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| ID | Type | Description | Link |
|---|---|---|---|
| 2023jyxm1150 | Other Grant/Funding Number | 2023 Anhui Province Quality Engineering Project |
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The goal of this clinical trial is to evaluate whether AI-based simulated patient training can improve clinical reasoning and history-taking skills in medical students. The main questions it aims to answer is:
Does GPT-based simulated patient training improve medical students' history-taking skills compared to traditional role-playing methods?
Participants will:
Participants in the intervention group perform medical history-taking conversations with an AI-simulated patient. Receive AI-generated structured feedback on their performance. The control group participated in role-playing exercises with instructors who acted as patients, receiving feedback after each session. Complete standardized assessments to evaluate clinical reasoning and decision-making skills.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| intervention group | Experimental | using GPT-simulated patients |
|
| control group | Active Comparator | using traditional role-playing |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| GPT-simulated patients | Behavioral | GPT-simulated patients |
| |
| Measure | Description | Time Frame |
|---|---|---|
| structured clinical examination to measure students' abilities in history taking | Pre and Post Training: This primary endpoint measures improvements in students' clinical skills using a structured clinical examination conducted both before and after the training. The total score is out of 100 points, aggregated from four components: History Collection (30 points): Assesses the level of detail in the chief complaint and symptoms (10 points), the ability to understand and identify patient information (10 points), and the appropriateness and logic of follow-up questions (10 points). Clinical Reasoning (30 points): Evaluates the thoroughness of diagnostic thinking (15 points) and efficiency in processing information and forming clinical judgments (15 points). Communication Skills (20 points): Includes interaction with patients (10 points) and clarity of information delivery (10 points). Professional Behavior (20 points): Measures adherence to clinical procedural norms (10 points) and professional attitude towards patients (1 | From enrollment to the end of treatment at 4 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Training Feedback Assessment | Training Feedback Assessment Measurement Tool: Structured Questionnaire on a 5-point Likert scale. Components Assessed:
|
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Inclusion Criteria:Medical education enrollment:
Students enrolled in a medical or health-related professional program.
Clinical coursework completion:
Students who have completed basic clinical coursework, including foundational topics in patient communication and clinical reasoning.
Age group:
Participants aged 18-30 years to reflect typical medical student demographics.
Language proficiency:
Adequate proficiency in the language used for the study (e.g., English) to effectively interact with the AI-simulated patient and understand feedback.
Willingness and availability:
Students who provide informed consent and are willing to participate in all required study activities, including training sessions and assessments.
Access to technology:
Ability to access and use the necessary technology, such as a computer and internet connection, to complete the simulated patient interactions.
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Exclusion Criteria:Non-medical background:
Students not enrolled in medical or related health professions programs. Students in early years of study who have not completed basic clinical coursework.
Technical limitations:
Inability to access or use the required technology (e.g., computer or online platforms).
Time constraints:
Inability to complete all required training and assessments within the study timeline.
Language barriers:
Insufficient proficiency in the language used for the study (e.g., English) to effectively communicate or understand the simulated patient interactions.
Health-related factors:
Conditions that may impair participation, such as significant hearing or vision impairment, or severe psychological conditions.
Prior participation in similar studies:
Students who have already participated in studies involving similar AI-based simulated patient training or feedback.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Second Affiliated Hospital of Anhui Medical University | Hefei | Anhui | 230601 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 40640776 | Derived | Wang Z, Fan TT, Li ML, Zhu NJ, Wang XC. Feasibility study of using GPT for history-taking training in medical education: a randomized clinical trial. BMC Med Educ. 2025 Jul 10;25(1):1030. doi: 10.1186/s12909-025-07614-9. |
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| traditional role-playing |
| Behavioral |
traditional role-playing |
|
| From enrollment to the end of treatment at 4 weeks |
| Student Satisfaction Survey | Measurement Tool: Satisfaction Questionnaire on a 5-point Likert scale. Components Assessed:
| From enrollment to the end of treatment at 4 weeks |