Related Experiment Video
Updated: Jan 12, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Multidisciplinary perspectives on personalised prevention in youth mental health
Johanna Löchner1,2, Mariana Bolivar3, Lesley Booth3
1Department Clinical Psychology and Psychotherapy for Children and Adolescents, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen-Nürnberg, Germany.
Abstract:
The pervasive impact of mental illnesses extends beyond individual suffering, affecting families, communities, and societies at large. Prevention efforts are imperative to mitigate this burden, promoting well-being and resilience across diverse populations. A particularly vulnerable period is adolescence, which is associated with numerous mental health issues that are exacerbated by declining healthy behaviours as well as socioeconomic inequalities. But adolescence also presents an opportune moment for early intervention. However, recognising warning signs and providing timely support involves considerable hurdles, so innovative prevention measures are needed. Advancements in AI, particularly in emotion recognition, offer promise for early mental health intervention. Yet, current AI achievements fall short in addressing the mental healthcare gap. This vision paper seeks to outline future directions and recommendations for effective preventive approaches by integrating experts of the necessary multidisciplinary field to develop, evaluate and implement novel and promising prevention approaches. Therefore, representatives based in Europe from diverse fields such as clinical psychology, computer science, physical activity, nutrition, economics, entrepreneurship, politics, and digital innovation propose potential avenues to integrate efficient treatment, AI methodology, and comprehensive implementation strategies that align with user needs. Based on a literature review and expert consensus, key ingredients suggested for effective preventive measures for mental health include holistic, individualised, AI-based mHealth interventions, leveraging smart and passive data from digital biomarkers for monitoring and feedback, evaluating cost-effectiveness, conducting participatory research to ensure user acceptance, and identifying barriers and facilitators for integration into regular healthcare systems. By utilising AI-driven interventions for adolescents, we can address the urgent need for preventive mental healthcare, ultimately enhancing the well-being of future generations.
Related Concept Videos
Community Based Intervention
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Theoretical Approaches to Psychological Disorder
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
Models of Health Promotion and Illness Prevention II
The agent-host-environment model states that disease results...
Models of Health Promotion and Illness Prevention I
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Levels of Health Promotion and Illness Prevention
In primary prevention, actions taken before disease onset prevent the disease from...
Preventive Healthcare Services

