Using clinical history taking chatbot mobile app for clinical bedside teachings – A prospective case control study
Open accessAbstract
Introduction: A novel chatbot mobile app for training of undergraduate medical students' clinical history taking skills was developed in 2021. Students were able to take clinical history from the virtual patient for bedside teaching. A case-control study was conducted to evaluate the effectiveness of learning with chatbot mobile app, versus conventional bedside teachings with real patients. Methods: 132 final year medical students were randomized into two groups - Conventional bedside teaching with clinical history taken from a real patient, and Bedside teaching with clinical history taken from the Chatbot. Independent blinded assessment of students' history taking skills was conducted. Students' performance were assessed by standardized marking scheme. Results: Median age was 23 years old (Range 21-30 years old). There were 62 female and 70 male students.64 students were randomized into conventional group while 68 students were randomized into the chatbot group. Baseline demographic data were comparable between the two groups.Blinded assessment of students' performance in clinical history taking were comparable between the conventional group and chatbot group (p > 0.05). Conclusion: With the promising results we have demonstrated in this study, we believe training of history taking skills by chatbot will be a feasible alternative to conventional bedside teaching.
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Han, J.-W., Park, J., & Lee, H. (2022) · BMC Medical Education · doi:10.1186/s12909-022-03898-3 · Cited by 187 · see citing works
“Based on the results of this study, it is suggested that chatbot programs can be an alternative to the existing clinical practice methods [17].”
BackgroundResultA bibliometric analysis of artificial intelligence chatbots in educational contexts
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Using ChatGPT for medical education: the technical perspective
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- Authors
- Co, M., John Yuen, T. H., & Cheung, H. H.
- Affiliations
- Queen Mary Hospital (CN)
- Corresponding author
- Co, Michael
- ORCID
- Co, Michael
- Venue
- Heliyon
- Publisher
- Elsevier BV
- Published
- 2022-06
- Volume
- 8
- Issue
- 6
- Pages
- e09751
- ISSN
- 2405-8440 (ISSN-L)
- PMC
- PMC9234591
- OpenAlex
- W4283120867
- Cited by
- 31
- References
- 12
- Citations by year
- 2026: 3 · 2025: 9 · 2024: 6 · 2023: 9 · 2022: 4
- FWCI
- 2.11
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Heliyon (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Medicine › Physiology › Simulation-Based Education in Healthcare
- Keywords
- chatbots, clinical history taking, medical education, bedside teaching, virtual patients, mobile application, undergraduate medical students, history-taking skills, simulation-based training
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