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Record W2763247684 · doi:10.1177/2325957417732834

Consistent Condom Use with Paying and Nonpaying Partners among Female Sex Workers in Iran: Findings of a National Biobehavioral Survey

2017· article· en· W2763247684 on OpenAlexaff
Mohammad Karamouzian, Behnam Sadeghirad, Hamid Sharifi, Abbas Sedaghat, Ali Akbar Haghdoost, Ali Mirzazadeh

Bibliographic record

VenueJournal of the International Association of Providers of AIDS Care (JIAPAC) · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsMcMaster UniversityUniversity of British Columbia
FundersKerman University of Medical SciencesGlobal Fund to Fight AIDS, Tuberculosis and Malaria
KeywordsCondomMedicineDemographyPromotion (chess)Psychological interventionFemale sexSex workSex workersEnvironmental healthPopulationHuman immunodeficiency virus (HIV)Family medicineNursingResearch methodologySyphilis

Abstract

fetched live from OpenAlex

OBJECTIVES: Little is known about the dynamics of condom use among female sex workers (FSWs) in Iran. We investigated the correlates of consistent condom use (CCU) among FSWs, using data from a national biobehavioral surveillance survey in 2010. METHODS: A total of 872 FSWs were recruited using a facility-based sampling strategy from 21 sites in 13 cities in Iran. Data were collected through face-to-face interviews using a standardized questionnaire. RESULTS: Overall, 33.6% and 17.3% of FSWs reported CCU with paying and nonpaying sex partners, respectively. Consistent condom use with paying partners was significantly associated with temporary marriage, accessing family planning services and history of working in brothels. Conversely, temporary marriage or married status, condom rupture/slippage, and HIV seropositivity remained independently significantly associated with CCU with nonpaying sex partners. CONCLUSION: Our findings indicated the urgent need for scaling up condom promotion interventions catered toward FSWs and their sex partners to practice safe sex consistently.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.027
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.054
GPT teacher head0.342
Teacher spread0.288 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

Explore more

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