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Record W2788728765 · doi:10.1007/s10461-018-2043-3

HIV Testing and Counseling Among Female Sex Workers: A Systematic Literature Review

2018· review· en· W2788728765 on OpenAlexaff
Anna Tokar, Jacqueline E. W. Broerse, James Blanchard, María Roura

Bibliographic record

VenueAIDS and Behavior · 2018
Typereview
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Manitoba
FundersAgència de Gestió d'Ajuts Universitaris i de RecercaGeneralitat de CatalunyaMinisterio de Economía y CompetitividadJohns Hopkins Bloomberg School of Public HealthCentres de Recerca de CatalunyaJohns Hopkins University
KeywordsHealth psychologyPublic healthHuman immunodeficiency virus (HIV)PsychologyMen who have sex with menSex workMedicineClinical psychologyFamily medicineSyphilisNursing

Abstract

fetched live from OpenAlex

HIV testing uptake continues to be low among Female Sex Workers (FSWs). We synthesizes evidence on barriers and facilitators to HIV testing among FSW as well as frequencies of testing, willingness to test, and return rates to collect results. We systematically searched the MEDLINE/PubMed, EMBASE, SCOPUS databases for articles published in English between January 2000 and November 2017. Out of 5036 references screened, we retained 36 papers. The two barriers to HIV testing most commonly reported were financial and time costs-including low income, transportation costs, time constraints, and formal/informal payments-as well as the stigma and discrimination ascribed to HIV positive people and sex workers. Social support facilitated testing with consistently higher uptake amongst married FSWs and women who were encouraged to test by peers and managers. The consistent finding that social support facilitated HIV testing calls for its inclusion into current HIV testing strategies addressed at FSW.

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)0.005
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.025
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0080.010
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.050
GPT teacher head0.358
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations100
Published2018
Admission routes1
Has abstractyes

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