Antiretroviral therapy interruption among HIV positive people who use drugs in a setting with a community-wide HIV treatment-as-prevention initiative
Bibliographic record
Abstract
HIV Treatment as Prevention (TasP) initiatives promote antiretroviral therapy (ART) access and optimal adherence (≥95 %) to produce viral suppression among people living with HIV (PLHIV) and prevent the onward transmission of HIV. ART treatment interruptions are common among PLHIV who use drugs and undermine the effectiveness of TasP. Semi-structured interviews were conducted with 39 PLHIV who use drugs who had experienced treatment ART interruptions in a setting with a community-wide TasP initiative (Vancouver, Canada) to examine influences on these outcomes. While study participants attributed ART interruptions to “treatment fatigue,” our analysis revealed individual, social, and structural influences on these events, including: (1) prior adverse ART-related experiences among those with long-term treatment histories; (2) experiences of social isolation; and, (3) breakdowns in the continuity of HIV care following disruptive events (e.g., eviction, incarceration). Findings reconceptualise ‘treatment fatigue’ by focusing attention on its underlying mechanisms, while demonstrating the need for comprehensive structural reforms and targeted interventions to optimize TasP among drug-using PLHIV.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".