Clinical reasoning and the occupational therapy curriculum
Bibliographic record
Abstract
Abstract Several reasoning styles are used by occupational therapists when they evaluate clients' problems. This study investigated the influence of the occupational therapy curriculum in Hong Kong on therapists' clinical reasoning styles. Two groups of therapists with different clinical experience were recruited. Through interviews with the therapists after identifying clients' problems using the Canadian Occupational Performance Measure, their clinical reasoning styles were explored. The local occupational therapy curriculum was analysed to isolate the components that influence clinical reasoning. Results showed that more experienced therapists use conditional reasoning that considers clients' needs in their future lives whereas junior therapists use procedural reasoning that focuses on clients' disabilities. The analysis of the occupational therapy curriculum indicated that it prepared the students with an equal emphasis on theoretical and clinical subjects and fieldwork practice. The present curriculum was useful in providing educational preparation for novice therapists. However, the period of fieldwork practice can be lengthened to allow adequate maturation of clinical reasoning skills. Problem‐based learning can be incorporated to facilitate students' problem‐solving and self‐directed learning skills. Copyright © 2000 Whurr Publishers Ltd.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".