Collection 

Clinical applications of AI in mental health care

Submission status
Open
Submission deadline

In 1966, the first AI-powered mental health chatbot, Eliza was introduced. Now 57 years later, interest in AI has resurged in light of the chronic mental health workforce shortage and rising need for services. Researchers seeking to elucidate the mechanism of actions and preventive efforts are also turning to AI to synthesize genetic, neuroimaging, behavioral, and clinical data to glean new insights into these complex illnesses. While the first-generation AI applications for mental health developed in the 1960s and 1970s did not transform care, recent advances in computing, smartphones, algorithms, large language models, and data provide new opportunities for AI in mental health today. This collection will explore the latest advances and research in the newest generations of AI in mental health with a focus on clinically applicable, ethical, and transparent AI research.

npj Mental Health Research and npj Digital Medicine are collaborating on this joint collection to curate novel research that looks beyond feasibility to highlight how AI can be safely, ethically, and impactfully utilized to advance the understanding of mental illnesses and deliver better care to patients with these conditions. Reviews synthesizing current knowledge to help guide future developments are also encouraged as well as Perspectives on or from patient experiences, underserved communities, and technology developers. All submissions should be clinically focused in theme and feature methods that are transparent/reproducible in line with best practices and Nature Portfolio submission guidelines and editorial policies. 

Each journal will consider submissions covering:

npj Mental Health Research npj Digital Medicine
The effectiveness of AI-assisted interventions or comparing AI-based approaches with traditional therapeutic methods in real-world clinical settings and clinical trials 
 Readily reproducible and validated AI-based diagnostic tools and predictive models for mental health problems and mental health outcomes, such as treatment response, relapse rates, or suicide risk
The ethical challenges related to the use of AI in mental health, such as privacy concerns, informed consent, and potential biases in AI algorithms AI-powered digital interventions such as chatbots, virtual therapists, or mobile apps designed to provide mental health support, deliver therapy, or promote self-management
The real-world implementation and integration of AI technologies into existing mental health systems, including considerations of feasibility, acceptance, and barriers The analysis of large-scale mental health data sets using AI techniques to identify patterns, risk factors, or treatment efficacy
Human experiences of interacting with AI systems in mental health contexts, including patient outcomes, acceptance, trust, clinician-patient relationships, and perceptions of AI's role in the therapeutic process. The application of AI technologies to develop personalized treatment plans or recommendations based on individual characteristics, preferences, and treatment history
Submissions will be triaged and may be offered a transfer to the more appropriate journal, based on consultation between the Guest Editors of both journals.

This Collection supports and amplifies research related to SDG 3.

To submit, see the participating journals
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Editors

Dr. Eric Kuhn is a Clinical Psychologist at the Dissemination and Training Division of the VA National Center for PTSD (NCPTSD) and Associate Professor at Stanford University School of Medicine where he co-leads the Stanford Mental Health Technology and Innovation Hub. Dr. Kuhn is a founder of and leader in NCPTSD’s Mobile Mental Health Program, which has developed a suite of mobile apps designed to address PTSD and related comorbidities and currently directs the VA's Center for Mobile Apps Research Resources and Services (CMARRS). Dr. Kuhn has federally funded programs of research focusing on using technology, both web and mobile, to increase access to and engagement in PTSD and related mental health care and to make care more patient centered, efficient, and effective. Eric is an Associate Editor for npj Mental Health Research and will handle collection submissions to this journal. 

Dr. Maurice Mulvenna is Professor of Computer Science at Ulster University. Maurice’s research areas include artificial intelligence; data analytics; mental health & wellbeing data analysis; and assistive technologies. His most recent research focuses on working in partnership with mental health organisations, using artificial intelligence to uncover useful behavioural patterns in anonymised call and event data pertaining to crisis helplines, chatlines and suicidal behaviour in public places. He has chaired several conferences, including the 32nd British Human-Computer Interaction conference in 2018, 31st European Cognitive Ergonomics Conference in 2019, the 5th IEEE International Conference on Internet of People in 2019 and the International Conference on Information and Communication Technologies for Ageing Well and e-Health in 2021-2023. Maurice served for three years on UK Ofcom’s Advisory Committee on Older and Disabled People and currently serves on the editorial boards for academic journals including the Journal of Enabling Technologies and JMIR Rehabilitation and Assistive Technologies. Maurice is also a past winner of the European €200,000 IST Grand Prize, has won with colleagues the Best Innovation in Practice Award at the Dementia Care Awards, the Societal Impact Award at the UK National KTP Best of the Best Awards 2020 and recently won Highly Commended for the Mobile App of the Year at the 2021 Digital DNA Awards for the InspireD reminiscence for dementia app. He also won the Inaugural Award for Industry-Academic Collaboration from the Centre for Behaviour Change Conference on Behaviour Change for Health: Digital and Other Innovative Methods, in 2019 with colleagues. Maurice is an Editorial Board Member for npj Mental Health Research and will handle collection submissions to this journal.

Dr. John B. Torous is a dual board-certified psychiatrist and clinical informaticist with a background in electrical engineering and computer sciences.He is an assistant professor of psychiatry at Harvard Medical School and director of the division of digital psychiatry at Beth Isreal Deaconess Medical Center. Dr. Torous is active in investigating the potential of mobile mental health technologies for psychiatry, developing smartphone tools for clinical research, leading clinical studies of smartphone apps for diverse mental illnesses, and publishing on the research, ethical and patient perspectives of digital psychiatry. ​​John is an Associate Editor for npj Digital Medicine and will handle collection submissions to this journal. 

Dr. Raymond Bond is a professor of human-computer systems and has expertise in health and medical informatics (digital health). Raymond's work has involved human-computer interaction and data science/machine learning research in healthcare. Raymond has over 400 research outputs and has chaired/co-chaired a number of conferences: 1) 32nd International BCS Human Computer Interaction conference, 2) the 45th/ 46th Annual Conference of the International Society for Computerised Electrocardiology, 3) the 31st Annual European Conference of Cognitive Ergonomics, and 4) the Irish Human Computer Interaction symposium. He is currently chair of the International Digital Mental Health & Wellbeing Conference and is an Editorial Board Member for npj Digital Medicine.