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Record W3005281102 · doi:10.2196/14743

Web-Supported Social Network Testing for HIV Among Men Who Have Sex With Men With a Migration Background: Protocol for a Mixed Methods Pilot Study

2020· article· en· W3005281102 on OpenAlexvenueno aff
Eline Op de Coul, Chantal den Daas, Ralph Spijker, Titia Heijman, Marvin de Vos, Hannelore M Götz, Koenraad Vermey, Wim Zuilhof, Jossy van den Boogaard, Udi Davidovich, Freke Zuure

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersUniversiteit MaastrichtUniversiteit Utrecht
KeywordsMen who have sex with menSocial network (sociolinguistics)Sexual orientationMedicineStigma (botany)Human immunodeficiency virus (HIV)Peer groupPsychologyFamily medicineSocial mediaSocial psychologyWorld Wide WebPsychiatryComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Of newly diagnosed HIV positive men who have sex with men (MSM) in the Netherlands, 29% have a non-Western migration background (MSM-NW). Among MSM-NW, HIV positivity rates are high (0.8%-2.0%), as is the proportion of late stage infections (39%). Factors such as HIV and sexual orientation-related stigma may form barriers for timely testing. Innovative approaches for HIV testing are needed to better reach MSM-NW. Social network testing (SNT) for HIV is an evidence-supported approach where peer recruiters identify persons (network associates) who could benefit from testing in their social or sexual networks. Web-supported SNT might be particularly promising for reaching people who may not be reached by regular care. OBJECTIVE: The purpose of this paper is to describe the design of our pilot PREVENT (Peer-Empowered Voluntary Extended Network Testing). In this pilot, we will explore whether SNT using HIV self-tests is feasible and acceptable among MSM-NW in the Netherlands and whether it reaches those who were never or not recently tested for HIV (>1 year ago). METHODS: The project aims to include 50 to 60 MSM and MSM-NW peers who will distribute 4 to 5 oral HIV self-tests each aiming to reach 200 network associates (NAs). Enrollment of peers includes 4 steps: (1) fostering interest in becoming a peer by health care professionals at sexual health clinics, HIV treatment clinics, and community settings; (2) sending peer contact information to the peer coordinator; (3) registering peers and giving program instructions by the peer coordinator and referring to the Web-based training at time2test; and (4) receiving precoded HIV self-tests for distribution in the peers' networks. NAs who receive the self-test will log in with their test package code in the time2test application for step-by-step test instructions. After testing is complete, NAs receive tailored follow-up information depending on their test result. RESULTS: Between January and May 2019, 10 STI clinics and 7 HIV treatment clinics started recruiting peers. Results of the PREVENT pilot are expected in December 2020. CONCLUSIONS: This is the first Web-supported peer-driven SNT pilot using HIV self-tests in the Netherlands and one of the first in Europe. Implementation is considered successful if it reaches MSM-NW who were never or not recently tested for HIV. Additionally, it may encourage conversations within the networks about risk behavior and barriers to HIV testing, potentially contributing to the Joint United Nations Programme on HIV/AIDS goal of zero HIV infections. TRIAL REGISTRATION: Netherlands Trial Registry NL7424; https://www.trialregister.nl/trial/7424. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/14743.

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)0.043
metaresearch head score (Gemma)0.028
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.068
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0430.028
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.002
Science and technology studies0.0050.002
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0680.013

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 head0.339
GPT teacher head0.571
Teacher spread0.232 · 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 designNot applicable
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

Citations5
Published2020
Admission routes1
Has abstractyes

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