Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2022 Nov 1.
Published in final edited form as: Addict Behav. 2021 Jun 27;122:107030. doi: 10.1016/j.addbeh.2021.107030

A Daily Level Analysis of Drinking to Cope Motivation and Interpersonal Stress

Stephen Armeli a, Mark Litt b,c, Howard Tennen c
PMCID: PMC8335979  NIHMSID: NIHMS1721060  PMID: 34225029

Abstract

Interpersonal stress is a commonly reported drinking-related problem and evidence indicates that it is associated with drinking to cope (DTC) motivation. The preponderance of evidence for DTC motivation as a risk factor for increased interpersonal stress, however, comes mainly from studies examining between-person associations. Findings suggest that individuals who commonly report drinking to cope with stress show higher average levels of drinking-related interpersonal problems. To better understand the dynamic processes linking DTC motivation with interpersonal stress, we used a micro-longitudinal design to examine whether nighttime drinking-episode specific levels of three subtypes of DTC motivation (DTC related to anxiety, depressive affect and anger) were associated with concurrent and next-day levels of interpersonal stress, controlling for drinking levels. Participants (N=939) reported their drinking motives, drinking level, and drinking-related problems daily for 30 days during college and again approximately five years later (post-college). Results indicated that, controlling for drinking levels, DTC motivation associated with depressive affect and anger, but not anxiety, were positively associated with concurrent nighttime interpersonal stress. Only DTC related to anger was associated with higher levels of next-day interpersonal stress, controlling for previous night’s stress. The only other motive to predict next-day interpersonal stress was conformity motivation. None of the effects of motives varied across study wave. Findings are discussed in terms of how DTC anger might exacerbate interpersonal problems via processes associated with alcohol myopia.

Keywords: daily, drinking to cope motivation, anger, interpersonal stress

1. Introduction

Ample evidence indicates that young adults report drinking to cope with interpersonal problems (Carey, 1995; Carrigan et al., 1998; Lambe et al., 2015; Patrick et al., 2018). In addition, this reason for drinking has been found to predict drinking-related interpersonal problems even after controlling for drinking level (Dennhardt et al., 2016) and other drinking motives (Shank et al., 2020). These patterns suggest a feedback process in which interpersonal stress is not only an antecedent for coping-related alcohol use, but also an outcome. Indeed, there is a voluminous literature establishing alcohol use as a cause of interpersonal aggression (Giancola et al., 2010). However, this line of research has not examined the role of drinking to cope (DTC) motivation – independent of drinking level – in predicting aggression or other aspects of interpersonal stress. This is unfortunate given the important role of interpersonal stress in the development of alcohol use disorders (Marlatt & Gordon, 1985; Witkiewitz & Marlatt, 2004) and related factors such as depression (Hammen et al. 2009; Vrshek-Schallhorn et al., 2015).

Several frameworks have been put forth to explain the unique effect of DTC motivation on drinking-related problems. Cooper et al. (2016) posited that general avoidance coping strategies, like DTC, draw attention to the negative aspects of these situations and results in a negative attentional bias. This bias could result in a tendency to interpret ambiguous or neutral remarks by others as insults, thus increasing the probability of conflict. Others (Armeli et al., 2014; Martens et al., 2008) have drawn on the Alcohol Myopia Model (AMM: Steele & Josephs, 1990) to help explain the unique effects of DTC motivation on drinking-related problems. This framework might be especially relevant to interpersonal stress given that it is commonly used to explain the alcohol-aggression link. According to the AMM, alcohol constricts attention to salient internal states and environmental cues. Thus, in the context of interpersonal conflict, provocation cues, rather than less salient inhibition cues for restraint, are more often acted upon (Giancola et al., 2010; Steele & Josephs, 1990). These processes might be intensified when individuals are drinking to cope with interpersonal stress, given that this motivation might increase focus on such problems. Indeed, past research indicates that DTC motivation is related to ruminating about problems (Bravo et al., 2018; Bravo et al., 2017).

Taken together, these models suggest that drinking episodes characterized by relatively higher levels of coping motivation might exert a temporally proximal effect on interpersonal problems, possibly exacerbating corresponding negative appraisals of such situations. However, support for DTC motivation-interpersonal stress link mostly comes from studies using research designs unable to address the question about whether changes in interpersonal stress are related to proximal changes in DTC motivation. This is unfortunate given the growing literature indicating that DTC motivation has both state- and trait-like variation (Votaw & Witkiewitz, 2021).

1.1. The present study

To examine the proximal association between DTC motivation and interpersonal stress, we used a micro-longitudinal design in which moderate to heavy drinkers reported daily on their drinking level, drinking motives and interpersonal stress for 30 days, first in college, then again approximately five years later, post-college. Our main question concerned whether nighttime drinking episodes characterized by relatively higher levels of DTC motivation, after controlling for drinking level and interpersonal stress that evening, were associated with higher levels of interpersonal stress the next day.

To better understand these processes, we examined discrete subtypes of DTC motivation given evidence that it is not a unitary construct. For example, findings indicate that individual differences in DTC with anxiety versus depressive affect are associated with divergent antecedents and outcomes (Grant et al., 2007; Mackinnon et al., 2014). At the daily level of analysis, using data from the college student wave of the present study, O’Hara et al. (2015) found that DTC-anxiety and DTC-depression were differentially related to the number of other people drinking and the gender mix of the drinking episode. Thus, in the present study, we included them separately in our predictive models.

We also examined DTC associated with anger as an additional predictor of interpersonal stress. It has been hypothesized that one of the key processes underlying the alcohol-aggression link is the degree to which AMM processes shift focus either to or away from anger (Giancola et al., 2010; Steele & Josephs, 1988). We posited that DTC with anger might raise the salience of that emotion, possibly leading to increased interpersonal conflict. This would be consistent with research showing that anger-rumination is associated with interpersonal aggression (Bushman et al., 2005). Given its key theoretical role in interpersonal conflict, we expected DTC with anger should demonstrate strongest positive association with interpersonal stress.

We also controlled for social enhancement and conformity drinking motivation, allowing us to rule out any possible confounding effects with respect to the effects of the DTC motivation subtypes. Evidence indicates that enhancement and conformity motivation are uniquely related to certain types of drinking-related problems (Merrill & Read, 2010), including interpersonal problems (Shank et al., 2020), at least at the between-person level of analysis. However, no study has examined their association with interpersonal stress at the within-person daily level of analysis. It is also possible that some drinking motivations act in a protective fashion with regard to interpersonal stress. Drinking to improve social situations or to enhance positive emotions might be related to lower levels of interpersonal stress in that they might help shift attention away from problems and help to amplify positive affective states (e.g., Fairbairn & Sayette, 2013), thus reducing the probability of reacting to provocation (e.g., Giancola et al., 2011).

Finally, by collecting the daily observations over two distal time points, not only did we increase the generalizability of our findings, it allowed us to determine if the associations of interest changed across this developmental period. Evidence suggests that DTC motivation might become more problematic as individuals progress through early adulthood (Littlefield et al., 2010; Perkins, 1999). Indeed, using the sample examined in the present study, Shank et al. (2020) showed that the effect of DTC motivation on drinking-related interpersonal problems became stronger from college to post college years; similar findings were observed for conformity motivation. However, Shank et al. examined associations between retrospectively assessed reports of individuals’ overall levels of drinking motives and related problems at each wave. Changes in these between-person associations across waves might not be informative about more dynamic daily within-person processes, which was the central focus in the present study.

2. Methods

2.1. Participants

The sample was part of a larger study of college student daily alcohol use and well-being (see Armeli et al., 2014 for details). At wave 1 we recruited 1818 college students from the psychology department subject pool and through campus-wide emails at a northeastern university. Prospective participants had to be at least 18 years of age, consumed alcohol at least twice in the previous month (measured at pre-screening) and have no previous treatment for alcohol or drug abuse. For follow up five years later we selected moderate to heavy drinkers from wave 1, defined as having at least one heavy drinking day (≥ 4 drinks for women and ≥ 5 drinks for men) in both the 30-day baseline retrospective assessment and the 30-day daily diary reporting phase, and who had graduated or were no longer working towards an undergraduate degree. Out of the 1141 participants who met these criteria, 951 participated in wave 2 (83% of the targeted sample), and 929 participants overall had daily data for analysis (i.e., not included because they did not complete the daily portion of the study or failed to reach 50% daily adherence). The final sample was 54% women, 86% White, and had a mean age of 19.2 years (SD = 1.3) at wave 1 and 24.6 years (SD = 1.3) at wave 2. Comparisons between our final sample and the remainder of the eligible 1141 showed no differences in age (p = .67). We did find significant gender (p < .01) and ethnicity (p < .01) differences such that, compared to those who participated in wave 2, those excluded were more likely to be men (62% of excluded vs. 46% of completers) and minorities (24% of excluded vs. 13% of completers).

2.2. Procedure

At both time points, individuals first logged in to a secure website where they acknowledged the informed consent process and completed an initial baseline survey. Then, approximately two weeks later, they began the daily phase in which they completed a brief (5–7 minute) internet-based survey for 30 days between 2:30 pm and 7:00 pm in wave 1 (in college) and between 4:00 pm and 8:30 pm in wave 2 (post-college). These time windows were selected to coincide with naturally occurring end of daytime responsibilities (school at wave 1; graduate school/work at wave 2), but before typical evening activities began. The daily survey included questions about interpersonal problems and alcohol use and motives for drinking that occurred the previous evening and the current day, up to reporting time. Daily diary adherence was high in both waves; for the current study, we had complete daily data on 87.6% at wave 1 and 93.2% at wave 2.

2. 3. Measures

Interpersonal stress.

Each day participants reported whether they had a “Conflict/argument with….” with (a) “friends”; (b) “boy/girlfriend, romantic other, spouse”; and (c) “others” during the previous evening and for the current day up to the reporting time. If events occurred, they were separately rated for how stressful they were on a 7-point scale (0 = “not at all stressful” to 6 = “extremely stressful”). If no events occurred, they were coded as zero (“not at all stressful”). This resulted in 3 stress ratings for both the previous evening and the current day. Composite interpersonal stress scores for the previous night and for the current day were created by averaging together the corresponding stress ratings.

Previous night’s alcohol use and drinking motives.

Each day participants reported how many drinks (responses: 0 to >15) they had in social (interacting with others) and non-social (alone; not interacting with others) contexts separately for the previous evening (i.e., after they completed the prior day’s survey). One drink was listed as “one 12-oz. can or bottle of beer, one 5-oz. glass of wine, one 12-oz. wine cooler or 1-oz. of liquor straight or in a mixed drink.” Given previous findings showing differential associations between distinct DTC subtypes and social and non-social drinking, we retained them as separate predictors.

On days when participants reported drinking, they were queried about their reasons for drinking using items created for daily administration broadly based on Cooper’s (1994) drinking motives questionnaire. Participants were asked, “Why did you drink last night?” responding to each reason using a 3-point scale (0 = no, 1 = somewhat, 2 = definitely). We assessed the following DTC motivation subtypes: DTC depression (“To feel less depressed”), DTC anxiety (“To feel less nervous”), and DTC anger (“Because I was angry”). Social (“To improve party/gathering”; “To make party/gathering more fun”), conformity (“Because my friends pressured me”; “To fit in with a group I like”) and enhancement (“To have fun”; “Because I liked the pleasant feeling”) motivations were assessed with two items each. Reliability (alphas) across wave 1 and 2, respectively, were .88 and .86 for social, .53 and .54 for conformity, and .63 and .60 for enhancement. To balance response costs, when no drinking was reported, participants were required about their reasons for not drinking.

For the main analyses, we examined the DTC anxiety, depression and anger subtypes. O’Hara et al.’s (2015) findings using data from the college wave of the current study provides evidence for the predictive validity of the single-item DTC anger item. Specifically, daily DTC anger was positively related to non-social drinking and showed a strong negative association with the prevalence of others drinking. Given the similar face validity for the DTC depression and anxiety items, we opted to use them as single-item indicators instead of using the set of items used by O’Hara et al., thus providing parallel test against the DTC anger indicator.

O’Hara et al. (2015) also provided evidence for the validity of the 2-item conformity, enhancement and social motives scales at the drinking episode level of analysis. For example, social, enhancement, and conformity motives all uniquely predicted drinks consumed in social situations (positively related), the number of others drinking during the drinking occasion (positively related), and party attendance (positively related); only social motivation predicted non-social drinking (negative association).

2.4. Data analysis

We first examined descriptive statistics and correlations among the mean levels of our daily variables. Next, we estimated 2-level (drinking days nested within persons) random-intercept multilevel models with HLM software (v6.02, Raudenbush et al. 2004). We examined two models: one predicting previous evening’s interpersonal stress and one predicting current day’s interpersonal stress. Models were estimated using restricted maximum likelihood and had the following specification. At level 1 (day-level), all models included previous evening’s drinking motives (i.e., three DTC-subtypes along with social, enhancement and conformity motives), social and non-social drinking levels, and six day of the week dummy codes (Saturday was the reference day). Motives and drinking levels were person-mean centered. We also included a study wave variable (college = 0, post college = 1). At level 2 (person-level), we included the means for all the person-mean centered level 1 predictors and a dummy code for sex (0=men, 1 = women). The model predicting current day’s interpersonal stress also included person-mean centered levels of previous evening’s interpersonal stress at level 1 and the mean nighttime stress at level 2. We reported robust (Huber-White) standard errors which provide more accurate estimates with non-normal data (Maas & Hox, 2004; Raudenbush & Bryk, 2002). For descriptive purposes, we estimated standardized coefficients using the formula provided by Hox (1995).

3. Results

Individuals had a total of 14,100 nighttime drinking occasions available for analysis (5604 at wave 1 and 8496 at wave 2), a mean of 15.2 drinking occasions (SD = 8.1) per person. Descriptive statistics and the between-person correlations for mean levels of the study variables are shown in Table 1. Of interest, mean levels of daytime and nighttime interpersonal stress were most strongly correlated with mean levels of DTC anger. In addition, mean levels of DTC anxiety, anger and depressive affect variables were highly correlated. Given the strong correlations among the DTC motive subtypes at the between-person level of analysis, we examined their within-person bi-variate correlations. Results showed weaker associations at this level of analysis: r = .18 for anger and anxiety, r = .26 for anxiety and depressive affect, and r = .45 for anger and depressive affect (all ps < .05).1

Table 1.

Descriptive statistics and correlations

M SD 1 2 3 4 5 6 7 8 9 10 11
1. Daytime interpersonal stress 0.11 0.24
2. Nighttime interpersonal stress 0.19 0.27 0.72**
3. Social drinks 4.16 1.89 −0.02 0.02
4. Nonsocial drinks 0.42 0.76 0.28** 0.23** 0.11**
5. DTC motivation composite 0.11 0.18 0.39** 0.39** 0.07* 0.22**
6. Coping Anxiety motives 0.18 0.29 0.24** 0.24** 0.10** 0.11** 0.86**
7. Coping Depression motives 0.10 0.22 0.35** 0.35** 0.02 0.24** 0.88** 0.55**
8. Coping Anger motives 0.05 0.14 0.49** 0.47** 0.03 0.27** 0.77** 0.43** 0.72**
9. Enhancement motives 1.06 0.42 −0.05 0.05 0.35** −0.03 0.19** 0.23** 0.15** 0.06
10. Conformity motives 0.13 0.21 0.30** 0.28** 0.16** 0.16** 0.62** 0.57** 0.48** 0.49** 0.17**
11. Social Motives 0.86 0.44 −0.01 0.09** 0.50** −0.01 0.27** 0.36** 0.15** 0.09** 0.66** 0.37**
12. Sex 0.54 0.50 −0.02 0.04 −0.37** −0.25** −0.01 0.00 −0.01 −0.02 0.01 −0.05 −0.07*
Open in a new tab

Note. All variables are aggregate (mean) daily variables across both waves except sex (0=men, 1 = women).

The results for the multilevel regression models are shown in Table 2. Of specific interest are the results for the level 1 (within-person) effects. Interpersonal stress was higher on evenings characterized by relatively high levels of DTC depression, DTC anger, and social motives, independent of the relative amount of alcohol consumed. Higher levels of social nighttime drinking were also related to higher levels of nighttime interpersonal stress. In addition, current day interpersonal stress was higher when the previous night was characterized by relatively higher levels of DTC anger and conformity drinking motives, controlling for previous night’s alcohol use and interpersonal stress.

Table 2.

Multilevel regression results predicting interpersonal stress

Night Interpersonal Stress Day Interpersonal Stress
Predictors B SE beta p B SE beta p
Level 2
Sex .031 .016 .058 .058 −.006 .013 −.013 .623
Mean Coping Anxiety motives .041 .036 .044 .254 .018 .025 .021 .468
Mean Coping Depression motives −.035 .080 −.028 .663 −.066 .040 −.059 .100
Mean Coping Anger motives .843 .178 .428 <.001 .334 .079 .185 <.001
Mean Enhancement motives −.017 .021 −.026 .418 −.022 .014 −.038 .127
Mean Conformity motives .084 .073 .065 .247 .073 .041 .061 .078
Mean Social Motives .027 .023 .044 .252 −.041 .019 −.074 .029
Mean social drinks −.007 .006 −.047 .239 .000 .004 −.004 .916
Mean nonsocial drinks .045 .015 .128 .004 .033 .026 .104 .204
Mean nighttime stress -- -- -- -- .631 .069 .690 <.001
Level 1
Wave −.101 .015 −.186 .000 .001 .010 .002 .919
Sunday .036 .012 .059 .004 −.001 .009 −.001 .940
Monday .010 .016 .010 .549 .027 .015 .031 .073
Tuesday −.004 .017 −.004 .826 .045 .017 .045 .010
Wednesday .058 .016 .065 .001 .036 .014 .044 .010
Thursday .038 .015 .044 .014 .019 .014 .025 .177
Friday .025 .015 .033 .086 .009 .010 .013 .406
Social drinks .005 .003 .054 .050 −.001 .002 −.008 .715
Non-social drinks .012 .006 .055 .058 .011 .005 .057 .024
Nighttime stress -- -- -- -- .291 .027 .612 <.001
Anxiety motives .006 .019 .007 .771 −.006 .013 −.009 .639
Depression motives .102 .027 .114 <.001 .017 .018 .020 .357
Anger motives .444 .048 .380 <.001 .143 .037 .134 <.001
Enhancement motives −.014 .012 −.029 .250 −.007 .010 −.015 .510
Conformity motives .037 .026 .035 .149 .084 .022 .086 <.001
Social motives .021 .011 .051 .050 .003 .008 .009 .667
Open in a new tab

Note. B = unstandardized regression coefficient; beta = standardized regression coefficient. Sex (0=men, 1= women); Wave: 0 = college, 1 = post-college. Day of the week dummy codes have Saturday as reference day.

Finally, we tested whether the associations between the DTC motive subtypes and interpersonal stress varied from college to post-college years by including wave × motive product terms in the level 1 model. We focused on the interactions for the DTC subtypes, but included the product terms for the other motives to control for their effects. None of the 6 wave × DTC motive subtype interactions was significant (ps ranging from .22 to .85).

4. Discussion

We found that nighttime episode-specific levels of drinking cope motivation, especially anger-related drinking to cope, was positively associated with concurrent and next-day levels of interpersonal stress, controlling for drinking levels. Drinking in social settings was also positively related to concurrent interpersonal stress, but not with next day’s interpersonal stress. This highlights the importance of understanding multiple aspects of drinking occasions – e.g., how much one drinks and the underlying reasons for drinking – when trying to understand the link between alcohol use and distinct types of drinking-related problems such as interpersonal problems.

Our findings are generally consistent with the alcohol myopia model which posits that alcohol use degrades information processing, causing individuals to focus on and react to salient cues in the environment, such as interpersonal conflict (Giancola et al., 2010). Our results add to this framework the utility of accounting for drinking motives. Stated in other words, although myopia-related processes occur during all drinking occasions, the underlying reasons for drinking might alter how these processes manifest in terms of behavior. Specifically, during times of increased interpersonal stress, drinking to cope with anger might increase individuals’ focus on instigator cues, thus sustaining or exacerbating anger (e.g., Bushman et al., 2005) and negative appraisals of the stressor. This process might increase the likelihood that these negative appraisals carry over into the next day, manifesting in the form of higher levels of interpersonal stress. The fact that we did not find this pattern with drinking to cope with anxiety or depressive affect might indicate that such emotions were less directly tied to interpersonal conflict or that drinking for these reasons do not focus attention as much on the underlying interpersonal problems.

Although our findings are consistent with predictions made by the alcohol myopia model, they should be interpreted with the following caveats. First, our assessment of drinking to cope with anger was not directly linked to anger stemming from concurrent interpersonal stressors and might have been associated with unrelated events. This, however, raises the possibility that drinking to cope with anger from any source could increase focus on unrelated proximal stressors, thus resulting in more negative appraisals of such events. Second, we cannot disentangle causal directions of our observed effects. One possibility is that higher levels of current day interpersonal stress resulted in greater attribution of previous night’s drinking to anger. Future studies using more fine-grained approaches, such as ecological momentary assessment, where drinking motives and stress are repeatedly sampled in real time would help to better understand these processes.

We should note that our main finding showing nighttime drinking to cope with anger related to next-day interpersonal stress had a small effect size. This might be explained by a variety of factors including the aforementioned ambiguity concerning the source of such anger. In addition, we did not assess the degree to which contextual factors, e.g., pleasant distractors in environment (e.g., Giancola et al., 2011), might have helped to distract attention away from the sources of anger. Omitted variables such as these might have introduced error variance, thus attenuating our observed effects. Finally, the weak effect could be due to the low base rate of interpersonal stressors in general and instances of drinking to cope. To address this future research might examine more at-risk samples, such as individuals involved in abusive relationships, who might show higher daily rates of interpersonal stress and alcohol use.

Regarding the other drinking motives, we found that previous evening’s conformity motivation was associated with next-day interpersonal stress. Our findings, however, are complicated by the fact that previous evening’s conformity motivation was not associated with concurrent nighttime interpersonal stress. This casts doubt on the possibility that drinking for conformity reasons elicited myopia-related processes that exacerbated concurrent stress levels resulting in a carry-over to the next day. Until replicated, we hesitate to speculate on the processes underlying this effect. We also found that social motives were positively associated with nighttime interpersonal stress – opposite to our prediction that it might act as a protective factor – but unrelated to next-day stress. One possible explanation for our finding is that social motivation was an outcome of interpersonal conflict, i.e., drinking to ease the stressful situations. Again, replication of this finding is warranted and more fine-grained assessment of motives throughout the drinking occasion would be needed to test this interpretation.

Finally, we found no evidence that the association between episode-specific levels of drinking to cope motivation and interpersonal stress varied across study wave. This finding is at odds with Shank et al.’s (2020) results showing that individual differences in drinking to cope motives were more strongly associated with mean levels of drinking-related interpersonal problems post-college compared to during college. These inconsistent patterns across level of analysis reinforces the risks associated with drawing conclusions about within-person processes from between-person associations.

Several additional limitations of our study merit mention. First, we used single-item indicators for discrete drinking motives, thus we were not able to evaluate their reliability. Low reliability was also an issue with our two-item conformity and enhancement motivation measures, thus possibly attenuating their effects on interpersonal stress. Second, our assessment of interpersonal stress focused only on conflicts and arguments. This might not have captured other possibly more prevalent types of interpersonal stress for young adults. For example, interpersonal stress can arise from one’s own mistakes or blunders in social situations, from others’ negative attitudes, or from an uncomfortable social atmosphere (Hashimoto et al., 2012). Our findings highlighting the prominent role of drinking to cope with anger, relative to other coping-related motives, might be due to our focus on conflict. Future research needs to examine other forms of interpersonal stress to better understand the roles of the distinct types of coping motives in eliciting negative consequences from drinking.

These limitations notwithstanding, our findings help to elucidate the daily processes that might link coping-related drinking, in this case drinking to cope with anger, to negative outcomes such as interpersonal stress. Future studies identifying how other coping-related drinking motives are associated with discrete types of stressors and drinking-related problems could have important implications for prevention and intervention efforts.

Highlights.

  • Drinking episode-specific levels of drinking to cope motivation are related to proximal levels interpersonal stress.

  • Drinking to cope with anger is associated with concurrent and next-day interpersonal stress, controlling for drinking level.

  • Conformity and social motives are associated interpersonal stress levels.

Acknowledgments

Statement 1: Role of Funding Sources

Funding for this study was provided by NIAAA Grants 5P60-AA003510 and 5T32-AA007290. NIAAA had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.

Footnotes

1.

The values represent Pearson correlations among the person-mean centered daily values for each DTC motive subtypes. Significance tests were calculated using HLM procedures.

Author Agreement

All authors have seen and approved the final version of this manuscript. The article is the authors’ original work, hasn’t received prior publication, and isn’t under consideration for publication elsewhere.

Author Disclosure Statements

Statement 3: Conflict of Interest

All of the authors declare that they have no conflicts of interest.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Armeli S, Covault J, & Tennen H. (2018). Long-term changes in the effects of episode-specific drinking to cope motivation on daily well-being. Psychology of Addictive Behaviors, 32(7), 715. 10.1037/adb0000409 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Armeli S, O’Hara RE, Ehrenberg E, Sullivan TP, & Tennen H, (2014) Episode-specific drinking to cope motivation, daily mood and fatigue-related symptoms among college students. Journal of Studies on Alcohol and Drugs, 75, 766–774. PMC4161697 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bolger N, & Laurenceau J-P (2013). Intensive longitudinal methods: An introduction to diary and experience sampling research. Guilford Press [Google Scholar]
  4. Bravo AJ, Pearson MR, & Henson JM (2017). Drinking to cope with depressive symptoms and ruminative thinking: A multiple mediation model among college students. Substance Use & Misuse, 52(1), 52–62. 10.1080/10826084.2016.1214151 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bravo AJ, Pilatti A, Pearson MR, Mezquita L, Ibáñez MI, & Ortet G. (2018). Depressive symptoms, ruminative thinking, drinking motives, and alcohol outcomes: A multiple mediation model among college students in three countries. Addictive Behaviors, 76, 319–327. 10.1016/j.addbeh.2017.08.028 [DOI] [PubMed] [Google Scholar]
  6. Bushman BJ, Bonacci AM, Pedersen WC, Vasquez EA, & Miller N. (2005). Chewing on It Can Chew You Up: Effects of Rumination on Triggered Displaced Aggression. Journal of Personality and Social Psychology, 88(6), 969–983. 10.1037/0022-3514.88.6.969 [DOI] [PubMed] [Google Scholar]
  7. Carey KB (1995). Heavy drinking contexts and indices of problem drinking among college students. Journal of Studies on Alcohol, 56(3), 287–292. 10.15288/jsa.1995.56.287 [DOI] [PubMed] [Google Scholar]
  8. Carrigan G, Samoluk SB, & Stewart SH (1998). Examination of the short form of the Inventory of Drinking Situations (IDS-42) in a young adult university student sample. Behaviour Research and Therapy, 36(7–8), 789–807. 10.1016/S0005-7967(98)00024-2 [DOI] [PubMed] [Google Scholar]
  9. Cooper ML (1994). Motivations for alcohol use among adolescents: Development and validation of a four-factor model. Psychological Assessment, 6(2), 117–128. 10.1037/1040-3590.6.2.117 [DOI] [Google Scholar]
  10. Cooper ML, Kuntsche E, Levitt A, Barber LL, & Wolf S. (2016). Motivational models of substance use: A review of theory and research on motives for using alcohol, marijuana, and tobacco. The Oxford handbook of substance use and substance use disorders, 1, 375–421. [Google Scholar]
  11. Dennhardt AA, Murphy JG, McDevitt-Murphy ME, & Williams JL (2016). Drinking motives mediate the relationship between alcohol reward value and alcohol problems in military veterans. Psychology of Addictive Behaviors, 30(8), 819–826. 10.1037/adb0000197 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Fairbairn CE, & Sayette MA (2013). The effect of alcohol on emotional inertia: A test of alcohol myopia. Journal of Abnormal Psychology, 122(3), 770–781. 10.1037/a0032980 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Giancola PR, Josephs RA, Parrott DJ, & Duke AA (2010). Alcohol myopia revisited: Clarifying aggression and other acts of disinhibition through a distorted lens. Perspectives on Psychological Science, 5(3), 265–278. 10.1177/1745691610369467 [DOI] [PubMed] [Google Scholar]
  14. Giancola PR, Duke AA, & Ritz KZ (2011). Alcohol, violence, and the alcohol myopia model: Preliminary findings and implications for prevention. Addictive Behaviors, 36(10), 1019–1022. 10.1016/j.addbeh.2011.05.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Grant VV, Stewart SH, O’Connor RM, Blackwell E, & Conrod PJ (2007). Psychometric evaluation of the five-factor Modified Drinking Motives Questionnaire--Revised in undergraduates. Addictive Behaviors, 32(11), 2611–2632. 10.1016/j.addbeh.2007.07.004 [DOI] [PubMed] [Google Scholar]
  16. Hammen C. (2009). Adolescent depression: Stressful interpersonal contexts and risk for recurrence. Current Directions in Psychological Science, 18(4), 200–204. 10.1111/j.1467-8721.2009.01636.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Hashimoto T, Mojaverian T, & Kim HS (2012). Culture, interpersonal stress, and psychological distress. Journal of Cross-Cultural Psychology, 43(4), 527–532. [Google Scholar]
  18. Hox J. (1995). Applied multilevel analysis. Amsterdam: TT-Publikaties. [Google Scholar]
  19. Lambe L, Mackinnon SP, & Stewart SH (2015). Dyadic conflict, drinking to cope, and alcohol-related problems: A psychometric study and longitudinal actor–partner interdependence model. Journal of Family Psychology, 29(5), 697–707. 10.1037/fam0000098.supp (Supplemental) [DOI] [PubMed] [Google Scholar]
  20. Littlefield AK, Sher KJ, & Wood PK (2010). Do changes in drinking motives mediate the relation between personality change and “maturing out” of problem drinking? Journal of Abnormal Psychology, 119(1), 93. 10.1037/a0017512 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Maas C, & Hox J, (2004). The influence of violations of assumptions on multilevel parameter estimates and their standard errors, Computational Statistics & Data Analysis, 46, 427–440. [Google Scholar]
  22. Mackinnon SP, Kehayes I-LL, Clark R, Sherry SB, & Stewart SH (2014). Testing the four-factor model of personality vulnerability to alcohol misuse: A three-wave, one-year longitudinal study. Psychology of Addictive Behaviors, 28(4), 1000–1012. 10.1037/a0037244 [DOI] [PubMed] [Google Scholar]
  23. Marlatt GA, & Gordon JR (1985). Relapse prevention: Maintenance strategies in the treatment of addictive behaviors. New York: Guilford Press. [Google Scholar]
  24. Martens MP, Neighbors C, Lewis MA, Lee CM, Oster-Aaland L, & Larimer ME (2008). The roles of negative affect and coping motives in the relationship between alcohol use and alcohol-related problems among college students. Journal of Studies on Alcohol and Drugs, 69(3), 412–419. 10.15288/jsad.2008.69.412 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Merrill JE & Read JP (2010). Motivational pathways to unique types of alcohol consequences. Psychology of Addictive Behaviors, 24(4), 705–711. 10.1037/a0020135 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. O’Hara RE, Armeli S, & Tennen H. (2015). College students’ drinking motives and social-contextual factors: Comparing associations across levels of analysis. Psychology of Addictive Behaviors, 29(2), 420–429. 10.1037/adb0000046 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Patrick ME, & Schulenberg JE (2011). How trajectories of reasons for alcohol use relate to trajectories of binge drinking: National panel data spanning late adolescence to early adulthood. Developmental Psychology, 47(2), 311. 10.1037/a0021939 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Patrick ME, Rhew IC, Lewis MA, Abdallah DA, Larimer ME, Schulenberg JE, & Lee CM (2018). Alcohol motivations and behaviors during months young adults experience social role transitions: Microtransitions in early adulthood. Psychology of Addictive Behaviors, 32(8), 895–903. 10.1037/adb0000411 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Perkins HW (1999). Stress-motivated drinking in collegiate and postcollegiate young adulthood: life course and gender patterns. Journal of Studies on Alcohol, 60(2), 219–227. 10.15288/jsa.1999.60.21. [DOI] [PubMed] [Google Scholar]
  30. Raudenbush SW, & Bryk AS (2002). Hierarchical linear models: Applications and data analysis methods. London: Sage. [Google Scholar]
  31. Raudenbush SW, Bryk AS, & Congdon R. (2004). HLM 6 for Windows [Computer software]. Lincolnwood, IL: Scientific Software International, Inc. [Google Scholar]
  32. Shank F, Armeli S, Hamilton HR, & Tennen H. (2020). Post-college changes in the association between drinking motives and drinking-related problems. Addictive Behaviors, 111. 10.1016/j.addbeh.2020.106568 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Steele CM, & Josephs RA (1990). Alcohol myopia: Its prized and dangerous effects. American Psychologist, 45(8), 921–933. 10.1037/0003-066X.45.8.921 [DOI] [PubMed] [Google Scholar]
  34. Steele CM, & Josephs RA (1988). Drinking your troubles away: II An attention-allocation model of alcohol’s effect on psychological stress. Journal of Abnormal Psychology, 97(2), 196–205. 10.1037/0021-843X.97.2.196 [DOI] [PubMed] [Google Scholar]
  35. Votaw VR, & Witkiewitz K. (2021). Motives for substance use in daily life: a systematic review of studies using ecological momentary assessment. Clinical Psychological Science. 10.1177/2167702620978614 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Vrshek-Schallhorn S, Stroud CB, Mineka S, Hammen C, Zinbarg RE, Wolitzky-Taylor K, & Craske MG (2015). Chronic and episodic interpersonal stress as statistically unique predictors of depression in two samples of emerging adults. Journal of Abnormal Psychology, 124(4), 918–932. 10.1037/abn0000088 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Witkiewitz K, & Marlatt GA (2004). Relapse Prevention for Alcohol and Drug Problems: That Was Zen, This Is Tao. American Psychologist, 59(4), 224–235. 10.1037/0003-066X.59.4.224 [DOI] [PubMed] [Google Scholar]

RESOURCES