Summary of the Best Evidence for Non‐Pharmacological Management of Sleep Disturbances in Intensive Care Unit Patients
Bibliographic record
Abstract
AIM: To retrieve, evaluate and summarise the best evidence for non-pharmacological management of sleep disturbances in ICU patients, and to provide basis for clinical nursing practice. DESIGN: This study was an evidence summary followed by the evidence summary reporting standard of Fudan University Center for Evidence-based Nursing. METHODS: All evidence on non-pharmacological management of sleep disturbances in ICU patients from both domestic and international databases and relevant websites was systematically searched, including guidelines, expert consensuses, best practice, clinical decision-making, evidence summaries and systematic review. DATA SOURCES: UpToDate, BMJ Best Practice, Joanna Briggs Institute, Scottish Intercollegiate Guidelines Network, National Guideline Clearinghouse, National Institute for Health and Clinical Excellence, Yi Maitong Guidelines Network, Registered Nurses Association of Ontario, Canadian Medical Association: Clinical Practice Guideline, Guidelines International Network, WHO, the Cochrane Library, CINAHL, Embase, PubMed, Web of Science, CNKI, WanFang database, VIP database, SinoMed, The American Psychological Association, European Sleep Research Society, American Academy of Sleep Medicine and National Sleep Foundation were searched from the establishment of the databases to June 1, 2024. RESULTS: A total of 18 pieces of literature were included, involving 4 guidelines, 2 expert consensuses, 1 best practice and 11 systematic reviews. 25 pieces of evidence covering 4 categories of risk factors, sleep monitoring, non-pharmaceutical intervention, education and training were summarised. CONCLUSION: This study summarises the best evidence for non-pharmacological management of sleep disturbances in ICU patients. In clinical application, medical staff should make professional judgements and fully combine clinical situations and patient preferences to select evidence, laying a theoretical foundation for later empirical research to reduce the incidence of sleep disturbances in ICU patients and improve the sleep quality of critically ill patients. IMPLICATIONS FOR THE PROFESSION AND PATIENT CARE: Medical staff can refer to the best evidence to provide reasonable non-pharmacological management plans for sleep disturbances in ICU patients, improving their sleep quality and life satisfaction. IMPACT: The management of sleep disturbances in critically ill patients has not received sufficient attention and standardisation. This study summarises 25 pieces of the best evidence for non-pharmacological management of sleep disturbances in critically ill patients. Accurate and standardised evaluation and monitoring are the foundation of sleep management for ICU patients. This summary of evidence can help ICU nurses enhance their clinical practice. REPORTING METHOD: This evidence summary followed the evidence summary reporting specifications of Fudan University Center for Evidence-based Nursing, which were based on the methodological process for the summary of the evidence produced by the Joanna Briggs Institute. This study was based on the evidence summary reporting specifications of the Fudan University Center for the Evidence-based Nursing; the registration number is 'ES20231708'. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.
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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 | 0.014 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.015 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".