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Virtual Communities, Machine Learning and IoT: Opportunities and Challenges in Mental Health Research

Virtual Communities, Machine Learning and IoT: Opportunities and Challenges in Mental Health Research
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Author(s): Christo El Morr (York University, Toronto, Canada)
Copyright: 2021
Pages: 9
Source title: Research Anthology on Mental Health Stigma, Education, and Treatment
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-8544-3.ch022

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Abstract

Mental health challenges such as stress, anxiety and depression are on the rise worldwide. Health virtual communities (VCs) is a rising paradigm that has proven to be efficient and effective in delivering mental health interventions that address self-management, diagnosis and treatment targeting people facing mental health challenges. However, current Health VCs have limited application; they lack the ability to provide access to coordinated services and to continuously collect and integrate data originating from different devices in a streamlined manner. The Internet of Things (IoT) and machine learning represent a unique opportunity to expand the Health Virtual Community applications in the mental health domain; however, they represent a unique situation where challenges arise. This article will discuss the opportunities and challenges that virtual communities, machine learning and IoT represent for mental health research.

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