COLLEGE DRINKING AND ALCOHOL-RELATED SNS POSTING 1 ...

COLLEGE DRINKING AND ALCOHOL-RELATED SNS POSTING

College students drinking and posting about drinking: Forwarding a model of motivations, behaviors, and consequences Charee M. Thompson Ohio University Lynsey K. Romo North Carolina State University Appears in Journal of Health Communication (2016)

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Abstract College drinking continues to remain a public health problem, which has been exacerbated by alcohol-related posts on social networking sites (SNSs). Although existing research has linked alcohol consumption, alcohol posts, and adverse consequences to one another, comprehensive explanations for these associations have been largely unexplored. Thus, we reasoned that students’ personal motivations (i.e., espousing an alcohol identity, needing entertainment, and adhering to social norms) influence their behaviors (i.e., alcohol consumption and alcohol-related posting on SNSs), which can lead to alcohol problems. Using structural equation modeling, we analyzed data from 364 undergraduate students and found general support for our model. In particular, espousing an alcohol identity predicted alcohol consumption and alcohol-related SNS posting; needing entertainment predicted alcohol consumption but not alcohol-related SNS posting; and adhering to social norms predicted alcohol-related SNS posting but not alcohol consumption. In turn, alcohol consumption and alcohol-related SNS posting predicted alcohol problems. Surprisingly, alcohol-related SNS posting was a stronger predictor of alcohol problems than alcohol consumption. We discuss the findings within their applied applications for college student health.


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College students’ drinking and posting about alcohol: Forwarding a model of motivations, behaviors, and consequences Alcohol is the most abused substance on campuses (Perkins, 2002), with almost half of college drinkers reporting binge drinking within the last two weeks (National Institute on Alcohol Abuse and Alcoholism, 2013). Problem drinking is associated with such negative outcomes as driving under the influence, alcohol poisoning, abuse and dependency, and death (Hingson, Zha, & Weitzman, 2009; Jennison, 2004; National Institute on Alcohol Abuse and Alcoholism, 2013). Even with these risks, approximately 76% of college students have consumed alcoholic beverages in the past year and roughly 63% have drunk alcohol in the past 30 days, with 40% getting intoxicated during that time (Johnston, O’Malley, Bachman, Schulenberg, & Miech, 2014). Social networking sites (SNSs) are also very popular among college students, as 84% of college-aged individuals use Facebook, 31% use Twitter, and 37% use Instagram (Duggan & Smith, 2014). Most college students also post drinking-related content (e.g., pictures and/or textual references to drinking) on social networking sites (e.g., Egan & Moreno, 2011; Fournier & Clarke, 2011; Moreno et al., 2010). In fact, one study uncovered alcohol references in 99% of Facebook profiles sampled (van Hoof, Bekkers, & van Vuuren, 2014). Moreover, alcohol-related posting increases over time; Pumper and Moreno (2014) found that the percentage of dependent alcohol users who posted about alcohol on Facebook doubled from 39.1% to 90.4% over the course of the first year of college. As peers generally view alcohol references positively (Beullens & Schepers, 2013), posting alcohol-related content may contribute to students’ perceptions that drinking is normative (Fournier, Hall, Ricke, & Storey, 2013) and may increase students’ likelihood of


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drinking (D’Angelo, Zhang, Eickhoff, & Moreno, 2014). Indeed, among college students posting alcohol-related content in linked to increased alcohol use and problem drinking (e.g., Moreno, Christakis, Egan, Brockman, & Becker, 2012a; Ridout, Campbell, & Ellis, 2012; Stoddard, Bauermeister, Gordon-Messer, Johns, & Zimmerman, 2012). Glassman (2012) found that students posting pictures of themselves drinking on Facebook was the strongest predictor of their self-reported alcohol consumption, controlling for demographic variables (e.g., age and sex). Importantly, because students believe displaying alcohol is an indication of use (Moreno, Grant, Kacvinsky, Egan, & Fleming, 2012b), posting alcohol-related content can influence others to drink (Stoddard et al., 2012). Litt and Stock (2011) found that viewing alcohol-related content predicts positive attitudes towards consumption and decreased perceptions of vulnerability, which prompt students to consume alcohol. Though a great deal of research demonstrates associations between alcohol consumption, alcohol-related SNS posting, and alcohol problems, what accounts for these links remains unknown. Drawing from literature on drinking and SNS usage (e.g., Real & Rimal, 2007; Rosenberg & Egbert, 2011), we posit that motivations drive both alcohol consumption and alcohol-related posting on SNSs. In turn, these behaviors are related to alcohol problems. Thus, the goal of this paper is to develop and evaluate a conceptual model that accounts for the reasons consuming alcohol and posting alcohol-related content on SNSs are associated. In doing so, we can better inform university intervention and programming efforts to target risky drinking and posting behaviors. Motivations to Consume Alcohol and Post Alcohol-related Content on SNSs Toward a more comprehensive model, we undertake two conceptual tasks in this study: first, we conceptualize alcohol consumption and alcohol-related posting on SNSs as behaviors


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that lead to alcohol problems, or adverse consequences as a result of drinking, such as alcohol dependency, conflict with others, and missed class. Previous research explores the simple relationships between these behaviors (e.g., posting is positively related to drinking) or their links to alcohol problems (together and separately). However, college drinking and posting are likely co-occurring given that alcohol may lead to disinhibition (i.e., students are more willing to post inappropriate content while under the influence; Wang et al., 2011), and SNSs may be a way for college students to coordinate and identify drinking opportunities (Lange, Devos-Comby, Moore, Daniel, & Homer, 2011; Moreno et al., 2014; Ramezani, Terdal, Pepper, & Anderson, 2014). Individuals may also receive positive feedback about alcohol on SNSs that reinforces their positive feelings about both drinking and sharing alcohol-related content (e.g., Beullens & Schepers, 2013). Moreover, individuals with a strong connection to social media may be receiving and viewing messages that influence them to drink (D’Angelo et al., 2014). For these reasons, we examine alcohol consumption and alcohol-related posting on SNSs as separate behaviors and model them as simultaneous mediators that account for the link between motivations and alcohol problems. Second, we provide a conceptual framework to account for the links between alcohol consumption, alcohol-related posting on SNSs, and alcohol problems. To inform these connections, we reviewed separate drinking and alcohol-related SNS usage literatures. Each line of research reveals similar motivations for college students’ decisions to drink and/or post about alcohol on SNSs. In particular, across the literature, students who drink and/or post on SNSs likely espouse an alcohol identity (Ridout et al., 2012), have entertainment needs (Moreno, Kota, Schoohs, & Whitehill, 2013; Vander Ven, 2011), and want to follow social norms and feel pressured by others to do so (Moreno et al., 2013; Wang et al., 2011). Thus, we include these


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motivations in our model and predict they influence alcohol consumption and alcohol-related posting on SNSs, which in turn lead to alcohol problems. Espousing Alcohol Identities College students may be motivated to enact and display an alcohol identity in the presence of their peers because they perceive drinking is a defining characteristic of their selves (Gray, LePlante, Bannon, Ambady, & Shaffer, 2011) and that drinking is central to the college experience. Alcohol identities are linked to consuming alcohol and ensuing consequences. Lindgren and colleagues (2013) found college students’ implicit associations of the words “drinker” with “me” were strong predictors of consuming and craving alcohol, as well experiencing alcohol problems. Moreover, a salient alcohol identity predicts college students’ risky drinking (Gray et al., 2011), as well as alcohol-related problems (Ridout et al., 2012). Students who self-identify with alcohol may also be more inclined to post alcohol-related content on SNSs. Considering SNSs are spaces in which individuals can create and disclose particular identities (see Walther, 2011), posting about alcohol may be a way for individuals to self-represent as a drinker, particularly within cultures where drinking is normative (i.e., college). Indeed, Litt and Stock (2011) speculate that students may even use SNSs to misrepresent themselves as a (heavier) drinker to conform to college culture. These actions may be warranted, as many students believe alcohol displays accurately portray the poster’s alcohol use (Moreno et al., 2012b) and that such posts are socially acceptable (Ridout et al., 2012). To the extent that their drinking identity is affirmed by peers through “likes” of their posts, students’ drinking and posting about alcohol on SNSs may be reinforced. Therefore:


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H1: Espousing an alcohol identity positively predicts a) consuming alcohol, and b) posting alcohol-related content on SNSs; in turn, these behaviors positively predict alcohol problems. Needing Entertainment Another influence on students’ drinking and posting about alcohol on SNSs is their need for entertainment. Many college campuses are located in rural areas, including most of the Princeton Review’s “Top 10 Party Schools” (2013). Because youth in rural areas binge drink at higher rates than those in urban areas (Gale, Lenardson, Lambert, & Hartley, 2012), college students attending universities away from urban areas may be more likely to binge drink than their peers attending urban institutions. Additionally, both qualitative and quantitative investigations have linked students’ drinking and alcohol problems to their motivations to have fun (e.g., Vander Ven, 2011; Westgate et al., 2014). Research suggests that students also satisfy entertainment needs by posting about alcohol on SNSs (Westgate et al., 2014), and though they consider others’ Facebook posts about drunken behavior (e.g., vomiting) to be inappropriate, they do not sanction these behaviors and instead view them positively (Beullens & Scheper, 2013; Wolfer, 2014). Hence, we predict students do not only drink in order to entertain themselves, but also post about their alcohol experiences because they find it entertaining to document what they (and others) perceive to be a fun memory: H2: Needing entertainment positively predicts a) consuming alcohol, and b) posting alcohol-related content on SNSs; in turn, these behaviors positively predict alcohol problems.


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Adhering to Social Norms A third motivation that may influence students’ consumption and posting of alcohol is their desire to follow social norms, an individual tendency which can become more salient when risky behaviors are involved (e.g., Santor, Messervey, & Kusumakar, 2000). Because drinking is normative on most college campuses (see Vander Ven, 2011), students in this study may feel peer pressure to drink and perceive that to be popular and fit in among their peers, they need to drink and show others they drink by posting alcohol-related comments, statuses, and photos on SNSs. College students are aware of these social norms. In fact, research suggests that students overestimate the degree to which their peers drink (Yanovitzky, Stewart, & Lederman, 2006), and studies consistently find that social norms are the best predictor of college drinking (Neighbors, Lee, Lewis, Fossos, & Larimer, 2007). College students also perceive alcoholrelated SNS use to be typical. For example, students in Beullens and Schepers’ (2013) investigation reported that 72% of pictures and 73% of their peers’ SNS messages were displayed in a positive context. In sum, research suggests that students in this study who have a tendency to follow social norms will report drinking and posting about alcohol, and consequentially experiencing alcohol problems. Thus: H3: Adhering to social norms positively predicts a) consuming alcohol, and b) posting alcohol-related content on SNSs; in turn, these behaviors positively predict alcohol problems. The hypothesized model appears in Figure 1.


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Methods Sample Following IRB approval, during the fall of 2014 we recruited 364 undergraduate students from communication courses at a medium-sized Midwestern university. To participate students needed to have an active social media account for Facebook, Instagram, or Twitter; have had an alcoholic beverage in the last month; and be at least 18 years of age (M = 19.13, SD = 1.10). Students were awarded course credit for their participation. More females (61.3%) than males (38.7%) participated, and more freshmen (47.3%) participated than sophomores (27.5%), juniors (17.0%), and seniors (8.2%). Most of the sample was Caucasian (94.2%), followed by African American (3.6%), Hispanic (1.6%), American Indian (1.4%), Asian (1.1%), and other (1.9%). Participants could choose more than one ethnicity category. Procedures After consenting to participate, individuals completed an online survey wherein we asked about their social networking site affiliations, including how long they spend on each site per day and how many connections (i.e., friends, followers, and those they follow) they had on each site. Next, we asked participants to complete a series of scales intended to measure their needs and motivations (i.e., alcohol identity, social norms, and entertainment), alcohol consumption, alcohol problems, and alcohol-related social networking site behavior. Measures Motivations. We reasoned that three salient research-based motivations would predict alcohol consumption and alcohol-related SNS posting. The first, espousing an alcohol identity, was measured using the Alcohol Self-Concept Scale (Lindgren et al., 2013). The scale consists of five items (e.g., “Drinking is a part of ‘who I am’”) on a scale of 1 = Strongly disagree to 6 =


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Strongly agree. The second, needing entertainment, was measured using the Entertainment Drive subscale of the Need for Entertainment Scale (Brock & Livingston, 2004) scale. It is comprised of 12 items (e.g., “I spend most of my free time seeking out entertainment” and “If I don’t have enough fun in the evening, I find it hard to function properly the next day”), on a scale of 1 = Extremely unlike me to 5 = Extremely like me. See Table 1 for mean, standard deviation, and reliability information for all measures. The third motivation, adhering to social norms, was modeled as a latent variable and measured using the popularity and peer pressure subscales of the Peer Pressure, Popularity, and Conformity Scale (Santor et al., 2000). The popularity subscale taps individuals’ motivations to behave in certain ways in order to be accepted by their peer group and refers to more general situations. The peer pressure subscale taps individuals’ perceptions that their college peers are urging or pushing them to do certain things and measures these perceptions more generally. We chose these subscales because they represent two important aspects of adhering to social norms: the individual’s need to belong (i.e., popularity), and the influence of others (i.e., peer pressure). The conformity subscale was excluded because it asks about obedience to teachers’ and parents’ authority and rules, which is not relevant to social norms in a college context. The popularity subscale consists of 12 items (1 = Strongly disagree to 5 = Strongly agree) that include: “I have done things to make me more popular, even when it meant doing something I would not usually do,” “At times, I’ve ignored some people in order to be more popular with others,” and “I’ve gone to parties, just to be part of the crowd.” The peer pressure subscale consists of 11 items, including: “I’ve felt pressured to get drunk at parties,” “I’ve skipped classes, when others have urged me to,” and “At times, I’ve done dangerous or foolish things because others urged me to.”


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Next we constructed a model to assess the two-factor structure (e.g., popularity and peer pressure) of the latent variable, social norms. We used AMOS 22.0 software and estimated factor loadings via maximum likelihood procedures. Given that the model had zero degrees of freedom, we assumed “perfect” model fit and further evaluated the model using the first-order factor loadings, which were .74 for peer pressure and .67 for popularity. We retained the confirmatory factor structure within the structural model tested to account for any measurement error. Alcohol consumption. Our primary outcome measure was number of drinks consumed per week. Consistent with other researchers (e.g., Fournier et al., 2013; Yanovitzky, 2006), we measured drinking behavior by asking students to reflect on the past month and report on which days they tend to consume alcohol, as well as the typical number of drinks they consume per sitting. Students reported consuming the most drinks on Saturdays (M = 6.15, SD = 4.52), followed by Friday (M = 6.56, SD = 4.16) and Thursday (M = 1.67, SD = 3.14). Alcohol-related SNS Posting. Researchers generally code students’ SNS profiles for alcohol-related content in order to measure alcohol posts. For our purposes, we had students selfreport on these behaviors and created 12 items to measure the extent to which they post about alcohol posting on SNSs. Participants responded on a scale of 1 = Never to 7 = A great deal, to the 12 items, including: “I share what I am drinking on social networking sites,” “After I have been drinking alcohol, I will post about its effects (e.g., being hungover),” “Through social networking sites, I invite others to events where there will be alcohol,” “I post pictures of others drinking alcohol on social media,” “I find out about bars’ and other establishments’ drink specials and offerings through social media,” “I check-in through social media at bars or other establishments that serve alcohol,” “I use social applications (e.g., Untappd, a social networking application that allows users log and share the beers they drink) to keep track of the alcohol I


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consume,” “I post pictures of myself drinking alcohol on social networking sites,” “I get information about events where there will be alcohol through social networking sites,” “I post about my plans to drink in the future,” “I like or follow individuals or groups that are related to alcohol,” and “I share how I feel about alcohol (e.g., I love Bud Light!).” An exploratory factor analysis using principle axis factoring and varimax rotation yielded two factors with eigenvalues greater than one. Seven items comprised the first factor, which accounted for 51.82% of the variance. All loadings for this factor were greater than .60 (and lower than .40 for the second factor). This factor, labeled “posting,” included the following items: “I share what I am drinking on social networking sites,” “After I have been drinking alcohol, I will post about its effects (e.g., being hungover).” “Through social networking sites, I invite others to events where there will be alcohol,” “I post pictures of others drinking alcohol on social media,” “I post pictures of myself drinking alcohol on social networking sites,” “I post about my plans to drink in the future,” and “I share how I feel about alcohol (e.g., I love Bud Light!).” The second factor accounted for only 9.94% of the variance and is not considered in our analyses because it does not capture alcohol posts on SNSs, the focus of the current study. Alcohol problems. Last, we measured alcohol problems using the Rutgers Alcohol Problem Index (RAPI; White & Labouvie, 2000). The RAPI consists of 23 items, on a scale of 0 = None to 3 = More than 5 times, that examine the frequency participants experience negative consequences as a result of drinking. Example items include: “Went to work or school drunk,” and “Got into fights with other people (friends, relatives, strangers).” Scores were calculated as the sum of all the items, with a maximum score of 69. Table 1 contains correlations among the variables.


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Results We used AMOS 22.0, a structural equation modeling program, to model the associations between motivations, alcohol consumption, alcohol-related posting on SNSs, and alcohol problems. A covariance matrix was constructed and used as input to AMOS to estimate parameters using maximum likelihood procedures. Four fit indices were used to assess the model’s fit, and guidelines for fit indices were chosen a priori. Specifically, the model’s chisquare should not be significant; the model’s comparative fit index (CFI) should exceed .95; and the standardized root mean square residual (SRMR), as well as the root mean square error of approximation (RMSEA), should not exceed .08. In order to estimate indirect effects (i.e., the effect of each motivation on alcohol problems through consuming alcohol and posting alcoholrelated content on SNSs), as well as their significance, we used 95% bias corrected bootstrap confidence intervals with 5000 samples (see Hayes, 2009). As the hypothesized model did not fit the data well, χ2 = 49.48, df = 8, p < .001, CFI = .93, SRMR = .06, RMSEA = .12, we followed empirically-based model trimming procedures outlined by Kline (2011) and removed paths, beginning with the least significant path. Modification indices suggested that adding a path between social norms and alcohol problems would significantly improve model fit. The final model (see Figure 2) showed good fit of the data, χ2 = 10.16, df = 9, p = .34, CFI = 1.00, SRMR = .02, RMSEA = .02, and together the variables accounted for 37.7% (p < .05, 95% CIs [.28, .48]) of the variance in alcohol problems. Moreover, motivations accounted for 19.3% (p < .05, 95% CIs [.11, .25]) of the variance in alcohol consumption and 34.8% (p < .05, 95% CIs [.23, .44]) of the variance in alcohol-related posting on SNSs.


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We found partial support for our hypotheses. H1a and H1b were supported; espousing an alcohol identity positively predicted a) consuming alcohol and b) posting alcohol-related content on SNSs. In turn, these behaviors positively predicted alcohol problems. The total indirect effect of espousing an alcohol identity (equivalent to the total effect given no direct path between espousing an alcohol identity and alcohol problems) via consuming alcohol and posting alcoholrelated content on SNSs was β = .09, p < .01, 95% CIs [.05, .17]. The model supported H2a; needing entertainment positively predicted consuming alcohol, which in turn was associated with alcohol problems. The total indirect effect (equivalent to the total effect given no direct path between needing entertainment and alcohol problems) was β = .01, p < .01, 95% CIs [.00, .03]. The model did not, however, provide support for H2b; needing entertainment did not predict posting alcohol-related content on SNSs. H3a was not supported, and H3b was partially supported; adhering to social norms did not predict consuming alcohol but did predict posting alcohol-related content on SNSs. In turn, posting alcohol-related content on SNSs positively predicted alcohol problems. The indirect effect of adhering to social norms on alcohol problems through consuming alcohol and posting alcohol-related content on SNSs was β = .09, p < .01, 95% CIs [.05, .16]. The total effect of adhering to social norms on alcohol problems was β = .53, p < .05, 95% CIs [.44, .65], including the direct effect pictured in Figure 2. Discussion Our goal was to provide explanations for, and add nuance to, our understanding of the relationships among alcohol consumption, alcohol-related posting on SNSs, and alcohol problems. We reasoned that students’ personal motivations (i.e., espousing an alcohol identity, needing entertainment, and adhering to social norms) influence their behaviors (i.e., alcohol consumption and alcohol-related posting on SNSs), which can lead to alcohol problems. We


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generally found support for our conceptual model. We discuss the findings and their implications for college drinking interventions concerning the role of SNSs. As expected, both consuming alcohol and posting alcohol-related content on SNSs positively predicted alcohol problems. These findings are consistent with research linking drinking with drinking consequences (Hingson et al., 2009; Jennison, 2004), and associating posting about alcohol on SNSs with risk behaviors and drinking consequences (e.g., Moreno et al., 2012a; Ridout et al., 2012; Stoddard et al., 2012). Interestingly, posting alcohol-related content on SNSs was a stronger predictor of alcohol problems than alcohol consumption. It may be that students are posting alcohol-related content while under the influence of alcohol (Wang et al., 2011), thereby exacerbating alcohol problems. It is also possible that online behaviors can have offline consequences; by posting about alcohol on SNSs, students could perpetuate drinking norms that encourage them and others to drink and increase their likelihood for alcohol problems (D’Angelo et al., 2014; Westgate et al., 2014). Because our data are cross-sectional, it could be that drinking students are more likely to experience alcohol problems that they recount in a future SNS posting (e.g., “Blacked out last night...”; Moreno et al., 2014, p. 91). Each of these explanations highlight the central role that SNSs play concerning alcohol problems. Turning to the motivations that influence students to both drink and post about alcohol on SNSs, we found strong support for the role espousing an alcohol identity has on both consuming alcohol and posting alcohol-related content on SNSs. Consistent with existing literature, students who believe alcohol is a salient aspect of their identity reported greater alcohol problems, likely because they both drink (Gray et al., 2011; Ridout et al., 2012) and post about alcohol on SNSs (Griffiths & Casswell, 2010; Litt & Stock, 2011). Compared to the other motivations, espousing an alcohol identity may be more explicitly tied to alcohol-related behaviors. According to


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cognitive consistency theories, students may consume alcohol and post alcohol-related content on SNSs in order to align their beliefs about who they are—a college drinker—with their behaviors and their projected image (e.g., Neumann, Leffingwell, Wagner, Mignogna, & Mignogna, 2009). This would explain why espousing an alcohol identity was strongly related to both consuming alcohol and posting alcohol-related content on SNSs. Our findings also suggest that students may be more susceptible to alcohol problems when they use alcohol as a way to meet their entertainment needs. Entertainment needs predicted how much alcohol students consumed in a week, but not reports of alcohol-related postings on SNSs. One explanation for this finding is that the scope of students’ entertainment needs may be broad and met via means other than SNSs. Research cites a core reason students drink is that they desire to have a good time (Vander Ven, 2011; Westgate et al., 2014); however, research provides a variety of reasons students post about alcohol on SNSs, including that their close friends post such content, and that posting is so habitual it becomes a kind of “involuntary action” (Wang et al., 2011, p. 6). Finally, our results show that adhering to social norms, or having a desire to belong and feeling peer pressure to engage in certain behaviors, predicts posting alcohol-related content on SNSs but not consuming alcohol. The underlying social nature of norms and SNSs may explain the association between adhering to social norms and posting alcohol-related content on SNSs. Students who are concerned about fitting in might rely on SNSs as platforms for belonging and post alcohol content to reflect their adherence to drinking norms (Wang et al., 2011). One reason social norms were not significantly related to drinking is that our measures for social norms did not reference particular peers or social groups. Theoretical explanations for the influence of social norms grounded in social identity theory would suggest that students’ drinking behavior is


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influenced by their salient group identities. For example, one study found that students are more likely to drink if they perceive drinking is normative among their close friends versus general college peers (i.e., friends closer in social distance have a stronger influence; Yanovitzky et al., 2006). Moreover, Real & Rimal’s (2007) work on the theory of normative social behavior has shown that students who believe drinking is prevalent at their university report increased intentions to drink when their peers (i.e., friends and siblings) communicate about alcohol. Students in our study may have been referencing more socially-distant peers as they completed the measures, weakening social norms’ effect on drinking. Practical Implications Our findings have several practical implications for intervention and programming efforts targeting alcohol consumption. In particular, results underscore the central role that SNSs play in helping students coordinate, advertise, facilitate, and document their drinking experiences. In turn, students’ alcohol-related SNS use may have significant consequences for their personal and professional lives. Our findings suggest that posting alcohol-related content on SNSs may have greater drinking consequences for students than actually consuming alcohol. Instead of solely focusing on reducing underage or binge drinking, our study suggests that future research and programming efforts should consider how students’ drinking occurs in tandem with other behaviors (such as posting pictures of themselves drinking) that are likely to cause them problems. Efforts should focus on curtailing student drinking or teaching students how to make smart drinking choices (e.g., as espoused by anti-binge drinking campaigns) as well as teaching students how to post “smart” and explaining alcohol-related repercussions their drinking posts can have on themselves and others. Indeed, competence models (e.g., Spitzberg, 2006) would suggest that equipping students with knowledge and teaching them skills is critical to developing


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competence in online environments, and research has found that competence can buffer against the negative effects of posting about alcohol on SNSs (Authors, 2016). Insight provided by this study’s findings can aid policymakers in developing specific interventions to target the most at-risk populations—students with strong alcohol identities—as these students were most likely to consume alcohol and post about it. Such interventions could seek to educate students about non-alcohol related ways to achieve the motivations and goals they seek via drinking and alcohol-related posts. Universities can implement programs, host events, and even develop branding that moves college cultures and students’ identities away from drinking and towards other non-drinking centered activities. Relatedly, universities can tailor programming to students’ motivations and needs in order to curtail students’ tendencies to engage in certain alcohol-related behaviors that are linked to alcohol problems. In addition to screening students for these motivations, at-risk students can also be identified through SNSs. Kacvinsky & Moreno (2014) found that resident assistants used Facebook to gauge freshmen’s mental well-being and potential alcohol problems. Accordingly, colleges could train student leaders and others in administrative positions to scan SNSs for text and photos that may be indicative of college alcohol problems. Limitations and Future Directions for Research Though this study contributes to current understandings of college drinking and alcoholrelated SNS use, it is not without limitations. First, our sample was drawn from a university known for its drinking culture; it has appeared on Princeton Review’s Top Party Schools list repeatedly. As such, some variables, particularly alcohol identity, may be more salient to our sample than students from universities less known for their drinking cultures. In the same vein, future studies could include other variables, such as sensation-seeking (e.g., Glazer, Smith, Atkin,


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& Hamel, 2010), descriptive and injunctive norms (Real & Rimal, 2007), and social motives (Westgate et al., 2014) that have been linked to drinking and SNS behavior, thereby expanding the explanatory power of the model we have developed in this study and contributing to college drinking research. Furthermore, because our data are cross-sectional, we cannot make definitive conclusions about the causal relationships among this study’s variables. For example, though we found that espousing an alcohol identity predicted posting alcohol-related content on SNSs and consequently experiencing alcohol problems, the reverse associations may be true. Students who are facing alcohol problems may share those experiences on SNSs and receive support for and validation of their alcohol identity. Future studies could employ longitudinal designs to address this limitation.


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Table 1 Means, Standard Deviations, and Correlations among the Variables M

SD

α

1. Alcohol Identity

2.35

1.49

.95

2. Entertainment Need

3.83

.68

.78

.29***

3. Popularity

2.82

1.21

.93

.29***

.22***

4. Peer Pressure

2.80

1.10

.88

.38***

.34***

.49***

5. Alcohol Consumption

14.44

11.94

--

.42***

.25***

.09

.25***

6. Alcohol SNS Posting

1.54

.69

.92

.45***

.31***

.33***

.43***

.25***

7. Alcohol Problems

28.63

6.03

--

.35***

.26***

.34***

.47***

.26***

Variable

Note: *p < .05; **p < .01; ***p