Developing Computerized Adaptive Testing for a National Health Professionals Exam: An Attempt from Psychometric Simulations.

Abstract

The accurate assessment of health professionals' competence is critical for ensuring public health safety and quality of care. Computerized Adaptive Testing (CAT) based on the Item Response Theory (IRT) has the potential to improve measurement accuracy and reduce respondent burden. In this study, we conducted psychometric simulations to develop a CAT for evaluating the candidates' competence of health professionals. The initial CAT item bank was sourced from the Standardized Competence Test for Clinical Medicine Undergraduates (SCTCMU), a nationwide summative test in China, consisting of 300 multiple-choice items. We randomly selected response data from 2000 Chinese clinical medicine undergraduates for analysis. Two types of analyses were performed: first, evaluating the psychometric properties of all items to meet the requirements of CAT; and second, conducting multiple CAT simulations using both simulated and real response data. The final CAT item bank consisted of 121 items, for which item parameters were calculated using a two-parameter logistic model (2PLM). The CAT simulations, based on both simulated and real data, revealed sufficient marginal reliability (coefficient of marginal reliability above 0.750) and criterion-related validity (Pearson's correlations between CAT scores and aggregate scores of the SCTCMU exceeding 0.850). In national-level medical education assessment, there is an increasing need for concise yet valid evaluations of candidates' competence of health professionals. The CAT developed in this study demonstrated satisfactory reliability and validity, offering a more efficient assessment of candidates' competence of health professionals. The psychometric properties of the CAT could lead to shorter test durations, reduced information loss, and a decreased testing burden for participants.