Evaluating confidence in translational science principles to guide workforce development

Translational science (TS) workforce development initiatives are emerging to fast-track conversion of findings into applications to improve health. Principles of TS were developed to guide workforce development; however, few tools are available to evaluate confidence related to these principles to benchmark progress.

Our goal was to develop and validate a scale for assessing confidence related to the seven TS principles and get feedback about future workforce development opportunities that could be evaluated with this scale.

A cross-sectional survey was conducted in 2025 engaging 158 researchers and research staff affiliated with three Clinical and Translational Science Award hubs in Alabama, Massachusetts, and Ohio. Factor analysis was conducted to determine interrelatedness among the TS principles, reliability was assessed using Cronbach's alpha, and mixed effects models were used to examine differences in confidence levels.

Four factors emerged (α = 0.95 for full scale, 14 items), including Taking Risks for Impact (α = 0.85, 2 items), Multi-perspective Research (α = 0.88, 3 items), Collaborative Methods (α = 0.89, 6 items), and Efficiency and Productive Failure (α = 0.88, 3 items). Confidence levels varied significantly by factor (p < 0.001) with the lowest mean confidence (1 = lowest, 5 = highest) for the Efficiency and Productive Failure (2.56) and Taking Risks for Impact (2.79) factors. There were no differences in mean levels of confidence by demographics, site, or experience.

Findings provide guidance for prioritizing topics for future TS workforce development initiatives as well as a brief scale for evaluating how these interventions cultivate confidence across the seven TS principles.