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Objective Sleep Monitoring at Home in Older Adults: A Scoping Review
Blekinge Institute of Technology, Faculty of Engineering, Department of Health.ORCID iD: 0000-0001-8114-8813
Blekinge Institute of Technology, Faculty of Engineering, Department of Health.ORCID iD: 0000-0002-9099-0348
Blekinge Institute of Technology, Faculty of Engineering, Department of Health.ORCID iD: 0000-0002-2848-2377
Blekinge Institute of Technology, Faculty of Engineering, Department of Health.ORCID iD: 0000-0003-4312-2246
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2024 (English)In: Journal of Sleep Research, ISSN 0962-1105, E-ISSN 1365-2869Article, review/survey (Refereed) Epub ahead of print
Abstract [en]

Inadequate sleep in older adults is linked to health issues such as frailty, cognitive impairment, and cardiovascular disorders. Maintaining regular sleep patterns is important for healthy aging, making effective sleep monitoring essential. While polysomnography (PSG) is the gold standard for diagnosing sleep disorders, its regular use in home settings is limited. Alternative objective monitoring methods in the home can offer insights into natural sleep patterns and factors affecting them without the limitations of PSG.

This scoping review aims to examine current technologies, sensors, and sleep parameters used for home-based sleep monitoring in older adults. It also aims to explore various predictors and outcomes associated with sleep to understand the factors of sleep monitoring at home. 

We identified 54 relevant articles using PubMed, Scopus, Web of Science, and an AI tool (Research Rabbit), with 48 studies using wearable technologies and eight studies using non-wearable technologies. Further, six types of sensors were utilized. The most common technology employed was actigraphy wearables, while ballistocardiography and electroencephalography were less common. The most frequent objective parameters of sleep measured were Total Sleep Time (TST), Wakeup After Sleep Onset (WASO), and Sleep Efficiency (SE), with only six studies evaluating sleep architecture in terms of sleep stages. Additionally, six categories of predictors and outcomes associated with sleep were analyzed, including Health-related, Environmental, Interventional, Behavioral, Time and Place, and Social associations. These associations correlate with TST, WASO, and SE and include in-bed behaviors, exterior housing conditions, aerobic exercise, living place, relationship status, and seasonal thermal environments.

Place, publisher, year, edition, pages
John Wiley & Sons, 2024.
Keywords [en]
Objective sleep monitoring, Sleep, Technology, Sensors, Actigraphy, Healthy aging
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Applied Health Technology
Identifiers
URN: urn:nbn:se:bth-26996DOI: 10.1111/jsr.14436ISI: 001373689200001Scopus ID: 2-s2.0-85211222774OAI: oai:DiVA.org:bth-26996DiVA, id: diva2:1905315
Available from: 2024-10-13 Created: 2024-10-13 Last updated: 2024-12-27Bibliographically approved
In thesis
1. From Sleep Monitoring to Digital Determinants: Understanding the Role of Technology in Older Adults' Sleep Health
Open this publication in new window or tab >>From Sleep Monitoring to Digital Determinants: Understanding the Role of Technology in Older Adults' Sleep Health
2024 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Background: As the global population ages and digital technology advances, the link between technology and sleep health in older adults becomes increasingly important. Digital tools can improve sleep through monitoring devices, increased digital social participation (DSP), and calming bedtime routines, but they also pose risks by disrupting sleep through device usage and the demands of a 24/7 society.

Objectives: This thesis explores the use of digital technologies in understanding sleep and its determinants in older adults and examines sleep health and its relationship with technology use in this population.

Method: We conducted a scoping review (Study1) and a cross-sectional quantitative population-based study (Study2). We identified 54 articles on home-based sleep monitoring technologies, identifying devices and their associated sleep parameters, predictors, and outcomes. We proceeded to examine the relationship between digital technology use and sleep health in older adults where we focused on technology use, DSP, technology enthusiasm, and anxiety. The analysis included both descriptive and inferential statistics.

Results: We found that wrist-worn actigraphy sensors are the most commonly used for home-based sleep monitoring in older adults, measuring total sleep time (TST), wake after sleep onset (WASO), and sleep efficiency (SE). Few studies used EEG or explored REM and NREM stages. We found six categories of predictors and outcomes. We found that in-bed behaviors like screen use were associated with TST, WASO, and SE (Study1). In quantitative analysis of a sample of 436 older adults (Study2), we found that increased technology use during awake after sleep-onset was associated with poor sleep timing. There was a positive correlation between DSP and technology enthusiasm with sleep health. Better DSP scores predicted better sleep satisfaction, efficiency, and duration. Conversely, technology anxiety was linked to poorer sleep health, including lower satisfaction, efficiency, and timing. Using a screen before sleep predicted better sleep timing and significantly better sleep health scores.

Conclusion: Together, these studies provide a comprehensive understanding of the positive and the negative aspects of how digital technologies impact sleep health inolder adults. The research emphasizes the need for a balanced approach to technology use, harnessing its benefits while minimizing negative effects.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2024. p. 103
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 2024:04
Keywords
Sleep health, Technology use, Older adults, Objective sleep monitoring, Applied health technology
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Research subject
Applied Health Technology
Identifiers
urn:nbn:se:bth-26955 (URN)978-91-7295-489-2 (ISBN)
Presentation
2024-11-25, J1630, BTH, Valhallavägen 1, Karlskrona, 13:00 (English)
Opponent
Supervisors
Available from: 2024-10-09 Created: 2024-09-30 Last updated: 2024-11-07Bibliographically approved

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Ghazi, Sarah NaumanBehrens, AndersBerner, JessicaSanmartin Berglund, JohanAnderberg, Peter

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