Generative AI-Based Simulation for Diagnostic Communication in Type 2 Diabetes (DIALOGUE-DM2)

National Autonomous University of Mexico ( UNAM )

Status: Completed

Conditions: Artificial Intelligence Simulation; Diagnostic Communication; Type 2 Diabetes Mellitus; Medical Education

Treatments: Behavioral: Traditional Training; Behavioral: AI-Based Simulation Training (DIALOGUE-DM2)

Study type: Interventional

Funder types: Other

Identifiers

NCT07252193

UNAM-DIALOGUE-DM2-2025

Details and patient eligibility

About

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.

Full description

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.

Assessments:

• Pre-test: All students complete one standardized patient scenario with faculty and AI evaluation prior to intervention.
• Training phase: Participants complete their assigned training (AI vs. standard).
• Post-test: Students complete a standardized diagnostic disclosure scenario. Independent faculty evaluators (blinded to group assignment) and the AI platform score performance.

Outcomes:

• Primary outcome: Change in diagnostic communication performance score from pre-test to post-test, measured by validated rubrics (Kalamazoo framework, MRS).
• Secondary outcomes:
• Student self-assessment of communication confidence.
• Domain-specific improvements (information delivery, empathy, risk explanation, shared decision-making).
• Agreement between human evaluators and AI scoring.

Ethics and Oversight:

The study has been reviewed and approved by the Research Ethics Committee of FES Iztacala, UNAM (Approval Number CE/FESI/042025/1915). Risks are minimal, as the intervention is educational and non-invasive.

Significance:

This is the first randomized controlled trial in Mexico to evaluate a generative AI-based simulation for diagnostic communication. Results will inform the integration of AI-driven training tools into medical education curricula and could contribute to scalable innovations in the training of healthcare professionals for chronic disease management, starting with type 2 diabetes.

Enrollment: 120 patients

Sex: All

Ages: 18 to 29 years old

Volunteers: Accepts Healthy Volunteers

Inclusion criteria

• 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).

Exclusion criteria

• 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.

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: Triple Blind

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120 participants in 2 patient groups

AI-Based Simulation Training (DIALOGUE-DM2)

Experimental group

Description:

Medical students assigned to this arm will receive training using the DIALOGUE-DM2 platform, which provides generative AI-driven simulated patients. Participants will engage in multiple diagnostic disclosure scenarios focused on type 2 diabetes and receive immediate feedback generated by the AI system. Feedback is aligned with validated communication frameworks (Kalamazoo, MRS). Training is conducted over several sessions prior to the post-test evaluation.

Treatment:

Behavioral: AI-Based Simulation Training (DIALOGUE-DM2)

Traditional Training

Active Comparator group

Description:

Medical students assigned to this arm will receive traditional communication skills training. This includes lectures, peer role-play, and faculty-supervised feedback sessions covering diagnostic disclosure in type 2 diabetes. Participants will complete the same number of training sessions as the intervention group before the post-test evaluation.

Treatment:

Behavioral: Traditional Training