ReviewHealthcare (Basel, Switzerland)2024
Enhancing Clinical Reasoning with Virtual Patients: A Hybrid Systematic Review Combining Human Reviewers and ChatGPT.
Review in Healthcare (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Application of deep machine learning in dental education: a systematic review of effectiveness in dental students' teaching learning outcomes.Evidence-based dentistry · 2026Pooled it
- GenAI-Supported Virtual Patients in Health Care Education: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Large Language Model-Based Virtual Patient Systems for History-Taking in Medical Education: Comprehensive Systematic Review.JMIR medical informatics · 2026Pooled it
- Virtual patients in medical education: a bibliometric analysis based on the wos core collection and scopus databases.Frontiers in medicine · 2026Pooled it
- AI for Clinical Competency Assessment: Scoping Review of Methods and Applications.JMIR medical education · 2026Article
- Mapping the research landscape of virtual reality and artificial intelligence in medical education evaluation: A bibliometric analysis.Medicine · 2026Article
- User Acceptance of an AI-Powered Medical History-Taking Training System Among Undergraduate Medical Students: Mixed Methods Study.JMIR medical education · 2026Article
- Educational Frameworks for Diagnostic Decision-Making in AI-Enhanced Head and Neck Pathology.Head and neck pathology · 2026Review
- Better teaching in the ICU: from educational principles to case-based, visualization-guided, and AI-enhanced training infrastructure.Critical care (London, England) · 2026Article
- Using AI-Based Virtual Simulated Patients for Training in Psychopathological Interviewing: Cross-Sectional Observational Study.JMIR medical education · 2025Observational
- Evaluation of an AI-Based Chatbot Providing Real-Time Feedback in Communication Training for Mental Health Care Professionals: Proof-of-Concept Observational Study.Journal of medical Internet research · 2025Observational
- Facilitating clinical reasoning for medical students in clinical settings: a scoping review.Korean journal of medical education · 2025Article
- AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.Journal of medical Internet research · 2025Observational
- The feasibility of using generative artificial intelligence for history taking in virtual patients.BMC research notes · 2025Article
- 10 tips for clinical educators in designing and delivering learning experiences to improve clinical reasoning for medical students.MedEdPublish (2016) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study presents a systematic review aimed at evaluating the effectiveness of virtual patients in enhancing clinical reasoning skills in medical education. A hybrid methodology was used, combining human reviewers and ChatGPT to assess the impact of conversational virtual patients on student learning outcomes and satisfaction.
methodsVarious studies involving conversational virtual patients were analyzed to determine the effect of these digital tools on clinical competencies. The hybrid review process incorporated both human assessments and AI-driven reviews, allowing a comparison of accuracy between the two approaches.
resultsConsistent with previous systematic reviews, our findings suggest that conversational virtual patients can improve clinical competencies, particularly in history-taking and clinical reasoning. Regarding student feedback, satisfaction tends to be higher when virtual patients' interactions are more realistic, often due to the use of artificial intelligence (AI) and natural language processing (NLP) in the simulators. Furthermore, the study compares the accuracy of AI-driven reviews with human assessments, revealing comparable results.
conclusionsThis research highlights AI's potential to complement human expertise in academic evaluations, contributing to more efficient and consistent systematic reviews in rapidly evolving educational fields.
Indexed as
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What OpenQuestion holds
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.