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Record W4388288443 · doi:10.1080/09540121.2023.2277151

Exploring a syndemic of poverty, cumulative violence, and HIV vulnerability among refugee youth: multi-method insights from a humanitarian setting in Uganda

2023· article· en· W4388288443 on OpenAlexafffund
Carmen H. Logie, Miranda G. Loutet, Moses Okumu, Madelaine Coelho, Simon Odong Lukone, Nelson Kisubi, Maya Latif, Alyssa McAlpine, Peter Kyambadde

Bibliographic record

VenueAIDS Care · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsPublic Health OntarioUnited Nations University Institute for Water, Environment, and HealthWomen's College HospitalUniversity of Toronto
FundersGrand Challenges Canada
KeywordsSyndemicPovertyRefugeeTransactional sexOddsVulnerability (computing)Domestic violencePsychologyEnvironmental healthMedicinePoison controlLogistic regressionHuman immunodeficiency virus (HIV)Political sciencePopulationSuicide preventionFamily medicine

Abstract

fetched live from OpenAlex

Synergistic associations between social inequities and HIV vulnerabilities – known as a syndemic – are understudied with youth in humanitarian settings. We explored refugee youths’ HIV prevention needs in Bidi Bidi Refugee Settlement, Uganda. This multi-methods study involved 6 focus groups and 12 in-depth individual interviews (IDI) with refugee youth (n = 60) aged 16–24, and IDI with refugee elders (n = 8) and healthcare providers (n = 8). We then conducted cross-sectional surveys with refugee youth (16–24 years) (n = 115) to assess: poverty, recent sexual and gender-based violence (SGBV), and condom engagement motivation (CEM) (wanting to learn about condoms for HIV prevention). Multivariable logistic regression was used to estimate adjusted odds ratios for associations between poverty and SGBV with CEM. Qualitative narratives revealed poverty and trauma elevated substance use, and these converged to exacerbate SGBV. SGBV and transactional sex increased HIV vulnerabilities. Among survey participants, poverty and recent SGBV were associated with reduced odds of CEM. The interaction between poverty and recent SGBV was significant: the predicted probability of CEM among youth who experienced both poverty and SGBV was almost half than among youth who experienced poverty alone, SGBV alone, or neither. Findings signal the confluence of poverty, violence, and substance use elevate refugee youth HIV vulnerabilities.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.071
GPT teacher head0.338
Teacher spread0.268 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations5
Published2023
Admission routes2
Has abstractyes

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