Impact of a Theory-Based Intervention to Promote Medication Adherence in Patients With a History of Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: Patient discontinuation of cardioprotective medications after a cardiac ischemic event commonly occurs early after hospital discharge. Theory-based interventions could be effective in promoting better patient self-regulation of health-related behaviors and positive intentions to adhere to the recommended medical regimen. OBJECTIVE: The aim of this study was to evaluate the potential efficacy and feasibility of a theory-based intervention to promote adherence to cardioprotective medications. METHODS: In this mixed-methods quasi-experimental study with 3 time points, we recruited 45 participants with a positive intention to adhere and a history of myocardial infarction. They were recruited in primary care units in Brazil. Data collection occurred in 2 waves (Tb and T60). The intervention consisted of developing action and coping plans, delivered in a 30-minute face-to-face session, with face-to-face reinforcement at a 30-day interval. Quantitative data were submitted to descriptive, Wilcoxon, and McNemar analyses; qualitative data were submitted to content analysis. RESULTS: An increase in the proportion of patients adhering to medications at the end of follow-up was found (T60 - Tb, +60.0%; P < .001). In addition, a significant reduction was found for blood pressure (T60 - Tb, -8.6 mm Hg; P < .001), heart rate (T60 - Tb, -6.6 bpm; P < .001), and low-density lipoprotein (T60 - Tb, -6.2 mg/dL; P < .05). Qualitative results revealed that the intervention was feasible, with an attrition rate of zero. The intervention was found to be easy to apply to patients' daily lives, and there was adequate time for implementation. CONCLUSIONS: Our data confirm the potential efficacy of a theory-based intervention on the promotion of adherence to cardioprotective medications and on the related clinical end points, as well as its feasibility in the clinical context (Universal Trial Number: U1111-1189-9967).
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".