Cognitive behavioural treatment for insomnia in primary care: a systematic review of sleep outcomes
Bibliographic record
Abstract
Background Practice guidelines recommend that chronic insomnia be treated first with cognitive behavioural therapy for insomnia (CBT-I), and that hypnotic medication be considered only when CBT-I is unsuccessful. Although there is evidence of CBT-I’s efficacy in research studies, systematic reviews of its effects in primary care are lacking. Aim To review the effects on sleep outcomes of CBT-I delivered in primary care. Design and setting Systematic review of articles published worldwide. Method Medline, PsycINFO, EMBASE, and CINAHL were searched for articles published from January 1987 until August 2018 that reported sleep results and on the use of CBT-I in general primary care settings. Two researchers independently assessed and then reached agreement on the included studies and the extracted data. Cohen’s d was used to measure effects on sleep diary outcomes and the Insomnia Severity Index. Results In total, 13 studies were included. Medium-to-large positive effects on self-reported sleep were found for CBT-I provided over 4–6 sessions. Improvements were generally well maintained for 3–12 months post-treatment. Studies of interventions in which the format or content veered substantially from conventional CBT-I were less conclusive. In only three studies was CBT-I delivered by a GP; usually, it was provided by nurses, psychologists, nurse practitioners, social workers, or counsellors. Six studies included advice on withdrawal from hypnotics. Conclusion The findings support the effectiveness of multicomponent CBT-I in general primary care. Future studies should use standard sleep measures, examine daytime symptoms, and investigate the impact of hypnotic tapering interventions delivered in conjunction with CBT-I.
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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 | 0.010 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".