Generative AI-Assisted Teaching and Clinical Reasoning Among TCM Interns
2 other identifiers
interventional
38
1 country
1
Brief Summary
This study evaluated the effects of generative artificial intelligence (GAI)-assisted education on clinical reasoning performance among traditional Chinese medicine (TCM) interns. An assessor-blinded, nonrandomized, cluster-controlled educational intervention study was conducted at three hospital branches in Taiwan. Participants were assigned to either a GAI-assisted education group or a conventional education group according to their clinical training sites. The intervention group received a three-hour introductory training session on ChatGPT and was encouraged to use the tool independently for clinical case analysis during subsequent clinical rotations. The control group received conventional clinical education without structured GAI-assisted training. The primary outcome was clinical reasoning performance, assessed through clinical case reports independently evaluated by two blinded TCM educators. Secondary outcomes included perceptions of the four-element TCM diagnostic framework and perceptions of GAI-assisted learning.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P25-P50 for not_applicable
Started Feb 2024
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 20, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 2, 2024
CompletedStudy Completion
Last participant's last visit for all outcomes
May 30, 2025
CompletedFirst Submitted
Initial submission to the registry
October 15, 2026
CompletedFirst Posted
Study publicly available on registry
October 23, 2026
CompletedOctober 23, 2026
October 1, 2026
10 months
October 15, 2026
October 22, 2026
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
Change in Clinical Reasoning Performance Score
Clinical reasoning performance was assessed using written clinical case reports independently evaluated by two blinded traditional Chinese medicine educators. Ten domains were scored from 1 to 10, including disease location, etiology, disease nature, pathogenesis, differential diagnosis, prescription selection, pathophysiological reasoning, overall clinical decision-making, information analysis, and clinical applicability of prescriptions. Total scores ranged from 10 to 100, with higher scores indicating better clinical reasoning performance. The mean score from the two evaluators was used for analysis. Changes in scores from baseline (Month 0) to post-intervention (Month 3) were compared between groups.
Baseline (Month 0) and post-intervention (Month 3)
Secondary Outcomes (2)
Change in Perceptions of the Four Elements of TCM Etiology and Pathogenesis
Baseline (Month 0) and post-intervention (Month 3)
Change in Perceptions of and Satisfaction With GAI-Assisted Learning
Baseline (Month 0) and post-intervention (Month 3)
Study Arms (2)
GAI-Assisted Education
EXPERIMENTALParticipants received a three-hour introductory training session on the use of ChatGPT for traditional Chinese medicine clinical case analysis. Following the training, participants were allowed to use ChatGPT independently during clinical rotations without a prescribed minimum frequency or duration of use.
Conventional Clinical Education
ACTIVE COMPARATORParticipants received conventional traditional Chinese medicine clinical education, including clinical observation, case discussions, and instruction from supervising physicians, without structured generative AI-assisted training.
Interventions
A structured three-hour introductory training session was provided on the use of ChatGPT for traditional Chinese medicine clinical reasoning and case analysis. Training included demonstrations of disease location, etiology, disease nature, pathogenesis, differential diagnosis, and prescription decision-making. Participants subsequently used ChatGPT independently during clinical rotations as needed. No minimum frequency or duration of ChatGPT use was required.
Participants continued routine traditional Chinese medicine clinical training, including supervised clinical observation, case-based discussions, and instruction from supervising physicians. No structured training in or assigned use of generative artificial intelligence tools was provided.
Eligibility Criteria
You may qualify if:
- Aged 18 years or older.
- Enrolled in an undergraduate or postbaccalaureate traditional Chinese medicine (TCM) program.
- Completed the required TCM coursework and the first stage of the national TCM licensing examination.
- Provided informed consent to participate in the study.
You may not qualify if:
- Already licensed as a traditional Chinese medicine physician.
- Unable to complete the required study procedures.
- Declined to provide informed consent.
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Taipei City Hospital
Taipei, Taipei, 110, Taiwan
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- SINGLE
- Who Masked
- OUTCOMES ASSESSOR
- Masking Details
- Two independent traditional Chinese medicine educators evaluated clinical case reports without knowledge of participants' group assignments. Participants and instructors were not blinded because of the nature of the educational intervention.
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER GOV
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Attending Physician
Study Record Dates
First Submitted
October 15, 2026
First Posted
October 23, 2026
Study Start
February 20, 2024
Primary Completion
December 2, 2024
Study Completion
May 30, 2025
Last Updated
October 23, 2026
Record last verified: 2026-10
Data Sharing
- IPD Sharing
- Will not share
Individual participant data will not be publicly shared because the study involves educational assessment records and questionnaire responses from a relatively small cohort of medical interns. Data confidentiality and participant privacy will be maintained in accordance with the approved institutional review board protocol.