Predictors of Older Adults’ Capacity for Medication Management in a Self-Medication Program
Why this work is in the frame
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Bibliographic record
Abstract
UNLABELLED: The aim of this project was to identify variables that predicted older adults' ability to manage medications. METHODS: The study used a retrospective cohort design and was set in a self-medication program within a rehabilitation hospital. A random sample of charts from 301 participants in the self-medication program was reviewed. RESULTS: Logistic regression models accounted for 26.7% and 55.8% of the variance in the probability of making one or more self-medication errors during the initial and final weeks of the program, respectively. The importance of cognition in predicting medication management capacity was seen in bivariate and multivariate analyses and through a number of interactions with other predictors. Statistically significant predictors in one or both analyses included medication regimen complexity, Mini-Mental State Exam (MMSE) score, duration of institutionalization, depression, and interactions between (a) medication regimen complexity and MMSE score and (b) ability to cook and MMSE score. DISCUSSION: The direct effects of cognition and medication regimen complexity were important predictors of medication management capacity.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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