A mixed systematic review of interventions to support the well-being of refugee youth in school and community settings
Bibliographic record
Abstract
Purpose To systematically review the evidence for school and community based interventions aimed at improving the well-being of refugee children and youth. Design Mixed studies systematic review (PROSPERO CRD42021253571). Method Nine electronic databases were searched for articles published in English that investigated the effects of psychological interventions aimed at improving distress, mental health symptoms, or increase psychological functioning and were provided in school or community settings. The search was limited to January 1, 2013 to November 3, 2023. A grey literature search was completed using the WHO International Clinical Trials Registry. Quality appraisal and risk of bias was undertaken using the Mixed Methods Appraisal Tool. Results Thirty-four studies were deemed eligible for inclusion representing data from 9,400 children and youth and were narratively reviewed and synthesized. CBT interventions were the most studied intervention and reported the most positive results overall, including improvements to trauma, depression, and anxiety symptoms. Results for psychosocial, creative expressive therapies, and trauma systems therapy interventions were mixed. Thematic synthesis of qualitative data reflected youths’ experiences including feeling increased connection to others, decreased negative feelings, and increased well-being as benefits of the interventions. Conclusions Refugee children and youth benefit from evidence-based psychological interventions in school and community sites. CBT interventions were effective in both school and community settings. Other therapeutic modalities such as creative expressive therapies, psychosocial interventions, and trauma systems therapy reported less consistent results and would benefit from further study.
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 | 0.017 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".