Intuition in Occupational Therapists’ Clinical Reasoning: A Scoping Review
Bibliographic record
Abstract
This scoping review aimed to map the various facets of intuition in occupational therapy (OT), from its definitions, theoretical frameworks, epistemological paradigms to practical applications, highlighting its role in decision-making. Following the Joanna Briggs Institute methodology, a systematic search of five databases from 1990 to August 2023 identified 337 records related to OT and intuition. After removing duplicates and applying eligibility criteria, 22 studies were included. Two independent reviewers conducted the title/abstract and full-text screening. Thematic analysis synthesized descriptions of intuitive reasoning, and the studies' epistemologies were interpreted based on stated methodologies and knowledge conceptions. Key themes depicted OT's intuition as personalized knowledge developed through practice. Constructivist paradigms recognizing subjective meaning-making predominated (63.6%), while postpositivists related to self-reported intuition to decision outcomes quantitatively (22.7%). Despite increasing interdisciplinary attention, occupational therapists' intuition remains understudied. Integrating analytical and intuitive practice through reflection is crucial for client-centered expertise.
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 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 | 0.035 | 0.145 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.025 | 0.021 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".