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Digital Mental Health: Changes, Challenges and Success Strategies

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Behavioral and Mental Health".

Deadline for manuscript submissions: 31 January 2025 | Viewed by 14041

Special Issue Editor


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Guest Editor
Australian Institute for Suicide Research and Prevention, School of Applied Psychology, Griffith University, Messines Ridge Road, Mount Gravatt, QLD 4122, Australia
Interests: mental health care; suicide prevention; digital mental health; men; athletes; young people; older people

Special Issue Information

Dear Colleagues,

Mental illness and suicide are ongoing primary global health problems that need accessible and scalable solutions. For example, digital mental health (DMH) is a contemporary method of mental health care that is distinguished by the large-scale integration of telehealth, apps, and digital platforms, as well as the promise of big data, genomics and artificial intelligence (AI). DMH platforms are a key technology for the purpose of assessment, support, prevention, and treatment in mental health. The global emerging mental health devices and platforms market is predicted to grow from USD 2,568.6 million in 2021 to USD 18,717.5 million by 2030, at a compound annual growth rate of 21.1%. The effectiveness of technology in DMH is a major challenge. There is an extensive amount of DMH interventions (DMHIs) and technologies, in addition to the shifting focus and target populations. A hindering issue for the advancement of DMH is the sustained engagement of service users. This is because it is difficult for users and practitioners to discern which digital platforms and DMHIs are effective, usable and of good quality. Furthermore, it is necessary to clarify what mental health indications and populations these digital solutions are suitable for. This Special Issue invites papers on the changes, challenges and success strategies of this domain. The intent is to provide new insights and to pinpoint some focus areas for increasing the evidence base and engagement with DMH.

Dr. Luke Balcombe
Guest Editor

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Keywords

  • digital mental health
  • suicide prevention
  • mood, anxiety and personality disorders
  • loneliness
  • adult ADHD
  • autism spectrum
  • obsessive compulsive disorder
  • schizophrenia
  • alcohol and other drug addictions
  • engagement strategies for men's mental health
  • engagement strategies for children and adolescent mental health
  • linking strategies
  • engagement strategies for older people's mental health
  • digital solutions

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Published Papers (3 papers)

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Research

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12 pages, 1289 KiB  
Article
Mental Health Applications of Generative AI and Large Language Modeling in the United States
by Sri Banerjee, Pat Dunn, Scott Conard and Asif Ali
Int. J. Environ. Res. Public Health 2024, 21(7), 910; https://doi.org/10.3390/ijerph21070910 - 12 Jul 2024
Cited by 1 | Viewed by 2903
Abstract
(1) Background: Artificial intelligence (AI) has flourished in recent years. More specifically, generative AI has had broad applications in many disciplines. While mental illness is on the rise, AI has proven valuable in aiding the diagnosis and treatment of mental disorders. However, there [...] Read more.
(1) Background: Artificial intelligence (AI) has flourished in recent years. More specifically, generative AI has had broad applications in many disciplines. While mental illness is on the rise, AI has proven valuable in aiding the diagnosis and treatment of mental disorders. However, there is little to no research about precisely how much interest there is in AI technology. (2) Methods: We performed a Google Trends search for “AI and mental health” and compared relative search volume (RSV) indices of “AI”, “AI and Depression”, and “AI and anxiety”. This time series study employed Box–Jenkins time series modeling to forecast long-term interest through the end of 2024. (3) Results: Within the United States, AI interest steadily increased throughout 2023, with some anomalies due to media reporting. Through predictive models, we found that this trend is predicted to increase 114% through the end of the year 2024, with public interest in AI applications being on the rise. (4) Conclusions: According to our study, we found that the awareness of AI has drastically increased throughout 2023, especially in mental health. This demonstrates increasing public awareness of mental health and AI, making advocacy and education about AI technology of paramount importance. Full article
(This article belongs to the Special Issue Digital Mental Health: Changes, Challenges and Success Strategies)
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23 pages, 1851 KiB  
Article
Evolving Adult ADHD Care: Preparatory Evaluation of a Prototype Digital Service Model Innovation for ADHD Care
by Bronwin Patrickson, Lida Shams, John Fouyaxis, Jörg Strobel, Klaus Oliver Schubert, Mike Musker and Niranjan Bidargaddi
Int. J. Environ. Res. Public Health 2024, 21(5), 582; https://doi.org/10.3390/ijerph21050582 - 1 May 2024
Viewed by 2823
Abstract
Background: Given the prevalence of ADHD and the gaps in ADHD care in Australia, this study investigates the critical barriers and driving forces for innovation. It does so by conducting a preparatory evaluation of an ADHD prototype digital service innovation designed to help [...] Read more.
Background: Given the prevalence of ADHD and the gaps in ADHD care in Australia, this study investigates the critical barriers and driving forces for innovation. It does so by conducting a preparatory evaluation of an ADHD prototype digital service innovation designed to help streamline ADHD care and empower individual self-management. Methods: Semi-structured interviews with ADHD care consumers/participants and practitioners explored their experiences and provided feedback on a mobile self-monitoring app and related service innovations. Interview transcripts were double coded to explore thematic barriers and the enablers for better ADHD care. Results: Fifteen interviews (9 consumers, 6 practitioners) revealed barriers to better ADHD care for consumers (ignorance and prejudice, trust, impatience) and for practitioners (complexity, sustainability). Enablers for consumers included validation/empowerment, privacy, and security frameworks, tailoring, and access. Practitioners highlighted the value of transparency, privacy and security frameworks, streamlined content, connected care between services, and the tailoring of broader metrics. Conclusions: A consumer-centred approach to digital health service innovation, featuring streamlined, private, and secure solutions with enhanced mobile tools proves instrumental in bridging gaps in ADHD care in Australia. These innovations should help to address the gaps in ADHD care in Australia. These innovations should encompass integrated care, targeted treatment outcome data, and additional lifestyle support, whilst recognising the tensions between customised functionalities and streamlined displays. Full article
(This article belongs to the Special Issue Digital Mental Health: Changes, Challenges and Success Strategies)
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Review

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23 pages, 713 KiB  
Review
Evaluation of the Use of Digital Mental Health Platforms and Interventions: Scoping Review
by Luke Balcombe and Diego De Leo
Int. J. Environ. Res. Public Health 2023, 20(1), 362; https://doi.org/10.3390/ijerph20010362 - 26 Dec 2022
Cited by 21 | Viewed by 7368
Abstract
Background: The increasing use of digital mental health (DMH) platforms and digital mental health interventions (DMHIs) is hindered by uncertainty over effectiveness, quality and usability. There is a need to identify the types of available evidence in this domain. Aim: This study is [...] Read more.
Background: The increasing use of digital mental health (DMH) platforms and digital mental health interventions (DMHIs) is hindered by uncertainty over effectiveness, quality and usability. There is a need to identify the types of available evidence in this domain. Aim: This study is a scoping review identifying evaluation of the (1) DMH platform/s used; and (2) DMHI/s applied on the DMH platform/s. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guided the review process. Empirical studies that focused on evaluation of the use and application of DMH platforms were included from journal articles (published 2012–2022). A literature search was conducted using four electronic databases (Scopus, ScienceDirect, Sage and ACM Digital Library) and two search engines (PubMed and Google Scholar). Results: A total of 6874 nonduplicate records were identified, of which 144 were analyzed and 22 met the inclusion criteria. The review included general/unspecified mental health and/or suicidality indications (n = 9, 40.9%), followed by depression (n = 5, 22.7%), psychosis (n = 3, 13.6%), anxiety and depression (n = 2, 9.1%), as well as anxiety, depression and suicidality (n = 1, 4.5%), loneliness (n = 1, 4.5%), and addiction (n = 1, 4.5%). There were 11 qualitative studies (50%), 8 quantitative studies (36.4%), and 3 mixed-methods studies (n = 3, 13.6%). The results contained 11 studies that evaluated the DMH platform/s and 11 studies that evaluated the DMHI/s. The studies focused on feasibility, usability, engagement, acceptability and effectiveness. There was a small amount of significant evidence (1 in each 11), notably the (cost-)effectiveness of a DMHI with significant long-term impact on anxiety and depression in adults. Conclusion: The empirical research demonstrates the feasibility of DMH platforms and DMHIs. To date, there is mostly heterogeneous, preliminary evidence for their effectiveness, quality and usability. However, a scalable DMHI reported effectiveness in treating adults’ anxiety and depression. The scope of effectiveness may be widened through targeted strategies, for example by engaging independent young people. Full article
(This article belongs to the Special Issue Digital Mental Health: Changes, Challenges and Success Strategies)
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