Social processes and engagement along the HIV care continuum: a mixed methods exploratory study with diverse African American/Black and Latine emerging adults living with HIV
Bibliographic record
Abstract
BACKGROUND: Racial/ethnic and age-related disparities in HIV care continuum engagement are serious in the US. American/Black and Latine (AABL) young/emerging adults living with HIV have the lowest rates of engagement, but aspects of their experiences and some subpopulations are understudied. The present study is grounded in social action theory and uses a sequential explanatory mixed methods design to explore social interaction processes (e.g., social networks, trust), and their relationships to HIV management, in a diverse cohort including those with non-suppressed HIV viral load. METHODS: Participants engaged in baseline assessments (N = 271). A subset (N = 62) was purposively sampled for maximum variability for qualitative interviews. Quantitative data were analyzed with descriptive statistics and logistic regression. The primary outcomes were engagement in HIV care and viral suppression. Quantitative results were used to develop qualitative research questions, and qualitative data were analyzed with directed content analysis. Joint display methods were used to integrate results. RESULTS: On average, participants were 25 years old (SD = 2). The majority (59%) were Latine/Hispanic, 41% were African American/Black. Nearly all were male (96%) and sexual minorities (93%). Nearly half (49.1%) were born outside the US/Puerto Rico. Most were well-engaged in care (72%) and virally suppressed (81%). The proportion of network members who used illicit drugs reduced the odds of being well-engaged in HIV care (OR = 0.38; p = 0.014) and suppression (OR = 0.32; p = 0.009) at the bivariate level. Satisfaction with HIV care (OR = 1.18; p = 0.016) and trust in providers (OR = 1.04; p = 0.045) increased the odds of viral suppression. In qualitative results we found social networks were vital to well-being, but, like participants, located in strained socioeconomic circumstances. In this context, we organized results into five themes: (1) social losses were disruptive to HIV management; (2) service settings and care providers were important network members; (3) family disapproval of sexual/gender minority status had negative effects; (4) immigrant participants were highly reliant on service settings; and (5) networks influenced participants’ drug use and their drug use also reduced the size and changed the composition of networks. CONCLUSIONS: The present study advances knowledge on social interaction processes among diverse AABL young/emerging adults living with HIV, and highlights points of intervention.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".