Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
Prevention Science
Published in: Prevention Science 1/2015

01-01-2015

The Process of Adoption of Evidence-based Tobacco Use Prevention Programs in California Schools

Authors: Melissa A. Little, Pallav Pokhrel, Steve Sussman, Louise Ann Rohrbach

Published in: Prevention Science | Issue 1/2015

Login to get access

Abstract

Although there are a number of research-validated substance use prevention programs available for wide-scale dissemination, very little is known about the factors that influence adoption of evidence-based prevention programs in schools. We tested a model of the mechanisms of program adoption in schools that was guided by diffusion of innovations and social ecological theories. Cross-sectional data were collected from a sample of school district and county office of education tobacco use prevention education coordinators throughout California. Structural equation modeling was used to test the effects of community and organizational variables on the adoption of prevention programs via school administrators’ beliefs and the organization’s receipt of funding for the program. Results supported the hypothesis that the process of adoption begins with forming beliefs about the program, leading to adoption through the receipt of funding. In addition, we found direct effects of various community- and organizational-level factors on beliefs, receipt of funding, and adoption. These results are likely to inform policies that affect school districts’ use of evidence-based substance use prevention programming, which should ultimately lead to reductions in negative health outcomes among adolescents. Specifically, this study identifies various factors that could be targeted for improvement to enhance evidence-based program adoption. To our knowledge, this is the first study to empirically elucidate the process of adoption of evidence-based tobacco prevention programs in schools.
Literature
Beets, M., Flay, B., Vuchinich, S., Acock, A., Li, K.-K., & Allred, C. (2008). School climate and teachers’ beliefs and attitudes associated with implementation of the Positive Action program: A diffusion of innovations model. Prevention Science, 9, 264–275.CrossRefPubMed
Bentler, P. M. (2007). On tests and indices for evaluating structural models. Personality and Individual Differences, 42, 825–829.CrossRef
Blake, S. M., Ledsky, R. A., Sawyer, R. J., Goodenow, C., Banspach, S., Lohrmann, D. K., et al. (2005). Local school district adoption of state-recommended policies on HIV prevention education. Preventive Medicine: An International Journal Devoted to Practice and Theory, 40, 239–248.CrossRef
California Department of Education. (2001). Getting results: Developing safe and healthy kids update 2. Sacramento: Healthy Kids Program Office, California Department of Education.
California Department of Education. (2011b). Tobacco Use Prevention Education (TUPE) competitive grant applicants. Sacramento: Prepared by the Safe and Healthy Kids Program Office, California Department of Education.
Center for Substance Abuse Prevention. (2009). Identifying and selecting evidence-based interventions revised guidance document for the strategic prevention framework state incentive grant program. HHS Pub. No. (SMA)09-4205. Rockville, MD: Center for Substance Abuse Prevention, Substance Abuse and Mental Health Services Administration.
Cho, H., Hallfors, D. D., Iritani, B. J., & Hartman, S. (2009). The influence of “No Child Left Behind” legislation on drug prevention in US schools. Evaluation Review, 33, 446–463.CrossRefPubMed
Coburn, C., Toure, J., & Yamashita, M. (2009). Evidence, interpretation, and persuasion: Instructional decision making at the district central office. Teachers College Record, 111, 1115–1161.
Durlak, J., & DuPre, E. (2008). Implementation matters: A review of research on the influence of implementation on program outcomes and the factors affecting implementation. American Journal of Community Psychology, 41, 327–350.CrossRefPubMed
Ellickson, P. L. (1995). Schools. In R. H. Coombs & D. Ziedonis (Eds.), Handbook on drug abuse prevention: A comprehensive strategy to prevent the abuse of alcohol and other drugs (pp. 93–120). Needham Heights: Ally & Bacon.
Ennett, S. T., Ringwalt, C. L., Thorne, J., Rohrbach, L. A., Vincus, A., Simons-Rudolph, A., et al. (2003). A comparison of current practice in school-based substance use prevention programs with meta-analysis findings. Prevention Science, 4, 1–14.CrossRefPubMed
Estabrooks, P. A., & Glasgow, R. E. (2006). Translating effective clinic-based physical activity interventions into practice. American Journal of Preventive Medicine, 31, 45–56.CrossRef
Fagan, A. A., & Mihalic, S. (2003). Strategies for enhancing the adoption of school-based prevention programs: Lessons learned from the blueprints for violence prevention replications of the Life Skills Training program. Journal of Community Psychology, 31, 235–253.CrossRef
Fagan, A. A., Hanson, K., Hawkins, J. D., & Arthur, M. W. (2008). Bridging science to practice: Achieving prevention program implementation fidelity in the community youth development study. American Journal of Community Psychology, 41, 235–249.CrossRefPubMed
Flay, B. R., Biglan, A., Boruch, R. F., Castro, F. G., Gottfredson, D., Kellam, S., et al. (2005). Standards of evidence: Criteria for efficacy, effectiveness, and dissemination. Prevention Science, 6, 151–175.CrossRefPubMed
Ginexi, E., Mabry, P., Collins, L., Rivera, D., Ridenour, T., Valente, T., et al. (2010). Systems science methodology for prevention science. Paper presented at the Society for Prevention Research 18th Annual Meeting, Denver, Colorado.
Gingiss, P. M., Roberts-Gray, C., & Boerm, M. (2006). Bridge-It: A system for predicting implementation fidelity for school-based tobacco prevention programs. Prevention Science, 7, 197–207.CrossRefPubMed
Green, L. W., & Glasgow, R. E. (2006). Evaluating the relevance, generalization, and applicability of research: Issues in external validation and translation methodology. Evaluation and the Health Professions, 29, 126–153.CrossRefPubMed
Greenberg, M. T. (2010). School-based prevention: Current status and future challenges. Effective Education, 2, 27–52.CrossRef
Gregory, A., Henry, D. B., & Schoeny, M. E. (2007). School climate and implementation of a preventive intervention. American Journal of Community Psychology, 40, 250–260.CrossRefPubMed
Hallfors, D., & Godette, D. (2002). Will the ‘Principles of Effectiveness’ improve prevention practice? Early findings from a diffusion study. Health Education Research, 17, 461–470.CrossRefPubMed
Ho, R. (2006). Handbook of univariate and multivariate data analysis and interpretation with SPSS. New York: Chapman and Hall/VRV, Taylor & Francis Group.CrossRef
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1–55.CrossRef
Kreuter, M. W., & Bernhardt, J. M. (2009). Reframing the dissemination challenge: A marketing and distribution perspective. American Journal of Public Health, 99, 2123–2127.PubMedCentralCrossRefPubMed
Mihalic, S., Fagan, A., & Argamaso, S. (2008). Implementing the Life Skills Training drug prevention program: Factors related to implementation fidelity. Implementation Science, 3, 5.PubMedCentralCrossRefPubMed
Muthén, L. K., & Muthén, B. O. (1998–2012). Mplus: User’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
National Research Council and Institute of Medicine. (2009). Preventing mental, emotional, and behavioral disorders among young people: Progress and possibilities. In M. E. O’Connell, T. Boat, & K. E. Warner (Eds.), Committee on the prevention of mental disorders and substance abuse among children, youth, and young adults: Research advances and promising interventions. Washington: The National Academies Press.
Payne, A. A., Gottfredson, D. C., & Gottfredson, G. D. (2006). School predictors of the intensity of implementation of school-based prevention programs: Results from a national study. Prevention Science, 7, 225–237.CrossRefPubMed
Quality Education Direct Inc. (2009). QED California district 2008 database: Data users guide. Denver: Quality Education Direct Inc.
Ringwalt, C. L., Ennett, S., Vincus, A., Thorne, J., Rohrbach, L. A., & Simons-Rudolph, A. (2002). The prevalence of effective substance use prevention curricula in US middle schools. Prevention Science, 3, 257–265.CrossRefPubMed
Ringwalt, C., Hanley, S., Vincus, A., Ennett, S., Rohrbach, L., & Bowling, J. (2008). The prevalence of effective substance use prevention curricula in the nation’s high schools. Journal of Primary Prevention, 29, 479–488.PubMedCentralCrossRefPubMed
Roberts-Gray, C., Gingiss, P. M., & Boerm, M. (2007). Evaluating school capacity to implement new programs. Evaluation and Program Planning, 30, 247–257.CrossRefPubMed
Rogers, E. M. (1983). Diffusion of innovations (2nd ed.). New York: The Free Press.
Rohrbach, L. A., Howard-Pitney, B., Unger, J. B., Dent, C. W., Howard, K. A., Cruz, T. B., et al. (2002). Independent evaluation of the California tobacco control program: Relationships between program exposure and outcomes, 1996–1998. American Journal of Public Health, 92, 975–984.PubMedCentralCrossRefPubMed
Rohrbach, L. A., Ringwalt, C. L., Ennett, S. T., & Vincus, A. A. (2005). Factors associated with adoption of evidence-based substance use prevention curricula in US school districts. Health Education Research, 20, 514–526.CrossRefPubMed
Rohrbach, L. A., Grana, R., Sussman, S., & Valente, T. W. (2006). Type II translation: Transporting prevention interventions from research to real-world settings. Evaluation and the Health Professions, 29, 302–333.CrossRefPubMed
Rohrbach, L. A., Gunning, M., Grana, R., Gunning, G., & Sussman, S. (2010). Dissemination of Project Towards No Drug Abuse (TND): Findings from a survey of program adopters. Substance Use & Misuse, 45, 2551–2566.CrossRef
Sallis, J. F., Owen, N., & Fisher, E. B. (2008). Ecological models of health behavior. In K. Glanz, B. K. Rimer, & K. Viswanath (Eds.), Health behavior and health education: Theory, research, and practice (4th ed., pp. 465–486). San Francisco: Jossey-Bass.
SAS Institute Inc. SAS/C Online Doc TM. (2000). Release 9.0. Cary: SAS Institute.
Shinn, M. (2003). Understanding implementation of programs in multilevel systems. Prevention & Treatment, 6.
Skara, S., & Sussman, S. (2003). A review of 25 long-term adolescent tobacco and other drug use prevention program evaluations. Preventive Medicine, 37, 451–474.CrossRefPubMed
Snyder, F., Vuchinich, S., Acock, A., Washburn, I., Beets, M., & Li, K. K. (2010). Impact of the positive action program on school-level indicators of academic achievement, absenteeism, and disciplinary outcomes: A matched-pair, cluster randomized, controlled trial. Journal of Research on Educational Effectiveness, 3, 26–55.PubMedCentralCrossRefPubMed
Spillane, J. P. (1998). State policy and the non-monolithic nature of the local school district: Organizational and professional considerations. American Educational Research Journal, 35, 33–63.CrossRef
Spoth, R., Rohrbach, L., Greenberg, M., Leaf, P., Brown, C. H., Fagan, A., et al. (2013). Addressing core challenges for the next generation of type 2 translation research and systems: The translation science to population impact (TSci Impact) framework. Prevention Science, 14, 319–351.PubMedCentralCrossRefPubMed
Substance Abuse and Mental Health Services Administration, & United States Department of Health and Human Services. (2010). SAMHSA model programs. Retrieved from http://​nrepp.​samhsa.​gov/​.
United States Department of Health and Human Services, & Substance Abuse and Mental Health Services Administration. (2010). National registry of evidence-based programs and practices (NREPP). Retrieved from http://​nrepp.​samhsa.​gov/​index.​asp.
Yu, C.-Y., & Muthén, B. (2002). Evaluation of model fit indices for latent variable models with categorical and continuous outcomes. Paper presented at the annual meeting of the American Educational Research Association, New Orleans, LA.
Metadata
Title
The Process of Adoption of Evidence-based Tobacco Use Prevention Programs in California Schools
Authors
Melissa A. Little
Pallav Pokhrel
Steve Sussman
Louise Ann Rohrbach
Publication date
01-01-2015
Publisher
Springer US
Published in
Prevention Science / Issue 1/2015
Print ISSN: 1389-4986
Electronic ISSN: 1573-6695
DOI
https://doi.org/10.1007/s11121-013-0457-8

Other articles of this Issue 1/2015

Prevention Science 1/2015 Go to the issue

Erratum

Erratum to: Toward the Development of Preventive Interventions to Reduce HRSB, HIV/AIDS, and Multiple Problem Behaviors

OriginalPaper

Understanding “Agency” in the Translation of a Health Promotion Program

Erratum

Erratum to: Surviving or Thriving: Quality Assurance Mechanisms to Promote Innovation in the Development of Evidence-Based Parenting Interventions

OriginalPaper

Assessing the Quality of a Non-randomized Pragmatic Trial for Primary Prevention of Falls among Older Adults

OriginalPaper

Reciprocal Relations between Coalition Functioning and the Provision of Implementation Support

OriginalPaper

Misperception of Peer Weight Norms and Its Association with Overweight and Underweight Status Among Adolescents