Advocating for a sleep-friendly hospital status
Bibliographic record
Abstract
We welcome the call by Diane Lim and colleagues1Lim DC Najafi A Afifi L et al.The need to promote sleep health in public health agendas across the globe.Lancet Public Health. 2023; 8: e820-e826Summary Full Text Full Text PDF Scopus (4) Google Scholar to promote sleep health in public health agendas globally and strongly support their excellent and comprehensive range of recommendations. As a group of multidisciplinary paediatric professionals, we want to advocate for policies to support sleep in hospitals. Despite hospitals being centres for healing and recovery, one of the most fundamental strategies to achieve these aims—sleep—is typically not included as part of any treatment plan. Numerous studies have shown that environmental, institutional, and care provider factors disrupt inpatient sleep.2Fidler AL Voorhees S Zhou ES Stacciarini JM Fedele DA A systematic review and proposed conceptual model of sleep disturbances during pediatric hospitalizations.Sleep. 2022; 45zsac038 Crossref Scopus (5) Google Scholar, 3Peirce LB Orlov NM Erondu AI et al.Caregiver and staff perceptions of disruptions to pediatric inpatient sleep.J Clin Sleep Med. 2018; 14: 1895-1902Crossref PubMed Scopus (16) Google Scholar, 4Stremler R Micsinszki S Adams S Parshuram C Pullenayegum E Weiss SK Objective sleep characteristics and factors associated with sleep duration and waking during pediatric hospitalization.JAMA Netw Open. 2021; 4e213924 Crossref Scopus (11) Google Scholar Although awareness of these issues is growing, there appears to be little motivation to introduce the necessary changes that will lead to substantial, sustainable improvements. We call on WHO and UNICEF to back a “sleep-friendly” hospital status5Orlov NM Arora VM A call for a “sleep-friendly” designation in hospitals.Sleep. 2022; 45zsac066 Crossref Scopus (4) Google Scholar to lead to a quantum shift in sleep opportunities for inpatients, and their often coresident carers, in hospitals worldwide. By optimising sleep in hospital, recovery times could be shorter, longer-term outcomes improved, and there could be tangible economic, physical, and mental health benefits. To achieve sleep-friendly status, clear policies or standards are required. These should include how to protect and optimise hospital staff's sleep. Better sleep among health-care providers reduces errors and burnout and potentially improves staff retention.6Kancherla BS Upender R Collen JF et al.What is the role of sleep in physician burnout?.J Clin Sleep Med. 2020; 16: 807-810Crossref PubMed Scopus (17) Google Scholar Finally, contact with hospitals should be seen as an important opportunity to educate and model good sleep behaviours and to screen for healthy sleep and sleep disorders in as routine a way as we measure weight—including plotting hours of sleep against expected centiles for age. We declare no competing interests. AF is supported by an institutional research training grant (National Institutes of Health grant number T32DK063929). The need to promote sleep health in public health agendas across the globeHealthy sleep is essential for physical and mental health, and social wellbeing; however, across the globe, and particularly in developing countries, national public health agendas rarely consider sleep health. Sleep should be promoted as an essential pillar of health, equivalent to nutrition and physical activity. To improve sleep health across the globe, a focus on education and awareness, research, and targeted public health policies are needed. We recommend developing sleep health educational programmes and awareness campaigns; increasing, standardising, and centralising data on sleep quantity and quality in every country across the globe; and developing and implementing sleep health policies across sectors of society. Full-Text PDF Open Access
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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 | 0.015 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.013 | 0.026 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.020 | 0.024 |
| Insufficient payload (model declined to judge) | 0.079 | 0.018 |
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".