An Ecological Account of Clinical Reasoning
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.016 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".