Creating healthier futures for ill children

Digital health for youth mental health

The challenges around the detection and treatment of mental health problems offer a great opportunity for the augmentation of digital health, such as health apps, web and text messaging. The potential of digital medicine is even further strengthened given the fact that 75% of mental disorders onset during youth (15-24 years; 1) - an age group known for being digitally savvy. Furthermore, the last decade has seen a fundamental change in the way mental health is identified and treated as highlighted in the recent article by Uhlhaas and Torous (2019; 2).

The challenges for early detection

The shift in mindset towards mental health has resulted in focusing on early diagnosis and intervention, particularly in young people, rather than treating established mental disorders in adulthood (2). This is especially important given that early intervention in young patient groups may lead to improved outcomes long-term (2). However, despite the recognised value of early detection and diagnosis of mental disorders, the current services fail to implement it efficiently due to stigma and underfunding. As a result, it has been reported that less than 1 in 5 adolescents in the US receive appropriate treatment for mental disorder (3). With that in mind, Uhlaas and Torous (2019) argue that digital medicine is highly relevant when it comes to youth mental health in two fundamental aspects: detection of emerging mental illness and providing youth-friendly treatment.

The potential of digital health in youth

Digital health can assist young people during several points of the evolvement of mental disorder. For example, digital tools can be used to help young patients identify symptoms and connect them with appropriate care (2). In addition to helping manage the emerging mental condition, it can also assist youth in monitoring recovery, providing unique education and preventing and detecting relapse, given that these tools are packed with sufficient sensitivity and specificity (2).

For example, recent findings show promising results in using web-based screening platform to detect patients who are at risk or who have already developed psychosis (4). Similarly, evidence-based mobile health apps have shown to predict relapse (5). Moreover, Triumf recently published research demonstrating that digital therapeutics delivered through a mobile application, and more specifically game environment, holds great promise in improving mental wellbeing and quality of life in pediatric cancer patients (6). Together, these findings highlight the potential of using digital medicine to provide novel therapeutic opportunities.

Concerns of digital health

Despite the positive findings, it is also important to note that not all digital health can lead to improved management of mental health conditions. Research on the lack of evidence based, comprehensive, privacy sensitive tools highlight the need for clinically proven, sensitive, high-quality digital technologies before they are ready for widespread clinical use (7, 8). Nevertheless, the combination of unmet need amongst youth and the potential of scalable, accessible digital technologies guide the way towards effective and impactful management of mental health in the future.


  1. Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. Archives of general psychiatry, 62(6), 593-602.
  2. Uhlhaas, P., & Torous, J. (2019). Digital tools for youth mental health.
  3. Merikangas, K. R., He, J. P., Burstein, M., Swendsen, J., Avenevoli, S., Case, B., ... & Olfson, M. (2011). Service utilization for lifetime mental disorders in US adolescents: results of the National Comorbidity Survey–Adolescent Supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 50(1), 32-45.
  4. McDonald, M., Christoforidou, E., Van Rijsbergen, N., Gajwani, R., Gross, J., Gumley, A. I., ... & Uhlhaas, P. J. (2018). Using online screening in the general population to detect participants at clinical high-risk for psychosis. Schizophrenia bulletin, 45(3), 600-609.
  5. Barnett, I., Torous, J., Staples, P., Sandoval, L., Keshavan, M., & Onnela, J. P. (2018). Relapse prediction in schizophrenia through digital phenotyping: a pilot study. Neuropsychopharmacology, 43(8), 1660.
  6. Tark, R., Metelitsa, M., Akkermann, K., Saks, K., Mikkel, S., & Haljas, K. (2019). Usability, Acceptability, Feasibility, and Effectiveness of a Gamified Mobile Health Intervention (Triumf) for Pediatric Patients: Qualitative Study. JMIR serious games, 7(3), e13776.
  7. Torous, J., Larsen, M. E., Depp, C., Cosco, T. D., Barnett, I., Nock, M. K., & Firth, J. (2018). Smartphones, sensors, and machine learning to advance real-time prediction and interventions for suicide prevention: a review of current progress and next steps. Current psychiatry reports, 20(7), 51.
  8. Bry, L. J., Chou, T., Miguel, E., & Comer, J. S. (2018). Consumer smartphone apps marketed for child and adolescent anxiety: A systematic review and content analysis. Behavior therapy, 49(2), 249-261.

Kaari Kink


Kaari Kink

With her background in health sciences and physical activity, she brings expertise in inducing behavioral change.