Use of prescription and nonprescription hypnotics in a Canadian elderly population.
Bibliographic record
Abstract
BACKGROUND: Hypnotics are commonly used by older adults, yet little is known about the patterns of their use and effectiveness in this population. METHODS: Three thousand eight hundred sixty anonymous, self-report surveys were distributed to community pharmacies (n=356) across Canada to obtain information on the patterns of use of hypnotics from elderly volunteers. RESULTS: The mean age of respondents was 72+/-7 years (range 60 to 95 years) and 66% were women. In the past year, 53% of respondents used hypnotics. Prescription products accounted for 83% of the past year's use (66% benzodiazepines, 11% zopiclone, 4% antidepressants, 2% opioids), and 17% of the products used were over-the-counter (5% herbal, 5% antihistamines, 3% analgesics). Use was regular (50% daily) and chronic (mean duration six years: range two weeks to 30 years). Hypnotics significantly (P<0.001) improved subjective sleep latency (mean 32 min compared with 93 min), number of nocturnal awakenings (mean two compared with four) and total hours of sleep (mean 7 h compared with 4 h). Effectiveness was highly rated: at the most recent use of the product, mean 7.6 (SD+/-2.2) of 10; initially, 7.9 (SD+/-2.3) with a significance of P=0.02. Most respondents (59%) reported side effects, mainly dry mouth (30%), memory problems (22%) and daytime sleepiness (22%), although 60% rated the side effects as mild. The mean number of other medications used was five (range zero to 17). Of the 54 subjects who used nonprescription sleep products, only half (52%) indicated that their physician was aware of this use. CONCLUSIONS: Prescription drugs were primarily used for sleep and were perceived to be effective even with long term use, despite mild side effects.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".