Successfully Collecting Quantitative Data From Random Samples of Nursing Homes and Residents

Abstract

This case presents a rigorous approach used to successfully recruit and collect quantitative data from nursing home staff members and residents. The study presented in this case was conducted for my dissertation research. The goal of the study was to understand the complex phenomena of social integration for nursing home residents and its relation to health and well-being outcomes. To gather data, this study utilized a two-stage multilevel sampling technique to obtain a stratified random sample of nursing homes (N = 30) and a random sample of older adult residents from each of the nursing homes (N = 140, from each facility n = 3-6). This study utilized structured interviews with nursing home residents using a planned missing data design as well as brief surveys with staff members to collect data. Within the complex policy and program structures of nursing homes, the use of random sampling (as opposed to convenience sampling) at multiple levels (nursing home and resident) required the use of multiple, carefully planned steps. This included making phone calls, utilizing specific inclusion criteria, obtaining informed consent at multiple levels, and providing small monetary incentives. This case presents methodological considerations related to sampling, recruitment, and data collection. It also presents some of the lessons learned in collecting data for this study. This approach can be translated within various fields to recruit and gather health and related information from specialized populations.

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