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Record W2066297743 · doi:10.12927/whp.2009.20399

Gender-Related Factors Influencing HIV Serostatus Disclosure in Patients Receiving HAART in West Africa

2009· article· en· W2066297743 on OpenAlexvenueno aff
Cathy Ndiaye, Cathérine Boileau, Marı́a Victoria Zunzunegui, S. Koala, S. Ag Aboubacrine, Pascal Niamba, Vincent Nguyen, S. Rashed

Bibliographic record

VenueWorld health & population · 2009
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
Fundersnot available
KeywordsSerostatusHuman immunodeficiency virus (HIV)MedicineEnvironmental healthFamily medicineViral load

Abstract

fetched live from OpenAlex

Disclosure of HIV serostatus remains an important tool for the prevention of new infections and early initiation of treatment for HIV-positive individuals' regular sexual partners. Our aim is to identify factors associated with disclosure to partner in patients taking antiretroviral treatment, with a gender- and sex-based approach. In this study conducted in Mali and Burkina Faso, men (154) and women (164) who reported being in a marital or cohabitating relationship were included. Sex-specific bivariate analyses and multivariate logistic regression were performed to identify determinants of disclosure. Disclosure to partner was 72.1% in men and 79.9% in women. Results of bivariate and multivariate analyses indicated that cohabiting with partner was strongly associated with disclosure in both men and women. In men only, older age, literacy and having good communication with the treating doctor were significantly associated with disclosure. Among women, disclosure was associated with having children and high self-reported importance of religion. Future research and interventions promoting disclosure should take into account these differences reflecting the social construction of gender roles in these settings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.014
Threshold uncertainty score0.558

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.036
GPT teacher head0.345
Teacher spread0.309 · 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 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

Citations25
Published2009
Admission routes1
Has abstractyes

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