Influence of a Disrupted Practice Context on Occupational Therapists' Clinical Reasoning: A Qualitative Study
Bibliographic record
Abstract
Background: Clinical reasoning in occupational therapy involves integrating client factors, professional knowledge, and practice context to guide decision-making. The COVID-19 pandemic disrupted health care contexts, potentially affecting therapists' reasoning. This study explored the factors that influenced occupational therapists' clinical reasoning during this crisis. Method: A qualitative descriptive study was conducted using semi-structured remote interviews with 11 occupational therapists in Quebec, Canada. The 60-min interviews, realized in 2021 and 2022, were recorded, transcribed verbatim, and analyzed inductively to identify reasoning-related themes. Deductive analysis involved coding text segments based on the 14 domains of the Theoretical Domains Framework. Transcripts were coded by two authors using QDA Miner software. Results: The sample included mostly women with clinical experience ranging from 4 to 34 years. In addition to the 14 TDF domains identified through deductive analysis, the inductive analysis revealed 11 key themes, including “weight given to client/family,” “client safety," or “ethical reasoning.” The therapists indicated that priority was given to the client's preferences. Their adaptation to the disrupted context was based on professional experience. In their view, demonstrated creativity and resilience reflected good professional adaptability. Anchoring in core occupational therapy values and ethics emerged as providing direction when evidence was limited. Conclusion: Therapists' professional values served as guides for navigating uncertainty. A client-centered approach took on greater importance in disrupted contexts. Findings indicate that using resilience and reflection can enhance context-adaptive reasoning.
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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 | 0.018 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.014 | 0.011 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".