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Effectiveness of a social influences smoking prevention program as a function of provider type, training method, and school risk

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  • Cameron, R.
  • Brown, K.S.
  • Best, J.A.
  • Pelkman, C.L.
  • Madill, C.L.
  • Manske, S.R.
  • Payne, M.E.

Abstract

Objectives. This study determined the effect of provider (nurse or teacher) and training method (workshop or self-preparation) on outcomes of a social influences smoking prevention program. Methods. One hundred elementary schools were stratified by school risk score (high risk = high smoking rate among senior students) and assigned randomly to conditions: (1) teacher/self- preparation, (2) teacher/workshop, (3) nurse/self-preparation, (4) nurse/workshop, and (5) control. Intervention occurred in grades 6 to 8. Smoking status at the end of grade 8 was the primary endpoint variable. Results. Intervention reduced grade 8 smoking rates in high-risk schools (smoking rates of 26.9% in control vs 16.0% in intervention schools) but not in low-risk schools. There were no significant differences in outcome as a function of training method and no significant differences in outcome between teacher-provided and nurse-provided interventions in high- and medium-risk schools. Although nurses achieved better outcomes than did teachers in love- risk schools, neither provider type achieved outcomes superior to the control condition in those schools. Conclusions. Workshop training did not affect outcomes. Teachers and nurses were equally effective providers. Results suggest that programming should target high-risk schools.

Suggested Citation

  • Cameron, R. & Brown, K.S. & Best, J.A. & Pelkman, C.L. & Madill, C.L. & Manske, S.R. & Payne, M.E., 1999. "Effectiveness of a social influences smoking prevention program as a function of provider type, training method, and school risk," American Journal of Public Health, American Public Health Association, vol. 89(12), pages 1827-1831.
  • Handle: RePEc:aph:ajpbhl:1999:89:12:1827-1831_8
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    Cited by:

    1. Richard J. Cook & Jerald F. Lawless, 2020. "Failure time studies with intermittent observation and losses to follow‐up," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1035-1063, December.
    2. Richard J. Cook & Leilei Zeng & Grace Y. Yi, 2004. "Marginal Analysis of Incomplete Longitudinal Binary Data: A Cautionary Note on LOCF Imputation," Biometrics, The International Biometric Society, vol. 60(3), pages 820-828, September.
    3. Li, Haocheng & Shu, Di & He, Wenqing & Yi, Grace Y., 2019. "Variable selection via the composite likelihood method for multilevel longitudinal data with missing responses and covariates," Computational Statistics & Data Analysis, Elsevier, vol. 135(C), pages 25-34.
    4. Anindya Sen & Tony Wirjanto, 2010. "Estimating the impacts of cigarette taxes on youth smoking participation, initiation, and persistence: empirical evidence from Canada," Health Economics, John Wiley & Sons, Ltd., vol. 19(11), pages 1264-1280, November.
    5. Anindya Sen, 2009. "Estimating the impacts of household behavior on youth smoking: evidence from Ontario, Canada," Review of Economics of the Household, Springer, vol. 7(2), pages 189-218, June.

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