Bibliographic record
Abstract
BACKGROUND: Difficulty sleeping is a common complaint by older people which leads to medication use to help attain sleep. OBJECTIVES: This study provides a population-based description of medication, specifically taken to help with sleep, by Canadians over the age of 60. The proportion of this sleep medication that is prescribed, and the determinants of prescribed versus over the-counter (OTC) sleep medication use will also be presented. METHODS: The Canadian Community Health Survey, 2002, provided the study population of 9,393 respondents over the age of 60. RESULTS: Almost 16% of Canadians over 60 reported taking sleep medication over the past year, of which 85% was prescribed by physicians. Sleep medication is higher for women, increases with age, poor health, chronic illness and poor quality sleep,and was especially high for people with a recent major depressive episode. Prescribed sleep medication increased with age, low income, low education, poor health, chronic illness and residence in the province of Quebec. Adjusting for health status or insurance covering medication costs made little difference. CONCLUSIONS: This study provides important new information on the use of sleep medication by older Canadians. Overall sleep medication use and proportion of sleep medication prescribed are separate parameters with potentially different distributions, e.g., Quebec showed the same amount of sleep medication use as elsewhere, but a much higher proportion of it was prescribed.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".