Identifying Characteristics of ‘Straightforward Cases’ for which Support Personnel Could Recommend Home Bathing Equipment
Bibliographic record
Abstract
Introduction: The general consensus is that an occupational therapist should carry out the assessment for recommending home bathing equipment. Nevertheless, in response to a shortage of human resources, home-care occupational therapists in Quebec, Canada, frequently transfer the clinical task of recommending bathing equipment to support personnel in ‘straightforward cases’. However, there is no consensus on what constitutes such cases, and clinicians lack information on how to define a straightforward case. Objective: To characterise ‘straightforward cases’ when recommending bathing equipment in home-care occupational therapy. Design: The RAND/UCLA Appropriateness Method, combining a literature review with a three-round survey and one focus group meeting of nine occupational therapists. Results: Eight characteristics required for describing straightforward cases for bathing equipment recommendations were identified. They cover the three dimensions of the Canadian Model of Occupational Performance and Engagement: the occupation, the person, and the person's home environment. Conclusion: The literature review and collective opinion of experienced occupational therapists made it possible to agree on a common language to describe straightforward cases for bathing equipment. The characteristics identified will, it is hoped, support the critical thinking of clinicians deciding whether or not to transfer the task of recommending bathing equipment to support personnel.
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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 | 0.010 | 0.102 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".