Medication non-adherence among outpatients with myocardial infarction: A hospital-based study
Bibliographic record
Abstract
BackgroundDespite the availability of effective medications for the treatment of myocardial infarction (MI), treatment outcomes are suboptimal due to medication non-adherence. The aim of this study was to assess medication adherence and its associated factors among patients with MI.MethodsThis cross-sectional study was conducted on outpatients with MI in the cardiology clinic at a major hospital in Jordan. Medication adherence was assessed using the validated Arabic version of the 4-item Medication Adherence Scale. Ordinal regression was conducted to identify the variables associated with medication non-adherence.ResultsA total of 333 patients participated in the study. The median age was 58 years (57–60). Medication non-adherence was expressed by 54.6 % of the participants. Having less than college/university education (Coefficient = −0.625, 95%Cl (−1.191 to −0.06), P = 0.03) and increased medication-related concerns (Coefficient = −0.065, 95 % Cl (−0.126 to −0.003), P = 0.04) were associated with decreased medication adherence. Other factors, including having no family history of cardiovascular disease (CVD) (Coefficient = 0.757, 95%Cl (0.218–1.295), P = 0.006) and increased medication necessity (Coefficient = 0.186, 95%Cl (0.133–0.239), P < 0.001) were associated with high medication adherence.ConclusionThe current study demonstrated a high rate of medication non-adherence in MI patients, necessitating the need to develop tailored pharmaceutical care interventions that address patients' medication-related beliefs, focusing on their perceptions of medication necessity and concerns, particularly in patients with low education level and those with a positive family history of CVD.
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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 | 0.004 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".