The roles of attachment and social support in post-traumatic stress among refugees and asylum seekers
Bibliographic record
Abstract
BACKGROUND: Refugees and asylum seekers (RAS) are often exposed to stressors before, during, and after migration, with trauma and post-migration living difficulties (PMLD) frequently associated with elevated post-traumatic stress (PTS). Preliminary studies suggest that attachment insecurity plays a role in the link between PMLD and PTS in RAS. However, the mechanisms by which attachment insecurity mediates PTS are not well understood. Perceived social support may represent a key psychological pathway through which attachment insecurity impacts PTS. OBJECTIVES: This study investigated 1) whether attachment insecurity (i.e. anxious and avoidant attachment) mediates the association between stressors (i.e., trauma exposure, PMLD) and PTS, and 2) whether perceived social support further mediates the relationship between attachment insecurity and PTS. METHODS: The sample comprised 417 RAS (54.0 % male; mean age 33.7 years) from eight different regions in Switzerland. Participants responded to questionnaires assessing trauma exposure, PMLD, attachment insecurity, perceived social support, and PTS. Path analysis was used to test two models: 1) a mediation model (i.e., model 1) with attachment anxiety and avoidance as mediators between stressors (i.e., trauma, PMLD) and PTS, and 2) model 1 with perceived social support as an additional mediator between attachment insecurity and PTS. RESULTS: Attachment anxiety and avoidance mediated the association between PMLD and PTS, but not between trauma and PTS. Perceived social support did not improve explained variance in PTS. CONCLUSIONS: Attachment is an important psychological mechanism when studying traumatised RAS who experience substantial PMLD. The role of perceived social support needs to be further investigated.
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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 | 0.004 |
| 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 | 0.001 |
| 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".