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A Graphical, Computer-Based Decision-Support Tool to Help Decision Makers Evaluate Policy Options Relating to Physical Activity

  • Antronette K. Yancey
    Correspondence
    Address correspondence to: Antronette K. Yancey, MD, MPH, UCLA School of Public Health, 31-235 CHS, 650 Charles Young Drive South, Los Angeles CA 90095
    Affiliations
    Department of Health Services, University of California Los Angeles, Los Angeles, California

    UCLA Kaiser Permanente Center for Health Equity, University of California Los Angeles, Los Angeles, California

    Center for Health Policy Research, University of California Los Angeles, Los Angeles, California

    Division of Cancer Prevention and Control Research, University of California Los Angeles, Los Angeles, California
    Search for articles by this author
  • Brian L. Cole
    Affiliations
    Department of Health Services, University of California Los Angeles, Los Angeles, California

    Center for Health Policy Research, University of California Los Angeles, Los Angeles, California
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  • William J. McCarthy
    Affiliations
    Department of Health Services, University of California Los Angeles, Los Angeles, California

    UCLA Kaiser Permanente Center for Health Equity, University of California Los Angeles, Los Angeles, California

    Division of Cancer Prevention and Control Research, University of California Los Angeles, Los Angeles, California

    School of Public Health, and the Psychology Department, University of California Los Angeles, Los Angeles, California
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      Abstract

      This pilot study builds on efforts to develop evaluation methods to compare and contrast potential strategies designed to increase population physical activity generally, and to reduce disparities in activity levels more specifically. The study presents a user-friendly, semi-quantitative decision-support tool of intermediate complexity that may better enable quick, flexible first-pass “ballpark” decision making by state and local health agencies instead of traditional evidence-based scientific reviews. The tool produces a summary score from ratings on 18 criteria, adjusted by fixed or variable weights to incorporate salient community contextual factors. Stair use, workplace activity breaks, and school construction siting are presented as samples. This first iteration of the decision-support tool is intended to be refined empirically by the experiences and policy outcomes of agencies adopting the innovation. This decision-support tool may expand the capacity of public health practitioners to conduct first-pass assessments of policy options for physical activity promotion in underserved communities.
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