This article uses semistructured interview and survey data to outline two complementary approaches to measuring the level of community participation in research—a

Cover: On Measuring Community Participation in Research

On Measuring Community Participation in Research

Published in: Health Education and Behavior, v. 40, no. 3, June 2013, p. 346-354

Posted on RAND.org on January 01, 2012

by Dmitry Khodyakov, Susan Stockdale, Andrea Jones, Joseph Mango, Felica Jones, Elizabeth Lizaola

WINNER — 2014 Lawrence W. Green Paper of the Year Award

Health Education & Behavior

Research Questions

  1. How can community engagement in research be measured?
  2. What are the relative merits of different measurement approaches?

Active participation of community partners in research aspects of community–academic partnered projects is often assumed to have a positive impact on the outcomes of such projects. The value of community engagement in research, however, cannot be empirically determined without good measures of the level of community participation in research activities. Based on our recent evaluation of community–academic partnered projects centered around behavioral health issues, this article uses semistructured interview and survey data to outline two complementary approaches to measuring the level of community participation in research—a "three-model" approach that differentiates between the levels of community participation and a Community Engagement in Research Index (CERI) that offers a multidimensional view of community engagement in the research process. The primary goal of this article is to present and compare these approaches, discuss their strengths and limitations, summarize the lessons learned, and offer directions for future research. We find that whereas the three-model approach is a simple measure of the perception of community participation in research activities, CERI allows for a more nuanced understanding by capturing multiple aspects of such participation. Although additional research is needed to validate these measures, our study makes a significant contribution by illustrating the complexity of measuring community participation in research and the lack of reliability in simple scores offered by the three-model approach.

Key Findings

We Developed and Compared Two Approaches to Measuring Community Engagement

The study used semistructured interview and survey data to propose two approaches to measuring community engagement in research:

  • The first is a nominal level measure called a “three-model” approach, which we developed based on the interview data. It differentiates between three levels of community participation (no participation, consultation, and engagement).
  • The second is a 12-item measure called Community Engagement in Research Index (CERI), which we developed based on the survey data. CERI not only covers different levels, but also different areas of community engagement in research.

While the Three-Model Approach Provides a Simple Description of Perceived Levels of Community Participation in Research, CERI Allows for a More Nuanced Understanding of Community Engagement

  • The three-model approach has high face validity (i.e., it made sense to respondents), is easy-to-use, and is useful for revealing the difference between academic and community partners' perceptions of the level of community participation in research.
  • However, this nominal measure may have low content validity (i.e., the extent to which it measures all aspects of community engagement) and does not capture the complex nature of partnered research in which levels of community engagement vary depending on the stage of the research process (study design, data collection, data analysis, dissemination of findings).
  • The CERI approach is more suitable for capturing and quantifying community participation. CERI demonstrated stronger content validity than the three-model approach because the index items capture engagement in specific activities across different stages of the research process.
  • Additional research is needed to validate these results.
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