EVALUATING CROSS-SECTOR COMMUNITY COLLABORATION FOR PARKINSON’S: THE HEALTHY PARKINSON’S COMMUNITIESTM (HPC) NETWORK

Abstract

SUSANA MARLYN CARLOS EVALUATING CROSS-SECTOR COMMUNITY COLLABORATION FOR PARKINSON’S: THE HEALTHY PARKINSON’S COMMUNITIES (HPC) NETWORK Under the direction of SUZIE MADDEN, DrPH, MPH Parkinson’s Disease (PD) is a significantly increasing public health concern, and the neurodegenerative disease requires a holistic, collaborative approach to addressing all aspects of the disease as well as working toward prevention. Many national, statewide, regional, and local Parkinson’s-oriented organizations exist, and there is little effort to coordinate these players toward improving the local community. The objective of the study was to evaluate individual local-level coalition-building efforts, utilizing a survey and interview process to measure success factors and areas for improvement. The research question was, “How to measure existing collective action effectively?” The two main tools utilized for the study included the Community Coalition Action Theory (CCAT) and the Wilder Collaborative Factors Inventory (WCFI). The survey expanded upon the WCFI to assess the outlined factors, and the interviews helped define these factors qualitatively for future community development. A total of 14 community leaders participated in the survey, of which 5 were also interviewed. Statistical Rho correlations were conducted to test the association between success factors within a category, against the category, and against outcome data. The first series of correlations for success factors within each category resulted in one significant pairing between mutual respect and the ability to compromise (under membership characteristics). The second series of correlations for each category with its relative success factors yielded significant correlations for at least one success factor for each category. The third correlation for categories and outcome variables highlighted membership characteristics, and resources stood out as substantial categories highly associated with the outcomes tested using linear regressions. The linear regressions resulted in one significant outcome where the category of resources predicted access to resources and programs (F(1,10) = 8.10, p < 0.01, R2 = 39%). In addition, the two tools utilized (WCFI and CCAT) have not been employed together to define coalitions and pose a significant research pathway that maps information visually and with data.