TY - JOUR
T1 - Like to Drink: Dynamics of Liking Alcohol Posts and Effects on Alcohol Use
AU - Kurten, Sebastian
AU - Vanherle, Robyn
AU - Beullens, Kathleen
AU - Gebhardt, Winifred
AU - van den Putte, Bas
AU - Hendriks, Hanneke
PY - 2022/1/4
Y1 - 2022/1/4
N2 - Alcohol posts on social media frequently receive likes that are often perceived by emerging adults as peer approval of alcohol consumption and have been linked to their drinking intentions in previous research. This research, however, has generally not considered the fact that liking is a reciprocal behavior that differs from day to day. By conducting an app-integrated daily diary study and employing a network analytic approach, the current study contributes to this line of research by providing a better understanding of the dynamics of likes for alcohol posts and how these likes, in turn, affect emerging adults' actual alcohol use. In total, 265 college students (Mage = 20.49, SDage = 1.89, 74% female) participated in the daily diary study. They answered daily questionnaires about their alcohol use, and we monitored their online activities (posting and liking) via an app. We used exponential random graph models to predict the probability of receiving a like on a post and generalized linear mixed effect models to estimate the likelihood of participants drinking alcohol. First, the results showed that participants received, on average, more likes for alcohol posts than for non-alcohol posts (30 vs. 15 likes). Second, likes were given more often if they were reciprocal. Last, liking alcohol posts significantly predicted participants' alcohol consumption on the same day. The fact that liking alcohol posts relates to daily drinking behavior is disconcerting because one click or ‘like’ might reinforce a young person's drinking behavior on that day; hence, future research and interventions should focus more thoroughly on this worrying form of online approval.
AB - Alcohol posts on social media frequently receive likes that are often perceived by emerging adults as peer approval of alcohol consumption and have been linked to their drinking intentions in previous research. This research, however, has generally not considered the fact that liking is a reciprocal behavior that differs from day to day. By conducting an app-integrated daily diary study and employing a network analytic approach, the current study contributes to this line of research by providing a better understanding of the dynamics of likes for alcohol posts and how these likes, in turn, affect emerging adults' actual alcohol use. In total, 265 college students (Mage = 20.49, SDage = 1.89, 74% female) participated in the daily diary study. They answered daily questionnaires about their alcohol use, and we monitored their online activities (posting and liking) via an app. We used exponential random graph models to predict the probability of receiving a like on a post and generalized linear mixed effect models to estimate the likelihood of participants drinking alcohol. First, the results showed that participants received, on average, more likes for alcohol posts than for non-alcohol posts (30 vs. 15 likes). Second, likes were given more often if they were reciprocal. Last, liking alcohol posts significantly predicted participants' alcohol consumption on the same day. The fact that liking alcohol posts relates to daily drinking behavior is disconcerting because one click or ‘like’ might reinforce a young person's drinking behavior on that day; hence, future research and interventions should focus more thoroughly on this worrying form of online approval.
U2 - 10.1016/j.chb.2021.107145
DO - 10.1016/j.chb.2021.107145
M3 - Article
SN - 0747-5632
VL - 129
JO - Computers in Human Behavior
JF - Computers in Human Behavior
M1 - 107145
ER -