The association between social network members sharing alcohol-related social media content and alcohol outcomes among college student drinkers

'Black Out Rage Gallon' (aka borg): An investigation of a risky drinking trend on TikTok

ISSUE ADDRESSED

A 'Black Out Rage Gallon' (borg) is a customised, individual alcoholic beverage popularised on TikTok, whereby half the water in a gallon jug is replaced with alcohol (usually spirits), flavourings, electrolytes and caffeine. We investigated the characteristics and portrayal of the emerging alcohol trend associated with the hashtag descriptor #borg on TikTok.

METHODS

We identified highly viewed TikTok videos with the #borg hashtag (n = 103) and conducted a content analysis, capturing viewer engagement ('likes', shares, comments), techniques used, characteristics of featured individuals, and the portrayal of alcohol and risky drinking behaviours.

RESULTS

Alcohol was visible in three quarters of the videos analysed (n = 78, average amount of alcohol present 865 mL per borg) and consumed in one third of the videos (n = 34). One quarter of videos (n = 25) promoted alleged benefits of borg consumption compared to other alcohol products or approaches to drinking, yet only nine videos included a warning about potential harms.

CONCLUSIONS

The borg trend on TikTok may encourage risky drinking, by portraying it in a style that younger viewers are likely to see as fun and entertaining. SO WHAT?: We were able to gain a better understanding of how this potentially health harming activity is represented on a social media platform that is popular with young people. The speedy dissemination of this trend highlights the need to monitor, investigate and counter emerging trends. Concurrently, there is an urgent need for content restrictions to limit the visibility and promotion of risky alcohol consumption on TikTok.

Associations between frequency of exposure to peer-generated alcohol-related posts and alcohol use within a social network of college students

Peer alcohol use, commonly assessed via perceptions of how many drinks peers consume, is a robust predictor of college drinking. These perceptions are formed by in-person exposure to peer drinking but also may be affected by seeing alcohol-related content (ARC) shared on peer social media accounts. Most research assesses exposure by asking about the frequency of ARC sharing by a whole friend group, potentially missing influences from specific friends. Social network methods collect information about specific friends and their behavior but few studies have used these methods to examine the effects of ARC on drinking, nor have they examined potential moderators of this relationship. The purpose of this study was to examine whether perceived frequency of exposure to ARC shared by social network members on social media is associated with participant alcohol use after controlling for network members' self-reported alcohol use, and if participant gender and relationship qualities with network members moderate this association. Participants were 994 college students (Mage = 21.17, SD = 0.47; 61.8 % female; 55.4 % White; 12.3 % Hispanic) who completed a web-based survey. Due to the social network design, network autocorrelation analyses were conducted, which revealed that greater perceived frequency of exposure to network member ARC was significantly associated with higher alcohol quantity above and beyond network members' alcohol use. Peer ARC had a unique association with drinking behavior independent of in-person peer alcohol use, although the cross-sectional design precludes making causal inferences. Clinicians delivering alcohol interventions to college students may wish to discuss exposure to ARC as another important source of peer influence and how media literacy may help reduce the effects.

Social Network Analysis of e-Cigarette-Related Social Media Influencers on Twitter/X: Observational Study

BACKGROUND

An e-cigarette uses a battery to heat a liquid that generates an aerosol for consumers to inhale. e-Cigarette use (vaping) has been associated with respiratory disease, cardiovascular disease, and cognitive functions. Recently, vaping has become increasingly popular, especially among youth and young adults.

OBJECTIVE

The aim of this study was to understand the social networks of Twitter (now rebranded as X) influencers related to e-cigarettes through social network analysis.

METHODS

Through the Twitter streaming application programming interface, we identified 3,617,766 unique Twitter accounts posting e-cigarette-related tweets from May 3, 2021, to June 10, 2022. Among these, we identified 33 e-cigarette influencers. The followers of these influencers were grouped according to whether or not they post about e-cigarettes themselves; specifically, the former group was defined as having posted at least five e-cigarette-related tweets in the past year, whereas the latter group was defined as followers that had not posted any e-cigarette-related tweets in the past 3 years. We randomly sampled 100 user accounts among each group of e-cigarette influencer followers and created corresponding social networks for each e-cigarette influencer. We compared various network measures (eg, clustering coefficient) between the networks of the two follower groups.

RESULTS

Major topics from e-cigarette-related tweets posted by the 33 e-cigarette influencers included advocating against vaping policy (48.0%), vaping as a method to quit smoking (28.0%), and vaping product promotion (24.0%). The follower networks of these 33 influencers showed more connections for those who also post about e-cigarettes than for followers who do not post about e-cigarettes, with significantly higher clustering coefficients for the former group (0.398 vs 0.098; P=.005). Further, networks of followers who post about e-cigarettes exhibited substantially more incoming and outgoing connections than those of followers who do not post about e-cigarettes, with significantly higher in-degree (0.273 vs 0.084; P=.02), closeness (0.452 vs 0.137; P=.04), betweenness (0.036 vs 0.008; P=.001), and out-of-degree (0.097 vs 0.014; P=.02) centrality values. The followers who post about e-cigarettes also had a significantly (P<.001) higher number of followers (n=322) than that of followers who do not post about e-cigarettes (n=201). The number of tweets in the networks of followers who post about e-cigarettes was significantly higher than that in the networks of followers who do not post about e-cigarettes (93 vs 43; P<.001). Two major topics discussed in the networks of followers who post about e-cigarettes included promoting e-cigarette products or vaping activity (55.7%) and vaping being a help for smoking cessation and harm reduction (44.3%).

CONCLUSIONS

Followers of e-cigarette influencers who also post about e-cigarettes have more closely connected networks than those of followers who do not themselves post about e-cigarettes. These findings provide a potentially practical intervention approach for future antivaping campaigns.

Following social media influencers who share alcohol-related content is associated with college drinking

INTRODUCTION

Frequent exposure to peer-shared alcohol-related content (ARC) on social media is associated with greater alcohol consumption and related consequences among undergraduates. Social media influencers also share ARC; yet, the effect of exposure to influencer-shared ARC on alcohol outcomes has not been examined. The current study examined whether following influencers who share ARC and the frequency of sharing were associated with alcohol outcomes, and associations between influencer type (e.g., actors) and alcohol outcomes.

METHODS

Undergraduates (N = 528) from two universities in the United States completed an online survey assessing demographics, social media use, alcohol use and related consequences. They listed up to five influencers they followed and viewed the most content from. A series of linear regression models were conducted.

RESULTS

Having a larger proportion of influencers sharing ARC was associated with greater quantity, frequency and peak drinks, but not consequences. Frequency of influencers sharing ARC was associated with greater quantity and peak drinks, but not frequency or consequences. Findings remained significant, even after controlling for peer ARC. Actor ARC, everyday person ARC and 'other' type influencer ARC were associated with several alcohol outcomes.

DISCUSSION AND CONCLUSIONS

This study added to the literature by examining how following influencers who share ARC, and sharing frequency, were associated with drinking outcomes over and above exposure to peer ARC. It also examined whether ARC content from specific types of influencers was associated with alcohol outcomes. Findings highlight that the source of ARC is relevant when studying the effects of ARC exposure on college drinking.

Frequency and Timing of Sent and Received Alcohol-Related Text Messages: Associations with Alcohol Use and Related Consequences among Adolescents and Young Adults

Background: Research supports the notion that adolescents and young adults communicate about alcohol via text messages and that this form of communication is associated with alcohol use. However, little is known about how this compares to social media content sharing or about the timing of sending and receiving alcohol-related text messages and associations with alcohol-related outcomes. The present study aimed to 1) document whether adolescents and young adults are willing to share alcohol content via text messages they are not willing to share via social media, and 2) determine associations between frequency and timing of alcohol-related text messages (both sent and received) with self-reported alcohol use and consequences. Methods: A total of 409 participants (63.30% female; age 15-25, M = 21.10, SD = 2.69) completed a baseline survey as part of a larger study. Results: While 84.50% of participants reported that they were willing to send text messages referencing alcohol that they would not share on social media, 90.00% reported that their friends would be willing to do so. Results of negative binomial regressions indicated that sending and receiving more alcohol-related text messages per week and sending and receiving text messages before and during drinking, but not after drinking, were positively associated with typical drinks per week. Neither frequency of sending and receiving text messages or timing (before, during, after) were associated with negative consequences. Conclusions: Results suggest that frequency and timing of alcohol-related text messaging may provide insights into alcohol consumption patterns among adolescents and young adults and warrants future research.