Participant retention practices in longitudinal clinical research studies with high retention rates

BMC Med Res Methodol. 2017 Feb 20;17(1):30. doi: 10.1186/s12874-017-0310-z.


Background: There is a need for improving cohort retention in longitudinal studies. Our objective was to identify cohort retention strategies and implementation approaches used in studies with high retention rates.

Methods: Longitudinal studies with ≥200 participants, ≥80% retention rates over ≥1 year of follow-up were queried from an Institutional Review Board database at a large research-intensive U.S. university; additional studies were identified through networking. Nineteen (86%) of 22 eligible studies agreed to participate. Through in-depth semi-structured interviews, participants provided retention strategies based on themes identified from previous literature reviews. Synthesis of data was completed by a multidisciplinary team.

Results: The most commonly used retention strategies were: study reminders, study visit characteristics, emphasizing study benefits, and contact/scheduling strategies. The research teams were well-functioning, organized, and persistent. Additionally, teams tailored their strategies to their participants, often adapting and innovating their approaches.

Conclusions: These studies included specialized and persistent teams and utilized tailored strategies specific to their cohort and individual participants. Studies' written protocols and published manuscripts often did not reflect the varied strategies employed and adapted through the duration of study. Appropriate retention strategy use requires cultural sensitivity and more research is needed to identify how strategy use varies globally.

Keywords: Cohort; Follow-up studies; Longitudinal; Methods; Patient dropouts; Research design/Standards; Retention strategies.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural

MeSH terms

  • Clinical Trials as Topic*
  • Data Collection / methods*
  • Humans
  • Longitudinal Studies
  • Patient Dropouts*
  • Research Design*