Boosting access to evidence-based insomnia care: our experience with a stepped care approach in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Insomnia is a major issue due to its prevalence, health effects, and economic burden. In Canada, 45% of the population report trouble initiating or maintaining sleep and 16% meet criteria for insomnia disorder. Despite evidence that sedative-hypnotic medications have limited long-term effectiveness and pose risks to patient and public health, pharmacotherapy remains commonplace. Cognitive behavioral therapy for insomnia (CBT-I) is the recommended first-line intervention for insomnia; however, access to CBT-I is uneven and inequitable. We developed a stepped care model aimed at boosting Canadians' access to CBT-I. The model promotes a flexible, equitable approach to the effective management of insomnia by optimizing the efficient use of CBT-I resources and reducing chronic sedative-hypnotic medication use. Self-guided approaches are the foundation. Subsequent steps include interventions by primary care providers and community pharmacists, trained CBT-I providers, and behavioral sleep experts. In this commentary, we illustrate how this model can optimize intervention access and how it provides a framework for the training of various healthcare providers in evidence-based insomnia care. We include research evidence from each step and discuss the place of this model within Canadian healthcare systems. We hope the concepts from this broad, applied approach will be valuable for other countries.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it