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Bridge-it: a system for predicting implementation fidelity for school-based tobacco prevention programs.

Phyllis M Gingiss1, Cynthia Roberts-Gray, Melynda Boerm

  • 1Department of Health and Human Performance, University of Houston, TX, 77204-6015, USA. pmgingiss@uh.edu

Prevention Science : the Official Journal of the Society for Prevention Research
|June 23, 2006
PubMed
Summary

Implementing school programs effectively is key to reducing youth smoking rates. The Bridge-It system accurately predicts a school

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Area of Science:

  • Public Health
  • Program Implementation Science
  • Adolescent Health

Background:

  • School-based programs are crucial for preventing tobacco use and addiction.
  • Poor program implementation often leads to reduced effectiveness in preventing youth smoking.
  • Accurate prediction of implementation fidelity is needed to optimize program success.

Purpose of the Study:

  • To test the Bridge-It system for estimating the likelihood of future implementation fidelity in school-based tobacco prevention programs.
  • To assess the system's accuracy in predicting program implementation success over time.
  • To identify factors influencing successful program implementation in schools.

Main Methods:

  • Utilized baseline and two-year follow-up data from 47 middle and high schools in the Texas Tobacco Prevention Initiative.

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  • Employed the Bridge-It system, comprising an eight-factor, 36-item survey and a Bayesian model.
  • Collected data on program components, implementation support, and non-program factors.

    • Main Results:

    • The Bridge-It system's forecast of implementation fidelity was correct in 74% of cases (p < .01).
    • Model reliability was confirmed through regression analyses.
    • Baseline capacity factors (program, support, non-program) predicted follow-up implementation fidelity.

    Conclusions:

    • The Bridge-It system effectively estimates the likelihood of future implementation fidelity for school-based prevention programs.
    • Integrating such systems can enhance understanding of implementation factors and guide capacity building.
    • Early identification of schools likely to face implementation challenges allows for tailored support and resource allocation.