Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review
Article
Article Title | Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review |
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ERA Journal ID | 211194 |
Article Category | Article |
Authors | Gopalakrishnan, Abinaya (Author), Venkataraman, Revathi (Author), Gururajan, Raj (Author), Xujuan, Zhou (Author) and Genrich, Rohan (Author) |
Journal Title | PeerJ Computer Science |
Journal Citation | 8, pp. 1-34 |
Article Number | e1042 |
Number of Pages | 34 |
Year | 2022 |
Publisher | PeerJ |
Place of Publication | United Kingdom |
ISSN | 2376-5992 |
Digital Object Identifier (DOI) | https://doi.org/10.7717/peerj-cs.1042 |
Web Address (URL) | https://peerj.com/articles/cs-1042 |
Abstract | Mental health issues are a serious consequence of the COVID-19 pandemic, influencing about 700 million people worldwide. These physiological issues need to be consistently observed on the people through non-invasive devices such as smartphones, and fitness bands in order to remove the burden of having the conciseness of continuously being monitored. On the other hand, technological improvements have enhanced the abilities and roles of conventional mobile phones from simple communication to observations and improved accessibility in terms of size and price may reflect growing familiarity with the smartphone among a vast number of consumers. As a result of continuous monitoring, together with various embedded sensors in mobile phones, raw data can be converted into useful information about the actions and behaviors of the consumers. Thus, the aim of this comprehensive work concentrates on the literature work done so far in the prediction of mental health issues via passive monitoring data from smartphones. This study also explores the way users interact with such self-monitoring technologies and what challenges they might face. We searched several electronic databases (PubMed, IEEE Xplore, ACM Digital Libraries, Soups, APA PsycInfo, and Mendeley Data) for published studies that are relevant to focus on the topic and English language proficiency from January 2015 to December 2020. We identified 943 articles, of which 115 articles were eligible for this scoping review based on the predetermined inclusion and exclusion criteria carried out manually. These studies provided various works regarding smartphones for health monitoring such as Physical activity (26.0 percent; 30/115), Mental health analysis (27.8 percent; 32/115), Student specific monitoring (15.6 percent; 18/115) are the three analyses carried out predominantly. |
Keywords | Mobile phone, Sensor, Smartphone, Passive sensing, Mental health, Ambient sensors, Mental health monitoring |
ANZSRC Field of Research 2020 | 460207. Modelling and simulation |
460905. Information systems development methodologies and practice | |
Byline Affiliations | School of Business |
SRM Institute of Science and Technology, India | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q79vx/mobile-phone-enabled-mental-health-monitoring-to-enhance-diagnosis-for-severity-assessment-of-behaviours-a-review
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