Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review

Gopalakrishnan, Abinaya and Venkataraman, Revathi and Gururajan, Raj ORCID: https://orcid.org/0000-0002-5919-0174 and Xujuan, Zhou and Genrich, Rohan (2022) Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review. PeerJ Computer Science, 8:e1042. pp. 1-34.

[img]
Preview
Text (Published Version)
peerj-cs-1042.pdf
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview

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.


Statistics for USQ ePrint 50671
Statistics for this ePrint Item
Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Faculty/School / Institute/Centre: Current - Faculty of Business, Education, Law and Arts - School of Business (18 Jan 2021 -)
Date Deposited: 04 Aug 2022 04:38
Last Modified: 28 Sep 2022 05:22
Uncontrolled Keywords: Mobile phone, Sensor, Smartphone, Passive sensing, Mental health, Ambient sensors, Mental health monitoring
Fields of Research (2020): 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460207 Modelling and simulation
46 INFORMATION AND COMPUTING SCIENCES > 4609 Information systems > 460905 Information systems development methodologies and practice
Socio-Economic Objectives (2020): 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220408 Information systems
Identification Number or DOI: https://doi.org/10.7717/peerj-cs.1042
URI: http://eprints.usq.edu.au/id/eprint/50671

Actions (login required)

View Item Archive Repository Staff Only