Non-pharmacological interventions for sleep quality and insomnia during pregnancy: A systematic review.
Bibliographic record
Abstract
OBJECTIVE: To systematically review the literature regarding non-pharmacological inteventions for improving sleep quality and insomnia during pregnancy. METHODS: An electronic search strategy was conducted using several online databases (CINAHL, PubMed, Medline, Index to Chiropractic Literature) from inception to March 2013. Inclusion criteria consisted of studies evaluating non-pharmacological interventions, published in English in a peer reviewed journal, and assessed sleep quality or insomnia. The full text of suitable articles was reviewed by the authors, and scored using a risk of bias assessment. RESULTS: 160 articles were screened and seven studies met the inclusion criteria in the form of three prospective RCTs, one prospective longitudinal trial, one experimental pilot study, and two prospective quasi-randomized trials. Quality scores ranged from five to eight out of twelve on the risk of bias scoring criteria. CONCLUSIONS: Exercise, massage, and acupuncture may be associated with improved sleep quality during pregnancy, however, due to the low quality and heterogeneity of the studies yielded, a definitive recommendation cannot be made. Further higher quality research is indicated.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".