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Record W3041705494 · doi:10.1186/s13031-020-00289-7

Contextual factors associated with depression among urban refugee and displaced youth in Kampala, Uganda: findings from a cross-sectional study

2020· article· en· W3041705494 on OpenAlexafffund
Carmen H. Logie, Moses Okumu, Simon Mwima, Robert Hakiza, Doreen Chemutai, Peter Kyambadde

Bibliographic record

VenueConflict and Health · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchOntario Ministry of Research, Innovation and ScienceCanada Research ChairsCanada Foundation for Innovation
KeywordsRefugeeMental healthCross-sectional studyPublic healthDepression (economics)MedicineSocial supportPsychologyClinical psychologyEnvironmental healthPsychiatrySocial psychologyGeography

Abstract

fetched live from OpenAlex

Abstract Background Advancing mental health among refugee and displaced adolescents and youth is critically important, as chronic psychological stress can have lifelong harmful impacts. These groups experience socio-environmental stressors that can harm mental health. Informed by a social contextual framework, this study explored the prevalence of depression among urban refugee and displaced youth in Kampala, Uganda and associations with symbolic (violence), relational (social support), and material (food and community insecurity) contexts. Methods We implemented a cross-sectional survey with refugee and displaced adolescent girls and young women and adolescent boys and young men aged 16–24 living in Kampala’s informal settlements. We conducted peer-driven recruitment, whereby peer navigators shared study information with their networks and in turn participants were invited to recruit their peers. We conducted gender disaggregated analyses, including stepwise multiple regression to examine factors associated with depression. We then conducted structural equation modeling (SEM) using weighted least squares estimation to examine direct paths from violence, food insecurity, and community insecurity to depression, and indirect effects through social support. Results Among participants (n = 445), young women (n = 333) reported significantly higher depression symptoms than young men (n = 112), including any symptoms (73.9% vs. 49.1%,p < 0.0001), mild to moderate symptoms (60.4% vs. 45.5%,p = 0.008), and severe symptoms (13.5% vs 3.6%,p = 0.002). SEM results among young women indicate that the latent violence factor (lifetime sexual and physical violence) had direct effects on depression and social support, but social support did not mediate the path from violence to depression. The model fit the data well: χ2(3) = 9.82,p = 0.020; RMSEA = 0.08, 90% CI [0.03, 0.14], CFI = 0.96). Among young men, SEM findings indicate that food insecurity had direct effects on social support, and an indirect effect on depression through the mediating role of social support. Fit indices suggest good model fit: χ2(3) = 2.09,p = 0.352; RMSEA = 0.02, 90% CI [0.000, 0.19], CFI = 0.99. Conclusions Findings reveal widespread depression among urban refugee and displaced youth in Kampala, disproportionately impacting young women. Contextual factors, including food insecurity and violence, increase depression risks. Strategies that reduce gender-based violence and food insecurity, and increase social support networks, have the potential to promote mental health among urban refugee and displaced youth.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.098
GPT teacher head0.368
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations49
Published2020
Admission routes2
Has abstractyes

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