The Adherence Support Gap: The ‘Ideal' Versus ‘Reality’ of Antiretroviral Adherence Support Provided by HIV Health Providers in Clinical Practice
Bibliographic record
Abstract
BACKGROUND: Guidelines suggest that clinicians should provide their patients with antiretroviral adherence support, but there is uncertainty about the types of adherence support clinicians think are important, the methods they use to provide adherence support, and the barriers they face in providing such support in clinical practice. OBJECTIVE: To study clinician perspectives on the importance of different antiretroviral adherence support activities and compare these with clinicians' self-reported actual adherence support practices. METHODS: From March to August 2005, surveys were mailed to physicians, pharmacists, and nurses who provide care to HIV patients in Ontario, Canada. The 84-item survey asked providers to rate how necessary it was to provide 30 types of adherence support activities and how frequently they actually provided each of the types of adherence support. From this, we assessed healthcare provider perceptions of best or ideal practices in supporting medication adherence and actual or usual care in adherence support provision. We also examined whether an adherence support gap existed between the provision of best practice adherence support and actual adherence support in clinical practice. RESULTS: One hundred sixty-nine of 300 mailed surveys were returned, for a response rate of 56%. Respondents were highly specialized in HIV care and nearly all practiced in urban settings. Respondents indicated that most of the surveyed adherence support activities should be provided to all patients. However, most clinicians did not actually provide these adherence supports to their patients to the extent that they desired. We calculated an adherence support gap that ranged from 31% to 75% across the different types of adherence support activities. CONCLUSIONS: We observed important adherence support gaps between ideal best practices in the provision of adherence support and actual provision of adherence support in clinical practice.
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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 | 0.034 | 0.120 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.004 |
| 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".