Non-Compliance with Drug Treatment and Reading Difficulties with Regard to Prescription Labelling among Seniors
Bibliographic record
Abstract
UNLABELLED: BACKGROUND; The link between experiencing difficulties in reading or understanding and non-compliance with drug treatment among seniors is not clearly established. OBJECTIVES: We measured the effect of both difficulties in reading, as well as difficulties in understanding prescription labelling, on non-compliance with drug treatments among seniors. Since the use of a pill organizer prepared by a pharmacist may compensate for the problems in reading, we also checked the potential modifying effect of the use of a pill organizer on these two associations. METHOD: Data on non-compliance with drug treatment, comprehension of prescription labelling and on the factors potentially linked to non-compliance, were collected during face-to-face interviews with 325 seniors. RESULTS: In all, 126 respondents (38.8%) were not able to read all the prescription labels and 218 (67.1%) did not fully understand all the information. 153 respondents were non-compliant with their drug treatment. After adjusting for sex, age, living alone or not, having had help with taking the medication, use of a pill organizer, having had sufficient funds to procure his medicine during the previous month, belief in the efficacy of his medication, perception of his state of health, satisfaction with physician-given and pharmacist-given information, as well as the complexity of the treatment, the two associations remained statistically non-significant. The use of a pill organizer was not a modifying factor. CONCLUSION: Our results did not demonstrate the existence, among seniors, of an association between non-compliance and difficulty in reading and understanding prescription labelling.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".