School Reintegration Following Psychiatric Hospitalization: A Review of Available Transition Programs.
Bibliographic record
Abstract
Objectives: This study aimed to 1) identify transition programs for school reintegration after youth psychiatric hospitalization, and 2) assess these programs using criteria established by Blueprints for Healthy Youth Development. Method: Principles outlined by the Evidence for Policy and Practice Information and Coordinating Centre were used to systematically search 15 electronic databases up to October 2021 for both published and unpublished reports of transition programs. Reports meeting inclusion criteria were examined through three steps: 1) coding of available information, 2) synthesis of programs and 3) assessment of intervention specificity. Results: Thirteen reports met the inclusion criteria and identified eight transition programs. Program theories were rarely explicit about the causal mechanisms and outcomes of their interventions. Nevertheless, areas of consensus emerge as to core components of these programs including: 1) the involvement of a multidisciplinary team, 2) the implementation of a multicomponent intervention, 3) the development of a reintegration plan, 4) the need for gradual transitions, and 5) extended support through frequent contact. Conclusion: School reintegration programs following psychiatric hospitalization are still rare. They can be hard to implement due to the challenges they impose for inter-professional and intersectoral collaborations. Despite this, four of the eight programs are in a good position for an evaluation of their promising standing. Nevertheless, well-designed controlled trials and cohort studies are needed.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".