Refugee Children’s Social–Emotional Capacities: Links to Mental Health upon Resettlement and Buffering Effects on Pre-Migratory Adversity
Bibliographic record
Abstract
Refugee children who experience severe pre-migratory adversity often show varying levels of mental health upon resettlement. Thus, it is critical to identify the factors that explain which refugee children experience more vs. less healthy outcomes. The present study assessed child social–emotional capacities (i.e., emotion regulation, sympathy, optimism, and trust) as potential moderators of associations between child, parental, and familial pre-migratory adversities and child mental health (i.e., internalizing and externalizing symptoms) upon resettlement. Participants were N = 123 five- to 12-year-old Syrian refugee children and their mothers living in Canada. Children and mothers reported their pre-migratory adverse life experiences, and mothers reported their children’s current social–emotional capacities, internalizing symptoms, and externalizing symptoms. Greater familial (i.e., the sum of children’s and their mother’s) pre-migratory adversity was associated with higher child internalizing and externalizing symptoms upon resettlement. Higher emotion regulation and optimism were associated with lower internalizing and externalizing symptoms, and higher sympathy was associated with lower externalizing symptoms. In contrast, higher trust was associated with higher internalizing symptoms. Finally, higher child optimism buffered against the positive association between familial pre-migratory adversity and child internalizing symptoms. In sum, select social–emotional capacities may serve as potential protective factors that support mental health and buffer against the deleterious effects of pre-migratory adversity in refugee children.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".