Factors Associated with Different Patterns of Nonadherence to HIV Care in Dar es Salaam, Tanzania
Bibliographic record
Abstract
Health system responsiveness (HSR), a measure of patient health care experience, may influence adherence to HIV/AIDS care and be an important predictor of outcomes. We studied the relationship between HSR, patient factors, and visit nonadherence in 16 President's Emergency Plan for AIDS Relief-supported HIV/AIDS clinics in Dar es Salaam. An HSR survey was administered in 2009, and all clinic visits 1 year following the interviews were analyzed for 720 patients on antiretrovirals (ARVs). Definitions of visit nonadherence were (1) low visit constancy ([VC], no visit in ≥1 quarter), (2) gaps in care (>60 days between visits), (3) no visit in last quarter (VLQ). The relationships between factors were analyzed using multivariate analysis with adjusted odds ratio (AOR) and 95% confidence intervals (CI) reported. Few patients were nonadherent using VLQ (14%) and VC (28%). Gaps in care were more common (49.6%) and associated with younger age (AOR: 3.86 [2.02-7.40]), no explanation of side effects (AOR: 2.21 [1.49-3.28]), and shorter antiretroviral therapy (ART) duration (0-3 months AOR: 1.49 [1.09-2.03]; 3-6 months AOR: 2.44 [1.40-4.25]). No VLQ was associated with younger age (AOR: 3.40 [1.63-7.07]), poor health care worker (HCW) communication (AOR: 4.83 [1.39-16.78]), and less time on ART (0-3 months AOR: 5.04 [2.47-10.30]; 3-6 months AOR: 3.09 [1.72-5.57]). Younger age, poor HCW communication, and shorter ART duration also predicted lower VC, as did higher patient-HCW ratios. The rates of visit nonadherence differed based on the definitions used. Younger age, shorter time on ART, and poor HCW communication predicted lower adherence regardless of the definition. More work is needed to understand the relationship between HSR, patient factors, and different patterns of visit nonadherence and their impact on ART outcomes.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".