Multi-tablet, Single-Tablet, or Long-Acting Antiretroviral Treatment for HIV: A Cross-sectional Study of Patient Preferences in the United States and Spain
Bibliographic record
Abstract
Adherence to antiretroviral therapy (ART) underpins the successful treatment of HIV infection. New long-acting injectable ART agents have recently been approved by the United States Food and Drug Administration, the European Medicines Agency, and Health Canada, among other regulatory agencies, but are not routinely given to people with HIV (PWH). In this cross-sectional survey study, PWH in the USA and Spain completed a survey exploring their preference regarding oral versus injectable ART. Chi-square tests were used to determine differences between variables and univariate and multivariate testing were used to examine factors associated with preference. The most preferred ART option in the USA was one ART tablet once a day (44.4%), whereas in Spain it was an intramuscular (IM) ART injection once every two months (61.9%). Among all participants, having received an HIV diagnosis more recently, less satisfaction with current ART, and having received an IM injection in the past were associated with a preference for IM ART. Limitations include the cross-sectional design and the convenient sample. Further research employing mixed methodology is warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".