The Relationships Among Social Capital, HIV Self-Management, and Substance Use in Women
Bibliographic record
Abstract
Women living with HIV (WLHIV) face unique challenges to successfully self-manage HIV including substance use and limited social capital. We conducted a 6-month mixed-methods study to describe how social capital influences HIV self-management and substance use among WLHIV. Participants completed a self-report survey and in-depth interview at baseline, and 3 and 6 months. Descriptive statistics, t-tests, and generalized estimating equations (GEEs) were used to examine quantitative relationships. Qualitative data were analyzed using qualitative description. Current substance users reported lower social capital compared with past substance users (2.63 vs. 2.80; p = .34). Over time, substance use and social capital were associated with HIV self-management (Wald χ 2 = 28.43; p < .001). Qualitative data suggest that HIV self-management is influenced by overlapping experiences with social capital, including influential trust, community, and value of self can be complicated by ongoing substance use. Social capital can facilitate improved HIV self-management; however, substance use and trauma can weaken this relationship.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".