P5-S4.06 Sticking to it: the effect of maximally assisted therapy on antiretroviral treatment adherence among a cohort of unstably housed people living with HIV in BC, Canada
Bibliographic record
Abstract
Background Housing is a known determinant of health behaviour, including adherence to antiretroviral therapy. Within the Longitudinal Investigations into Supportive and Ancillary Health Services (LISA) cohort, unstable housing is inversely associated with adherence. The Maximally Assisted Therapy (MAT) program uses a multidisciplinary approach to support people living with HIV/AIDS (PHA) who have a history of addictions, mental health disorders and homelessness. We investigated the efficacy of support services, including the MAT program, in improving adherence for unstably housed PHA. Methods The LISA cohort is a cross-sectional study of individuals on antiretroviral therapy in British Columbia. Interviewer-administered surveys collect information regarding housing, drug use, utilisation of health services and other clinically relevant socio-demographic factors. Clinical variables, such as CD4 count and viral load, were obtained through longitudinal linkages with the Drug Treatment Program (DTP) at the BC Centre for Excellence in HIV/AIDS. Logistic regression was used to determine factors associated with adherence (≥95% vs <95%) among unstably housed LISA participants (n=212). Results Between 2007 and 2010 approximately 1000 participants were interviewed. This analysis is based on 644 interviews, of which the DTP reports optimal adherence [≥95% 12 month refill] for 367 (57%) individuals. Median age was 46 and 475 (73.7%) were male. We found that unstably housed participants attending the MAT program were 4.76 times more likely to be ≥95% adherent [95% CI 1.72 to 13.13] than those who did not. Other factors associated with optimal adherence included recent incarceration (Adjusted OR [AOR]=0.20 [95% CI 0.05 to 0.80]) and not currently using illicit drugs (AOR=0.40 [95% CI 0.16 to 0.99]). Conclusion The MAT program provides a model for other urban centers dealing with concurrent and interrelated adherence barriers: high-risk drug use, mental health disorders and homelessness. In the absence of sustainable housing solutions, programs such as MAT are crucial to achieving optimal treatment adherence in this population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".