Clinical and demographic correlates of medication and visit adherence in a large randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Patient characteristics are associated with adherence, which has implications for planning clinical research or designing payment systems that reward superior outcomes. It is unclear to what extent clinician efforts to improve adherence can attenuate these associations. METHODS: To identify factors predicting visit and medication adherence in settings designed to optimize adherence, we did a retrospective analysis of participants in the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). ALLHAT recruited participants at 632 sites in North America, Puerto Rico, and the U.S. Virgin Islands for random assignment to antihypertensive treatment with amlodipine, chlorthalidone, or lisinopril. Site investigators reported clinic characteristics at the time they applied to participate in the study and research coordinators used standardized methods to measure patient characteristics. We defined adequate visit adherence as attending at least 80 % of scheduled visits; adequate medication adherence was defined as taking 80 % or more of the randomly assigned medication at all study visits. RESULTS: The 31,250 ALLHAT participants eligible for the visit adherence analysis attended 78.5 % of scheduled study visits; 68.9 % attended more than 80 % of scheduled visits. Clinic setting was predictive of both forms of adherence; adherence was worst at private clinics; clinics that enrolled more study participants had superior adherence. Adjusting for clinic characteristics and clinical factors, women, younger participants, Blacks and smokers were less likely to have adequate visit adherence. Among the 28,967 participants eligible for the medication adherence analysis, 21,261 (73.4 %) reported adequate medication adherence. In adjusted analyses, younger and less educated participants, Blacks, and smokers were less likely to report adequate adherence. CONCLUSIONS: Participant demographics were associated with adherence despite strenuous efforts to optimize adherence. Our results could inform decisions by researchers planning trials and policymakers designing payment systems. TRIAL REGISTRATION: NCT00000542 . Registered 27 October 1999.
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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 | 0.015 | 0.001 |
| 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".