Considération des activités de loisirs par des ergothérapeutes suisses dans la réadaptation de personnes présentant une hémiplégie
Bibliographic record
Abstract
BACKGROUND: Participation in leisure activities by people with hemiplegia is greatly reduced. There is limited information regarding the extend to which client participation is taken into consideration in the current practice of occupational therapy. PURPOSE: The purpose of this study is to examine the way by which occupational therapists working at the Centres médico-sociaux (CMS) Vaudois take into consideration the leisure activities of people with hemiplegia. METHODS: An investigation was undertaken by correspondence with occupational therapists working at the CMS. Of the 54 questionnaires received, 31 were considered for analysis. RESULTS: The majority (87 %) of participating occupational therapists explore the areas of leisure activities. Objectives linked to this field are achieved by 55% of the clients. Diverse interventions are favoured in order to reach these objectives. CONCLUSION: Occupational therapists appear to frequently address the subject of leisure activities with their clients. However, they identify objectives with only a limited percentage of their clients and utilise few of the available resources in order to reach these objectives.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".