Gopalakrishnan Abinaya, Venkataraman Revathi, Gururajan Raj, Zhou Xujuan, Genrich Rohan
Department of Networking and Communications, School of Computing, SRM Institute of Science and Technology, Kattankulathur, Chennai, India.
School of Business, University of Southern Queensland, Toowoomba, Australia.
PeerJ Comput Sci. 2022 Aug 2;8:e1042. doi: 10.7717/peerj-cs.1042. eCollection 2022.
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.
心理健康问题是新冠疫情的一个严重后果,影响着全球约7亿人。这些生理问题需要通过智能手机和健身手环等非侵入性设备持续观察民众,以消除持续被监测所带来的心理负担。另一方面,技术进步提升了传统手机的功能和作用,从简单通信发展到具备观察功能,而且在尺寸和价格方面的可及性提高,这可能反映出广大消费者对智能手机越来越熟悉。通过持续监测,再加上手机中各种嵌入式传感器,原始数据可以转化为有关消费者行为和举动的有用信息。因此,这项全面工作的目标集中在迄今通过智能手机被动监测数据来预测心理健康问题的文献研究上。本研究还探讨了用户与这种自我监测技术的互动方式以及他们可能面临的挑战。我们在几个电子数据库(PubMed、IEEE Xplore、ACM数字图书馆、Soups、APA PsycInfo和Mendeley Data)中搜索了2015年1月至2020年12月期间发表的与该主题相关且语言为英语的研究。我们识别出943篇文章,其中115篇文章根据预先确定的纳入和排除标准经人工筛选符合本范围综述的要求。这些研究提供了关于用于健康监测的智能手机的各种研究,比如身体活动(26.0%;30/115)、心理健康分析(27.8%;32/115)、针对学生的监测(15.6%;18/115)是主要开展的三项分析。