Medication Management Frameworks in the Context of Self-Management: A Scoping Review
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
PURPOSE: Many individuals take multiple prescribed and unprescribed medications, also known as polypharmacy, which can be problematic. Improving medication self-management is important; however, most medication management frameworks focus on adherence and limit the integration of the core components of self-management. Therefore, the objective of this scoping review was to identify what is reported in the literature on medication management frameworks or models within the context of self-management. METHODS: Electronic databases (Medline, Embase, CINAHL and Cochrane Library) and grey literature (healthcare and government organization websites) were searched for articles that described a framework or model developed or adapted for medication management, included components of self-management and was published from January 2000 to January 2020. During the screening of titles and abstracts, 5668 articles were reviewed, 5242 were excluded and 426 were then assessed at the full-text level. Thirty-nine articles met the eligibility criteria and were included in the review. RESULTS: About half of the frameworks were newly developed (n=20), while the other half were adapted from, or applied, a previous model or framework (n=19). The majority of frameworks focused on medication adherence and most of the self-management domains were categorized as medical management, followed by emotional and role management. CONCLUSION: Medication self-management is a complex process and often impacts multiple areas of an individual's life. It is important for future frameworks to incorporate a comprehensive, holistic conceptualization of self-management that is inclusive of the three self-management domains - medical, emotional and role management.
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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 | 0.001 |
| 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) | 0.000 | 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