Adherence to Lipid-lowering Therapy and the Use of Preventive Health Services: An Investigation of the Healthy User Effect
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Patients who adhere to preventive therapies may be more likely to engage in a broad spectrum of behaviors consistent with a healthy lifestyle. Because many of these behaviors cannot be measured easily, observational studies of outcomes associated with the long-term use of preventive therapies are subject to the so-called "healthy user bias." To better understand this effect, the authors examined the association between adherence to statin therapy and the use of preventive health services in a Pennsylvania cohort of 20,783 new users of statins between 1996 and 2004. After adjustment for age, gender, and various comorbid conditions, patients who filled two or more prescriptions for a statin during a 1-year ascertainment period were more likely than patients who filled only one prescription to receive prostate-specific antigen tests (hazard ratio (HR)=1.57, 95% confidence interval (CI): 1.17, 2.19), fecal occult blood tests (HR=1.31, 95% CI: 1.12, 1.53), screening mammograms (HR=1.22, 95% CI: 1.09, 1.38), influenza vaccinations (HR=1.21, 95% CI: 1.12, 1.31), and pneumococcal vaccinations (HR=1.46, 95% CI: 1.17, 1.83) during follow-up. These results suggest that patients who adhere to chronic therapies are more likely to seek out preventive health services, such as screening tests and vaccinations. Further work is needed to identify study design and analysis methods that can be used to minimize the healthy user bias in studies of preventive therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 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 | 0.001 |
| 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 it