Global mental health concerns impact a significant number of individuals, with young people (aged 12–25) navigating a high-risk period linked to mental illness onset. Approximately 75% of mental health conditions emerge before age 25, significantly affecting decades of productive adult life. Recently, the prevalence of mental health problems in young people has risen steadily, driving an increased demand for support.
In the meantime, technology adoption and technological advances offer opportunities for accessible, cost-effective evidence-based psychotherapy. Several technologies have emerged to offer psychological interventions in daily life. These technologies support a variety of mental health disorders, such as anxiety, depression, and bipolar disorder. The robust computational capacities of different technologies, the integration of sensors, and the capability to connect with other wearable devices offer the potential to assist in timely or high-risk situations and also to anticipate when such situations might arise.
Additionally, the increasing adoption of artificial intelligence (AI) tools among young people reflects a growing trend, promising improved early identification and intervention strategies, and revolutionizing the landscape of mental health care. Studies have shown that AI applications can enhance mental health outcomes in various contexts. However, the quality of studies evaluating these AI tools varies, with some lacking rigorous methodologies or robust evidence supporting their effectiveness. It is crucial for future research to focus on the effectiveness and quality of AI applications, ensuring they are evidence-based and reliable.
The primary goal of this Research Topic is to bring together researchers from diverse backgrounds to address the challenges and opportunities in the evolving landscape of technological interventions to support the mental health of youth. We aim to explore the use of technologies to support youth mental health and the latest developments in the field. Recent advances in online platforms, app-based interventions, wearable devices, remote monitoring technologies, and AI applications present an opportunity to provide personalized and accessible mental health resources. This includes developing generation models to offer mental support to individuals seeking help, developing explainable models to support decision-making, and employing advanced machine learning techniques to predict or detect different mental states. Additionally, we aim to examine the effectiveness of AI tools and the quality of studies conducted in this area.
We invite authors to submit original research articles, reviews, methods articles, data reports, opinion articles, and perspectives articles that address the following themes, but are not limited to:
- Early detection and prevention of mental states through the use of technology
- Application of machine learning, deep learning or other advanced methods to detect or predict the mental health states of young people
- Design and development of early interventions or other interventions to support young people´s mental health, considering application to specific contexts
- Automatic approaches to early detection or prevention of mental health disorders, considering application to specific mental disorders such as depression, anxiety, and bipolar disorder
- Design and development of innovative technologies for youth mental health
- Design, development and evaluation of novel AI-based intervention approaches to support mental health for young people
- Effectiveness of AI tools and the quality of studies assessing their impact
- Innovative AI-based studies on a variety of mental health conditions for young people
- Discussion of ethical and methodological issues related to advanced approaches to youth digital mental health
Keywords:
Youth, digital mental health, technology, mental health, artificial intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
Global mental health concerns impact a significant number of individuals, with young people (aged 12–25) navigating a high-risk period linked to mental illness onset. Approximately 75% of mental health conditions emerge before age 25, significantly affecting decades of productive adult life. Recently, the prevalence of mental health problems in young people has risen steadily, driving an increased demand for support.
In the meantime, technology adoption and technological advances offer opportunities for accessible, cost-effective evidence-based psychotherapy. Several technologies have emerged to offer psychological interventions in daily life. These technologies support a variety of mental health disorders, such as anxiety, depression, and bipolar disorder. The robust computational capacities of different technologies, the integration of sensors, and the capability to connect with other wearable devices offer the potential to assist in timely or high-risk situations and also to anticipate when such situations might arise.
Additionally, the increasing adoption of artificial intelligence (AI) tools among young people reflects a growing trend, promising improved early identification and intervention strategies, and revolutionizing the landscape of mental health care. Studies have shown that AI applications can enhance mental health outcomes in various contexts. However, the quality of studies evaluating these AI tools varies, with some lacking rigorous methodologies or robust evidence supporting their effectiveness. It is crucial for future research to focus on the effectiveness and quality of AI applications, ensuring they are evidence-based and reliable.
The primary goal of this Research Topic is to bring together researchers from diverse backgrounds to address the challenges and opportunities in the evolving landscape of technological interventions to support the mental health of youth. We aim to explore the use of technologies to support youth mental health and the latest developments in the field. Recent advances in online platforms, app-based interventions, wearable devices, remote monitoring technologies, and AI applications present an opportunity to provide personalized and accessible mental health resources. This includes developing generation models to offer mental support to individuals seeking help, developing explainable models to support decision-making, and employing advanced machine learning techniques to predict or detect different mental states. Additionally, we aim to examine the effectiveness of AI tools and the quality of studies conducted in this area.
We invite authors to submit original research articles, reviews, methods articles, data reports, opinion articles, and perspectives articles that address the following themes, but are not limited to:
- Early detection and prevention of mental states through the use of technology
- Application of machine learning, deep learning or other advanced methods to detect or predict the mental health states of young people
- Design and development of early interventions or other interventions to support young people´s mental health, considering application to specific contexts
- Automatic approaches to early detection or prevention of mental health disorders, considering application to specific mental disorders such as depression, anxiety, and bipolar disorder
- Design and development of innovative technologies for youth mental health
- Design, development and evaluation of novel AI-based intervention approaches to support mental health for young people
- Effectiveness of AI tools and the quality of studies assessing their impact
- Innovative AI-based studies on a variety of mental health conditions for young people
- Discussion of ethical and methodological issues related to advanced approaches to youth digital mental health
Keywords:
Youth, digital mental health, technology, mental health, artificial intelligence
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.