Vets, denialists and rememberers: social typologies of patient adherence and non-adherence to HAART from the perspective of HIV care providers
Bibliographic record
Abstract
For many people living with HIV/AIDS taking highly active antiretroviral therapy (HAART) is difficult due to various individual and social factors, including the side effects of these medications, HIV/AIDS stigma and poor patient-provider relationships. Most studies that examine barriers to and facilitators of adherence to HAART have been conducted with people on these medications, which is critical to improving adherence among various HIV-affected groups. Less attention has been paid to the experiences of HIV care providers, which is an important gap in the literature considering the key role they play in the delivery of HAART and the management of patient treatment plans. This paper presents findings from a qualitative pilot study that explored how HIV care providers assess adherence and non-adherence to HAART among their HIV-positive patients in Vancouver, British Columbia. Drawing upon individual interviews conducted with HIV physicians (n = 3), social service providers (n = 3) and pharmacists (n = 2), this discussion focuses on the social typologies our participants use to assess patient success and failure related to adherence. Eleven unique categories are featured and the diversity within and across these categories illustrate a broad spectrum of adherence-related behaviours among patients and the social meanings providers attribute to these behaviours. As one of the first explorations of the social typologies used by HIV care providers to assess patient performance on HAART, these data contribute valuable insights into the experiences of providers within the context of adherence-related care delivery.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.032 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.004 |
| 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".