Pill for this and a pill for that: A cross‐sectional survey of use and understanding of medication among adults with multimorbidity
Bibliographic record
Abstract
OBJECTIVE: To understand the challenges managing medication use and knowledge of people living with multimorbidity. METHODS: A cross-sectional survey of 234 adults with multimorbidity, identified using retrospective hospital discharge data. Participants were recruited from two primary health organisations in New Zealand. RESULTS: Three quarters of participants (75%) were prescribed four or more medications, and one in four (27%) were prescribed eight or more medications. Participants reported knowing what their medications were for (88%, 95% CI 81.4-93.8) and when to take them (99%, 95% CI 97.5-99.9). However, over a fifth (22%, 95% CI 13.7-30.4) reported some problems managing multiple medications, and 40% (95% CI 30.2-50.2) reported a problem with side effects. CONCLUSION: The results highlight the need to consider how prescribing can be adapted for people with multimorbidity and move beyond the application of multiple disease-specific guidelines.
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.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".