Elsevier

Preventive Medicine

Volume 34, Issue 6, June 2002, Pages 581-589
Preventive Medicine

Regular Article
Short-Term Effects of a Randomized Computer-Based Out-of-School Smoking Prevention Trial Aimed at Elementary Schoolchildren

https://doi.org/10.1006/pmed.2002.1021Get rights and content

Abstract

Background. Smoking prevention programs usually run during school hours. In our study, an out-of-school program was developed consisting of a computer-tailored intervention aimed at the age group before school transition (11- to 12-year-old elementary schoolchildren). The aim of this study is to evaluate the additional effect of out-of-school smoking prevention.

Methods. One hundred fifty-six participating schools were randomly allocated to one of four research conditions: (a) the in-school condition, an existing seven-lesson program; (b) the out-of-school condition, three computer-tailored letters sent to the students' homes; (c) the in-school and out-of-school condition, a combined approach; (d) the control condition. Pretest and 6 months follow-up data on smoking initiation and continuation, and data on psychosocial variables were collected from 3,349 students.

Results. Control and out-of-school conditions differed regarding posttest smoking initiation (18.1 and 10.4%) and regarding posttest smoking continuation (23.5 and 13.1%). Multilevel logistic regression analyses showed positive effects regarding the out-of-school program. Significant effects were not found regarding the in-school program, nor did the combined approach show stronger effects than the single-method approaches.

Conclusions. The findings of this study suggest that smoking prevention trials for elementary schoolchildren can be effective when using out-of-school computer-tailored interventions.

References (44)

  • BR Flay et al.

    The television, school, and family smoking prevention and cessation project: VIII. Student outcomes and mediating variables

    Prev Med

    (1995)
  • A Dijkstra et al.

    Targeting smokers with low readiness to change with tailored and nontailored self-help materials

    Prev Med

    (1999)
  • Stivoro, Annual report 1996, The Hague, Dutch Foundation on Smoking and Health,...
  • De Zwart, W, Stam, H, Kuipers, S, Jeugd en riskant gedrag 1996: Roken, drinken, drugsgebruik en gokken onder scholieren...
  • PJ Bush et al.

    Alcohol, cigarette, and marijuana use among fourth-grade urban schoolchildren in 1988/89 and 1990/91

    Am J Public Health

    (1993)
  • S Kelder et al.

    Longitudinal tracking of adolescent smoking, physical activity, and food choice behaviors

    Am J Public Health

    (1994)
  • W Bruvold

    A meta-analysis of adolescent smoking prevention programs

    Am J Public Health

    (1993)
  • RI Evans et al.

    Deterring the onset of smoking in children: knowledge of immediate physiological effects and coping with peer pressure, media pressure, and parent modeling

    J Appl Social Psychol

    (1978)
  • K Conrad et al.

    Why children start smoking cigarettes: predictors of onset

    Br J Addict

    (1992)
  • J Petraitis et al.

    Reviewing theories of adolescent substance use: organizing pieces in the puzzle

    Psychologic Bull

    (1995)
  • D Nutbeam et al.

    Evaluation of two school smoking education programmes under normal classroom conditions

    Br Med J

    (1993)
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    This study was made possible by grants from the European Commission and the Dutch Cancer Foundation. This study is part of a European three-country project, called “Octopus,” in which the United Kingdom (University of Birmingham), Spain (University of Oviedo), and The Netherlands (Maastricht University) were participating. We are grateful to coproject leaders M.L. Lopes and H. Thomas and their colleagues for their cooperation in the project. We thank J. Berben for software construction, and all schools and health educators of local departments for their participation in the project.

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    To whom reprint requests should be addressed. Fax: 31-43-3671032. E-mail: [email protected].

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