In the face of adversity: Refugee children’s traumatic stressors, trust, and prosocial behavior
Bibliographic record
Abstract
This study investigated the relationship between traumatic life stress, trust, and prosocial behavior as a positive mental health outcome in Syrian refugee children in Canada. Trust is a resilience factor shown to promote adjustment after resettlement. The specific goals of the study were to test the influence of refugee children’s traumatic life stress on their prosocial behavior and the mediating role of trust in this link. Five- to 12-year-old Syrian refugee children ( N = 124) and their caregivers ( N = 51) who recently resettled in Canada participated in this study. Children retrospectively reported their experiences of traumatic life stressors, and caregivers reported their children’s current level of trust and prosocial behavior using questionnaires. Traumatic life stress (e.g., witnessing violence and conflict, separation from family, death of family members) was negatively related to refugee children’s trust in others, while trust was related to more prosocial behaviors, confirming its mediating role. These results suggest that experiencing more traumatic life stressors is associated with less prosocial behaviors as a positive mental health outcome through lower levels of trust. The current findings suggest that fostering trust may be a promising avenue for intervention to promote prosocial behavior and resilience in refugee children who are resettling in a new society.
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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 | 0.002 | 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) | 0.001 | 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".