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Sorting it out: pile sorting as a mixed methodology for exploring barriers to cancer screening |
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| Authors: | Hung-Wen Yeh Byron J Gajewski David G Perdue Angel Cully Lance Cully K Allen Greiner Won S Choi Christine Makosy Daley |
| Institution: | 1. Department of Biostatistics, The University of Kansas Medical Center, Kansas City, KS, 66160, USA 2. Center for American Indian Community Health, The University of Kansas Medical Center, Kansas City, KS, 66160, USA 3. School of Nursing, The University of Kansas Medical Center, Kansas City, KS, 66160, USA 4. The American Indian Cancer Foundation, and Minnesota Gastroenterology P.A., Minneapolis, MN, 55441, USA 5. Department of Family Medicine, The University of Kansas Medical Center, Kansas City, KS, 66160, USA 6. Department of Preventive Medicine & Public Health, The University of Kansas Medical Center, Kansas City, KS, 66160, USA |
| Abstract: | We discuss a mixed methodology for analyzing pile sorting data. We created a list of 14 barriers to colon cancer screening and recruited 18, 13, and 14 participants from three American Indian (AI) communities to perform pile sorting. Quantitative data were analyzed by cluster analysis and multidimensional scaling. Differences across sites were compared using permutation bootstrapping. Qualitative data collected during sorting were compiled by AI staff members who determined names for the clusters found in quantitative analysis. Results showed five clusters of barriers in each site although barriers in the clusters varied slightly across sites. Simulation demonstrated type I error rates around the nominal 0.05 level whereas power depended on the numbers of clusters, and between and within cluster variability. |
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