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Article: Project INTEGRATE: An integrative study of brief alcohol interventions for college students

TitleProject INTEGRATE: An integrative study of brief alcohol interventions for college students
Authors
KeywordsAlcohol interventions
Issue Date2015
Citation
Psychology of Addictive Behaviors, 2015, v. 29, n. 1, p. 34-48 How to Cite?
Abstract© 2014 American Psychological Association.This article provides an overview of a study that synthesizes multiple, independently collected alcohol intervention studies for college students into a single, multisite longitudinal data set. This research embraced innovative analytic strategies (i.e., integrative data analysis or meta-analysis using individual participant-level data), with the overall goal of answering research questions that are difficult to address in individual studies such as moderation analysis, while providing a built-in replication for the reported efficacy of brief motivational interventions for college students. Data were pooled across 24 intervention studies, of which 21 included a comparison or control condition and all included one or more treatment conditions. This yielded a sample of 12,630 participants (42% men; 58% first-year or incoming students). The majority of the sample identified as White (74%), with 12% Asian, 7% Hispanic, 2% Black, and 5% other/mixed ethnic groups. Participants were assessed 2 or more times from baseline up to 12 months, with varying assessment schedules across studies. This article describes how we combined individual participant-level data from multiple studies, and discusses the steps taken to develop commensurate measures across studies via harmonization and newly developed Markov chain Monte Carlo (MCMC) algorithms for 2-parameter logistic item response theory models and a generalized partial credit model. This innovative approach has intriguing promises, but significant barriers exist. To lower the barriers, there is a need to increase overlap in measures and timing of follow-up assessments across studies, better define treatment and control groups, and improve transparency and documentation in future single intervention studies.
Persistent Identifierhttp://hdl.handle.net/10722/228227
ISSN
2015 Impact Factor: 2.78
2015 SCImago Journal Rankings: 1.591

 

DC FieldValueLanguage
dc.contributor.authorMun, Eun Young-
dc.contributor.authorDe La Torre, Jimmy-
dc.contributor.authorAtkins, David C.-
dc.contributor.authorWhite, Helene R.-
dc.contributor.authorRay, Anne E.-
dc.contributor.authorKim, Su Young-
dc.contributor.authorJiao, Yang-
dc.contributor.authorClarke, Nickeisha-
dc.contributor.authorHuo, Yan-
dc.contributor.authorLarimer, Mary E.-
dc.contributor.authorHuh, David-
dc.date.accessioned2016-08-01T06:45:30Z-
dc.date.available2016-08-01T06:45:30Z-
dc.date.issued2015-
dc.identifier.citationPsychology of Addictive Behaviors, 2015, v. 29, n. 1, p. 34-48-
dc.identifier.issn0893-164X-
dc.identifier.urihttp://hdl.handle.net/10722/228227-
dc.description.abstract© 2014 American Psychological Association.This article provides an overview of a study that synthesizes multiple, independently collected alcohol intervention studies for college students into a single, multisite longitudinal data set. This research embraced innovative analytic strategies (i.e., integrative data analysis or meta-analysis using individual participant-level data), with the overall goal of answering research questions that are difficult to address in individual studies such as moderation analysis, while providing a built-in replication for the reported efficacy of brief motivational interventions for college students. Data were pooled across 24 intervention studies, of which 21 included a comparison or control condition and all included one or more treatment conditions. This yielded a sample of 12,630 participants (42% men; 58% first-year or incoming students). The majority of the sample identified as White (74%), with 12% Asian, 7% Hispanic, 2% Black, and 5% other/mixed ethnic groups. Participants were assessed 2 or more times from baseline up to 12 months, with varying assessment schedules across studies. This article describes how we combined individual participant-level data from multiple studies, and discusses the steps taken to develop commensurate measures across studies via harmonization and newly developed Markov chain Monte Carlo (MCMC) algorithms for 2-parameter logistic item response theory models and a generalized partial credit model. This innovative approach has intriguing promises, but significant barriers exist. To lower the barriers, there is a need to increase overlap in measures and timing of follow-up assessments across studies, better define treatment and control groups, and improve transparency and documentation in future single intervention studies.-
dc.languageeng-
dc.relation.ispartofPsychology of Addictive Behaviors-
dc.subjectAlcohol interventions-
dc.titleProject INTEGRATE: An integrative study of brief alcohol interventions for college students-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.1037/adb0000047-
dc.identifier.scopuseid_2-s2.0-84941187680-
dc.identifier.volume29-
dc.identifier.issue1-
dc.identifier.spage34-
dc.identifier.epage48-
dc.identifier.eissn1939-1501-

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