Beyond thinking fast and slow: Implications of a transtheoretical model of clinical reasoning and error on teaching, assessment, and research
Abstract
From dual process to a family of theories known collectively as situativity, both micro and macro theories of cognition inform our current understanding of clinical reasoning (CR) and error. CR is a complex process that occurs in a complex environment, and a nuanced, expansive, integrated model of these theories is necessary to fully understand how CR is performed in the present day and in the future. In this perspective, we present these individual theories along with figures and descriptive cases for purposes of comparison before exploring the implications of a transtheoretical model of these theories for teaching, assessment, and research in CR and error.
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Comprehensive models of cognition, such as the transtheoretical model, incorporate external factors, including interactions with team members or databases, which could be implemented for LLMs with Retrieval Augmented Generation.
“Comprehensive models of cognition, such as the transtheoretical model31 incorporate external factors, including interactions with team members or databases, which could be implemented for LLMs with Retrieval Augmented Generation31.”
From Large Language Models lack essential metacognition for reliable medical reasoning (2025) · cites this paper as [31]
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Large Language Models lack essential metacognition for reliable medical reasoning
Griot, M., Hemptinne, C., Vanderdonckt, J., & Yuksel, D. (2025) · Nature Communications · doi:10.1038/s41467-024-55628-6 · Cited by 113 · see citing works
“Comprehensive models of cognition, such as the transtheoretical model 31 incorporate external factors, including interactions with team members or databases, which could be implemented for LLMs with Retrieval Augmented Generation 31 .”
- Authors
- Parsons, A. S., Wijesekera, T. P., Olson, A. P. J., Torre, D., Durning, S. J., & Daniel, M.
- Affiliations
- University of Virginia (US)
- Yale University (US)
- University of Minnesota (US)
- University of Central Florida (US)
- Uniformed Services University of the Health Sciences (US)
- University of California San Diego (US)
- Corresponding author
- Parsons, Andrew S.
- ORCID
- Venue
- Medical Teacher
- Publisher
- Informa UK Limited
- Published
- 2024-06-05
- Volume
- 47
- Issue
- 4
- Pages
- 665-676
- ISSN
- 0142-159X (ISSN-L)
- 1466-187X
- OpenAlex
- W4399357279
- Cited by
- 12
- References
- 100
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 2
- FWCI
- 6.66
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Medical Teacher (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Family Practice › Clinical Reasoning and Diagnostic Skills
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Innovations in Medical Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- clinical reasoning, medical errors, dual-process theory, fast and slow thinking, transtheoretical model, medical education, clinical reasoning assessment, complex cognition
- MeSH terms
- Clinical Reasoning, Clinical Competence, Cognition, Education, Medical, Humans, Models, Psychological, Models, Theoretical, Teaching, Thinking, Models, Educational, Medical Errors
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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