Leveraging evaluation of quality on medical education research with ChatGPT.

The Medical Education Research Study Quality Instrument (MERSQI) is widely used to evaluate the quality of quantitative research in medical education. It has strong evidence of validity and is endorsed by guidelines. However, the manual appraisal process is time-consuming and resource-intensive, highlighting the need for more efficient methods.

Performance of ChatGPT, Bard, Claude, and Bing on the Peruvian National Licensing Medical Examination: a cross-sectional study.

Purpose: We aimed to describe the performance and evaluate the educational value of justifications provided by artificial intelligence chatbots, including GPT-3.5, GPT-4, Bard, Claude, and Bing, on the Peruvian National Medical Licensing Examination (P-NLME).

Methods: This was a cross-sectional analytical study.

Factors associated with medical students’ scores on the National Licensing Exam in Peru: a systematic review.

Purpose: This study aimed to identify factors that have been studied for their associations with National Licensing Examination (ENAM) scores in Peru.

Methods: A search was conducted of literature databases and registers, including EMBASE, SciELO, Web of Science, MEDLINE, Peru’s National Register of Research Work, and Google Scholar. The following key terms were used: “ENAM” and “associated factors.