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Record W2991118087 · doi:10.2196/16401

An Employment Intervention Program (Work2Prevent) for Young Men Who Have Sex With Men and Transgender Youth of Color (Phase 2): Protocol for a Single-Arm Mixed Methods Pilot Test to Assess Feasibility and Acceptability

2019· article· en· W2991118087 on OpenAlexvenueno aff
Brandon J. Hill, Darnell Motley, Kris Rosentel, Alicia VandeVusse, Robert Garofalo, John A. Schneider, Lisa M. Kuhns, Michele D. Kipke, Sari L. Reisner, Betty Rupp, Maria Sanchez, Micah McCumber, Laura Renshaw, Rachel West Goolsby, Matthew Shane Loop

Bibliographic record

VenueJMIR Research Protocols · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Minority Health and Health DisparitiesNational Institute of Child Health and Human DevelopmentNational Institute of Mental HealthUniversity of North Carolina at Chapel HillNational Institutes of Health
KeywordsIntervention (counseling)TransgenderMen who have sex with menWomen of colorSexual orientationPublic healthPsychologyGerontologyYoung adultMedicineClinical psychologyFamily medicineHuman immunodeficiency virus (HIV)Social psychologyNursingPsychiatrySociologyRace (biology)Gender studies

Abstract

fetched live from OpenAlex

BACKGROUND: Young cisgender men who have sex with men (YMSM), young transgender women (YTW), and gender nonconforming (GNC) youth of color face substantial economic and health disparities. In particular, HIV risk and infection among these groups remains a significant public health issue. In 2017, 17% of all new HIV diagnoses were attributed to male-to-male sexual contact among adolescents and young adults aged 13 to 24 years. However, such disparities cannot be attributed to individual-level factors alone but rather are situated within larger social and structural contexts that marginalize and predispose YMSM, YTW, and GNC youth of color to increased HIV exposure. Addressing social and structural risk factors requires intervention on distal drivers of HIV risk, including employment and economic stability. The Work2Prevent (W2P) study aims to target economic stability through job readiness and employment as a structural-level intervention for preventing adolescent and young adult HIV among black and Latinx YMSM, YTW, and GNC youth. This study seeks to assess intervention feasibility and acceptability in the target populations and determine preliminary efficacy of the intervention to increase employment and reduce sexual risk behaviors. OBJECTIVE: The goal of the research is to pilot-test a tailored, theoretically informed employment intervention program among YMSM, YTW, and GNC youth of color. This intervention was adapted from Increased Individual Income and Independence, an existing evidence-based employment program for HIV-positive adults during phase 1 of the W2P study. METHODS: The employment intervention will be pilot-tested among vulnerable YMSM, YTW, and GNC youth of color in a single-arm pre-post trial to assess feasibility, acceptability, and preliminary estimates of efficacy. RESULTS: Research activities began in March 2018 and were completed in November 2019. Overall, 5 participants were enrolled in the pretest and 51 participants were enrolled in the pilot. CONCLUSIONS: Interventions that address the social and structural drivers of HIV exposure and infection are sorely needed in order to successfully bend the curve in the adolescent and young adult HIV epidemic. Employment as prevention has the potential to be a scalable intervention that can be deployed among this group. TRIAL REGISTRATION: ClinicalTrials.gov NCT03313310; https://clinicaltrials.gov/ct2/show/NCT03313310. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/16401.

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)0.019
metaresearch head score (Gemma)0.014
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 score0.056
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.014
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0020.001
Science and technology studies0.0050.002
Scholarly communication0.0020.003
Open science0.0040.003
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0560.009

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 head0.407
GPT teacher head0.627
Teacher spread0.220 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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