Bridge-It: A System for Predicting Implementation Fidelity for School-Based Tobacco Prevention Programs

Bridge-It: A System for Predicting Implementation Fidelity for School-Based Tobacco Prevention... Properly implemented school programs to prevent tobacco use and addiction can lower smoking prevalence up to 60%. However, numerous programs are not successful due to poor implementation. A system for estimating likelihood of future implementation fidelity of school-based prevention programs was tested using data collected at baseline and two year follow-up in 47 middle schools and high schools participating in the Texas Tobacco Prevention Initiative. The Bridge-It system includes an eight-factor, 36-item survey to analyze capacity for program implementation and a companion Bayesian model which provides estimations of likelihood of implementation fidelity several years after program initiation. The survey also asks about amount of implementing activity for each of the multiple components recommended in federal guidelines for school programs to prevent tobacco use. Criterion referenced cross-tabulations showed the system's forecast of implementation fidelity was correct in 74% of cases (p < .01). Model reliability was confirmed in regression analyses. Implementation fidelity at follow-up was predicted by the combination of the model's eight capacity factors at baseline. It includes program, implementation support, and non-program factors. Integration of the Bridge-It system, or comparable tools, into the dissemination and evaluation of school-based prevention programs can help to increase understanding of factors that influence implementation and provide guidance for capacity building. If administrators can identify at baseline schools likely to fall short of implementation goals, plans for resource allocation and provision of guidance, training, and technical assistance can be specifically tailored to identified needs. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Prevention Science Springer Journals

Bridge-It: A System for Predicting Implementation Fidelity for School-Based Tobacco Prevention Programs

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Publisher
Springer US
Copyright
Copyright © 2006 by Society for Prevention Research
Subject
Medicine & Public Health; Public Health; Health Psychology; Child and School Psychology
ISSN
1389-4986
eISSN
1573-6695
D.O.I.
10.1007/s11121-006-0038-1
Publisher site
See Article on Publisher Site

Abstract

Properly implemented school programs to prevent tobacco use and addiction can lower smoking prevalence up to 60%. However, numerous programs are not successful due to poor implementation. A system for estimating likelihood of future implementation fidelity of school-based prevention programs was tested using data collected at baseline and two year follow-up in 47 middle schools and high schools participating in the Texas Tobacco Prevention Initiative. The Bridge-It system includes an eight-factor, 36-item survey to analyze capacity for program implementation and a companion Bayesian model which provides estimations of likelihood of implementation fidelity several years after program initiation. The survey also asks about amount of implementing activity for each of the multiple components recommended in federal guidelines for school programs to prevent tobacco use. Criterion referenced cross-tabulations showed the system's forecast of implementation fidelity was correct in 74% of cases (p < .01). Model reliability was confirmed in regression analyses. Implementation fidelity at follow-up was predicted by the combination of the model's eight capacity factors at baseline. It includes program, implementation support, and non-program factors. Integration of the Bridge-It system, or comparable tools, into the dissemination and evaluation of school-based prevention programs can help to increase understanding of factors that influence implementation and provide guidance for capacity building. If administrators can identify at baseline schools likely to fall short of implementation goals, plans for resource allocation and provision of guidance, training, and technical assistance can be specifically tailored to identified needs.

Journal

Prevention ScienceSpringer Journals

Published: May 23, 2006

References

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