This article, titled “What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies,” published in the Journal of Occupational Health in 2024, addresses a critical need in the rapidly evolving field of digital mental health. Authored by Naomichi Tani and a team of experts from various disciplines including ergonomics, information systems, occupational health, and digital mental health, this opinion piece provides a systematized classification of digital health technologies for mental health interventions. The study was received on July 20, 2023, revised on September 21, 2023, and accepted on October 10, 2023, with advance access publication occurring on November 9, 2023.
The widespread adoption of digital health technology for mental health interventions globally has highlighted the importance of using digital phenotyping to identify an individual’s mental health status. However, the authors note a lack of consensus on the technical classification of these digital health technologies, including those related to digital phenotyping, which hinders accurate trend identification in mental health interventions. This absence of a clear classification system also poses challenges for occupational health technology developers and service providers in understanding the availability of applicable technologies. The coronavirus disease pandemic further underscored the need for new occupational health strategies incorporating digital health technologies, as teleworking negatively impacted workers’ physical and mental health. The World Health Organization (WHO) and International Labour Organization have called for occupational health services to integrate digital health technologies for ergonomic, mental, and psychosocial support.
To address this gap, the study aimed to systematize digital health technologies currently used or expected to be widely used in mental health prevention and intervention. The authors define digital health technology interventions in mental health as “healthcare services aimed at primary prevention provided to the general workforce using information and communication technology and digital technology,” encompassing services that use technical algorithms (e.g., apps, communication robots, wearable devices, self-monitoring) and those that do not (e.g., online counseling).
Methodology:
The study employed a rigorous approach combining a review of systematic review articles with the Delphi method.
- Systematic Review:
- Initially, a search was conducted on PubMed and Google Scholar for articles on “digital phenotyping” and “mental health” from the last five years, specifically filtering for systematic reviews.
- Inclusion criteria required systematic reviews that collected and analyzed data for digital phenotyping of mental health, articles relevant to technical classification, full articles, and English language publications.
- Exclusion criteria included articles not about digital phenotyping technology, systematic reviews unrelated to mental health interventions, gray literature, or review protocols.
- This initial search identified four eligible systematic review articles.
- Recognizing potential selection bias due to the lack of a detailed technical classification consensus on digital phenotypes, the authors adopted a 1-level backward snowballing method. This involved identifying new papers from the reference lists of the initial articles.
- Through this snowballing approach, an additional eight review articles were incorporated, resulting in a comprehensive review of 12 articles on digital health technologies for mental health interventions. The reviewed studies mentioned numerous technologies such as accelerometry, GPS, microphones, heart rate sensors, screen activity, call logs, social media logs, chatbots, online therapy, and virtual reality, highlighting their diverse and often unsystematized nature.
- Delphi Technique:
- To systematize the technologies identified from the literature review, the Delphi method was utilized. This technique involves surveying experts repeatedly until their opinions converge.
- Experts from various disciplines participated, including psychology, occupational health, physiology, information science, labor science, nursing, physical therapy, and ergonomics.
- The process involved an administrator (N.T.) preparing a tentative technical classification based on review results, panelists providing input via email, and the administrator revising the proposal based on feedback. This iterative process continued until a consensus was reached on the question: “What are the digital health technology intervention situations and categories used to measure or monitor mental health?”.
Key Findings: The 11 Technical Categories:
Through this rigorous process, the experts agreed upon 11 technical categories for digital health interventions in mental health:
- Heart Rate Estimation: This category includes both traditional contact measurements by wearable devices and increasingly effective non-contact methods for measuring heart rate.
- Exercise/Physical Activity: Monitoring daily exercise is considered necessary for preventing mental health issues, with studies showing that even one hour of exercise per week can significantly lower the incidence of future depression. Many reviewed studies utilized physical activity approaches through digital phenotyping.
- Sleep Estimation: Given that individuals with insomnia have approximately twice the risk of developing depression, monitoring sleep status is crucial for mental health prevention. Sleep estimation is a widely utilized digital health technology.
- Contactless Heart Rate/Pulse Wave Estimation: This category was specifically included due to the reported effectiveness of non-contact methods for measuring heart rate, differentiating it from general heart rate estimation.
- Voice and Emotion Analysis: This involves using smartphone microphones and cameras to infer emotions through voice-based facial recognition, a technology expected to be frequently used for mood estimation in the future.
- Self-Care/Cognitive Behavioral Therapy (CBT)/Mindfulness: These interventions are increasingly delivered internet-based or via apps, with CBT and mindfulness potentially conducted by chatbots or online therapists.
- Dietary Management: Online and app-based dietary approaches are expected to see more extensive use, particularly as digital health technology interventions prove effective for eating disorders.
- Psychological Safety: This category addresses organizational efforts crucial for mental health, with interventions like crew resource management potentially offered through apps in the future.
- Communication Robots: With the rise of AI, mental health interventions leveraging communication robots, such as animal robots and robot therapy, are being considered.
- Avatar/Metaverse Devices: Although current avatar therapy has not shown clear efficacy, the authors included this category due to the potential for future AI innovations and extended reality approaches to become useful interventions.
- Brain Wave Devices: Despite not being widely used yet, brain wave devices were included as a category due to their potential in light of future technological innovations.
Conclusion and Implications:
The authors emphasize that these 11 categories were intentionally defined to include technologies expected to become widely used in the future, making them socially implementable and useful for mental health interventions. From an occupational health perspective, the study suggests that the use of these technologies should extend beyond individual workers to include employer-initiated organizational interventions, noting a current lag in employer-friendly tools.
The systematization presented in this study is considered a temporary classification to organize the current landscape, with the understanding that the 11 categories should be updated periodically as digital health technology continues to evolve rapidly. This study is expected to contribute significantly to future research and policy-making in the areas of digital mental health and e-Health.
Reference: Tani, N., Fujihara, H., Ishii, K., Kamakura, Y., Tsunemi, M., Yamaguchi, C., Eguchi, H., Imamura, K., Kanamori, S., Kojimahara, N., & Ebara, T. (2024). What digital health technology types are used in mental health prevention and intervention? Review of systematic reviews for systematization of technologies. Journal of Occupational Health, 66(1), uiad003. https://doi.org/10.1093/JOCCUH/uiad003
