Psychosocial support during displacement due to a natural disaster: relationships with distress in a lower-middle income country
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Past studies show relationships between disaster-related displacement and adverse psychosocial health outcomes. The development of psychosocial interventions following displacement is thus increasingly prioritized. However, data from low- and middle-income countries (LMICs) are lacking. In October 2017, the population of Ambae Island in Vanuatu, a lower-middle income country, was temporarily displaced due to volcanic activity. We analyzed distress among adults displaced due to the event and differences based on the psychosocial support they received. METHODS: Data on experiences during displacement, distress and psychosocial support were collected from 443 adults 2-3 wk after repatriation to Ambae Island. Four support categories were identified: Healthcare professional, Traditional/community, Not available and Not wanted. We analyzed differences in distress by sex and group using one-way ANOVA and generalized linear models. RESULTS: Mean distress scores were higher among women (1.90, SD=0.97) than men (1.64, SD=0.98) (p<0.004). In multivariate models, psychosocial support group was associated with distress among women (p=0.033), with higher scores among women who reported no available support compared with every other group. Both healthcare professional and traditional support networks were widely used. CONCLUSIONS: Women might be particularly vulnerable to distress during disaster-related displacement in LMICs, and those who report a lack of support might be at greater risk. Both healthcare professional and traditional networks provide important sources of support that are widely used and might help to ameliorate symptoms.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it