Enhancing the Measure of Participation Burden in Protocol Design to Incorporate Logistics, Lifestyle, and Demographic Characteristics

Ther Innov Regul Sci. 2021 Nov;55(6):1239-1249. doi: 10.1007/s43441-021-00336-2. Epub 2021 Aug 30.


Background: Growing interest in improving patient participation convenience and the feasible execution of clinical trials has increased demand for new approaches to leverage patient input in the protocol design process.

Methods: This study builds on prior work conducted by the Tufts Center for the Study of Drug Development in collaboration with ZS. A comprehensive participant burden algorithm based on protocol procedures, participation requirements and lifestyle preferences was developed and tested. Clinical trial preferences and perceptions from 3002 global patients were analyzed to inform and derive the algorithm. It was next tested against a convenience sample of 266 completed protocols. Descriptive statistics, significance tests, and regression analyses were performed.

Results: Mean participant burden scores were highly associated with, and predictive (p < 0.01) of, screen failure rates, overall clinical trial duration and the number of substantial protocol amendments; and predictive (p < 0.05) of protocol treatment duration. Of 11 subgroups assessed, those that most influenced the algorithm and drove higher overall burden scores included disease condition, caregiver reliance, race, prior experience as a clinical trial participant and participant age. Geographic area and participant sex showed only minimal influence.

Conclusion: This study presents advancement and refinement in measuring participation burden that will assist drug development teams and protocol authors in retrospectively understanding clinical trial performance outcomes and in prospectively informing protocol design decisions.

Keywords: Participation burden; Patient burden; Patient engagement; Protocol design.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Demography
  • Humans
  • Life Style
  • Patient Participation*
  • Research Design*
  • Retrospective Studies