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Record W2766054318 · doi:10.2196/publichealth.7933

Preliminary Findings of a Technology-Delivered Sexual Health Promotion Program for Black Men Who Have Sex With Men: Quasi-Experimental Outcome Study

2017· article· en· W2766054318 on OpenAlexvenueno aff
Charles H. Klein, Tamara Kuhn, Danielle Huxley, Jamie Kennel, Elizabeth Withers, Carmela Lomonaco

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 DisparitiesSmall Business Innovation Research
KeywordsReproductive healthMen who have sex with menOutcome (game theory)PsychologyHealth promotionPublic healthMedicineFamily medicinePopulationEnvironmental healthNursingHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

BACKGROUND: Human immunodeficiency virus (HIV) disproportionately affects black men who have sex with men (MSM), yet there are few evidence-based interventions specifically designed for black MSM communities. In response, the authors created Real Talk, a technology-delivered, sexual health program for black MSM. OBJECTIVE: The objective of our study was to determine whether Real Talk positively affected risk reduction intentions, disclosure practices, condom use, and overall risk reduction sexual practices. METHODS: The study used a quasi-experimental, 2-arm methodology. During the first session, participants completed a baseline assessment, used Real Talk (intervention condition) or reviewed 4 sexual health brochures (the standard of care control condition), and completed a 10-minute user-satisfaction survey. Six months later, participants from both conditions returned to complete the follow-up assessment. RESULTS: A total of 226 participants were enrolled in the study, and 144 completed the 6-month follow-up. Real Talk participants were more likely to disagree that they had intended in the last 6 months to bottom without a condom with a partner of unknown status (mean difference=-0.608, P=.02), have anal sex without a condom with a positive man who was on HIV medications (mean difference=-0.471, P=.055), have their partner pull out when bottoming with a partner of unknown HIV status (mean difference=-0.651, P=.03), and pull out when topping a partner of unknown status (mean difference=-0.644, P=.03). Real Talk participants were also significantly more likely to disagree with the statement "I will sometimes lie about my HIV status with people I am going to have sex with" (mean difference=-0.411, P=.04). In terms of attitudes toward HIV prevention, men in the control group were significantly more likely to agree that they had less concern about becoming HIV positive because of the availability of antiretroviral medications (mean difference=0.778, P=.03) and pre-exposure prophylaxis (PReP) (mean difference=0.658, P=.05). There were, however, no significant differences between Real Talk and control participants regarding actual condom use or other risk reduction strategies. CONCLUSIONS: Our findings suggest that Real Talk supports engagement on HIV prevention issues. The lack of behavior findings may relate to insufficient study power or the fact that a 2-hour, standalone intervention may be insufficient to motivate behavioral change. In conclusion, we argue that Real Talk's modular format facilitates its utilization within a broader array of prevention activities and may contribute to higher PReP utilization in black MSM communities.

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)0.012
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.064

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.062
GPT teacher head0.418
Teacher spread0.356 · 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 designNon-randomized trial
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

Citations24
Published2017
Admission routes1
Has abstractyes

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