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Record W4297570957 · doi:10.1097/acm.0000000000004899

An Ecological Account of Clinical Reasoning

2022· review· en· W4297570957 on OpenAlexaff
Bjorn Watsjold, Jonathan S. Ilgen, Glenn Regehr

Bibliographic record

VenueAcademic Medicine · 2022
Typereview
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAffordanceEcological psychologyContext (archaeology)PsychologyCompetence (human resources)Engineering ethicsCognitive psychologySocial psychology

Abstract

fetched live from OpenAlex

PURPOSE: The prevailing paradigms of clinical reasoning conceptualize context either as noise that masks, or as external factors that influence, the internal cognitive processes involved in reasoning. The authors reimagined clinical reasoning through the lens of ecological psychology to enable new ways of understanding context-specific manifestations of clinical performance and expertise, and the bidirectional ways in which individuals and their environments interact. METHOD: The authors performed a critical review of foundational and current literature from the field of ecological psychology to explore the concepts of clinical reasoning and context as presented in the health professions education literature. RESULTS: Ecological psychology offers several concepts to explore the relationship between an individual and their context, including affordance, effectivity, environment, and niche. Clinical reasoning may be framed as an emergent phenomenon of the interactions between a clinician's effectivities and the affordances in the clinical environment. Practice niches are the outcomes of historical efforts to optimize practice and are both specialty-specific and geographically diverse. CONCLUSIONS: In this framework, context specificity may be understood as fundamental to clinical reasoning. This changes the authors' understanding of expertise, expert decision making, and definition of clinical error, as they depend on both the expert's actions and the context in which they acted. Training models incorporating effectivities and affordances might allow for antiableist formulations of competence that apply learners' abilities to solving problems in context. This could offer both new means of training and improve access to training for learners of varying abilities. Rural training programs and distance education can leverage technology to provide comparable experience to remote audiences but may benefit from additional efforts to integrate learners into local practice niches.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0030.002
Science and technology studies0.0030.016
Scholarly communication0.0050.006
Open science0.0020.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.269
GPT teacher head0.550
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2022
Admission routes1
Has abstractyes

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