HIV medication adherence, substance use, sexual risk behaviors and psychological distress among younger black men who have sex with men and transgender women: Preliminary findings
Bibliographic record
Abstract
Background: In the United Sates, young Black men who have sex with men and transgender women (YBMSM/TW) ages 16 to 29 bear the highest burden of new HIV infections. HIV medication adherence is critical for maintaining the quality of life for infected persons, supporting secondary prevention efforts and reducing community viral loads. However, few studies have examined the relationship between medication adherence and health related factors such as substance use, sexual risk behaviors and psychological distress symptoms among YBMSM/TW. This represents the primary focus of this exploratory study. Methods: B aseline data is from Project nGage, a RCT that enroll ed 86 newly diagnosed YBMSM/TW (age s 18-29). Measures on medication adherence, substance use, sexual risks behaviors and psychological distress symptoms were assessed. Results: Study findings indicated that medication adherence was related to less alcohol use, alcohol desire, alcohol compulsion, and having a partner who used marijuana as a sex drug. Findings also indicated that medication adherence was related to decreased feelings of psychological distress. Study findings did not indicate any relationship between medication adherence and group or unprotected anal sex. Conclusion: Our study findings indicated that HIV medication adherence, among YBMSM/TW was a significant correlate of lower substance use and psychological distress, and that service providers may enhance such gains by promoting medication adherence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".