ArticleCureus2023
Proof of Concept: Using ChatGPT to Teach Emergency Physicians How to Break Bad News.
Article in Cureus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Large Language Models and Empathy: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Performance of ChatGPT-3.5 and GPT-4 in national licensing examinations for medicine, pharmacy, dentistry, and nursing: a systematic review and meta-analysis.BMC medical education · 2024Pooled it
- Generative Artificial Intelligence-Driven Clinical Case Simulation in Temporomandibular Disorder Education: ChatGPT Versus Real Patients.Journal of dental education · 2026Article
- Hematology-Oncology Fellows' Use of Artificial Intelligence: A Multicenter Educational Practice and Needs Assessment Survey.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026Article
- Artificial intelligence in the emergency department-- applications, perceptions and limitations: a narrative review.World journal of emergency medicine · 2026Review
- Evaluating the Pediatric Behavior Guidance of Students Based on Actual Clinical Transcripts Scored by Faculty and Large Language Models: Pilot Comparative Study.JMIR medical education · 2026Article
- Reimagining pharmacology education.Pharmacological reviews · 2026Review
- Reflecting on 25 years of SPIKES: bad news communication in our modern era.The oncologist · 2026Article
- Real-World Impact and Educational Effectiveness of an AI-Powered Medical History-Taking System: Retrospective Propensity Score-Matched Cohort Study.JMIR medical education · 2026Article
- Understanding the ideal resources to study the UKMLA.BMC medical education · 2026Article
- Large language models in emergency medicine education: opportunities, challenges, and implementation pathways.Frontiers in public health · 2026Review
- Article
- The Validity of Generative Artificial Intelligence in Evaluating Medical Students in Objective Structured Clinical Examination: Experimental Study.JMIR formative research · 2025Article
- Learning Through Simulation: Counselor Trainees' Interactions with ChatGPT as a Client.Behavioral sciences (Basel, Switzerland) · 2025Article
- Article
- Development and Validation of a Large Language Model-Based System for Medical History-Taking Training: Prospective Multicase Study on Evaluation Stability, Human-AI Consistency, and Transparency.JMIR medical education · 2025Article
- DIALOGUE: A Generative AI-Based Pre-Post Simulation Study to Enhance Diagnostic Communication in Medical Students Through Virtual Type 2 Diabetes Scenarios.European journal of investigation in health, psychology and education · 2025Article
- Exploration of the Role of ChatGPT in Teaching Communication Skills for Medical Students: A Pilot Study.Medical science educator · 2025Article
- Assessing ChatGPT's Capability as a New Age Standardized Patient: Qualitative Study.JMIR medical education · 2025Article
- Development of a GPT-4-Powered Virtual Simulated Patient and Communication Training Platform for Medical Students to Practice Discussing Abnormal Mammogram Results With Patients: Multiphase Study.JMIR formative research · 2025Article
Corrections and comments
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Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Breaking bad news is an essential skill for practicing physicians, particularly in the field of emergency medicine (EM). Patient-physician communication teaching has previously relied on standardized patient scenarios and objective structured clinical examination formats. The novel use of artificial intelligence (AI) chatbot technology, such as Chat Generative Pre-trained Transformer (ChatGPT), may provide an alternative role in graduate medical education in this area. As a proof of concept, the author demonstrates how providing detailed prompts to the AI chatbot can facilitate the design of a realistic clinical scenario, enable active roleplay, and deliver effective feedback to physician trainees. Methods ChatGPT-3.5 language model was utilized to assist in the roleplay of breaking bad news. A detailed input prompt was designed to outline rules of play and grading assessment via a standardized scale. User inputs (physician role), chatbot outputs (patient role) and ChatGPT-generated feedback were recorded. Results ChatGPT set up a realistic training scenario on breaking bad news based on the initial prompt. Active roleplay as a patient in an emergency department setting was accomplished, and clear feedback was provided to the user through the application of the Setting up, Perception, Invitation, Knowledge, Emotions with Empathy, and Strategy or Summary (SPIKES) framework for breaking bad news. Conclusion The novel use of AI chatbot technology to assist educators is abundant with potential. ChatGPT was able to design an appropriate scenario, provide a means for simulated patient-physician roleplay, and deliver real-time feedback to the physician user. Future studies are required to expand use to a targeted group of EM physician trainees and provide best practice guidelines for AI use in graduate medical education.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.