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Community and Team Member Factors that Influence the Early Phase Functioning of Community Prevention Teams: The PROSPER Project

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Abstract

This research examines the early development of community teams in a specific university–community partnership project called PROSPER (Spoth et al., Prev Sci 5:31–39, 2004). PROSPER supports local community teams in rural areas and small towns to implement evidence-based programs intended to support positive youth development and reduce early substance use. The study evaluated 14 community teams and included longitudinal data from 108 team members. Specifically, it examined how community demographics and team member characteristics, perceptions, and attitudes at initial team formation were related to local team functioning 6 months later, when teams were planning for prevention program implementation. Findings indicate that community demographics (poverty), perceived community readiness, characteristics of local team members (previous collaborative experience) and attitudes toward prevention played a substantial role in predicting the quality of community team functioning 6 months later. Editors’ Strategic Implications: The authors identify barriers to successful long-term implementation of prevention programs and add to a small, but important, longitudinal research knowledge base related to community coalitions.

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Notes

  1. Although one could draw distinctions, we utilize the terms coalitions, partnerships, and local teams interchangeably in this manuscript. These terms in our usage refer to a range of informal through formal collaborative groups formed to enact positive change in a community.

  2. As reported previously (Chilenski et al. 2007) the full PROSPER model includes 14 intervention communities. The smaller number of communities involved in this data analyses is due to the two intervention communities that dropped out early in the project and subsequently were replaced. The two new intervention communities missed participating in this first post-test data collection, at 6 months.

  3. The percentage of students that receive a free or reduced lunch and the median household income can also be used to assess the economic risk of our community sample. The percentage of students receiving free and reduced lunch was 28.5% (SD = 10.6, range = 10.4–48%), and the median household income for the community sample was $37,114 (SD = 6,596).

  4. The Pennsylvania school district data was compiled from the Pennsylvania System of School Assessment District Report Cards (2003). The Iowa school district data was compiled from the Iowa Department of Education Data Spreadsheets (2003).

  5. Technical reports with complete description of all constructs and scales can be obtained from the first author.

  6. These regression analyses can be obtained from the first author.

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Acknowledgment

Work on this article was supported by research grant DA 013709 from the National Institute on Drug Abuse.

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Authors and Affiliations

  1. Prevention Research Center, Pennsylvania State University, Henderson Bldg S, University Park, PA, 16803, USA

    Mark T. Greenberg, Mark E. Feinberg & Sarah Meyer-Chilenski

  2. Iowa State University, Ames, IA, USA

    Richard L. Spoth & Cleve Redmond

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  1. Mark T. Greenberg
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  2. Mark E. Feinberg
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  3. Sarah Meyer-Chilenski
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  4. Richard L. Spoth
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  5. Cleve Redmond
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Correspondence to Mark T. Greenberg.

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Greenberg, M.T., Feinberg, M.E., Meyer-Chilenski, S. et al. Community and Team Member Factors that Influence the Early Phase Functioning of Community Prevention Teams: The PROSPER Project. J Primary Prevent 28, 485–504 (2007). https://doi.org/10.1007/s10935-007-0116-6

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