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Record W1964768923 · doi:10.1177/1010539514537677

Evaluation of a Community-Based HIV Preventive Intervention for Female Sex Workers in Rural Areas of Karnataka State, South India

2014· article· en· W1964768923 on OpenAlexaff
Reynold Washington, Anita Nath, Shajy Isac, Prakash Javalkar, Banadakoppa M Ramesh, Parinita Bhattacharjee, Stephen Moses

Bibliographic record

VenueAsia Pacific Journal of Public Health · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Manitoba
FundersUnited States Agency for International Development
KeywordsOutreachCondomMedicineReferralIntervention (counseling)Community health workersRural areaFamily medicineEnvironmental healthReproductive healthHuman immunodeficiency virus (HIV)Community healthProgram evaluationHotlineDemographyPublic healthPopulationNursingHealth servicesSyphilis

Abstract

fetched live from OpenAlex

To examine changes in behavioral outcomes among rural female sex workers (FSWs) involved in a community-based comprehensive HIV preventive intervention program in south India. A total of 14, 284 rural FSWs were reached by means of a community-based model for delivering outreach, medical, and referral services. Changes in behavior were assessed using 2 rounds of polling booth surveys conducted in 2008 and 2011. In all, 95% of the mapped FSWs were reached at least once, 80.3% received condoms as per need, and 71% received health services for sexually transmitted infections. There was a significant increase in condom use (from 60.4% to 72.4%, P = .001) and utilization of HIV counseling and testing services (from 63.9% to 92.4%; P = .000) between the 2 time periods. This model for a community-based rural outreach and HIV care was effective and could also be applied to many other health problems.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.383
Teacher spread0.308 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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