Evidence map›Paper›PMID 38735160›Full record

ArticleAddictive behaviors2024

Examining the social and behavioral dynamics of substance use in a longitudinal network study in rural Appalachia.

Elizabeth M Upton, Joseph LaRocca, Abby E Rudolph, April M Young, Jennifer R Havens

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Article in Addictive behaviors, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Elizabeth M UptonDepartment of Mathematics and Statistics, Williams College, Williamstown, MA, USA. Electronic address: emu1@williams.edu.
Joseph LaRoccaDepartment of Mathematics and Statistics, Williams College, Williamstown, MA, USA.
Abby E RudolphDepartment of Epidemiology and Biostatistics, Temple University College of Public Health, Philadelphia, PA, USA.
April M YoungDepartment of Epidemiology and Environmental Health, University of Kentucky College of Public Health, Lexington, KY, USA; Center on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington, KY, USA.
Jennifer R HavensCenter on Drug and Alcohol Research, Department of Behavioral Science, University of Kentucky College of Medicine, Lexington, KY, USA.

Funding

Examining the Impact of the Twin Epidemics of Methamphetamine and Opioid Use on Overdose, Risky Sex and Treatment Engagement among PWUD in Two Rural Appalachian CohortsR01DA033862 · NIDA · UNIVERSITY OF KENTUCKY · PI Jennifer R Havens · 2012 to 2026
$6.9M
Social networks and HIV risk among rural drug usersR01DA024598 · NIDA · UNIVERSITY OF KENTUCKY · PI HAVENS, JENNIFER R · 2008 to 2012
$2.6M
NIDA NIH HHS R01 DA024598NIDA NIH HHS R01 DA033862
6 · The paper itself

Abstract

backgroundPrior studies have shown that individuals and their peers often have similar substance use behaviors, but the mechanisms driving these similarities - particularly in rural settings, are not well understood. The primary objectives of this analysis are to (1) identify factors that contribute to relationship turnover and maintenance within a rural network of persons who use drugs (PWUD), (2) determine whether assimilation and/or homophily shape participants use of injection drugs, heroin, and stimulants (methamphetamine and cocaine), and (3) assess the extent that these mechanisms influence networks ties and/or behaviors and whether these effects vary across time.

methodsSociometric network data were collected from a cohort of PWUD in rural Eastern Kentucky at baseline (2008-2010) and at four follow-up visits conducted approximately semiannually. Stochastic actor-oriented models (SAOMS) were used to model network structure and participant behaviors as jointly dependent variables and to identify characteristics associated with the maintenance, dissolution, and formation of network ties and changes in drug use behaviors.

resultsFindings suggest (1) greater network stability over time for reciprocal and transitive relationships, (2) both homophily and assimilation played a greater role in shaping injection drug use (IDU) initiation and cessation than they did in shaping heroin and stimulant use, and (3) the importance of these mechanisms appeared consistent over time.

conclusionGiven the stability of particular network structures and evidence of both homophily and assimilation with respect to drug-use behaviors, interventions that leverage social networks could be used to motivate health-promoting behaviors.

Indexed as

Rural PopulationSubstance-Related DisordersAdultAppalachian RegionCocaine-Related DisordersFemaleHeroin DependenceHumansKentuckyLongitudinal StudiesMaleMiddle AgedSocial SupportSubstance Abuse, IntravenousYoung AdultAssimilationHomophilyInjection drug useSocial network analysisStochastic actor-oriented model

Identifiers

PMID38735160
PMCPMC11181469

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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.