Beyond Basic Needs: Exploring Important Occupational Domains and Occupational Performance of Nursing Home Habitants in France
Bibliographic record
Abstract
Identifying important meaningful occupations of Nursing Home Habitants (NHH) is essential for tailored care. Staff often presume of NHHs' preferences according to stereotypes based on age, gender and autonomy. This study explores NHHs' important occupations and how age, level of autonomy and type of NH influence self-rated occupational performance (OP). Eleven occupational therapists working in nine Nursing homes (NHs) in France used the Canadian Occupational Performance Measure with 40 NHH. Autonomy was measured by the AGGIR Grid. Among 165 occupations social participation ranked highest importance, followed by ADL and health management. OP is explained by autonnomy and NH type of NH but not age, underscoring the need for individualized, non-stereotyped support.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".