GPT, History-taking Training, Medical Education
Conditions
Keywords
History-taking Training, Artificial Intelligence, Medical Education, GPT Simulation
Brief summary
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.
Interventions
BEHAVIORALGPT-simulated patients
GPT-simulated patients
BEHAVIORALtraditional role-playing
traditional role-playing
Sponsors
zhen wang
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
OTHER
Masking
SINGLE (Outcomes Assessor)
Eligibility
Sex/Gender
ALL
Healthy volunteers
Yes
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. \-
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. \-
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| structured clinical examination to measure students' abilities in history taking | From enrollment to the end of treatment at 4 weeks | 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 |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Training Feedback Assessment | From enrollment to the end of treatment at 4 weeks | Training Feedback Assessment Measurement Tool: Structured Questionnaire on a 5-point Likert scale. Components Assessed: * Post-class self-directed learning. * Enthusiasm for learning. * Communication and feedback skills. * Expressiveness. * Interview logical reasoning ability. * Anxiety levels during the interview process. Description: This secondary endpoint collects feedback on the training methods' effectiveness through a structured questionnaire. Each aspect is rated on a 5-point Likert scale, where 1 indicates 'strongly disagree' and 5 indicates 'strongly agree'. |
| Student Satisfaction Survey | From enrollment to the end of treatment at 4 weeks | Measurement Tool: Satisfaction Questionnaire on a 5-point Likert scale. Components Assessed: * Diversity of diseases encountered during training. * Naturalness of patient interaction. * Usability of the training methods. * Likelihood of recommending the training to peers. Description: This secondary endpoint evaluates student satisfaction concerning various aspects of the training experience. The questionnaire assesses each factor on a 5-point Likert scale, where 1 is 'very dissatisfied' and 5 is 'very satisfied'. |
Countries
China
Outcome results
None listed