Family practice patients' adherence to statin medications.
Bibliographic record
Abstract
OBJECTIVE: To measure family practice patients' adherence to statin medications and to identify factors associated with adherence to these medications. DESIGN: Cross-sectional study using a mailed self-report survey sent to 400 patients. SETTING: Two academic family practice clinics in Halifax, NS. PARTICIPANTS: A total of 284 patients aged 40 or older who were prescribed statin medications by their family physicians, either for the first time or as a renewal during a 20-month period. MAIN OUTCOME MEASURES: Level of adherence to statin medications as measured by patients' self-report on the Morisky scale; association between high adherence on the Morisky scale and 38 patient-reported factors. RESULTS: Response rate was 82.5%. Average age of patients was 65 years, 57% were men, 62% had been on statin medications for more than 2 years, and 97% reported that their family physicians managed their cholesterol levels. More than 63% of patients reported high adherence as measured by the Morisky scale. On multiple logistic regression, being older than 65, taking 4 to 6 other prescribed medications, and having a lifestyle that included regular exercise or a healthy diet were significant independent predictors of high adherence scores on the Morisky scale. CONCLUSION: Almost two-thirds (63%) of patients who were prescribed statins by their family physicians reported high adherence to the medications. Strategies to improve adherence would best be directed at patients who are younger or taking fewer than 4 or more than 6 other prescribed medications. Patients should be encouraged to maintain a lifestyle of regular exercise and a healthy diet, as this was associated with better adherence to statin medications.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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".