Generative AI Simulation for Diagnostic Communication in Type 2 Diabetes: A Randomized Controlled Trial (DIALOGUE-DM2)
试验速览
- 阶段
- 不适用
- 状态
- 已完成
- 发起方
- 入组人数
- 120
- 试验地点
- 1
- 主要终点
- Change in Diagnostic Communication Performance Score
研究概览
简要总结
This randomized controlled trial evaluates the effectiveness of a generative artificial intelligence (AI)-based simulation program in improving diagnostic communication skills among medical students. The study is conducted at the Faculty of Higher Studies Iztacala, National Autonomous University of Mexico (UNAM).
A total of 120 medical students are randomized to either an intervention group using the DIALOGUE-DM2 AI simulation platform or a control group following traditional educational methods. Participants complete a pre-test, receive training according to group assignment, and then undergo a post-test evaluation.
The primary outcome is improvement in diagnostic communication skills, measured by standardized patient scenarios and validated rubrics. Secondary outcomes include self-reported confidence, communication domains, and inter-rater agreement between faculty evaluators and AI scoring.
This trial aims to provide high-quality evidence on the potential of generative AI to enhance communication training in medical education, specifically in the context of type 2 diabetes diagnosis.
详细描述
This study builds on a prior pilot trial (published in 2024) that demonstrated the feasibility of using generative artificial intelligence (AI) to train medical students in diagnostic communication. The current trial extends that work with a randomized, blinded, controlled design and a larger sample size.
Design:
The study is a randomized, blinded, parallel-group, controlled trial conducted at the Faculty of Higher Studies Iztacala (FES Iztacala), UNAM. A total of 120 medical students are enrolled and randomized (1:1) into either the intervention group (AI-based simulation training) or the control group (traditional training with standardized patients and faculty feedback).
Intervention:
- Intervention group: Students interact with the DIALOGUE-DM2 platform, which provides generative AI-driven simulated patients. They complete multiple diagnostic disclosure scenarios and receive immediate feedback on performance, based on standardized communication rubrics.
- Control group: Students receive standard training, including lectures and supervised practice with peer role-play and faculty-guided feedback.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Health Services Research
- 盲法
- Triple (Participant, Investigator, Outcomes Assessor)
盲法说明
Participant, Investigator, Outcomes Assessor
入排标准
- 年龄范围
- 18 Years 至 29 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Medical students currently enrolled in the Faculty of Medicine (Medical Surgeon Program), UNAM-FES Iztacala.
- •Age between 18 and 30 years.
- •Able to provide informed consent.
- •Willing to participate in all study phases (pre-test, intervention, post-test).
排除标准
- •Prior participation in the DIALOGUE pilot study.
- •Previous formal training in diagnostic communication beyond the standard medical curriculum.
- •Incomplete availability for scheduled sessions.
- •Refusal or inability to provide informed consent.
结局指标
主要结局
Change in Diagnostic Communication Performance Score
时间窗: Approximately 12 weeks (from pre-test to post-test per participant).
Improvement in diagnostic communication skills, measured using validated rubrics - the Kalamazoo Essential Elements Communication Checklist and the Medical Communication Rating Scale (MCRS) - applied to standardized patient scenarios. Independent blinded faculty evaluators and AI scoring will be used. Scores range from 0 to 100, with higher values indicating better diagnostic communication performance.
次要结局
- Change in Student Self-Reported Confidence in Diagnostic Communication(Approximately 12 weeks (from pre-test to post-test per participant).)
- Change in Domain-Specific Diagnostic Communication Scores (Kalamazoo Framework and Medical Communication Rating Scale)(Approximately 12 weeks (from pre-test to post-test per participant).)
- Agreement Between Human Evaluators and AI Scoring(Assessed at post-test, approximately 12 weeks after baseline per participant.)
- Student Satisfaction With the Assigned Training Method(Assessed immediately after completion of the post-test, approximately 12 weeks after baseline per participant.)
研究者
Héctor Iván Saldívar Cerón
Principal Investigator, FES Iztacala, UNAM
Universidad Nacional Autonoma de Mexico