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Record W4310049721 · doi:10.2196/44157

A Peer-Led Digital Intervention to Reduce HIV Prevention and Care Disparities Among Young Brazilian Transgender Women (The BeT Study): Protocol for an Intervention Study

2022· article· en· W4310049721 on OpenAlexvenueno aff
Emília M. Jalil, Erin C. Wilson, Laylla Monteiro, Thaylla Varggas, Isabele Moura, Thiago S. Torres, Brenda Hoagland, Sandra Wagner Cardoso, Ronaldo I. Moreira, Valdiléa G. Veloso, Beatriz Grinsztejn

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Child Health and Human DevelopmentNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthStrong
KeywordsPsychological interventionTransgenderMedicineFamily medicineGerontologyIntervention (counseling)Transgender womenMen who have sex with menPsychologyHuman immunodeficiency virus (HIV)Psychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The HIV epidemic continues to disproportionately burden marginalized populations despite the availability of effective preventive and therapeutic interventions. Transgender women are severely affected by HIV worldwide including in Brazil and other low- and middle-income countries, with evidence of increasing new infections among young people. There is an urgent need for youth-specific HIV prevention and care interventions for young transgender women in Brazil. OBJECTIVE: This study aims to (1) address stigma in the Brazilian public health system and (2) reduce barriers to HIV care and prevention with systems navigation among young transgender women aged 18-24 years in Rio de Janeiro, Brazil. METHODS: The Brilhar e Transcender (BeT) study is a status-neutral, peer-led, single-arm digital intervention study enrolling 150 young transgender women in Rio de Janeiro, Brazil. The intervention was pilot tested and refined using data from a formative phase. The BeT intervention takes place over 3 months, is delivered remotely via mobile phone and in person by peers, and comprises three components: (1) BeT sessions, (2) digital interactions, and (3) automated messages. Eligibility criteria include identifying as transgender women, being aged 18-24 years, speaking in Portuguese, and living in the Rio de Janeiro metropolitan area in Brazil. The primary outcomes are HIV incidence, pre-exposure prophylaxis uptake, linkage to HIV care, and viral suppression. Primary outcomes were assessed at baseline and quarterly for 12 months. Participants respond to interviewer-based surveys and receive tests for HIV and sexually transmitted infections. RESULTS: The study has been approved by the Brazilian and the US local institutional review boards in accordance with all applicable regulations. Study recruitment began in February 2022 and was completed in early July 2022. Plans are to complete the follow-up assessment of study participants on July 2023, analyze the study data, and disseminate intervention results by December 2023. CONCLUSIONS: Interventions to engage a new generation of transgender women in HIV prevention and care are needed to curb the epidemic. The BeT study will evaluate a digital peer-led intervention for young transgender women in Brazil, which builds on ways young people engage in systems and uses peer-led support to empower transgender youth in self-care and health promotion. A promising evaluation of the BeT intervention may lead to the availability of this rapidly scalable status-neutral HIV intervention that can be translated throughout Brazil and other low- and middle-income countries for young transgender women at high risk of or living with HIV. TRIAL REGISTRATION: ClinicalTrials.gov NCT05299645; https://clinicaltrials.gov/ct2/show/NCT05299645. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44157.

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)0.016
metaresearch head score (Gemma)0.015
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 score0.063
Threshold uncertainty score0.212

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.015
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0020.003
Open science0.0030.003
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0630.008

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 head0.163
GPT teacher head0.552
Teacher spread0.389 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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