Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Nov 7, 2022
Open Peer Review Period: Nov 7, 2022 - Jan 2, 2023
Date Accepted: Feb 3, 2023
(closed for review but you can still tweet)
The Feasibility of using Smartphone sensors to track Insomnia, Depression and Anxiety in Adult and Young Adults: Narrative Review
ABSTRACT
Background:
Insomnia is defined as ‘difficulty getting to sleep, early wakening, or non-restorative sleep’1. Research has shown that participants who report reduced sleep duration are at an increased risk of developing cardiovascular disease, and symptomatic diabetes2. Men who suffered from insomnia were found to have a significantly increased risk of mortality, compared to normal sleepers (OR=4)3. This research shows that sleep disorder and acute insomnia (affecting one in every three people in the UK) 4 have a causal link to poorer health. This acute insomnia can also be developed to chronic insomnia if it is not treated early. More specially, mental health problems have been recognised to have casual links to anxiety, depression, heart disease, obesity, dementia, diabetes and cancer 5,6,7.
Objective:
The main body of research, and the focus of this review, is on the impact of insomnia on mental health and an analysis of the current technologies used to detect insomnia and mental health problems.
Methods:
Articles were found from a search of Google Scholar records (from 2013 to 2020) with keywords including ‘Mobile Phone’, ‘Mobile Applications’, ‘Health Apps’, ‘Insomnia’, ‘Mental Health’, ‘Sleep Monitoring’, ‘Depression’, ‘Anxiety’, ‘Sleep Disorder’, ‘Lack of Sleep’, ‘Digital Phenotyping’, ‘Mobile Sensing’, ‘Smartphone Sensors’, ‘Sleep Detector’. We have investigated the uses of smartphone sensors as a method of collecting data from individual regardless of whether the data source is active or passive. The 11 articles included present a narrative review of the current practices of digital phenotyping studies for tracking sleep patterns as well as detecting changes in mental health over a period of time.
Results:
Several research have been discussing technological methods to detect insomnia using smartphone sensors. Researchers have also investigated the changes in the smartphone sensors and link it with the mental health and wellbeing. Using these results could help to further study that could help to provide an early intervention when sleep disorder detected.
Conclusions:
Extreme sleepiness and insomnia not only influences physical health; it has a significant impact on mental health as well, such as depression with a prevalence of 18% to 21% among young adults aged 16 to 24 in the UK 8. Research has found that individual’s sleeping pattern can be tracked using mobile sensors. The current studies have discussed the uses of mobile sensors to track sleeping pattern as well as mental health problems. A unique opportunity to use smartphones to study changes in sleeping pattern and provide early detection/intervention for mental health problem e.g., depression and anxiety can be discussed. Clinical Trial: NA
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