Ergothérapie et intégration communautaire : examen de la portée en neurologie adulte
Bibliographic record
Abstract
BACKGROUND.: Although community integration (CI) is the ultimate goal of rehabilitation, it is rarely achieved in clinical settings. PURPOSE.: The purpose of this study was to (a) synthesize the state of occupational therapy knowledge related to CI for people with neurological issues and to (b) illustrate how CI is conceptualized within the literature. METHOD.: A scoping review was completed using two reviewers, resulting in the selection of 47 articles pertaining to four study populations. Themes common across all client populations were identified through content analysis, and an iterative synthesis was used to analyse the evolution of knowledge. FINDINGS.: The selected articles covered craniocerebral trauma ( n = 21, 9 experimental categories [EXP]), medullar injuries ( n = 11, 4 EXP), cerebrovascular injuries ( n = 9, 4 EXP), and multiple sclerosis ( n = 4, 1 EXP). CI was used interchangeably with the term social participation. Fifty-one percent of the articles defined CI solely as part of a measurement tool, and 10% did not provide a definition of CI. The physical dimension of CI had been studied more frequently than the social and psychological dimensions. IMPLICATIONS.: Innovative practices should work to enable community inclusion and full citizenship to support the long-term enablement.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".