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Irish LA, Bottera AR, Manasse SM, Christensen Pacella KA, Schaefer LM. The Integration of Sleep Research Into Eating Disorders Research: Recommendations and Best Practices. Int J Eat Disord 2024. [PMID: 38937938 DOI: 10.1002/eat.24241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 05/01/2024] [Accepted: 05/23/2024] [Indexed: 06/29/2024]
Abstract
OBJECTIVE Sleep disturbance is common among individuals with eating disorders (EDs), with approximately 50% of patients with EDs reporting sleep disturbance. Sleep problems may promote, exacerbate, or maintain ED symptoms through a variety of hypothesized mechanisms, such as impaired executive function, increased negative affect, and disruptions to appetitive rhythms. Although research investigating the role of sleep in EDs is growing, the current literature suffers from methodological limitations and inconsistencies, which reduce our ability to translate findings to improve clinical practice. The purpose of this forum is to propose a coordinated approach to more seamlessly integrate sleep research into ED research with particular emphasis on best practices in the definition and assessment of sleep characteristics. METHODS In this article, we will describe the current status of sleep-related research and relevant gaps within ED research practices, define key sleep characteristics, and review common assessment strategies for these sleep characteristics. Throughout the forum, we also discuss study design considerations and recommendations for future research aiming to integrate sleep research into ED research. RESULTS/DISCUSSION Given the potential role of sleep in ED maintenance and treatment, it is important to build upon preliminary findings using a rigorous and systematic approach. Moving forward as a field necessitates a common lens through which future research on sleep and EDs may be conducted, communicated, and evaluated.
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Affiliation(s)
- Leah A Irish
- Department of Psychology, North Dakota State University, Fargo, North Dakota, USA
- Sanford Research, Center for Biobehavioral Research, Fargo, North Dakota, USA
| | | | - Stephanie M Manasse
- Center for Weight, Eating, and Lifestyle Sciences, Drexel University, Philadelphia, Pennsylvania, USA
- Department of Psychological Brain Sciences, Drexel University, Philadelphia, Pennsylvania, USA
| | | | - Lauren M Schaefer
- Sanford Research, Center for Biobehavioral Research, Fargo, North Dakota, USA
- Department of Psychiatry, University of North Dakota School of Medicine and Health Sciences, Fargo, North Dakota, USA
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Sjöland O, Svensson T, Madhawa K, NT H, Chung UI, Svensson AK. Associations of Subjective Sleep Quality with Wearable Device-Derived Resting Heart Rate During REM Sleep and Non-REM Sleep in a Cohort of Japanese Office Workers. Nat Sci Sleep 2024; 16:867-877. [PMID: 38947940 PMCID: PMC11214547 DOI: 10.2147/nss.s455784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Accepted: 06/05/2024] [Indexed: 07/02/2024] Open
Abstract
Background Associations between subjective sleep quality and stage-specific heart rate (HR) may have important clinical relevance when aiming to optimize sleep and overall health. The majority of previously studies have been performed during short periods under laboratory-based conditions. The aim of this study was to investigate the associations of subjective sleep quality with heart rate during REM sleep (HR REMS) and non-REM sleep (HR NREMS) using a wearable device (Fitbit Versa). Methods This is a secondary analysis of data from the intervention group of a randomized controlled trial (RCT) performed between December 3, 2018, and March 2, 2019, in Tokyo, Japan. The intervention group consisted of 179 Japanese office workers with metabolic syndrome (MetS), Pre-MetS or a high risk of developing MetS. HR was collected with a wearable device and sleep quality was assessed with a mobile application where participants answered The St. Mary's Hospital Sleep Questionnaire. Both HR and sleep quality was collected daily for a period of 90 days. Associations of between-individual and within-individual sleep quality with HR REMS and HR NREMS were analyzed with multi-level model regression in 3 multivariate models. Results The cohort consisted of 92.6% men (n=151) with a mean age (± standard deviation) of 44.1 (±7.5) years. A non-significant inverse between-individual association was observed for sleep quality with HR REMS (HR REMS -0.18; 95% CI -0.61, 0.24) and HR NREMS (HR NREMS -0.23; 95% CI -0.66, 0.21), in the final multivariable adjusted models; a statistically significant inverse within-individual association was observed for sleep quality with HR REMS (HR REMS -0.21 95% CI -0.27, -0.15) and HR NREMS (HR NREMS -0.21 95% CI -0.27, -0.14) after final adjustments for covariates. Conclusion The present study shows a statistically significant within-individual association of subjective sleep quality with HR REMS and HR NREMS. These findings emphasize the importance of considering sleep quality on the individual level. The results may contribute to early detection and prevention of diseases associated with sleep quality which may have important implications on public health given the high prevalence of sleep disturbances in the population.
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Affiliation(s)
- Olivia Sjöland
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Thomas Svensson
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
- Graduate School of Health Innovation, Kanagawa University of Human Services, Kawasaki-Ku, Kawasaki-Shi, Kanagawa, Japan
| | - Kaushalya Madhawa
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
| | - Hoang NT
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
| | - Ung-Il Chung
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Graduate School of Health Innovation, Kanagawa University of Human Services, Kawasaki-Ku, Kawasaki-Shi, Kanagawa, Japan
- Clinical Biotechnology, Center for Disease Biology and Integrative Medicine, Graduate School of Medicine, Tokyo, Japan
| | - Akiko Kishi Svensson
- Precision Health, Department of Bioengineering, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
- Department of Diabetes and Metabolic Diseases, The University of Tokyo, Tokyo, Japan
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Bailly S, Mendelson M, Baillieul S, Tamisier R, Pépin JL. The Future of Telemedicine for Obstructive Sleep Apnea Treatment: A Narrative Review. J Clin Med 2024; 13:2700. [PMID: 38731229 PMCID: PMC11084346 DOI: 10.3390/jcm13092700] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2024] [Revised: 04/24/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Obstructive sleep apnea is a common type of sleep-disordered breathing associated with multiple comorbidities. Nearly a billion people are estimated to have obstructive sleep apnea, which carries a substantial economic burden, but under-diagnosis is still a problem. Continuous positive airway pressure (CPAP) is the first-line treatment for OSAS. Telemedicine-based interventions (TM) have been evaluated to improve access to diagnosis, increase CPAP adherence, and contribute to easing the follow-up process, allowing healthcare facilities to provide patient-centered care. This narrative review summarizes the evidence available regarding the potential future of telemedicine in the management pathway of OSA. The potential of home sleep studies to improve OSA diagnosis and the importance of remote monitoring for tracking treatment adherence and failure and to contribute to developing patient engagement tools will be presented. Further studies are needed to explore the impact of shifting from teleconsultations to collaborative care models where patients are placed at the center of their care.
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Affiliation(s)
- Sébastien Bailly
- HP2 Laboratory, Inserm U1300, Grenoble Alps University, 38000 Grenoble, France; (S.B.); (M.M.); (S.B.); (R.T.)
| | - Monique Mendelson
- HP2 Laboratory, Inserm U1300, Grenoble Alps University, 38000 Grenoble, France; (S.B.); (M.M.); (S.B.); (R.T.)
| | - Sébastien Baillieul
- HP2 Laboratory, Inserm U1300, Grenoble Alps University, 38000 Grenoble, France; (S.B.); (M.M.); (S.B.); (R.T.)
| | - Renaud Tamisier
- HP2 Laboratory, Inserm U1300, Grenoble Alps University, 38000 Grenoble, France; (S.B.); (M.M.); (S.B.); (R.T.)
| | - Jean-Louis Pépin
- HP2 Laboratory, Inserm U1300, Grenoble Alps University, 38000 Grenoble, France; (S.B.); (M.M.); (S.B.); (R.T.)
- Laboratoire EFCR, CHU de Grenoble, CS10217, 38043 Grenoble, France
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Liang Z, Melcer E, Khotchasing K, Hoang NH. Co-design personal sleep health technology for and with university students. Front Digit Health 2024; 6:1371808. [PMID: 38655450 PMCID: PMC11035743 DOI: 10.3389/fdgth.2024.1371808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 03/28/2024] [Indexed: 04/26/2024] Open
Abstract
University students often experience sleep disturbances and disorders. Personal digital technologies present a great opportunity for sleep health promotion targeting this population. However, studies that engage university students in designing and implementing digital sleep health technologies are scarce. This study sought to understand how we could build digital sleep health technologies that meet the needs of university students through a co-design process. We conducted three co-design workshops with 51 university students to identify design opportunities and to generate features for sleep health apps through workshop activities. The generated ideas were organized using the stage-based model of self-tracking so that our findings could be well-situated within the context of personal health informatics. Our findings contribute new design opportunities for sleep health technologies targeting university students along the dimensions of sleep environment optimization, online community, gamification, generative AI, materializing sleep with learning, and personalization.
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Affiliation(s)
- Zilu Liang
- Ubiquitous and Personal Computing Lab, Faculty of Engineering, Kyoto University of Advanced Science (KUAS), Kyoto, Japan
| | - Edward Melcer
- Alternative Learning Technologies and Games Lab, Department of Computational Media, University of California, Santa Cruz (UCSC), CA, United States
| | - Kingkarn Khotchasing
- Ubiquitous and Personal Computing Lab, Faculty of Engineering, Kyoto University of Advanced Science (KUAS), Kyoto, Japan
| | - Nhung Huyen Hoang
- Ubiquitous and Personal Computing Lab, Faculty of Engineering, Kyoto University of Advanced Science (KUAS), Kyoto, Japan
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Manners J, Kemps E, Guyett A, Stuart N, Lechat B, Catcheside P, Scott H. Estimating vigilance from the pre-work shift sleep using an under-mattress sleep sensor. J Sleep Res 2024:e14138. [PMID: 38185773 DOI: 10.1111/jsr.14138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/14/2023] [Accepted: 12/18/2023] [Indexed: 01/09/2024]
Abstract
Predicting vigilance impairment in high-risk shift work occupations is critical to help to reduce workplace errors and accidents. Current methods rely on multi-night, often manually entered, sleep data. This study developed a machine learning model for predicting vigilance errors based on a single prior sleep period, derived from an under-mattress sensor. Twenty-four healthy volunteers (mean [SD] age = 27.6 [9.5] years, 12 male) attended the laboratory on two separate occasions, 1 month apart, to compare wake performance and sleep under two different lighting conditions. Each condition occurred over an 8 day protocol comprising a baseline sleep opportunity from 10 p.m. to 7 a.m., a 27 h wake period, then daytime sleep opportunities from 10 a.m. to 7 p.m. on days 3-7. From 12 a.m. to 8 a.m. on each of days 4-7, participants completed simulated night shifts that included six 10 min psychomotor vigilance task (PVT) trials per shift. Sleep was assessed using an under-mattress sensor. Using extra-trees machine learning models, PVT performance (reaction times <500 ms, reaction, and lapses) during each night shift was predicted based on the preceding daytime sleep. The final extra-trees model demonstrated moderate accuracy for predicting PVT performance, with standard errors (RMSE) of 19.9 ms (reaction time, 359 [41.6]ms), 0.42 reactions/s (reaction speed, 2.5 [0.6] reactions/s), and 7.2 (lapses, 10.5 [12.3]). The model also correctly classified 84% of trials containing ≥5 lapses (Matthews correlation coefficient = 0.59, F1 = 0.83). Model performance is comparable to current fatigue prediction models that rely upon self-report or manually entered data. This efficient approach may help to manage fatigue and safety in non-standard work schedules.
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Affiliation(s)
- Jack Manners
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
- College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia
| | - Eva Kemps
- College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia
| | - Alisha Guyett
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
- College of Medicine and Public Health, Flinders University, Adelaide, Australia
| | - Nicole Stuart
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
- College of Education, Psychology, and Social Work, Flinders University, Adelaide, Australia
| | - Bastien Lechat
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
| | - Peter Catcheside
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
| | - Hannah Scott
- Flinders Health and Medical Research Institute: Sleep Health, Flinders University, Adelaide, Australia
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