Soutien d’intensité variable (SIV) et rétablissement : que nous apprennent les études expérimentales et quasi expérimentales ?
Bibliographic record
Abstract
How should case management be organized for people who have severe mental illness, but do not need Assertive Community Treatment or similar high-intensity programs? To address this question, the authors conducted a systematic review of studies published in English between 1980 and 2010. Five main case management models were identified: broker, clinical case management, rehabilitation, strengths and intensive case management. In all, 11 experimental and 13 quasi-experimental studies evaluating case management programs not targeted at a typical ACT clientele were identified. These studies suggest that the strengths model, which can be viewed as a way of structuring intensive case management for a moderate-need population, is the best supported by evidence if one desires to see effects not only on hospital days, but also on other domains such as symptoms, quality of life and social functioning. It is also compatible with a recovery orientation. The evidence in its favor, however, remains modest.
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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 | 0.090 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".