Peer associations for substance use and exercise in a college student social network.

Barnett, Nancy P.; Ott, Miles Q.; Rogers, Michelle L.; Loxley, Michelle P.; Linkletter, Crystal D.; Clark, Melissa A.

doi:10.1037/a0034687

Cited by 62 publications

(77 citation statements)

References 44 publications

(59 reference statements)

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“…The majority of studies have focused on alcohol use, with a few focused on combined alcohol and marijuana, tobacco, and gambling behaviors [26, 27, 28, 29] , and one study focused on non-medical use of prescription drugs [30]. Five studies focused on the general college population, with two studies focused on college students in residence halls [26, 31]), two studies focused on mandated college students [32, 33], one study comparing students in a psychology and engineering program [34], two studies focused specifically on fraternities and sororities [29, 35] and one study focused only on female college students [36].…”

Section: Resultsmentioning

confidence: 99%

“…Five studies focused on the general college population, with two studies focused on college students in residence halls [26, 31]), two studies focused on mandated college students [32, 33], one study comparing students in a psychology and engineering program [34], two studies focused specifically on fraternities and sororities [29, 35] and one study focused only on female college students [36]. …”

Section: Resultsmentioning

confidence: 99%

“…The majority of studies were based on a personal network design, with three studies requiring students to nominate important people within a whole network [26, 29, 31]. The studies that focused on students in the psychology and engineering programs and fraternities and sororities were naturally whole network designs [34, 35].…”

Section: Resultsmentioning

confidence: 99%

“…Studies that examined other metrics of social network influence found that being more central, having more reciprocated ties, and being in more tightly interconnected networks were associated with increased alcohol use in particular [29, 31, 34, 35, 36]. Moreover, two studies found that even within networks, clusters of individuals can be identified and vary in type of behavior and level of use or involvement [26, 28]. …”

Section: Resultsmentioning

confidence: 99%

“…For instance, studies asked participants to report on networks of various sizes ranging from three close peers [27] to entire Facebook networks [36]. In addition, studies that assessed egocentric networks asked participants to think of and define their social networks in a variety of ways, including listing important people [26, 31, 32, 33], close friends [27, 30, 38], close friends on campus [33], individuals that have had the most impact [28], and best friends, family members, co-workers, etc. [28, 37].…”

Section: Gaps Limitations and Controversiesmentioning

confidence: 99%

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Social Network Factors and Addictive Behaviors Among College Students

2016

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Purpose of the review To provide an overview of studies within the past five years examining the impact of social network factors on addictive behaviors among college students, to discuss gaps, limitations, and controversies in the field, and to summarize with a discussion of future directions and implications for interventions. Recent findings A review of 13 studies indicated that greater network exposure, centrality, reciprocated ties, and more tightly interconnected networks were associated with greater alcohol use and other addictive behaviors among college students. Summary Greater research is needed that expands beyond alcohol use to other addictive behaviors among college students. Additionally, more studies are needed that longitudinally study the impact of changes in social networks on addictive behaviors and vice versa, as well as studies examining sociocentric (whole) networks. Social network approaches offer innovative perspectives in understanding social influences on addictive behaviors and novel intervention strategies for potentially reducing addictive behaviors among college students.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Gaps Limitations and Controversiesmentioning

confidence: 99%

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Social Network Factors and Addictive Behaviors Among College Students

2016

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Bayesian Peer Calibration with Application to Alcohol Use

Ott

Hogan

Gile

et al. 2016

Statistics in Medicine

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Peers are often able to provide important additional information to supplement self-reported behavioral measures. The study motivating this work collected data on alcohol in a social network formed by college students living in a freshman dormitory. By using two imperfect sources of information (self-reported and peer-reported alcohol consumption), rather than solely self-reports or peer-reports, we are able to gain insight into alcohol consumption on both the population and the individual level, as well as information on the discrepancy of individual peer-reports. We develop a novel Bayesian comparative calibration model for continuous, count and binary outcomes that uses covariate information to characterize the joint distribution of both self and peer-reports on the network for estimating peer-reporting discrepancies in network surveys, and apply this to the data for fully Bayesian inference. We use this model to understand the effects of covariates on both drinking behavior and peer-reporting discrepancies.

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