Brief Report: Substance Use Care Continuum in Women With and Without HIV in the Southern United States
Bibliographic record
Abstract
BACKGROUND: Substance use (SU) contributes to poor outcomes among persons living with HIV. Women living with HIV (WWH) in the United States are disproportionately affected in the South, and examining SU patterns, treatment, and HIV outcomes in this population is integral to addressing HIV and SU disparities. METHODS: WWH and comparable women without HIV (WWOH) who enrolled 2013-2015 in the Women's Interagency HIV Study Southern sites (Atlanta, Birmingham/Jackson, Chapel Hill, and Miami) and reported SU (self-reported nonmedical use of drugs) in the past year were included. SU and treatment were described annually from enrollment to the end of follow-up. HIV outcomes were compared by SU treatment engagement. RESULTS: At enrollment, among 840 women (608 WWH, 232 WWOH), 18% (n = 155) reported SU in the past year (16% WWH, 24% WWOH); 25% (n = 38) of whom reported SU treatment. Over time, 30%, 21%, and 18% reported SU treatment at 1, 2, and 3 years, respectively, which did not significantly differ by HIV status. Retention in HIV care did not differ by SU treatment. Viral suppression was significantly higher in women who reported SU treatment only at enrollment ( P = 0.03). CONCLUSIONS: We identified a substantial gap in SU treatment engagement, with only a quarter reporting treatment utilization, which persisted over time. SU treatment engagement was associated with viral suppression at enrollment but not at other time points or with retention in HIV care. These findings can identify gaps and guide future strategies for integrating HIV and SU care for WWH.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".