Objectives: Cohort studies must implement effective retention strategies to produce internally valid and generalizable results. Ensuring all study participants are retained, particularly those involved in the criminal legal system, ensures study findings and future interventions will be relevant to this group, who are often lost to follow-up: critical to achieving health equity. Our objective was to characterize retention strategies and describe overall retention among an 18-month longitudinal cohort study of persons on community supervision prior to and during the COVID-19 pandemic.
Methods: We implemented various retention strategy best-practices (e.g., multiple forms of locator information, training study staff on rapport building, study-branded items). During the COVID-19 pandemic, we developed and describe new retention strategies. We calculated overall retention and analyzed differences between those retained and lost to follow-up by demographic characteristics.
Results: Prior to the start of the COVID-19 pandemic, 227 participants enrolled across three sites (N = 46 North Carolina; N = 99 Kentucky; N = 82 Florida). Of these, 180 completed the final 18-month visit, 15 were lost to follow-up, and 32 were ineligible. This resulted in an overall retention of 92.3% (180/195). While most participant characteristics did not differ by retention status, a greater proportion of those experiencing unstable housing were lost to follow-up.
Conclusion: Our findings highlight that when retention strategies are flexible, particularly during a pandemic, high retention is still achievable. In addition to retention best-practices (e.g., frequent requests for updated locator information) we suggest other studies consider retention strategies beyond the study participant (e.g., paying participant contacts) and incentivize on-time study visit completion (e.g., providing a bonus when completed the study visit on time).
Copyright: © 2023 Uhrig Castonguay et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.