Applying the Index of Vulnerability approach to understand water insecurity and other social-ecological factors associated with depression among urban refugee youth in Kampala, Uganda
Bibliographic record
Abstract
Water insecurity and other social-ecological factors may be associated with depression in low and middle-income contexts (LMICs). This is understudied among urban refugee youth in LMICs, who experience multiple forms of marginalization. We conducted a cross-sectional survey with a peer-driven sample of urban refugee youth aged 16–24 in Kampala, Uganda. We explored: the prevalence of depression (moderate, moderately severe); associations between social-ecological (structural, community, interpersonal, intrapersonal) factors and depression; and associations between an Index of Vulnerability (IoV) comprised of social-ecological stressors and depression. Among n = 335 participants (mean age: 20.8 years, standard deviation: 3.1), in multivariable analyses, longer time in Uganda, water insecurity, lower social support, parenthood, and recent intimate partner violence were associated with moderate depression; and longer time in Uganda, water insecurity, and lower social support were associated with moderately severe depression. IoV scores were associated with moderate depression among men and women, and moderately severe depression among women. The IoV scores accounted for more variance in moderate/moderately severe depression among women than any single indicator; among men, water insecurity was most strongly associated with moderate depression. Future research can explore strategies to address water insecurity and other social-ecological stressors to promote health and wellbeing with urban refugee youth.
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How this classification was reachedexpand
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 | 0.001 | 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) | 0.000 | 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 teacher head, 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".