MétaCan
Menu
Back to cohort
Record W3125011885 · doi:10.3390/sexes2010006

Sexually Transmitted Infections among Street, Hotel, and Residence-Based Female Sex Workers in Dhaka, Bangladesh: Prevalence from Three HIV/STI Drop-in-Centers

2021· article· en· W3125011885 on OpenAlexaff
Tasmia Jebin Farabi, Yamin Tauseef Jahangir, Afrin Ahmed Clara, Mohammad Hayatun Nabi, Mohammad Delwer Hossain Hawlader

Bibliographic record

VenueSexes · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMedicineResidencePsychological interventionCondomDemographyEnvironmental healthFemale sexGerontologyHuman immunodeficiency virus (HIV)SyphilisFamily medicineNursing

Abstract

fetched live from OpenAlex

Introduction: Considering a growing number of female sex workers (FSWs) in Bangladesh, there remains a greater need to reduce sexually transmitted infection (STI) rates, as lower social and cultural status cause FSWs to have less access to education, employment opportunities, and health care, including opportunities for HIV tests, counseling, and medical care. Methods: A cross-sectional study was conducted among 546 street, hotel, and residence-based FSWs. This current study aimed to identify the prevalence and to ascertain the associated risk factors among the FSW populations in Dhaka. Results: We found a majority of the participants were in the working age of more than 26 years for the FSW profession, with a mean age of 28 years. While the majority were unemployed (42.5%), alcohol abuse (p = 0.01) and drug dependency (p = 0.01) had an association, and inconsistency of condom use had a higher risk factor (AOR = 3.54) for a new STI case. Conclusions: FSW-oriented service platform should be integrated with health literacy interventions in urban and rural locations in Bangladesh. Understanding the differences in risk patterns and tailoring intervention will increase contraception use and lower STI cases and improve overall FSW quality of life.

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 score0.147
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.268
Teacher spread0.252 · 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueSexesSame topicSex work and related issuesFrench-language works237,207