Discharge Decision-Making, Enabling Occupations, and Client-Centred Practice
Bibliographic record
Abstract
BACKGROUND: Occupational therapists working in hospitals are confronted with increasingly complex discharge decisions. However, the relationship of discharge-planning strategies to the professional concepts of client-centred practice and enabling occupations has been unclear. PURPOSE: This study explored the relationship between the models of decision-making used by occupational therapists, and the professional issues of enabling occupation and client-centred practice. METHODS: Qualitative interviews were conducted with 10 occupational therapists. Data were analyzed for the presence and emergence of themes. RESULTS: Therapists try to balance the sometimes competing issues of safety and autonomy. Therapists often engage in negotiated decision-making. However, clients are sometimes excluded, despite therapists' commitment to client-centred processes. Consideration of occupations is often neglected. PRACTICE IMPLICATIONS: Client-defined models of decision-making are insufficient for frail, cognitively- impaired people. A new, client-centred Negotiated Model of Decision-Making is proposed, which facilitates decisions to enable older people with their occupations.
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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 | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 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".