Innovative competency-based education approach to radiology residency: integrating modular training in clinical practice and research

OBJECTIVES: This study aimed to design and evaluate a competency-based education (CBE)-oriented modular training model for radiology residents, emphasizing interdisciplinary integration and disease-focused instruction to enhance clinical competence. MATERIALS AND METHODS: This prospective controlled study included 75 radiology residents enrolled in standardized training from September 2020 to July 2024. A CBE-oriented modular training model was developed, structured around approximately 27 radiologic subspecialties and incorporating interdisciplinary instruction, clinical team rotations, and image post-processing skill training. The participants were assigned to either the experimental group (CBE training) or the control group (traditional training). Teaching effectiveness was evaluated by comparing theoretical and practical exam scores via statistical analysis. RESULTS: Overall, there were no significant differences in theoretical (83.26 ± 6.99 vs 81.76 ± 7.54; p > 0.05) or practical scores (86.79 ± 8.90 vs 84.91 ± 10.71; p > 0.05) between the two groups. However, subgroup analysis revealed that, among residents in the non-graduate subgroup, the experimental group achieved significantly higher theoretical (p = 0.0179) and practical scores (p = 0.028) than the control group. No significant differences were observed in the enrolled-graduate subgroup (p > 0.05). CONCLUSIONS: The competency-based modular training model significantly improved clinical competence among residents in the non-graduate subgroup but showed less additional benefit in the enrolled-graduate subgroup. This study offers insights for advancing radiology residency training reform. CRITICAL RELEVANCE STATEMENT: The distinct effectiveness of this approach was particularly beneficial for trainees with diverse educational backgrounds. This training model enhances residents' clinical competence and research capabilities and provides insights for global radiology education reform, aligning training paradigms with evolving clinical and technological advancements. KEY POINTS: A CBE-oriented modular training model for radiology residents was developed, integrating interdisciplinary learning, team-based clinical training, and image post-processing instruction. Although no overall difference in examination scores was observed between the two groups, residents in the non-graduate subgroup achieved significantly better theoretical and practical scores under the CBE model.

Authors

Institutions

Publication Details

Journal
Insights into Imaging
Published
2026-06-25
DOI
https://doi.org/10.1186/s13244-026-02335-z
Primary Topic
Innovations in Medical Education
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Innovative competency-based education approach to radiology residency: integrating modular training in clinical practice and research

Zixing Huang, Ningna Fan, Xi-Jiao Liu, Z L Li et al.
Insights into Imaging
Innovations in Medical Education
article

Innovative competency-based education approach to radiology residency: integrating modular training in clinical practice and research

Zixing Huang, Ningna Fan, Xi-Jiao Liu, Z L Li, Lei Ye, Na Hu, Shang Wan, Bin Song, Xibiao Yang
article en

Abstract

OBJECTIVES: This study aimed to design and evaluate a competency-based education (CBE)-oriented modular training model for radiology residents, emphasizing interdisciplinary integration and disease-focused instruction to enhance clinical competence. MATERIALS AND METHODS: This prospective controlled study included 75 radiology residents enrolled in standardized training from September 2020 to July 2024. A CBE-oriented modular training model was developed, structured around approximately 27 radiologic subspecialties and incorporating interdisciplinary instruction, clinical team rotations, and image post-processing skill training. The participants were assigned to either the experimental group (CBE training) or the control group (traditional training). Teaching effectiveness was evaluated by comparing theoretical and practical exam scores via statistical analysis. RESULTS: Overall, there were no significant differences in theoretical (83.26 ± 6.99 vs 81.76 ± 7.54; p > 0.05) or practical scores (86.79 ± 8.90 vs 84.91 ± 10.71; p > 0.05) between the two groups. However, subgroup analysis revealed that, among residents in the non-graduate subgroup, the experimental group achieved significantly higher theoretical (p = 0.0179) and practical scores (p = 0.028) than the control group. No significant differences were observed in the enrolled-graduate subgroup (p > 0.05). CONCLUSIONS: The competency-based modular training model significantly improved clinical competence among residents in the non-graduate subgroup but showed less additional benefit in the enrolled-graduate subgroup. This study offers insights for advancing radiology residency training reform. CRITICAL RELEVANCE STATEMENT: The distinct effectiveness of this approach was particularly beneficial for trainees with diverse educational backgrounds. This training model enhances residents' clinical competence and research capabilities and provides insights for global radiology education reform, aligning training paradigms with evolving clinical and technological advancements. KEY POINTS: A CBE-oriented modular training model for radiology residents was developed, integrating interdisciplinary learning, team-based clinical training, and image post-processing instruction. Although no overall difference in examination scores was observed between the two groups, residents in the non-graduate subgroup achieved significantly better theoretical and practical scores under the CBE model.

Insights into ImagingVol. 17(1)
Sichuan University (CN), West China Medical Center of Sichuan University (CN), West China Hospital of Sichuan University (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, Sichuan University
Quality Education
Openalex Percentile: Top 6%
Innovations in Medical Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.