Using behavioral science to increase core outcome set use in trials.

ABSTRACT

OBJECTIVES: Core outcome sets (COS) are agreed sets of outcomes for use in clinical trials, which can increase standardization and reduce heterogeneity of outcomes in research. Using a COS, or not, is a behavior that can potentially be increased using behavioral strategies. The aim of this study was to identify behavioral intervention components to potentially increase use of COS in trials. METHODS: This project was informed by the Behavior Change Wheel framework. Two reviewers extracted barriers and facilitators to COS use from four recently published studies examining COS use in trials. Barriers and facilitators were coded to the Capability, Opportunity, Motivation-Behavior (COM-B) model, which forms part of the Behavior Change Wheel. COM-B findings were mapped to intervention functions by two reviewers, and then mapped to behavior change techniques (BCTs). Full-team Affordability, Practicability, Effectiveness/Cost-effectiveness, Acceptability, Side effects/Safety, Equity ratings were used to reach consensus on intervention functions and BCTs. BCTs were operationalized using examples of tangible potential applications and were categorized based on similarity. RESULTS: Barriers and facilitators were identified for all capability, opportunity and motivation aspects of the COM-B model. Five intervention functions (education, training, enablement, persuasion, and modeling) and 15 BCTs were identified. Thirty-six BCT examples were developed, including providing information on benefits of COS for health research, and information choosing COS. BCT examples are categorized by approaches related to "workshops," "guidance," "audio/visual resources," and "other resources." CONCLUSION: Study findings represent diverse ways to potentially increase COS use in trials. Future work is needed to examine effects of these behavioral intervention components on COS use. If effective, increased use of COS can improve outcome reporting and minimize outcome heterogeneity and research waste.