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Updated: Sep 10, 2025

Multi-Modal Home Sleep Monitoring in Older Adults
Published on: January 26, 2019
Examining sleep health and its associations with technology use among older adults in Sweden: insights from a
Sarah Nauman Ghazi1, Anders Behrens2, Johan Sanmartin Berglund2
1Department of Health, Blekinge Institute of Technology, Valhallavägen, Karlskrona, 371 41, Blekinge, Sweden. sarah.n.ghazi@bth.se.
Introduction:
Exploring the association between technology use and sleep health in older adults is important as digital engagement becomes integrated into society.
Objective:
This study aimed to examine sleep health and its association with technology use in a population-based cohort of 60 years and older.
Methods:
This cross-sectional, population-based study (2023) included 436 older adults from the Swedish National Study on Aging and Care, Blekinge (SNAC-B) population. These participants were sent questionnaires about their sleep, internet usage, Digital Social Participation (DSP), Technology Anxiety (TA), Technology Enthusiasm (TE), and use of information and communication technology. We used a multidimensional instrument, SATED, to measure sleep health. In this study, we conducted statistical analyses using the chi2 test, T-test, Pearson correlation, and backward linear and logistic regression.
Results:
Our study found that older adults (60 years+) have a mean sleep health score of 7.40 (SD = 2.03). TE ([Formula: see text], [Formula: see text]) and DSP ([Formula: see text], [Formula: see text]) were positively associated with better sleep health, while TA ([Formula: see text], [Formula: see text]) was negatively associated. Frequent internet users(M = 7.6) and engaging with screens before bedtime (M = 7.7) had higher sleep health scores compared to non-frequent users (M = 6.90, [Formula: see text]) and none or seldom engagement with screens before bedtime (M = 7.10, [Formula: see text]) respectively. Linear regression showed TE positively associated (β = 0.241, [Formula: see text]) while TA negatively associated (β = -0.220, [Formula: see text]) with sleep health. DSP was found to be a predictor of better satisfaction (OR: 1.32, [Formula: see text]), efficiency (OR: 1.16, [Formula: see text]), and duration of sleep (OR:1.16, [Formula: see text]). Lower TA predicted better satisfaction (OR: 0.81, [Formula: see text]), timing (OR: 0.74, [Formula: see text]), and efficiency (OR:0.78, [Formula: see text]) of sleep. Older adults who use technology one hour before sleep have better sleep timing (OR: 3.003, [Formula: see text]), while those who do use mobile phones with a screen during the awake period after sleep onset have poor sleep timing (OR:0.016, [Formula: see text]).
Conclusions:
DSP and TE support better sleep health, while TA negatively impacts sleep satisfaction, timing, and efficiency. Encouraging positive digital engagement and minimizing technology-related stress may promote healthier sleep in older adults.
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