Prevalence of Insomnia and its Treatment in Canada
Bibliographic record
Abstract
OBJECTIVES: To estimate the prevalence of insomnia and examine its correlates (for example, demographics and physical and mental health) and treatments. METHODS: A sample of 2000 Canadians aged 18 years and older responded to a telephone survey about sleep, health, and the use of sleep-promoting products. Respondents with insomnia were identified using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision, and the International Classification of Diseases, Tenth Edition, criteria. RESULTS: Among the sample, 40.2% presented at least 1 symptom of insomnia (that is, trouble falling or staying asleep, or early morning awakening) for a minimum of 3 nights per week in the previous month, 19.8% were dissatisfied with their sleep, and 13.4% met all criteria for insomnia (that is, presence of 1 insomnia symptom 3 nights or more per week for at least 1 month, accompanied by distress or daytime impairment). Insomnia was associated with female sex, older age, and poorer self-rated physical and mental health. Thirteen per cent of respondents had consulted a health care provider for sleep difficulties once in their lifetime. Moreover, 10% had used prescribed medications for sleep in the previous year, 9.0% used natural products, 5.7% used over-the-counter products, and 4.6% used alcohol. There were differences between French- and English-speaking adults, with the former group presenting lower rates of insomnia (9.5%, compared with 14.3%) and consultation (8.7%, compared with 14.4%), but higher rates of prescribed medications (12.9%, compared with 9.3%) and the use of natural products (15.6%, compared with 7.4%). CONCLUSIONS: Insomnia is a prevalent condition, although few people seek professional consultation for this condition. Despite regional differences in the prevalence and treatments used to manage insomnia, prescribed medications remain the most widely used therapeutic option.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".