Are there gender differences in the prescribing of hypnotic medications for insomnia?
Bibliographic record
Abstract
Gender differences in the prescribing patterns of general classes of medications for insomnia were examined. The classes of medications included: zopiclone, antidepressants, benzodiazepines, antihistamines and no medication. The sample comprised a sub-set of respondents from 2620 questionnaires of the Canadian Multicentre Sleep Database. Respondents for this database were contacted through physicians, announcements in the media and local pharmacies. The results indicated that gender alone was not associated with differential prescribing for insomnia, nor was gender associated with patterns of medication use such as frequency of taking medication, length of use, taking more or less medication than prescribed or attempts to stop taking medication. Demographic factors were included in the analysis and age and marital status were associated with different prescribing patterns for men and women with insomnia. It is possible that physicians refer to stereotypic expectations when prescribing hypnotics.
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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 | 0.000 |
| 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) | 0.003 | 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".