Factors Associated with Preferences for Long-Acting Injectable Antiretroviral Therapy Among Adolescents and Young People Living with HIV in South Africa
Bibliographic record
Abstract
Long-acting injectable anti-retroviral therapy (LAART) may overcome barriers to long-term adherence and improve the survival of adolescents and young people living with HIV (AYLHIV). Research on the acceptability of LAART for this age-group is limited. We asked 953 AYLHIV about their preferred (theoretical) ART mode of delivery (pill, injectable, or other) in 2017-2018, before LAART was available or known to AYLHIV in South Africa. One in eight (12%) AYLHIV preferred LAART over single or multiple pill regimens. In multivariate analyses, six factors were associated with LAART preference: medication stock-outs (aOR = 2.56, 95% CI 1.40-4.68, p = 0.002), experiencing side-effects (aOR = 1.84, 95% CI 1.15-2.97, p = 0.012), pill-burden (aOR = 1.88, 95% CI 1.20-2.94, p = 0.006), past-year treatment changes (aOR = 1.63, 95% CI 1.06-2.51, p = 0.025), any HIV stigma (aOR = 2.22, 95% CI 1.39-3.53, p ≤ 0.001) and recent ART initiation (aOR = 2.02, 95% CI 1.09-3.74, p = 0.025). In marginal effects modelling, 66% of adolescents who experienced all factors were likely to prefer LAART, highlighting the potential high acceptability of LAART among adolescents and young people living with HIV struggling to adhere and have good HIV treatment outcomes. Adolescent boys who reported high ART pill burden were more likely to prefer LAART than their female peers in moderation analyses, suggesting that LAART may be particularly important to improve treatment outcomes among male AYLHIV as they become older. Adding LAART to existing treatment options for AYLHIV, particularly higher risk groups, would support AYLHIV to attain and sustain viral suppression-the third 95, and reduce their risk of AIDS-related mortality.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".