Exploring ecosocial contexts of alcohol use and misuse during the COVID-19 pandemic among urban refugee youth in Kampala, Uganda: Multi-method findings
Bibliographic record
Abstract
Urban refugees may be disproportionately affected by socio-environmental stressors that shape alcohol use, and this may have been exacerbated by additional stressors in the COVID-19 pandemic. This multi-method study aimed to understand experiences of, and contextual factors associated with, alcohol use during the pandemic among urban refugee youth in Kampala, Uganda. We conducted a cross-sectional survey (n=335), in-depth individual interviews (IDI) (n=24), and focus groups (n=4) with urban refugee youth in Kampala. We also conducted key informant interviews (n=15) with a range of stakeholders in Kampala. We conducted multivariable logistic regression analyses with survey data to examine socio-demographic and ecosocial (structural, community, interpersonal) factors associated with ever using alcohol and alcohol misuse. We applied thematic analyses across qualitative data to explore lived experiences, and perceived impacts, of alcohol use. Among survey participants (n=335, mean age= 20.8, standard deviation: 3.01), half of men and one-fifth of women reported ever using alcohol. Among those reporting any alcohol use, half (n = 66, 51.2%) can be classified as alcohol misuse. In multivariable analyses, older age, gender (men vs. women), higher education, and perceived increased pandemic community violence against women and children were associated with significantly higher likelihood of ever using alcohol. In multivariable analyses, very low food security, relationship status, transactional sex, and lower social support were associated with increased likelihood of alcohol misuse. Qualitative findings revealed: (1) alcohol use as a coping mechanism for stressors (e.g., financial insecurity, refugee-related stigma); and (2) perceived impacts of alcohol use on refugee youth health (e.g., physical, mental). Together findings provide insight into multi-level contexts that shape vulnerability to alcohol mis/use among urban refugee youth in Kampala and signal the need for gender-tailored strategies to reduce socio-environmental stressors.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 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".