Uptake and adherence to highly active antiretroviral therapy among HIV‐infected people with alcohol and other substance use problems: the impact of substance abuse treatment
Bibliographic record
Abstract
AIM: We examined the association of substance abuse treatment with uptake, adherence and virological response to highly active antiretroviral therapy (HAART) among HIV-infected people with a history of alcohol problems. DESIGN: Prospective cohort study. METHODS: A standardized questionnaire was administered to 349 HIV-infected participants with a history of alcohol problems regarding demographics, substance use, use of substance abuse treatment and uptake of and adherence to HAART. These subjects were followed every 6 months for up to seven occasions. We defined substance abuse treatment services as any of the following in the past 6 months: 12 weeks in a half-way house or residential facility; 12 visits to a substance abuse counselor or mental health professional; or participation in any methadone maintenance program. Our outcome variables were uptake of antiretroviral therapy, 30-day self-reported adherence and HIV viral load suppression. FINDINGS: At baseline, 59% (205/349) of subjects were receiving HAART. Engagement in substance abuse treatment was independently associated with receiving antiretroviral therapy (adjusted OR; 95% CI: 1.70; 1.03-2.83). Substance abuse treatment was not associated with 30-day adherence or HIV viral load suppression. More depressive symptoms (0.48; 0.32-0.78) and use of drugs or alcohol in the previous 30 days (0.17; 0.11-0.28) were associated with worse 30-day adherence. HIV viral load suppression was positively associated with higher doses of antiretroviral medication (1.29; 1.15-1.45) and older age (1.04; 1.00-1.07) and negatively associated with use of drugs or alcohol in the previous 30 days (0.51; 0.33-0.78). CONCLUSION: Substance abuse treatment was associated with receipt of HAART; however, it was not associated with adherence or HIV viral load suppression. Substance abuse treatment programs may provide an opportunity for HIV-infected people with alcohol or drug problems to openly address issues of HIV care including enhancing adherence to HAART.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".