Impact of Residence on Prevalence and Intensity of Prescription Drug Use Among Older Adults
Bibliographic record
Abstract
BACKGROUND: Higher levels of morbidity among older adults result in greater need for pharmaceutical products and pharmacy services compared with the need in the general population. Rural residents reportedly have reduced access to healthcare services secondary to transportation difficulties, a limited supply of healthcare workers and facilities, and financial constraints. OBJECTIVE: To examine differences in the prevalence and intensity of prescription pharmaceutical use among urban and rural older adults in Manitoba, Canada. METHODS: Participant data from the 1996/1997 Manitoba Study of Health and Aging were linked to pharmaceutical claims data recorded in Manitoba Health's Drug Program Information Network. The effect of residence on the prevalence and intensity of drug use was determined, in addition to the effects of other sociodemographic characteristics, measures of health, and health service utilization. RESULTS: The prevalence of prescription pharmaceutical use did not differ between urban and rural residents (90.6% vs 89.5%, respectively; p = 0.60). Users of home-care services (OR 1.93; 95% CI 1.09 to 3.39), those who perceived their income as adequate (2.38; 95% CI 1.09 to 5.17), and those with a higher number of chronic health problems (1.42; 95% CI 1.26 to 1.62) were significantly more likely to access prescription medications. Rural and urban residents were equally likely to be high users of prescription drugs (21.3% vs 20.0%, respectively; p = 0.64). CONCLUSIONS: Poor health status is associated with a higher prevalence and intensity of use of prescription drugs among older Manitobans. Rural residence is not a barrier to receipt of prescription pharmaceuticals.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".