AVAPROMISE: A randomized clinical trial for increasing adherence through behavioural modification in essential hypertension.
Bibliographic record
Abstract
BACKGROUND: Patients with hypertension often do not adhere to their medications. OBJECTIVE: To improve medication adherence in patients with essential hypertension by modifying their behaviours. PATIENTS AND METHODS: From general practice settings, 4864 patients with essential hypertension were recruited and randomly assigned to receive the angiotensin receptor blocker irbesartan (Avapro) with (intervention group) or without (nonintervention group) a behavioural modification program (Avapromise) based on a model of change. Patients were followed up for 12 months. Patients were subgrouped based on their stage of change in the behavioural change continuum, and the intervention was tailored to address the needs of the particular subgroup. The primary efficacy measure was rate and time to discontinuation with irbesartan. RESULTS: At the end of the study, there was no significant difference in the discontinuation rates between the intervention (25.4%, 95% CI 23.7 to 27.2) and nonintervention (25.5%, 95% CI 23.8 to 27.3) groups (P=0.94). The time to discontinuation (P=0.87) and the extrapolated rate of discontinuation estimated from the Kaplan-Meir curve (intervention 23.1%, 95% CI 21.3 to 24.8; nonintervention 23.5%, 95% CI 21.8 to 25.3) were not different between the groups. CONCLUSIONS: This behavioural modification intervention based on a model of change was not efficacious at increasing rates of adherence in patients with essential hypertension in this setting. More individualized interventions may be required to increase adherence in this population.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".