Prescription medication use practices among non-institutionalised older persons
Bibliographic record
Abstract
Abstract Objective To investigate the prescription medication use practices of a sample of non-institutionalised older persons and to determine any differences with age (65–74 years versus 75 years and over). Method Data were gathered via 204 detailed in-home interviews, completed between March, 1993, and November, 1995. Respondents were identified through general practitioners (GPs). Practice patterns investigated included routines to assist with remembering when to use regular prescription medication, alterations to prescribed regimens, the borrowing and lending of prescription medication and patterns of prescription medication storage. Setting The study was conducted in Melbourne, Australia. Key findings Most respondents were found to have well-defined routines to assist with remembering when to use their prescription medication and in almost two-thirds of cases this was to use the medication with a meal. Almost a quarter of respondents said that on at least one occasion over the past few years they had intentionally used a lower dose of a medication than was prescribed and slightly less than one in 10 had intentionally used a higher dose. Less than one in 10 respondents admitted to having borrowed prescription medication on at least one occasion; almost double that number had lent medication. Most respondents stored their prescription medication appropriately, usually in the kitchen. Only 10 per cent of respondents were found to have more than three additional packs of the prescription medication they currently used. The hoarding of older medications was not uncommon; 42 per cent had prescription medication they no longer used. No differences in practice patterns were found with age. Conclusion Previous concerns about widespread poor quality use of medicines among non-institutionalised older persons were not generally supported by the findings of this study. However, the problems detected emphasise the need for vigilance. GPs and pharmacists could further promote the quality use of medicines among older persons through closer monitoring and review of prescription medication. Older persons need to be encouraged to discuss medicines and/or doses they feel are in some way inappropriate with their GP or pharmacist. Pharmacies should be promoted as places where unwanted or out-of-date medications can be taken for disposal.
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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".