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Record W2732622558 · doi:10.2196/publichealth.7397

Informing the Development of a Mobile Phone HIV Testing Intervention: Intentions to Use Specific HIV Testing Approaches Among Young Black Transgender Women and Men Who Have Sex With Men

2017· article· en· W2732622558 on OpenAlexvenueno aff
Beryl A. Koblin, Vijay Nandi, Sabina Hirshfield, Mary Ann Chiasson, Donald R. Hoover, Leo Wilton, DaShawn Usher, Victoria Frye

Bibliographic record

VenueJMIR Public Health and Surveillance · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health DisparitiesNational Institute of Child Health and Human DevelopmentEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentEmory University
KeywordsTransgender womenHuman immunodeficiency virus (HIV)TransgenderMobile phoneIntervention (counseling)Men who have sex with menAnal sexPhoneMedicinePsychologyFamily medicineComputer scienceNursingTelecommunications

Abstract

fetched live from OpenAlex

BACKGROUND: Regular human immunodeficiency virus (HIV) testing of persons at risk is critical to HIV prevention. Infrequent HIV testing and late diagnosis of HIV infection have been observed among young black men who have sex with men (MSM) and transwomen (transgender women)-two groups overrepresented in the HIV epidemic. OBJECTIVE: The objective of this study was to inform the development of a brief mobile phone intervention to increase HIV testing among young black MSM and transwomen by providing a tailored recommendation of an optimal HIV testing approach. We identified demographic, behavioral, psychosocial, and sociostructural factors associated with intentions to use three specific HIV testing approaches: self-testing, testing at a clinic or other provider, and couples HIV testing and counseling (CHTC). METHODS: Individuals were eligible for a Web-based survey if they were male at birth; were between the ages of 16 and 29 years; self-identified as black, African American, Caribbean black, African black, or multiethnic black; were not known to be HIV-infected; and reported insertive or receptive anal intercourse with a man or transwoman in the last 12 months. Recruitment occurred via banner advertisements placed on a range of social and sexual networking websites and apps in New York City and nationally, and via events attended by young black MSM and transwomen in New York City. Intention to test by each testing method was analyzed using logistic regression with best subset models and stepwise variable selection. RESULTS: Among 169 participants, intention to use a self-test was positively associated with comfort in testing by a friend or a partner at home (Adjusted odds ratio, AOR, 2.40; 95% CI 1.09-5.30), and stigma or fear as a reason not to test (AOR 8.61; 95% CI 2.50-29.68) and negatively associated with higher social support (AOR 0.48; 95% CI 0.33-0.72) and having health insurance (AOR 0.21; 95% CI 0.09-0.54). Intention to test at a clinic or other provider was positively associated with self-efficacy for HIV testing (AOR 2.87; 95% CI 1.48-5.59) and social support (AOR 1.98; 95% CI 1.34-2.92), and negatively associated with a lifetime history of incarceration (AOR 0.37; 95% CI 0.16-0.89). Intention to test by CHTC was negatively associated with higher educational level (Some college or Associate's degree vs high school graduate or less [AOR 0.81; 95% CI 0.39-1.70]; Bachelor's degree or more vs high school graduate or less [AOR 0.28; 95% CI 0.11-0.70]). CONCLUSIONS: Unique factors were associated with intention to test using specific testing approaches. These data will be critical for the development of a tailored intervention that shows promise to increase comfort and experiences with a variety of testing approaches among young black MSM and transwomen.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.116
GPT teacher head0.333
Teacher spread0.218 · 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 designQualitative
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

Citations21
Published2017
Admission routes1
Has abstractyes

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