline. Solitary drinking at baseline also predicted tension reduction expectancies at baseline, and coping motives at T2, controlling for coping motives at T1. Due to time constraints on follow-up assessments, tension reduction expectancies were only assessed at baseline, making the path from solitary drinking to tension reduction expectancies cross-sectional. Tension reduction expectancies at baseline were included as a predictor of T2 coping motives, which were specified as a predictor of T3 drinking consequences. We also included a mediational path from T1 solitary drinking to T3 alcohol consequences through T2 enhancement motives to test the specificity of the indirect effect through coping motives. Paths from solitary drinking to conformity and social motives were not included, as solitary drinking does not provide an opportunity to socialize or conform to the behavior of peers.

Although solitary drinking was the main predictor of interest, direct and indirect paths from T1 social drinking to T3 negative consequences were also included. These paths were identical to the solitary paths; however, the mediators of interest were enhancement, social, and conformity motives. All auto-regressive paths from T1 to T2 motives and from T1 to T3 alcohol consequences were included to allow for prospective prediction, accounting for prior motives and consequences. Concurrent exogenous variables and residuals of endogenous variables assessed at the same time-point were allowed to covary (Landis, Edwards, & Cortina, 2009). As such, T1 motives, drinking contexts, drinking quantity, and alcohol consequences were allowed to correlate and residuals for T2 motives were allowed to covary. Missing data patterns were assessed for all variables and Full Information Maximum Likelihood (FIML) was utilized if differences between retained and missing participants were absent/minimal. Bias-Corrected Bootstrapped Confidence Intervals (CIs) were used to test indirect effects, as they provide more accurate estimates given the asymmetric nature of confident intervals for the products of coefficients (MacKinnon et al., 2007). CIs that do not contain zero can be deemed statistically significant at the desired alpha level, which for this study was .05.

Lastly, multiple group models were estimated to test for invariance in path coefficients across sex, ethnicity, and race. Invariance was tested by comparing models that constrained all non-autoregressive structural paths to be equal to models that allowed these paths to freely vary across groups. Differences in model fit were examined using nested chi-square comparisons. If indications of multigroup variance were present, single degree of freedom tests were conducted to isolate specific paths that differed by group. Due to small sample sizes in some racial/ethnic groups, tests of invariance by ethnicity compared Non-Hispanic/Latinx participants to Hispanic/Latinx participants, and tests of invariance by race compared Caucasian participants to all minority/multiracial participants.

Results

Preliminary Analyses.

All alcohol use and negative consequence variables had outliers greater than 3 standard deviations from the mean. After winsorizing each of these cases (i.e., 8 cases for baseline consequences, 4 cases for baseline drinking quantity, 7 cases for follow-up problems) into the next highest integer within the distribution (Tabachnick & Fidell, 2007), all skewness and kurtosis values (< 1.5) were sufficiently normal for parametric analyses.

Missing data patterns were assessed for all variables. A total of 394 participants (88%) reported T2 follow-up data and 359 (80.1%) reported T3 follow-up data on negative alcohol consequences. There were no differences on any of the context or motives variables between those who completed surveys only at T1 versus those who completed T2 or T3 surveys. There was a significant difference in T1 drinking quantity between participants who reported only at T1 and those retained at T2 (t (64.9) = −2.04, p < .05), though the comparison of those who completed T1 only and those retained at T3 was not statistically significant. Additionally, the difference in T1 drinking quantity between those retained at T2 and those who did not complete the T2 survey was relatively small (.71 drinks). Given limited differences between those retained and those lost at follow-up, FIML was used for both independent and dependent variables.

Descriptive Analyses.

Means, standard deviations, and zero-order correlations are presented in Table 2. The current sample of drinkers endorsed moderate levels of T1 drinking quantity per drinking day (M = 4.63, SD = 2.21) and had a wide range of negative consequences from alcohol use (M = 7.39, SD = 6.59) at T1. As expected, mean levels of social drinking (M = 4.43, SD = 1.11) were higher than solitary drinking (M = 2.16, SD = 1.35). Solitary drinking was positively correlated with tension reduction expectancies at T1, coping motives at T1 and T2, enhancement motives at T1, and negative consequences at T1 and T3. In contrast, social drinking was inversely correlated with tension reduction expectancies at T1, but was positively correlated with all drinking motives, drinking quantity, and negative consequences across all time points.

Table 2:

Study Variable Means, Standard Deviations and Zero-Order Correlations

Variable Mean (SD) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
1. Solitary Drinking (Tl) 2.16 (1.35) -- .09 −.05 .17** .24** −.02 .11* .01 .16** −.09 .05 −.08 −.09 .10* .08* .17**
2. Social Drinking (Tl) 4.43 (1.11) -- .24** −.16** .22** .36** .31** .23** .17** .33** .17** .12* .13** .29** .20** .23**
3. Drink Per Day (Tl) 4.63 (2.21) -- −.07 .03 .10* .16** .09* .04 .12* .10 .04 .52** .26** .24** .26**
4. CEOA TR (Tl) 2.91 (.64) -- .04 −.04 .04 .13** .01 −.09 .03 −.06 .001 −.22 −.08 −.03
5. DMQCope(Tl) 2.03 (.84) -- .48** .44** .43** .58** .28** .20** .23** −.03 .33** .27** .37**
6. DMQ Social (Tl) 3.69 (.82) -- .55** .41** .28** .57** .29** .30** .01 .32** .22** .25**
7. DMQ Enhance (Tl) 3.24 (.83) -- .25** .24** .38** .56** .19** .07 .27** .22** .25**
8. DMQ Conformity (Tl) 1.62 (.68) -- .31** .27** .14** .57** .01 .29** .25** .27**
9. DMQ Cope (T2) 2.34 (.95) -- .41 ** .38** .45** .04 .17** .38** .41**
10. DMQ Social (T2) 3.71 (.85) -- .61** .33** .12* .23** .25** .30**
11. DMQ Enhance (T2) 3.31 (.87) -- .28** .16** .16** .29** .26**
12. DMQ Conformity (T2) 1.74 (.83) -- .02 .13** .31** .23**
13. Drink Per Day (T2) 4.21 (2.07) -- .12* .28** .24**
14. YAACQ (Tl) 7.39 (6.59) -- .42** .41**
15.YAACQ(T2) 9.02 (8.66) -- .58**
16. YAACQ (T3) 6.19 (7.26) --
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Note: CEOA TR = Tension Reduction Expectancies, DMQ COPE = Coping Drinking Motives, DMQ Social = Social Drinking Motives, DMQ Enhance = Enhancement Drinking Motives, DMQ Conformity = Conformity Drinking Motives, YAACQ = Total Sum of Young Adult Negative Alcohol Consequences.

**

p < .01,

*

p < .05,

Primary Analyses.

The conceptual model depicted in Figure 1 provided good fit to the data (X2(32) = 62.68, p < .001, RMSEA = .046 [.029, .063], CFI = .97, TLI = .95, SRMR = .03). At T1, solitary drinking was not significantly correlated with social drinking or drinking quantity, but social drinking was significantly correlated with drinking quantity. The direct path from T1 solitary drinking to T3 negative consequences was significant even when accounting for all mediated effects (b = .53, SE = .26, p = .04, 95% CI = [.04, 1.04]). Of central interest to the current study, T1 solitary drinking was associated with T1 tension reduction expectancies (b =.09, SE = .02, p < .001, 95% CI = [.04, .13]), but tension reduction expectancies were not associated with T2 coping motives (b = −.04, SE = .05, p =.46, 95% CI = [−.14, .07]). Thus, there was no indirect effect of solitary drinking on coping motives through tension reduction expectancies. However, T1 solitary drinking was associated with T2 coping motives (b = .05, SE = .03, p = .04, 95% CI = [.01, .10]), and T2 coping motives in turn were associated with T3 negative consequences (b = 2.12, SE = .45, p < .001, 95% CI = [1.27, 3.07]). The Bias-Corrected Bootstrapped CI indicated a significant indirect effect of solitary drinking on alcohol consequences operating through coping motives (b = .11, SE = .06, 95% CI = [.01, .26]), such that T1 solitary drinking predicted higher coping motives at T2, which in turn predicted more negative consequences at T3. T1 solitary drinking did not predict enhancement motives (b = .03, SE = .02, p = .12, 95% CI = [−.01, .08]), providing evidence for the specificity of the indirect effect through coping motives.

Path estimates were also tested from T1 social drinking to T2 drinking motives. Social drinking prospectively predicted higher social motives (b = .10, SE = .03, p < .01, 95% CI = [.03, .15]) but not conformity (b = .01, SE = .03, p = .95, 95% CI = [−.06, .06]), enhancement (b = .01, SE = .04, p = .99, 95% CI = [−.07, .07]), or coping motives (b = .03, SE = .03, p = .49, 95% CI = [−.05, .10]). T2 social (b = .15, SE = .32, p = .65, 95% CI = [−.65, 1.39]), enhancement (b = .36, SE = .47, p = .45, 95% CI = [−.57, 1.29]), and conformity motives (b = .52, SE = .46, p < .26, 95% CI = [−.39, 1.43]) were not associated with T3 negative consequences, and thus there were no indirect effects of T1 social drinking on T3 negative consequences through T2 drinking motives. For a depiction of all standardized model estimates, see Figure 2.

Figure 2:

Figure 2:

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Final Path Model. Note: The figure depicts standardized path estimates. All exogenous variables were allowed to freely correlate, as were the residuals for T2 drinking motives. Significant paths are shaded lines and non-significant paths are dotted lines. YAACQ = Young Adult Negative Alcohol Consequences. ** p < .01, * p < .05,

Because solitary drinking might also be a consequence of drinking to cope, a competing model was tested with reverse effects. T2 solitary and social drinking were treated as the mediating variables and T1 motives and drinking quantity were treated as predictor variables. T2 solitary and social drinking were included as predictors of T3 negative consequences, and autoregressive effects were included for social and solitary drinking (T1 to T2) and negative consequences (T1 to T3). Tension Reduction expectancies were not included in this model given that a) motives are presumed to be a proximal predictor of drinking and b) the previous models showed no relation between tension reduction expectancies and coping motives. This supplementary model also fit the data well (X2(8) = 18.86, p < .02, RMSEA = .055 [.023, .088], CFI = .98, TLI = .93, SRMR = .02). However, T1 drinking quantity (b = −.06, SE = .03, p < .04, 95% CI [−.11, −.01]) was the only prospective predictor of T2 solitary drinking, such that less T1 drinking was significantly associated with more solitary drinking controlling for effects of other motives and prior solitary drinking. Social motives at T1 were the only significant prospective predictor of T2 social drinking (b = .17, SE = .08, p < .03, 95% CI = [.01, .32]). T3 negative consequences were significantly associated with T1 coping motives (b = 1.83, SE = .48, p < .001, 95% CI = [.88, 2.78]), T1 drinking quantity (b = .51, SE = .16, p < .01, 95% CI = [.20, .81]), T2 solitary drinking (b = .68, SE = .23, p < .01, 95% CI = [.24, 1.13]), and T2 social drinking (b = .99, SE = .29, p < .001, 95% CI = [.44, 1.56]). However, there was not a significant prospective relation between T1 coping motives and T2 solitary drinking when accounting for the autoregressive solitary drinking path (See Figure 3). This model was also run with T1 tension reduction expectancies as a cross-sectional predictor of T1 coping motives (not significant), and results were unchanged.

Figure 3:

Figure 3:

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Reverse Path Model. Note: The figure depicts standardized path estimates. All exogenous variables were allowed to freely correlate, as were the residuals for T2 drinking motives. Significant paths are shaded lines and non-significant paths are dotted lines. YAACQ = Young Adult Negative Alcohol Consequences. ** p < .01, * p < .05 † p < .10

Multigroup Path Analyses.

Invariance by sex and race/ethnicity was tested by comparing models in which all parameters were allowed to vary by group to models in which the lagged structural paths (e.g., drinking contexts to drinking motives; drinking motives to alcohol problems) were constrained to equality by sex or race/ethnicity. The model that constrained lagged structural paths to be equivalent across sex (X2 (84) = 131.27, p < .001) did not show a significant decrement in fit from the model that allowed all paths to vary by sex (X2 (64) = 101.88, p < .01; ΔX2 (20) = 29.38, p = .08). However, since p < .10, we probed specific path differences via single degree of freedom tests. Three (of 20) constrained paths differed by sex. T1 solitary drinking was directly associated with more T3 negative consequences in women (b = 1.06, p < .01) but not men (b = .10, p = .79) (ΔX2 (1) = 4.472, p = .03). Additionally, T1 drinking quantity was associated with stronger T2 social motives in men (b = .04, p < .03) but not women (b = −.03, p = .26) (ΔX2 (1) = 5.95, p = .01), and T1 drinking quantity was not significantly associated with stronger T2 conformity motives in women (b = .05, p < .07) or men (b = −.03, p = .11) (ΔX2 (1) = 5.85, p = .02); however, the effects were in opposite directions. The model freeing these three paths but constraining the remaining paths (X2 (81) = 115.52 p < .001) did not significantly differ from the model allowing all paths to freely vary (ΔX2 (17) = 13.64, p = .69).

Next, models were compared for Hispanic/Latinx versus Non-Hispanic/Latinx participants and Caucasian versus racial minority/multiracial participants. For ethnicity, the constrained model (X2 (84) = 117.77, p < .001) was not significantly different from the fully unconstrained model (X2 (64) = 90.33, p < .02; ΔX2 (20) = 27.44, p = .12). For race, the constrained model (X2 (84) = 125.81, p < .001) did not show a significant decrement in fit relative to the model that allowed all paths to vary by race (X2 (64) = 96.17, p < .001; ΔX2 (20) = 29.64, p < .08). However, since p < .10, we probed specific paths. Single degree of freedom tests suggested that three (of 20) constrained paths differed by race. T1 drinking quantity was associated with more T3 negative consequences in racial minority participants (b = .99, p < .001) but not Caucasians (b = .01, p = .97) (ΔX2 (1) = 9.91, p < .01). In addition, T1 drinking quantity was significantly associated with stronger social motives in Caucasians (b = .06, p < .05) but not racial minority participants (b = −.01, p = .78) (ΔX2 (1) = 6.18, p < .05). Finally, greater T1 drinking quantity was (non-significantly) associated with stronger enhancement motives in Caucasians (b = .03, p = .12) and weaker enhancement motives in racial minority participants (b = −.04, p = .12) (ΔX2 (1) = 5.94, p < .05). The model freeing these three paths but constraining the remaining paths (X2 (81) = 108.21, p < .001) did not significantly differ from the model allowing all paths to freely vary (ΔX2 (17) = 12.04, p = .80).

Discussion

The current study aimed to prospectively test indirect effects of solitary drinking on negative alcohol consequences through tension reduction expectancies and coping motives. A recent study (Corbin et al., 2020) found cross-sectional evidence for these effects, though the indirect effect of solitary drinking through coping motives (but not tension reduction expectancies) was stronger than the indirect effect through both tension reduction expectancies and coping motives. The present study found prospective evidence for only the latter of these indirect paths, such that coping motives (T2) partially mediated the effect of solitary drinking (T1) on negative alcohol consequences (T3). Indirect effects of solitary drinking were also specific to coping motives, and a model testing the reverse direction of effects found that coping motives were not a prospective predictor of solitary drinking. These findings support SLT, where past solitary drinking serves as a reinforcing antecedent to coping motivation and negative consequences. These findings also suggest that different drinking motives might confer unique risk for negative alcohol consequences based upon the contexts in which young adults drink, highlighting the importance of targeting coping motives in interventions tailored toward solitary drinkers as a high-risk group.

The finding that solitary drinking was directly associated with coping motives rather than indirectly through tension reduction expectancies is consistent with broader motivational theories of alcohol use (Cox & Klinger, 1988; Cooper et al., 1998). Both theoretical and empirical work suggests that drinking motives represent a final pathway through which more distal risk factors operate (e.g., Cooper et al., 1995; Sher et al., 1999). Moreover, situational factors and incentives/disincentives are both proximal antecedents to drinking motivation (Cox & Klinger, 1988). Thus, drinking context may be an important situational predictor of drinking motivation. Cox & Klinger (1988) suggest that the availability of drinking is one particularly important situational characteristic. As such, the availability of alcohol at home and the ability to drink alone (with or without prior planning) may serve as an accessible outlet to cope.

Although tension reduction expectancies did not mediate the effects of solitary drinking on coping motives or negative alcohol consequences, there are several possible explanations for these findings. First, the measure of tension reduction expectancies used in the current study does not directly operationalize “tension reduction,” but rather low arousal positive expectancies (Morean et al., 2012; Corbin et al., 2020). The CEOA (Fromme et al., 1993) assesses whether an individual expects to feel a “relaxed body”, “calm”, and “peaceful”, but does not assess whether an individual expects alcohol to reduce negative effects that result from stress. Thus, it makes sense that solitary drinking was positively related to the CEOA tension reduction subscale, whereas social drinking was inversely related. An individual may not feel a “relaxed body” or “calm” when drinking in a stimulating drinking environment with friends, but he/she may well experience these effects when drinking at home. However, these effects may not differentiate an individual who feels relaxation in response to stress from an individual who experiences general low arousal positive effects, which may have reduced the magnitude of any relation between TR expectancies and coping motives in the current study. To better assess the impact of solitary drinking on coping motives indirectly through tension reduction expectancies, future research should use scales that ask directly about tension reduction from alcohol (i.e., the AEQ; Brown et al., 1985).

Another possibility for the lack of relation between tension reduction expectancies and coping motives is that coping motives address a broader range of emotions. Individuals may drink to reduce a variety of negative mood states other than tension, including sadness and anger. In fact, the DMQ-R coping scale has only one item directly related to anxiety, with remaining items addressing other mood states and constructs such as feeling low confidence. For instance, one item assesses drinking “because you feel more self-confident and sure of yourself”. As such, it makes sense that tension reduction expectancies may not be a strong prospective predictor of coping motives. A broader expectancy subscale (i.e., expectancies related to relief of negative affect more generally) may be more relevant to examine in future research on coping motives.

It is also worth noting that social drinking was not directly or indirectly associated with negative alcohol consequences. These findings are consistent with the broader literature, which suggests that social drinking may directly predict social/enhancement motives and heavier drinking, but not negative alcohol consequences (e.g., Corbin et al., 2020; Kuntsche et al., 2005; Merrill et al., 2014). This points to solitary drinking as a particularly important risk factor to target within prevention programming. Since the analyses controlled for social drinking and drinking quantity at T1, the findings suggest that it may truly be solitary drinking, rather than heavy drinking in a solitary setting (Gonzalez et al., 2012; Gonzalez & Skewes, 2013), that most strongly confers risk for later negative consequences. Thus, it may be particularly important to target drinking in solitary settings when trying to prevent a developmental sequence toward negative drinking consequences.

Given evidence for prospective effects of solitary drinking on negative drinking consequences, it is important to understand factors that lead young adults to engage in solitary drinking. Previous research suggests that individuals high in negative affect and individuals who endorse suicidal ideation are more likely to drink alone (e.g., Bilevicious et al., 2018; Gonzalez, 2009), but little is known about other individual differences that may logically predict solitary drinking. For example, individuals high in impulsivity, particularly negative urgency, may drink alone in an effort to reduce immediate negative affect. Similarly, individuals who are not part of heavy drinking peer groups may drink alone more frequently, as they may have fewer opportunities to engage in social drinking (e.g., Sher et al., 2001). Thus, future research should look at associations between solitary drinking and other situational (e.g., Greek membership) and personal (e.g., impulsivity) factors to identify those at greatest risk for negative consequences associated with solitary drinking.

Although the findings related to sex differences in the model were non-significant, it is worth noting that coping motives fully mediated the effects of solitary drinking for men, whereas the direct effect of solitary drinking remained for women. Although speculative, given the lack of overall sex differences in the model, it is possible that solitary drinking has more negative or mixed effects on emotions in women. It is possible that women, who report higher levels of rumination than men (Nolen-Hoeksema & Jackson, 2001), do not become fully distracted from ruminating thoughts when drinking in a solitary setting. Future studies of the characteristics of solitary drinking contexts (e.g., presence of distractors) may be helpful in addressing this possibility.

In contrast, we found no evidence of differences in the primary paths of interest by race/ethnicity. Only paths from drinking quantity to consequences and from drinking quantity to enhancement and social motives differed across race. These findings matched cross-sectional results from our previous paper (Corbin et al., 2020), suggesting invariance across race/ethnicity in paths related to solitary drinking, tension reduction expectancies, and coping motives. Thus, it appears that solitary drinking and coping motives may be relevant targets of intervention regardless of race and ethnicity.

Although the present study has many strengths and the findings have potentially important implications for prevention, the findings must be considered within the context of several limitations. First, the current sample had a restricted range of drinking and negative mood states. Exclusion criteria screened out individuals who met criteria for a current AUD, very light drinkers, and anyone with a past month mood or anxiety disorder. Thus, it is not clear if the results would generalize to a broader range of drinkers or individuals with mood and/or anxiety disorders. It is possible that mediation through tension reduction expectancies would be present among those with anxiety disorders (i.e., elevated stress), and the removal of such individuals from the current data set may have attenuated any such effects. In addition, it is possible that individuals with an AUD more often engage in solitary drinking, as solitary drinking and coping motivation may mark a shift toward drinking for negative reinforcement (e.g., Koob, 2013), indicating problematic patterns of use. Future research should replicate these findings in heavier and lighter drinking samples, as well as samples of clinically depressed and/or anxious individuals.

The current study also relied entirely upon self-report data on drinking, negative consequences, motivation, and expectancies. Past research suggests that self-reported alcohol use does not differ from collateral reports (Babor et al., 2000; LaForge et al., 2005), but it is possible that participants answered in a socially desirable way. Additionally, all variables were measured at a global rather than momentary level, suggesting that global alcohol expectancies and drinking motivation confer risk for negative consequences. Newer research shows that drinking motivation may fluctuate at the daily level (e.g., Stevenson et al., 2019), however the largest effect sizes on alcohol consequences are seen for trait-like rather than daily coping motivation. Regardless, future research using ecological momentary assessment to replicate and extend the results of the current study at the event-level would be informative in guiding prevention efforts.

One additional limitation of the current study is that it focused on solitary drinking as a homogenous construct, despite research suggesting that “drinking alone while in the presence of others” may also add to the prediction of alcohol consequences (e.g., Corbin et al., 2020). Unfortunately, there is no validated multiple-item measure of solitary drinking. Future studies are needed to develop such a measure and investigate other conceptualizations of solitary drinking that may add to the prediction of negative consequences.

Despite these limitations, the current study advances the literature regarding contextual influences on alcohol consequences by providing longitudinal data to support and extend past research. The results suggest that solitary drinking prospectively predicts negative alcohol consequences through increases in drinking to cope, and that these effects are consistent across sex, race, and ethnicity. These findings suggest that solitary drinking may be an important intervention target and highlight the importance of future research on the characteristics of individuals who engage in solitary drinking. Early prevention and educational programs could target individuals who frequently drink in solitary settings or are at risk for drinking in solitary settings (e.g., high negative affect) and educate them on the consequences and correlates of solitary drinking. In addition, coping skills interventions may attempt to interrupt the link between solitary drinking and coping motives, particularly for men, by helping individuals (particularly solitary drinkers) find alternative coping mechanisms.

Public Health Significance Statement.

Solitary drinking has been implicated as an early marker of risk for Alcohol Use Disorder (AUD). The current study identifies an important mechanism of risk, suggesting that frequent solitary drinkers may be at elevated risk for negative alcohol consequences due to stronger coping drinking motivation. The findings highlight the importance of targeting solitary drinkers in prevention efforts and providing alternatives to alcohol use as a coping strategy for this high-risk group.

Acknowledgments

This study was supported by Grant R01 AA021148 from the National Institute on Alcohol Abuse and Alcoholism to William R. Corbin. The authors report no conflicts of interest. A portion of the current findings were accepted in poster form to the 2020 Collaborative Perspectives on Addiction Conference.

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