The Relationship between Trauma and Attachment in Burundi’s School-Aged Children
Bibliographic record
Abstract
The exposure of children and adolescents to trauma is one of the most important public health challenges. These childhood experiences play a role in children's attachment patterns with their parents and peers. The objective of this study was to examine the relationship between exposure to trauma and the degree of attachment representations in school-aged children in Burundi. One hundred thirteen vulnerable children aged 7 to 12 years were recruited and referred by their teachers. We used an event list including the post-traumatic reaction index to measure their exposure to traumatic events and the People in My Life instrument to measure attachment representations. The results revealed that the children had experienced or witnessed at least one traumatic event. The results indicated that secure attachment representations were highest among children with their parents and lowest among children with their peers. The relationship between trauma experiences and children's attachment representations was significant with their parents and with their peers. Children's attachment representations with their parents and peers predicted their traumatic experiences. Future research should focus on how attachment relationships can facilitate counselors and clinicians in providing preventive psycho-education to adults and children to develop healthier functioning, through better knowledge of the complex interplay between traumas.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".