Evidence map›Paper›PMID 25222849›Full record

ArticleAddictive behaviors2015

Replicating cluster subtypes for the prevention of adolescent smoking and alcohol use.

Steven F Babbin, Wayne F Velicer, Andrea L Paiva, Leslie Ann D Brick, Colleen A Redding

Abstract read
In one paragraph

Article in Addictive behaviors, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. The reliability and validity of the Temptations to Try Smoking Scale in a group of Chinese adolescents.Psicologia, reflexao e critica : revista semestral do Departamento de Psicologia da UFRGS · 2023
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Sun Protection Belief Clusters: Analysis of Amazon Mechanical Turk Data.Journal of cancer education : the official journal of the American Association for Cancer Education · 2016
    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.

Steven F BabbinDepartment of Psychiatry, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
Wayne F VelicerCancer Prevention Research Center, University of Rhode Island, Kingston, RI, USA. Electronic address: velicer@uri.edu.
Andrea L PaivaCancer Prevention Research Center, University of Rhode Island, Kingston, RI, USA.
Leslie Ann D BrickCancer Prevention Research Center, University of Rhode Island, Kingston, RI, USA.
Colleen A ReddingCancer Prevention Research Center, University of Rhode Island, Kingston, RI, USA.

Funding

Behavioral Treatment of Adolescent Marijuana UseR01DA015186 · NIDA · UNIV OF ARKANSAS FOR MED SCIS · PI BUDNEY, ALAN JEFFREY · 2002 to 2017
$7.7M
Training in the Science of Co-Occurring DisordersT32DA037202 · NIDA · DARTMOUTH COLLEGE · PI Lisa A. Marsch · 2014 to 2026
$4.7M
Tailored Interventions to Prevent Substance AbuseR01DA020112 · NIDA · UNIVERSITY OF RHODE ISLAND · PI VELICER, WAYNE F · 2006 to 2010
$2.9M
NIDA NIH HHS DA020112NIDA NIH HHS R01 DA015186NIDA NIH HHS R01 DA020112NIDA NIH HHS T32 DA037202
6 · The paper itself

Abstract

introductionSubstance 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.

methodsAnalyses 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.

resultsAcross 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).

conclusionsFinding 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.

Indexed as

Attitude to HealthAdolescentAdolescent BehaviorAlcohol DrinkingChildCluster AnalysisFemaleHumansMaleMotivationReproducibility of ResultsSmokingSmoking PreventionAlcohol acquisitionCluster analysisPreventionSmoking acquisition

Identifiers

PMID25222849
PMCPMC4450721

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Registered trials

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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.