Skip to main content

Advertisement

Log in

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

  • Original Paper
  • Published:
Prevention Science Aims and scope Submit manuscript

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adelman, H., & Taylor, L. (1997). Addressing barriers to learning: Beyond school-linked services and full-service schools. American Journal of Orthopsychiatry, 67, 408–421.

    Article  PubMed  CAS  Google Scholar 

  • Allensworth, D., & Kolbe, L. (1987). The comprehensive school health program: Exploring an expanded concept. Journal of School Health, 57, 409–412.

    PubMed  CAS  Google Scholar 

  • Battistich, V. (2000). The use of implementation data in assessing the effectiveness of the Child Development Project. Presented at the meeting of the Society for Prevention Research, June 2000, Montreal.

  • Blake, S. M., Ledsky, R. A., Sawyer, R. J., Goodenow, C., Banspach, S., Lohrmann, D. K., & Hack, T. (2005). Local school district adoption of state-recommended policies on HIV prevention education. Preventive Medicine, 440, 239–248.

    Article  Google Scholar 

  • Bosworth, K., Gingiss, P., Pothoff, S., & Roberts-Gray, C. (1999). A Bayesian model to predict the success of the implementation of health and education innovations in school-centered programs. Evaluation and Program Planning, 22(1), 1–11.

    Article  Google Scholar 

  • Bull, S. S., Gillette, C., Glasgow, R. E., & Estabrooks, P. (2003). Worksite Health Promotion Research: To What Extent Can We Generalize the Results and What is Needed to Translate Research to Practice? Health Education and Behavior, 30(5), 537–546.

    Google Scholar 

  • Centers for Disease Control and Prevention (1994). Guidelines for school health programs to prevent tobacco use and addiction. Morbidity and Mortality Weekly Reports, 43(RR-2).

  • Dane, A., & Schneider, B. (1998). Program integrity in primary and secondary prevention: Are implementation effects out of control. Clinical Psychology Review, 18, 23–45.

    Article  PubMed  CAS  Google Scholar 

  • Dusenbury, L., Brannigan, R., Falco, M., & Hansen, W. B. (2003). A review of research on fidelity of implementation: Implications for drug abuse prevention in school settings. Health Education Research, 18(2), 237–256.

    Google Scholar 

  • Elliott, D., & Mihalic, S. (2004). Issues in disseminating and replicating effective prevention programs. Prevention Science, 5, 47–53.

    Article  PubMed  Google Scholar 

  • Eslea, M., & Smith, P. (1998). The long-term effectiveness of anti-bullying work in primary schools. Educational Research, 40, 203–218.

    Google Scholar 

  • Fetro, J. (1991). Step by Step to Substance Use Prevention: The Planner's Guide to School-Based Programs. Santa Cruz, CA: Network Publications.

    Google Scholar 

  • Fullan, M. (2005). Leadership and Sustainabilitiy: System Thinkers in Action. Thousand Oaks, CA: Corwin Press.

    Google Scholar 

  • Gingiss, P. L. (1992). A developmental approach to staff development: Meeting teachers’ post-inservice needs. Journal of School Health, 62(5), 161–166.

    PubMed  CAS  Google Scholar 

  • Gingiss, P. L. (1993). Peer coaching: Building collegial support for using innovative health programs. Journal of School Health, 63(2), 82–88.

    Google Scholar 

  • Gingiss, P., & Roberts-Gray, C. (2003). Assessment of Texas School Capacity and Infrastructure for Tobacco Program Implementation Two Years After Start-Up. Houston, TX:University of Houston. http://uh.edu/hnets/TobaccoSchEval.html/.

  • Glasgow, R. E. (2002) Evaluation of Theory-Based Interventions: The RE-AIM Model. In K. Glanz, F. M. Lewis, & B. K. Rimer (Eds.), Health Behavior and Health Education: Theory, Research, and Practice (3rd edn.). San Francisco: John Wiley & Sons, pp. 531–544.

    Google Scholar 

  • Greenberg, M. (2004). Current and future challenges in school-based prevention: The researcher perspective. Prevention Science, 5(1), 5–13.

    Article  PubMed  Google Scholar 

  • Hahn, E., Noland, M., Rayens, M., & Christie, D. (2002). Efficacy of training and fidelity of implementation of the Life Skills Training Program. Journal of School Health, 72(7), 282–287.

    PubMed  Google Scholar 

  • Hall, G., & Hord, S. (1987). Change in schools: Facilitating the process. Albany, NY: State University of New York Press.

    Google Scholar 

  • Hall, G. (1992). The local educational change process and policy implementation. Journal of Research in Science Education, 29(8), 877–904.

    Google Scholar 

  • Hall, G., & Hord, S. (2001). Implementing change: Patterns, principles, and potholes. Boston: Allyn and Bacon.

    Google Scholar 

  • Johnson, K., Hays, C., Center, H., & Daley, C. (2004). Building capacity and sustainable prevention innovations: A sustainability planning model. Evaluation and Program Planning, 27(2), 135–149.

    Article  CAS  Google Scholar 

  • Kam, C., Greenberg, M., & Walls, C. (2003). Examining the role of implementation quality in school-based prevention using the PATHS curriculum. Prevention Science, 4(1), 55–63.

    Article  PubMed  Google Scholar 

  • Kumpfer, K. (2002). Prevention of alcohol and drug abuse. Journal of Substance Abuse, 23(Suppl 3), 25–44.

    Google Scholar 

  • McCormick, L., Steckler, A., & McLeroy, K. (1995). Diffusion of innovation in schools: A study of adoption and implementation of school-based tobacco prevention curricula. American Journal of Health Promotion, 9(3), 210–219.

    PubMed  CAS  Google Scholar 

  • Mihalic, S., & Irwin, K. (2003). Blueprints for violence prevention: From research to real-world settings—Factors influencing the successful replication of model programs. Youth Violence and Juvenile Justice, 1(4), 307–329.

    Article  Google Scholar 

  • Meshack, A., Hu, S., Pallonen, U., McAlister, A., Gottlieb, N., & Huang, P. (2004). Texas Tobacco Prevention Pilot Initiative: Processes and effects. Health Education Research, 19(6), 651–668.

    Article  Google Scholar 

  • Mowbray, C., Holter, C., Teague, G., & Bybee, D. (2003). Fidelity criteria: Development, measurement, and validation. American Journal of Evaluation, 24(3), 315–340.

    Google Scholar 

  • National Cancer Policy Board, Institute of Medicine and National Research Council (2000). State Programs Can Reduce Tobacco Use, 2000: 19 pages. Available to read on line http://www.nap.edu/ or obtain copies from National Cancer Policy Board, 2101 Constitution Ave NW, Washington, DC 20418.

  • Parcel, G., Taylor, W., Brink, S., Gottlieb, N., Engquist, K., O’Hara, N., & Eriksen, M. (1989). Translating theory into practice: Intervention strategies for the diffusion of health promotion innovations. Family and Community Health, 12(3), 1–13.

    Google Scholar 

  • Pentz, M. (2003). Evidence-based prevention: Characteristics, impact, and future direction. Journal of Psychoactive Drugs, 35(Special Suppl.), 143–152.

    PubMed  Google Scholar 

  • Phillips, L. (1973). Bayesian Statistics for Social Scientists. New York: Thomas Y. Crowell Company.

    Google Scholar 

  • Rhode, K., Pizacani, B., Stark, M., Pietrukowica, M., Mosbaek, C., Romoli, C., Kohn, M., & Moore, J. (August 10, 2001). Effectiveness of school-based programs as a component of a Statewide Tobacco Control Initiative—Oregon, 1999–2000. Morbidity and Mortality Weekly Reports, 50(31), 663–666.

    Google Scholar 

  • Ringwalt, C., Ennett, S., Johnson, R., Rohrbach, L., Simons-Rudolph, A., Vincus, A., & Thorne, J. (2003). Factors associated with fidelity to substance use prevention curriculum guidelines in the Nation's middle schools. Health Education and Behavior, 30(3), 375–391.

    Article  Google Scholar 

  • Roberts-Gray, C. (1985). Managing the implementation of innovations. Evaluation and Program Planning, 8, 261–269.

    Article  Google Scholar 

  • Roberts-Gray, C., Solomon, T., Gottlieb, N., & Kelsey, E. (1998). Evaluation of Heart Partners: A strategy for promoting effective diffusion of school health programs. Journal of School Health, 68(3), 106–110.

    PubMed  CAS  Google Scholar 

  • Roberts-Gray, C., & Scheirer, M. (1988). Checking the congruence between a program and its organizational environment. New Directions in Program Evaluation, 40, 63–82.

    Article  Google Scholar 

  • Rohrbach, L., Graham, J., & Hansen, W. (1993). Diffusion of a school-based substance abuse prevention program: Predictors of program implementation. Preventive Medicine, 22, 237–260.

    Article  PubMed  CAS  Google Scholar 

  • Rooney, B., & Murray, D. (1996). A meta-analysis of smoking programs after adjustment for errors in unit of analysis. Health Education Quarterly, 23, 48–64.

    PubMed  CAS  Google Scholar 

  • Scheirer, M. A. (1994). Designing and using process evaluation. In J. Wholey, H. Hatry, & K. Newcomer (Eds.), Handbook of practical program evaluation. San Francisco: Jossey-Bass.

    Google Scholar 

  • Scheirer, M. (1981). Program Implementation: The Organizational Context. Beverly Hills, CA: Sage.

    Google Scholar 

  • Steckler, A., Goodman, R., McLeroy, K., Davis, S., & Koch, G. (1992). Measuring the diffusion of innovative health promotion programs. American Journal of Health Promotion, 6(3), 214–224.

    PubMed  CAS  Google Scholar 

  • Spoth, R., Greenberg, M., Bierman, K., & Redmond, C. (2004). PROSPER Community-University Partnership model for public education systems: Capacity-building for evidence-based, competence-building prevention. Prevention Science, 5(1), 31–40.

    Article  PubMed  Google Scholar 

  • SPSS for Windows (2001). Statistical Package for the Social Sciences. Chicago: Release 11.0.1, SPSS Inc.

    Google Scholar 

  • Steps for Success Implementation (2000). Core Knowledge - Schools – How to Get Started. Available on-line www.coreknowledge.org/ CKproto2/schools/start.htm

  • Taggart, V., Bush, P., Zuckerman, A., & Theiss, P. (1990). A process evaluation of the District of Columbia “Know Your Body” Project. Journal of School Health, 60, 60–66.

    PubMed  CAS  Google Scholar 

  • Texas Department of Health (2001). Texas Tobacco Prevention Initiative: Infrastructure and baseline data. 2001. Austin, TX: Texas Department of State Health Services.

    Google Scholar 

  • Topper, A. (2000). Technological innovation in Michigan K-12 schools: “Project Implementation Success,” available on-line www.edtech. connect.msu.edu/nextday/FinalReport_PIS_htm.

  • Zollinger, T., Saywell, R., Muegge, C., Wooldridge, J., Cummings, S., & Caine, V. (2003) Impacts of the Life Skills Training curriculum on middle school students’ tobacco use in Marion County, Indiana, 1997–2000. Journal of School Health, 73(9), 338–346.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This study was conducted as part of research sponsored by the Texas Department of State Health Services (TDSHS) under contract 74660013992.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Phyllis M. Gingiss.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gingiss, P.M., Roberts-Gray, C. & Boerm, M. Bridge-It: A System for Predicting Implementation Fidelity for School-Based Tobacco Prevention Programs. Prev Sci 7, 197–207 (2006). https://doi.org/10.1007/s11121-006-0038-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11121-006-0038-1

Keywords

Navigation