Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use. (January 2015)

• Record Type: Journal Article
• Authors: Babbin, Steven F.; Velicer, Wayne F.; Paiva, Andrea L.; Brick, Leslie Ann D.; Redding, Colleen A.
• Is Part Of: Addictive behaviors. Volume 40(2015)
• Page Start: 57
• Page End: 65
• Publication Date: 2015-01
• Subjects: Cluster analysis -- Prevention -- Alcohol acquisition -- Smoking acquisition; Substance abuse -- Periodicals; Alcoholism -- Periodicals; Drug addiction -- Periodicals; Nicotine addiction -- Periodicals; Smoking -- Periodicals; Gambling -- Psychological aspects -- Periodicals; Electronic journals; 362.29
• DOI: 10.1016/j.addbeh.2014.09.001
• Languages: English
• ISSNs: 0306-4603

Abstract

Abstract: Introduction: Substance abuse interventions tailored to the individual level have produced effective outcomes for a wide variety of behaviors. One approach to enhancing tailoring involves using cluster analysis to identify prevention subtypes that represent different attitudes about substance use. This study applied this approach to better understand tailored interventions for smoking and alcohol prevention. Methods: Analyses were performed on a sample of sixth graders from 20 New England middle schools involved in a 36-month tailored intervention study. Most adolescents reported being in the Acquisition Precontemplation (aPC) stage at baseline: not smoking or not drinking and not planning to start in the next six months. For smoking (N = 4059) and alcohol (N = 3973), each sample was randomly split into five subsamples. Cluster analysis was performed within each subsample based on three variables: Pros and Cons (from Decisional Balance Scales), and Situational Temptations. Results: Across all subsamples for both smoking and alcohol, the following four clusters were identified: (1) Most Protected (MP; low Pros, high Cons, low Temptations); (2) Ambivalent (AM; high Pros, average Cons and Temptations); (3) Risk Denial (RD; average Pros, low Cons, average Temptations); and (4) High Risk (HR; high Pros, low Cons, and very high Temptations). Conclusions: Finding the same four clusters within aPC for both smoking and alcohol, replicating the results across the five subsamples, and demonstrating hypothesized relations among the clusters with additional external validity analyses provide strong evidence of the robustness of these results. These clusters demonstrate evidence of validity and can provide a basis for tailoring interventions. Highlights: Most adolescents report not smoking or drinking and not planning to start. Cluster analysis was utilized to better understand attitudes about substance use. Four subtypes were found: Most Protected, Ambivalent, Risk Denial, and High Risk. These clusters replicated across subsamples for both smoking and alcohol. These subtypes can provide a basis for tailoring interventions.