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Record W2115769001 · doi:10.1017/s0021932010000647

RISKY BEHAVIOUR AND HIV PREVALENCE AMONG ZAMBIAN MEN

2011· article· en· W2115769001 on OpenAlexaff
Nisha Malhotra, Jonathan Yang

Bibliographic record

VenueJournal of Biosocial Science · 2011
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent Sexual and Reproductive Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSerostatusDemographyCondomMedicineSocioeconomic statusPopulationOdds ratioCross-sectional studyLogistic regressionSexual intercourseConfidence intervalEnvironmental healthGerontologyHuman immunodeficiency virus (HIV)ImmunologyViral loadInternal medicine

Abstract

fetched live from OpenAlex

The objective of this paper is to identify demographic, social and behavioural risk factors for HIV infection among men in Zambia. In particular, the role of alcohol, condom use and number of sex partners is highlighted as being significant in the prevalence of HIV. Multivariate logistic regressions were used to analyse the latest cross-sectional population-based demographic health survey for Zambia (2007). The survey included socioeconomic variables and HIV serostatus for consenting men (N = 4434). Risk for HIV was positively related to wealth status. Men who considered themselves to be at high risk of being HIV positive were most likely to be HIV positive. Respondents who, along with their sexual partner, were drunk during the last three times they had sexual intercourse were more likely to be HIV positive (adjusted odds ratio (AOR) 1.60; 95% confidence interval (CI) 1.00-2.56). Men with more than two sexual life partners and inconsistent condom use had a higher risk for being HIV positive (OR 1.89, 95% CI 1.45-2.46; and OR 1.49, 95% CI 1.10-2.02, respectively). HIV prevention programmes in Zambia should focus even more on these behavioural risk factors.

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)0.000
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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.118
GPT teacher head0.429
Teacher spread0.311 · 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

Citations5
Published2011
Admission routes1
Has abstractyes

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