Cross-sectional study of the quality of randomized control trials on problem-based learning in medical education

Clin Anat. 2023 Jan;36(1):151-160. doi: 10.1002/ca.23977. Epub 2022 Nov 16.

Abstract

Problem-based learning (PBL) is increasingly being used in medical education globally, but its effectiveness in teaching remains controversial. A randomized controlled trial (RCT) is the method of choice for evaluating its effectiveness. The quality of an RCT has a significant effect on this evaluation, but to date we have not seen an assessment of the quality of RCTs for PBL. Two researchers searched MEDLINE and EMBASE for RCTs addressing PBL in medical education. The overall quality of each report was measured on a 28-point overall quality score (OQS) based on the 2010 revised Comprehensive Standards for Reporting and Testing (CONSORT) Statement. Furthermore, to study the key factors affecting OQS more effectively, a linear regression model of those factors was established using SPSS. After literature screening, 30 RCTs were eventually included and analyzed. The median OQS was 15 (range, 7-20), which meant that half of the items in the revised 2010 CONSORT statement were poorly reported in at least 40% of the RCTs analyzed. The regression model showed that the year of publication of RCTs and the impact factors of the journals in which they were published were the main factors affecting OQS. The overall quality of reporting of RCTs on PBL teaching in medical education was not satisfactory. Some RCTs were subjectively selective in reporting certain items, leading to heterogeneity in quality. It is expected that statisticians will develop new standards more suitable for evaluating RCTs related to teaching research and that editors and peer reviewers will be required to review the relevant RCTs more strictly.

Keywords: linear models; medical education; problem-based learning; quantitative research; randomized controlled trial.

Publication types

  • Randomized Controlled Trial

MeSH terms

  • Cross-Sectional Studies
  • Education, Medical*
  • Humans
  • Linear Models
  • Problem-Based Learning*
  • Reference Standards