Psycho-social Stressors Experienced by Young war Refugees in Developed Countries: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Refugees escaping political unrest and war are an especially vulnerable group. Arrival in high-income countries (HICs) is associated with a 'new type of war', as war refugees experience elevated rates of psycho-social and daily stressors. PURPOSE: The purpose of this scoping review is to examine literature on psycho-social stressors amongst young war refugees in HICs and impact of stressors on intergenerational transmission of trauma within parent-child dyads. The secondary objectives are to identify the pre-migration versus post-migration stressors and provide a basis to inform future research projects that aim to lessen the burden of stress and inform evidence-based improvements in this population. METHODS: Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review Extension (PRISMA-ScR) guided the reporting of this review that was performed using a prescribed scoping review method. Extracted from five databases, 23 manuscripts published in 2010 or later met the inclusion criteria. RESULTS: Three themes emerged: pre-migration stressors, migration journey stressors and uncertainty, and post-migration stressors. While post-migration environments can mitigate the health and well-being of war refugees, socio-cultural barriers that refugees often experience at the host country prevent or worsen their psycho-social recovery. CONCLUSION: To assist the success of war refugees in HICs, therapeutic interventions must follow an intersectional approach and there needs to be a wider application of trauma informed models of care. Findings of this review may help inform future intervention studies aiming to improve the psycho-social health of this population.
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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 | 0.013 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.015 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| 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".