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Record W2491914640 · doi:10.1186/s12889-016-3356-7

Reducing violence and increasing condom use in the intimate partnerships of female sex workers: study protocol for Samvedana Plus, a cluster randomised controlled trial in Karnataka state, south India

2016· article· en· W2491914640 on OpenAlexafffund
Tara Beattie, Shajy Isac, Parinita Bhattacharjee, Prakash Javalkar, Calum Davey, T. Raghavendra, Sapna Nair, Satyanarayana Ramanaik, James Blanchard, Charlotte Watts, Martine Collumbien, Stephen Moses, Lori Heise

Bibliographic record

VenueBMC Public Health · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Manitoba
FundersSouth African Medical Research CouncilDepartment for International DevelopmentDepartment for International Development, UK GovernmentUniversity of Manitoba
KeywordsMedicineDomestic violenceBiostatisticsCondomCluster randomised controlled trialSexual violencePopulationSex workIntervention (counseling)Public healthPoison controlDemographyEnvironmental healthSuicide preventionFamily medicineNursingHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

BACKGROUND: Female sex workers (FSWs) are at increased risk of HIV and STIs compared to women in the general population, and frequently experience violence in their working and domestic lives from a variety of perpetrators, which can enhance this risk. While progress has been made in addressing violence by police and clients, little work has been done to understand and prevent violence by intimate partners (IPs) among FSW populations. METHODS: Samvedana Plus is a multi-level intervention programme that works with FSWs, their IPs, the sex worker community, and the general population, and aims to reduce violence and increase consistent condom use within these 'intimate' relationships. The programme involves shifting norms around the acceptability of beating as a form of discipline, challenging gender roles that give men authority over women, and working with men and women to encourage new relationship models based on gender equity and respect. The programme will aim to cover 800 FSWs and their IPs living in 47 villages in Bagalkot district, northern Karnataka. The study is designed to assess two primary outcomes: the proportion of FSWs who report: (i) physical or sexual partner violence; and (ii) consistent condom use in their intimate relationship, within the past 6 months. The evaluation will employ a cluster-randomised controlled trial design, with 50 % of the village clusters (n = 24) randomly selected to receive the intervention for the first 24 months and the remaining 50 % (n = 23) receiving the intervention thereafter. Statisticians will be blinded to treatment arm allocation. The evaluation will use an adjusted, cluster-level intention to treat analysis, comparing outcomes in intervention and control villages at midline (12 months) and endline (24 months). The evaluation design will involve quantitative and qualitative assessments with (i) all FSWs who report an IP (ii) IPs; and process/ implementation monitoring. Baseline data collection was completed in April 2015, and endline data collection is anticipated in May 2017. CONCLUSIONS: This is an innovative intervention programme that aims to address violence by IPs as part of HIV prevention programming with FSWs. Reducing violence is expected to reduce vulnerability to HIV acquisition, and help women to work and live without fear of violence. TRIAL REGISTRATION: Clinical Trials NCT02807259 Jun 24 2016 (retrospectively registered).

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)0.018
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.048
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.018
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0070.005
Bibliometrics0.0020.002
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0040.002
Research integrity0.0050.005
Insufficient payload (model declined to judge)0.0480.006

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 head0.129
GPT teacher head0.400
Teacher spread0.271 · 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 designRandomized trial
Domainnot available
GenreProtocol

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

Citations32
Published2016
Admission routes2
Has abstractyes

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