A prospective longitudinal study of depression, perceived stress, and perceived control in resettled Syrian refugees’ mental health and psychosocial adaptation
Bibliographic record
Abstract
= 235). Specifically, depressive symptoms, perceived stress, and perceived control were collected in Arabic at baseline and 1-year follow-up. Two theory-informed, cross-lagged panel models demonstrated that higher baseline depressive symptoms predicted lower perceived self-efficacy and lower perceived control at 1-year follow-up. Similarly, baseline depressive symptoms were concurrently correlated with higher perceived helplessness, lower perceived self-efficacy, and lower perceived control. Secondary regression analyses further demonstrated that baseline depressive symptoms predicted lower perceived social support and higher anxiety symptoms, though neither were assessed at baseline. Empirical results identify a potentially broad, precipitating, and persistent effect of depressive symptoms on Syrian refugees' psychosocial resources and adaptation post-migration, which is consistent with both the transactional model of stress and coping and the self-efficacy theory of depression, respectively. Clinically, the study results highlight the importance of early screening for depressive symptoms among refugee newcomers within a culturally and trauma-informed, integrated health setting. Furthermore, this study underscores the value and need for theoretically guided longitudinal studies to advance future research on refugee mental health and psychosocial adaptation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".