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Tani N, Fujihara H, Ishii K, Kamakura Y, Tsunemi M, Yamaguchi C, Eguchi H, Imamura K, Kanamori S, Kojimahara N, Ebara T. What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies. J Occup Health 2024; 66:uiad003. [PMID: 38258936 PMCID: PMC11020255 DOI: 10.1093/joccuh/uiad003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/21/2023] [Accepted: 10/10/2023] [Indexed: 01/24/2024] Open
Abstract
Digital health technology has been widely applied to mental health interventions worldwide. Using digital phenotyping to identify an individual's mental health status has become particularly important. However, many technologies other than digital phenotyping are expected to become more prevalent in the future. The systematization of these technologies is necessary to accurately identify trends in mental health interventions. However, no consensus on the technical classification of digital health technologies for mental health interventions has emerged. Thus, we conducted a review of systematic review articles on the application of digital health technologies in mental health while attempting to systematize the technology using the Delphi method. To identify technologies used in digital phenotyping and other digital technologies, we included 4 systematic review articles that met the inclusion criteria, and an additional 8 review articles, using a snowballing approach, were incorporated into the comprehensive review. Based on the review results, experts from various disciplines participated in the Delphi process and agreed on the following 11 technical categories for mental health interventions: heart rate estimation, exercise or physical activity, sleep estimation, contactless heart rate/pulse wave estimation, voice and emotion analysis, self-care/cognitive behavioral therapy/mindfulness, dietary management, psychological safety, communication robots, avatar/metaverse devices, and brain wave devices. The categories we defined intentionally included technologies that are expected to become widely used in the future. Therefore, we believe these 11 categories are socially implementable and useful for mental health interventions.
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Affiliation(s)
- Naomichi Tani
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
| | - Hiroaki Fujihara
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
| | - Kenji Ishii
- The Ohara Memorial Institute for Science of Labour, Tokyo 151-0051, Japan
| | - Yoshiyuki Kamakura
- Department of Information Systems, Faculty of Information Science and Technology, Osaka Institute of Technology, Osaka 573-0196, Japan
| | - Mafu Tsunemi
- Department of Occupational and Environmental Health, Nagoya City University Graduate School of Medical Sciences/Medical School, Nagoya 467-8601, Japan
| | - Chikae Yamaguchi
- Department of Nursing, Faculty of Nursing, Kinjo Gakuin University, Aichi 463-8521, Japan
| | - Hisashi Eguchi
- Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health,Kitakyushu 807-8555, Japan
| | - Kotaro Imamura
- Department of Digital Mental Health, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
| | - Satoru Kanamori
- Graduate School of Public Health, Teikyo University, Tokyo 173-8605, Japan
| | - Noriko Kojimahara
- Section of Epidemiology, Shizuoka Graduate University of Public Health, Shizuoka 420-0881, Japan
| | - Takeshi Ebara
- Department of Ergonomics, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Kitakyushu 807-8555, Japan
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