JMIR Mental Health

Cancer patients often face depression and anxiety, and Mindfulness-Based Interventions (MBIs), including internet-based versions, can effectively reduce these symptoms and improve their quality of life. This study aims to investigate the impact of Internet-based Mindfulness-Based Interventions (e-MBIs) on anxiety, depression, and stress symptoms in prostate and breast cancer patients.

Despite the efficacy of digital mental health technologies (DMHTs) in clinical trials, low uptake and poor engagement is common in real-world settings. Accordingly, digital technology experts or “Digital Navigators” are increasingly being used to enhance engagement and shared decision-making between health professionals and clients. Yet this area is relatively underexplored and there is a lack of data from naturalistic settings. In this paper we report observational findings from the implementation of a Digital Navigator in a multidisciplinary mental health clinic in Sydney, Australia. The Digital Navigator supported clients and health professionals to use a measurement-based DMHT, (the Innowell platform) for improved multidimensional outcome assessment and to guide personalized decision-making. Observational data is reported from implementation logs, platform usage statistics, and response rates to Digital Navigator e-mails and phone calls. Ultimately, support from the Digital Navigator led to improved data collection and clearer communications about goals for using the DMHT to track client outcomes, however this required strong partnerships between health professionals, digital navigator, and clients. The Digital Navigator helped to facilitate the integration of DMHT in to care, rather than providing a stand-alone service. Thus, collaborations between health professionals and Digital Navigators are mutually beneficial and empower clients to be more engaged in their own care.

Virtual reality exposure therapy (VRET) is a promising treatment approach for anxiety disorders. However, while its efficacy has been demonstrated in adults, research on the efficacy of VRET in the treatment of adolescents with anxiety disorders is largely lacking.

Social media is an integral part of adolescent’s daily lives, but the significant time adolescents invest in social media has raised concern about the effect on their mental health. Bans and severe restrictions on social media use are quickly emerging as an attempt to regulate social media use, however evidence supporting their effectiveness is limited. Adolescents experience several benefits from social media, including increased social connection, reduced loneliness, and a safe space for marginalized groups (e.g,. LGBTQ+) to interact. Rather than enforcing bans and severe restrictions, emotion regulation should be leveraged to help adolescents navigate the online social environment. This viewpoint paper proposes a nuanced approach towards regulating adolescent social media use by 1) discontinuing the use of ineffective bans, 2) recognizing the benefits social media use can have, and 3) fostering emotion regulation skills in adolescents to encourage the development of self-regulation.

Real-time monitoring captures information about suicidal thoughts and behaviors (STBs) as they occur and offers great promise to learn about STBs. However, this approach also introduces questions about how to monitor and respond to real-time information about STBs. Given the increasing use of real-time monitoring, there is a need for novel, effective, and scalable tools for responding to suicide risk in real time.

The use of digital biomarkers through remote patient monitoring offers valuable and timely insights into a patient's condition, including aspects such as disease progression and treatment response. This serves as a complementary resource to traditional healthcare settings leveraging mobile technology to improve scale and lower latency, cost and burden.

Anxiety disorders are among the most common mental health conditions in childhood but most children with anxiety disorders do not access evidence-based interventions. The delivery of therapeutic interventions via digital technologies has been proposed to significantly increase timely access to evidence-based treatment. Lumi Nova is a digital therapeutic intervention designed to deliver evidence-based anxiety treatment for 7-12-year-olds through a mobile application incorporating immersive gaming technology.

Large language models (LLMs) are advanced artificial neural networks trained on extensive datasets to accurately understand and generate natural language. While they have received much attention and demonstrated potential in digital health, their application in mental health, particularly in clinical settings, has generated considerable debate.

The field of mental health technology presently has significant gaps that need addressing, particularly in the domain of daily monitoring and personalized assessments. Current noninvasive devices such as wristbands and smartphones are capable of collecting a wide range of data, which has not yet been fully used for mental health monitoring.

Knowledge has become more open and accessible to a large audience with the "democratization of information" facilitated by technology. This paper provides a socio-historical perspective for the Theme Issue “Responsible Design, Integration, and Use of Generative AI in Mental Health”. It evaluates ethical considerations in utilizing Generative Artificial Intelligence (GenAI) for the democratization of mental health knowledge and practice. It explores the historical context of democratizing information, transitioning from restricted access to widespread availability due to the internet, open-source movements, and most recently, GenAI technologies such as Large Language Models (LLMs). The paper highlights why GenAI technologies represent a new phase in the democratization movement, offering unparalleled access to highly advanced technology as well as information. In the realm of mental health, this requires a delicate and nuanced ethical deliberation. Including GenAI in mental health may allow, among other things, improved accessibility to mental health care, personalized responses, conceptual flexibility, and could facilitate a flattening of traditional hierarchies between health care providers and patients. At the same time, it also entails significant risks and challenges that must be carefully addressed. To navigate these complexities, the paper proposes a strategic questionnaire for assessing AI based mental health applications. This tool evaluates both the benefits and the risks, emphasizing the need for a balanced and ethical approach for GenAI integration in mental health. The paper calls for a cautious yet positive approach to GenAI in mental health, advocating for the active engagement of mental health professionals in guiding GenAI development. It emphasizes the importance of ensuring that GenAI advancements are not only technologically sound but also ethically grounded and patient centered. Keywords: Ethics, Generative Artificial Intelligence, Mental Health

Artificial intelligence (AI) has been increasingly recognised as a potential solution to address mental health service challenges by automating tasks and providing new forms of support.

Novel technologies, such as ecological momentary assessment (EMA) and wearable biosensor wristwatches, are increasingly being utilized to assess outcomes and mechanisms of change in psychological treatments. However, there is still a dearth of information on the feasibility and acceptability of these technologies and whether they can be reliably used to measure variables of interest.