Evidence map›Paper›PMID 28921997›Full record

ArticlePsychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors2017

Simulating drinking in social networks to inform alcohol prevention and treatment efforts.

Kevin A Hallgren, Barbara S McCrady, Thomas P Caudell, Katie Witkiewitz, J Scott Tonigan

Open access · hybridAbstract read
In one paragraph

Article in Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Social Influence and Problematic Drinking: Insights from the COVID-19 Pandemic.Clinical psychological science : a journal of the Association for Psychological Science · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Do alcohol interventions affect peers who do not receive the intervention? Modeling treatment contagion effects via simulations of adolescent social networks.Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors · 2021
    Article
  8. Individual Variables Involved in Perceived Pressure for Adolescent Drinking.International journal of environmental research and public health · 2020
    Article
  9. Article
  10. Article
  11. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 2 institutions in 1 country.

Kevin A HallgrenDepartment of Psychiatry and Behavioral Sciences, University of Washington.
Barbara S McCradyCenter on Alcoholism, Substance Abuse, and Addictions, University of New Mexico.
Thomas P CaudellDepartment of Electrical and Computer Engineering, University of New Mexico.
Katie WitkiewitzCenter on Alcoholism, Substance Abuse, and Addictions, University of New Mexico.
J Scott ToniganCenter on Alcoholism, Substance Abuse, and Addictions, University of New Mexico.
University of New Mexico · USUniversity of Washington · US

Funding

Developing a tool to assess, provide feedback, and facilitate discussion of mechanisms of change in frontline addiction treatmentK01AA024796 · NIAAA · UNIVERSITY OF WASHINGTON · PI HALLGREN, KEVIN A. · 2016 to 2020
$870k
Targeting social networks to maximize alcohol use disorder treatment & preventionF31AA021031 · NIAAA · UNIVERSITY OF NEW MEXICO · PI HALLGREN, KEVIN A. · 2011 to 2013
$55k
National Institutes of Health; National Institute on Alcoholism and Alcohol AbuseNIAAA NIH HHS F31 AA021031NIAAA NIH HHS K01 AA024796
6 · The paper itself

Abstract

Adolescent drinking influences, and is influenced by, peer alcohol use. Several efficacious adolescent alcohol interventions include elements aimed at reducing susceptibility to peer influence. Modeling these interventions within dynamically changing social networks may improve our understanding of how such interventions work and for whom they work best. We used stochastic actor-based models to simulate longitudinal drinking and friendship formation within social networks using parameters obtained from a meta-analysis of real-world 10th grade adolescent social networks. Levels of social influence (i.e., friends affecting changes in one's drinking) and social selection (i.e., drinking affecting changes in one's friendships) were manipulated at several levels, which directly impacted the degree of clustering in friendships based on similarity in drinking behavior. Midway through each simulation, one randomly selected heavy-drinking actor from each network received an "intervention" that either (a) reduced their susceptibility to social influence, (b) reduced their susceptibility to social selection, (c) eliminated a friendship with a heavy drinker, or (d) initiated a friendship with a nondrinker. Only the intervention that eliminated targeted actors' susceptibility to social influence consistently reduced that actor's drinking. Moreover, this was only effective in networks with social influence and social selection that were at higher levels than what was found in the real-world reference study. Social influence and social selection are dynamic processes that can lead to complex systems that may moderate the effectiveness of network-based interventions. Interventions that reduce susceptibility to social influence may be most effective among adolescents with high susceptibility to social influence and heavier-drinking friends. (PsycINFO Database Record

Indexed as

Peer GroupPeer InfluenceAdolescentAlcohol DrinkingAlcoholic IntoxicationFemaleFriendsHumansLongitudinal StudiesMaleModels, PsychologicalSocial SupportUnderage Drinking

Identifiers

PMID28921997
PMCPMC5690806
OpenAlexW2755725511

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.