The objective of this study was to understand the existing practices and attitudes regarding inpatient sleep at the 2020 US News and World Report (USNWR) Honor Roll pediatric (n = 10) and adult (n = 20) hospitals. Section chiefs of Hospital Medicine from these institutions were surveyed and interviewed between June and August 2021. Among 23 of 30 surveyed physician leaders (response rate = 77%), 96% (n = 22) rated patient sleep as important, but only 43% (n = 10) were satisfied with their institutions' efforts. A total of 96% (n = 22) of institutions lack sleep equity practices. Fewer than half (48%) of top hospitals have sleep-friendly practices, with the most common practices including reducing overnight vital sign monitoring (43%), decreasing ambient light in the wards (43%), adjusting lab and medication schedules (35%), and implementing quiet hours (30%). Major themes from qualitative interviews included: importance of universal sleep-friendly cultures, environmental changes, and external incentives to improve patient sleep.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9544101 | PMC |
| http://dx.doi.org/10.1002/jhm.12917 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Adolescence is characterized by heightened emotion dysregulation, impulsivity, and engagement in high-risk behaviors, such as substance use, violence, and unprotected sexual activity. Dialectical Behavioral Therapy for Adolescents (DBT-A) is an evidence-based intervention that targets emotion regulation and impulsivity among adolescents, proven effective at decreasing high-risk behaviors. However, limited research exists on adolescents' perceptions of DBT-A, particularly in schools.
View Article and Find Full Text PDFMambaTab: A Plug-and-Play Model for Learning Tabular Data.
Proc (IEEE Conf Multimed Inf Process Retr)
August 2024
Department of Computer Science, University of Kentucky, Lexington, KY, USA.
Despite the prevalence of images and texts in machine learning, tabular data remains widely used across various domains. Existing deep learning models, such as convolutional neural networks and transformers, perform well however demand extensive preprocessing and tuning limiting accessibility and scalability. This work introduces an innovative approach based on a structured state-space model (SSM), MambaTab, for tabular data.
View Article and Find Full Text PDFThe mental health of older adults in the criminal justice system: a brief report from a nominal group.
J Forens Psychiatry Psychol
December 2024
Health and Justice Research Network, School of Health Sciences, University of Manchester, Manchester, UK.
The number of older people in prison is increasing, and this group has significant mental health needs. Despite this, little research has evaluated mental healthcare for older prisoners, and examples of best practice are unknown. This paper explored staff experiences of supporting the mental health needs of older prisoners to identify existing forms of care provision, challenges to implementation, and areas for improvement.
View Article and Find Full Text PDFAcrocyanosis: The Least Known Acrosyndrome Revisited With a Dermatologic Perspective.
Dermatol Res Pract
January 2025
Department of Dermatology, Acıbadem University School of Medicine, İstanbul, Turkey.
Acrocyanosis is a functional peripheral vascular disorder, currently categorized under the canopy of acrosyndromes, i.e., a group of clinically similar and significantly overlapping vascular disorders involving the acral skin.
View Article and Find Full Text PDFThe challenge of long-term stroke outcome prediction and how statistical correlates do not imply predictive value.
Brain Commun
January 2025
Department of Neurology, Inselspital, University Hospital Bern, University of Bern, 3010 Bern, Switzerland.
Personalized prediction of stroke outcome using lesion imaging markers is still too imprecise to make a breakthrough in clinical practice. We performed a combined prediction and brain mapping study on topographic and connectomic lesion imaging data to evaluate (i) the relationship between lesion-deficit associations and their predictive value and (ii) the influence of time since stroke. In patients with first-ever ischaemic stroke, we first applied high-dimensional machine learning models on lesion topographies or structural disconnection data to model stroke severity (National Institutes of Health Stroke Scale 24 h/3 months) and functional outcome (modified Rankin Scale 3 months) in cross-validation.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!