Virtual Communities, Machine Learning and IoT: Opportunities and Challenges in Mental Health Research
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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Online communities, whether static or mobile, proved to play a major role in digital health, including mental health.
“Online communities [27, 28], whether static or mobile, proved to play a major role in digital health [29–31], including mental health [11, 32, 33].”
From Effectiveness of online mindfulness interventions on medical students’ mental health: a systematic review (2021) · cites this paper as [33]
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“Online communities [27, 28], whether static or mobile, proved to play a major role in digital health [29– 31], including mental health [11, 32, 33].”
BackgroundSelf-citation
- Authors
- El Morr, C.
- Affiliations
- York University, Toronto, Canada
- ORCID
- El Morr, Christo
- Venue
- International Journal of Extreme Automation and Connectivity in Healthcare
- Publisher
- IGI Global Scientific Publishing
- Published
- 2019-01-01
- Volume
- 1
- Issue
- 1
- Pages
- 4-11
- ISSN
- 2577-4794 (ISSN-L)
- 2577-4808
- OpenAlex
- W2902673853
- Cited by
- 10
- References
- 49
- Citations by year
- 2024: 3 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 1
- FWCI
- 1.26
- Type
- journal article
- Language
- ng
- Open access
- closed
- Locations
- International Journal of Extreme Automation and Connectivity in Healthcare (publishedVersion)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
- Keywords
- mental health, Internet of Things, machine learning, mental health interventions, self-management, data integration, care coordination, stress, anxiety, depression
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