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Record W2995733933 · doi:10.1186/s13031-019-0242-9

Social ecological factors associated with experiencing violence among urban refugee and displaced adolescent girls and young women in informal settlements in Kampala, Uganda: a cross-sectional study

2019· article· en· W2995733933 on OpenAlexafffund
Carmen H. Logie, Moses Okumu, Simon Mwima, Robert Hakiza, Kibathi Peter Irungi, Peter Kyambadde, Emmanuel Kironde, Manjulaa Narasimhan

Bibliographic record

VenueConflict and Health · 2019
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsWomen's College HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchOntario Ministry of Research, Innovation and ScienceCanada Research ChairsCanada Foundation for InnovationWorld Health Organization
KeywordsRefugeeCross-sectional studyPublic healthHuman settlementInformal settlementsEnvironmental healthPoison controlHuman factors and ergonomicsMedicineSuicide preventionInjury preventionOccupational safety and healthHealth services researchBiostatisticsInternally displaced personEpidemiologySocioeconomicsGeographyDemographyPopulationSociologyEconomic growth

Abstract

fetched live from OpenAlex

Abstract Background Research on violence targeting urban forcibly displaced adolescent girls and young women (AGYW) is limited, particularly regarding polyvictimization (exposure to multiple forms of violence). Yet there is a global trend of refugee urbanization, and urban AGYW are at the nexus of violence disparities among adolescents, forcibly displaced persons, and slum dwellers. This study explored factors associated with young adulthood violence (> 16 years) (YAV) and intimate partner violence (IPV) among forcibly displaced AGYW in Kampala, Uganda. Methods We conducted a cross-sectional survey with forcibly displaced AGYW aged 16–24 from five informal settlement (slum) communities across Kampala (Kabalagala, Rubaga, Kansanga, Katwe, Nsambya) using peer network sampling. We assessed YAV (experienced at age 16 or above) (sexual, physical, emotional violence) and recent (past 12-month) IPV (physical, sexual, control violence). We conducted descriptive statistics, followed by multinomial logistic regression analyses to explore social ecological factors (e.g., intrapersonal: depression; interpersonal: sexual relationship power, community: food insecurity) associated with experiencing YAV and YAV polyvictimization, and IPV and IPV polyvictimization. Results Over half of participants (n = 333; mean age = 19.31; SD = 2.56, range = 16–24) reported YAV (n = 179; 53.7%) and 9.3% (n = 41) reported YAV polyvictimization. Most participants that were in an intimate relationship in the last 12 months (n = 200; 85.8%) reported IPV, among these, 45.5% reported one form of IPV and 54.5% reported IPV polyvictimization. In adjusted analyses, experiencing any YAV was significantly associated with: adolescent sexual and reproductive health (SRH) stigma; sexual relationship power; mobile app usage; depressive symptoms; childhood abuse; and childhood polyvictimization. In adjusted analyses YAV polyvictimization was associated with: depressive symptoms; childhood polyvictimization; sexual relationship power; and food insecurity. Recent IPV polyvictimization in adjusted analyses was associated with owning/using a mobile phone and depressive symptoms. Participants with higher sexual relationship power had lower odds of recent IPV polyvictimization. Conclusion Findings suggest that YAV and IPV polyvictimization require urgent attention among forcibly displaced AGYW in Kampala. Multi-level strategies are required to address intrapersonal e.g. (depression), interpersonal (e.g. childhood abuse, sexual relationship power) and community (e.g. adolescent SRH stigma, food insecurity) factors associated with experiencing violence. Future research can tailor approaches to advance health, agency and human rights among urban forcibly displaced AGYW.

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)0.001
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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.108
GPT teacher head0.433
Teacher spread0.324 · 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

Citations85
Published2019
Admission routes2
Has abstractyes

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