RELATIONSHIP BETWEEN CHILD MORTALITY, SOCIAL SUPPORT, AND PSYCHOLOGICAL DISTRESS AMONG WAR SURVIVORS IN VIETNAM
Bibliographic record
Abstract
Abstract Social support has been documented as a key factor contributing to improved well-being among grieving parents in the bereavement process. However, how different forms of support interact with the experiences of child death is less understood among aging populations in post-conflict settings. This study examined the psychological impact of child death on older Vietnamese with a focus on the mediating role of social support and the moderating effect of war exposure. Data came from the 2018 Vietnam Health and Aging Study of 2,447 older adults aged 60 and older. We assessed experience of child loss by enumerating the mortality and survivorship status for all children. Mental distress was measured using the Self-Reporting Questionnaire with nine items. Social support was conceptualized along two dimensions: 1) Received social support was divided into instrumental and emotional domains; 2) perceived social network support was broken down into functional and structural aspects. Path analysis substantiated a significant relationship between child death and heightened mental distress. Emotional and labor support significantly buffered the impact of child. Moderated mediation analysis suggested that individuals with higher levels of war exposure received a noticeable benefit from emotional support. However, other forms of support did not demonstrate a significant mediating role. Results underscore the value of emotional support in this context. Findings suggest the integration of mental health support within existing social services for older adults in Vietnam with an emphasis on providing emotional support to those who have experienced child loss.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".