Validation of the INCEPT: A Multisource Feedback Tool for Capturing Different Perspectives on Physicians’ Professional Performance
Van der Meulen MW et al. 2017. J Contin Educ Health Prof
Background: Multisource feedback (MSF) instruments are used to and must feasibly provide reliable and valid data on physicians’ performance from multiple perspectives. The “INviting Co-workers to Evaluate Physicians Tool” (INCEPT) is a multisource feedback instrument used to evaluate physicians’ professional performance as perceived by peers, residents, and coworkers. In this study, we report on the validity, reliability, and feasibility of the INCEPT.
Methods: The performance of 218 physicians was assessed by 597 peers, 344 residents, and 822 coworkers. Using explorative and confirmatory factor analyses, multilevel regression analyses between narrative and numerical feedback, item-total correlations, interscale correlations, Cronbach’s alpha and generalizability analyses, the psychometric qualities, and feasibility of the INCEPT were investigated.
Results: For all respondent groups, three factors were identified, although constructed slightly different: “professional attitude,” “patient-centeredness,” and “organization and (self)-management.” Internal consistency was high for all constructs (Cronbach’s alpha >/= 0.84 and item-total correlations >/= 0.52). Confirmatory factor analyses indicated acceptable to good fit. Further validity evidence was given by the associations between narrative and numerical feedback. For reliable total INCEPT scores, three peer, two resident and three coworker evaluations were needed; for subscale scores, evaluations of three peers, three residents and three to four coworkers were sufficient.
Conclusion: The INCEPT instrument provides physicians performance feedback in a valid and reliable way. The number of evaluations to establish reliable scores is achievable in a regular clinical department. When interpreting feedback, physicians should consider that respondent groups’ perceptions differ as indicated by the different item clustering per performance factor.