Sampling and Recruiting Community-Based Programs Using Community-Partnered Participation Research

Health Promot Pract. 2016 Mar;17(2):254-64. doi: 10.1177/1524839915605059. Epub 2015 Sep 18.

Abstract

The inclusion of community partners in participatory leadership roles around statistical design issues like sampling and randomization has raised concerns about scientific integrity. This article presents a case study of a community-partnered, participatory research (CPPR) cluster-randomized, comparative effectiveness trial to examine implications for study validity and community relevance. Using study administrative data, we describe a CPPR-based design and implementation process for agency/program sampling, recruitment, and randomization for depression interventions. We calculated participation rates and used cross-tabulation to examine balance by intervention status on service sector, location, and program size and assessed differences in potential populations served. We achieved 51.5% agency and 89.6% program participation rates. Programs in different intervention arms were not significantly different on service sector, location, or program size. Participating programs were not significantly different from eligible, nonparticipating programs on community characteristics. We reject claims that including community members in research design decisions compromises scientific integrity. This case study suggests that a CPPR process can improve implementation of a community-grounded, rigorous randomized comparative effectiveness trial.

Keywords: CBPR; anxiety; depression.

MeSH terms

  • Adult
  • Community Health Services / methods*
  • Community Health Services / organization & administration
  • Community-Based Participatory Research / methods*
  • Community-Based Participatory Research / organization & administration
  • Depression / diagnosis
  • Depression / prevention & control
  • Female
  • Humans
  • Male
  • Patient Selection
  • Program Evaluation
  • Randomized Controlled Trials as Topic / methods
  • Sampling Studies