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The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review

BACKGROUND: Since the era of smartphones started in early 2007, they have steadily turned into an accepted part of our lives. Poor sleep is a health problem that needs to be closely monitored before it causes severe mental health problems, such as anxiety or depression. Sleep disorders (eg, acute in...

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Detalles Bibliográficos
Autores principales: Alamoudi, Doaa, Breeze, Emma, Crawley, Esther, Nabney, Ian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984993/
https://www.ncbi.nlm.nih.gov/pubmed/36800211
http://dx.doi.org/10.2196/44123
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author Alamoudi, Doaa
Breeze, Emma
Crawley, Esther
Nabney, Ian
author_facet Alamoudi, Doaa
Breeze, Emma
Crawley, Esther
Nabney, Ian
author_sort Alamoudi, Doaa
collection PubMed
description BACKGROUND: Since the era of smartphones started in early 2007, they have steadily turned into an accepted part of our lives. Poor sleep is a health problem that needs to be closely monitored before it causes severe mental health problems, such as anxiety or depression. Sleep disorders (eg, acute insomnia) can also develop to chronic insomnia if not treated early. More specifically, mental health problems have been recognized to have casual links to anxiety, depression, heart disease, obesity, dementia, diabetes, and cancer. Several researchers have used mobile sensors to monitor sleep and to study changes in individual mood that may cause depression and anxiety. OBJECTIVE: Extreme sleepiness and insomnia not only influence physical health, they also have a significant impact on mental health, such as by causing depression, which has a prevalence of 18% to 21% among young adults aged 16 to 24 in the United Kingdom. The main body of this narrative review explores how passive data collection through smartphone sensors can be used in predicting anxiety and depression. METHODS: A narrative review of the English language literature was performed. We investigated the use of smartphone sensors as a method of collecting data from individuals, regardless of whether the data source was active or passive. 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,” and “sleep detector.” RESULTS: The 12 articles presented in this paper explain the current practices of using smartphone sensors for tracking sleep patterns and detecting changes in mental health, especially depression and anxiety over a period of time. Several researchers have been exploring technological methods to detect sleep using smartphone sensors. Researchers have also investigated changes in smartphone sensors and linked them with mental health and well-being. CONCLUSIONS: The conducted review provides an overview of the possibilities of using smartphone sensors unobtrusively to collect data related to sleeping pattern, depression, and anxiety. This provides a unique research opportunity to use smartphone sensors to detect insomnia and provide early detection or intervention for mental health problems such as depression and anxiety if insomnia is detected.
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spelling pubmed-99849932023-03-05 The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review Alamoudi, Doaa Breeze, Emma Crawley, Esther Nabney, Ian JMIR Mhealth Uhealth Review BACKGROUND: Since the era of smartphones started in early 2007, they have steadily turned into an accepted part of our lives. Poor sleep is a health problem that needs to be closely monitored before it causes severe mental health problems, such as anxiety or depression. Sleep disorders (eg, acute insomnia) can also develop to chronic insomnia if not treated early. More specifically, mental health problems have been recognized to have casual links to anxiety, depression, heart disease, obesity, dementia, diabetes, and cancer. Several researchers have used mobile sensors to monitor sleep and to study changes in individual mood that may cause depression and anxiety. OBJECTIVE: Extreme sleepiness and insomnia not only influence physical health, they also have a significant impact on mental health, such as by causing depression, which has a prevalence of 18% to 21% among young adults aged 16 to 24 in the United Kingdom. The main body of this narrative review explores how passive data collection through smartphone sensors can be used in predicting anxiety and depression. METHODS: A narrative review of the English language literature was performed. We investigated the use of smartphone sensors as a method of collecting data from individuals, regardless of whether the data source was active or passive. 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,” and “sleep detector.” RESULTS: The 12 articles presented in this paper explain the current practices of using smartphone sensors for tracking sleep patterns and detecting changes in mental health, especially depression and anxiety over a period of time. Several researchers have been exploring technological methods to detect sleep using smartphone sensors. Researchers have also investigated changes in smartphone sensors and linked them with mental health and well-being. CONCLUSIONS: The conducted review provides an overview of the possibilities of using smartphone sensors unobtrusively to collect data related to sleeping pattern, depression, and anxiety. This provides a unique research opportunity to use smartphone sensors to detect insomnia and provide early detection or intervention for mental health problems such as depression and anxiety if insomnia is detected. JMIR Publications 2023-02-17 /pmc/articles/PMC9984993/ /pubmed/36800211 http://dx.doi.org/10.2196/44123 Text en ©Doaa Alamoudi, Emma Breeze, Esther Crawley, Ian Nabney. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 17.02.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mHealth and uHealth, is properly cited. The complete bibliographic information, a link to the original publication on https://mhealth.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Review
Alamoudi, Doaa
Breeze, Emma
Crawley, Esther
Nabney, Ian
The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title_full The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title_fullStr The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title_full_unstemmed The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title_short The Feasibility of Using Smartphone Sensors to Track Insomnia, Depression, and Anxiety in Adults and Young Adults: Narrative Review
title_sort feasibility of using smartphone sensors to track insomnia, depression, and anxiety in adults and young adults: narrative review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9984993/
https://www.ncbi.nlm.nih.gov/pubmed/36800211
http://dx.doi.org/10.2196/44123
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