Patient support and education for promoting adherence to highly active antiretroviral therapy for HIV/AIDS
Bibliographic record
Abstract
BACKGROUND: Highly active antiretroviral therapy is associated with improved health outcomes for people living with HIV/AIDS. Unfortunately, full therapeutic benefit from HAART may require near-perfect adherence to prescribed regimens. OBJECTIVES: To determine the effectiveness of patient support and education interventions for improving adherence to highly active antiretroviral therapy (HAART) in people living with HIV and AIDS. SEARCH STRATEGY: Studies were identified using AIDSLINE, MEDLINE, CINAHL, HEALTHSTAR, PSYCHLIT, SOCIOLOGICAL ABSTRACTS, INTERNATIONAL PHARMACEUTICAL ABSTRACTS, SCIENCE CITATION INDEX, EMBASE, and abstracts from global AIDS meetings, ICAAC, and other major meetings from January 1996 to April 1999. Further information was sought through contact with authors, reference lists, and Collaborative Review Group databases. SELECTION CRITERIA: To be included, studies had to describe a supportive or educational intervention to improve adherence to a HAART regimen in HIV positive patients, and include a comparison group. Eligible HAART regimens were defined as consisting of at least three anti-HIV drugs one of which must be a protease inhibitor or non-nucleoside reverse transcriptase inhibitor. At least one measure of adherence was also required. DATA COLLECTION AND ANALYSIS: Data on study design, participants, interventions, and outcomes were extracted from the reports onto specifically designed data collection forms by at least two reviewers. MAIN RESULTS: One study satisfied the eligibility criteria. It compared a pharmacist-led intervention consisting of educational counseling and availability of follow-up telephone support with conventional dispensing of HAART pills. This intervention significantly improved adherence to HAART, and adherence to HAART significantly predicted undetectable viral load at 24 weeks. However, participating in the intervention did not significantly predict a subsequently undetectable viral load at 24 weeks. REVIEWER'S CONCLUSIONS: Implications for practice Currently a pharmacist-led program of educational and supportive counseling is the only available intervention which has been shown in a controlled study to improve adherence to HAART, with less evidence that viral load is subsequently reduced. Implications for research Controlled trials are urgently needed to determine which interventions can significantly improve adherence to HAART. Whether interventions that improve adherence also suppress viral load and improve clinical outcomes should also be considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".