Association Between Depressive and Anxiety Disorders and Adherence to Antihypertensive Medication in Community‐Living Elderly Adults
Bibliographic record
Abstract
OBJECTIVES: To identify the determinants of antihypertensive medication adherence in community-living elderly adults. DESIGN: Longitudinal observational study. SETTING: Population-based health survey in the province of Quebec, Canada. PARTICIPANTS: Data from a representative sample (N = 2,811) of community-dwelling adults in Quebec aged 65 and older participating in the Étude sur la Santé des Aînés study. The final study sample analyzed consisted of 926 participants taking antihypertensive drugs during the 2 years of the study. MEASUREMENTS: Adherence to antihypertensive medication was measured using days of supply obtained during a specified time period. Depression and anxiety disorders were assessed using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria, and physical health status was measured using the Charlson Comorbidity Index. Other factors considered were age, education, marital status, annual family income, and number of antihypertensive drugs that participants used. RESULTS: Mean antihypertensive proportion (percentage) of days supplied in was 92.5% in Year 1 and 59.4% in Year 2. The presence of depression and anxiety disorders and the number of antihypertensive medications significantly predicted medication adherence. The sex by depression and anxiety disorders interaction term was significant. CONCLUSION: Adherence to antihypertensive medication was significantly associated with depression and anxiety disorders in men but not women. The treatment of depression and anxiety disorders in individuals with hypertension may be helpful in improving medication adherence rates and healthcare outcomes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".