Reconceptualizing Medication Adherence: Six Phases of Dynamic Adherence
Bibliographic record
Abstract
Nonadherence is the Achilles' heel of effective psychiatric treatment. It affects the resolution of mental health symptoms and interferes with the assessment of treatment response. The meaning of the term adherence has evolved over time and is now associated with a variety of definitions and measurement methods. The result has been a poorly operationalized and nonstandardized term that is often interpreted differently by providers and patients. Drawing extensively from the literature, this article aims to (1) describe changes in the concept of adherence, drawing from the mental health treatment literature, (2) present a more comprehensive definition of adherence that recognizes the role of patient-provider transactions, (3) introduce dynamic adherence, a six-phase model, which incorporates the role of transactional processes and other factors that influence patients' adherence decisions, and (4) provide recommendations for providers to improve adherence as well as their relationships with patients.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.001 |
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; both teacher heads agree on what is shown here.
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".