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Key points
Efforts to reduce mental health illness need to focus on disease prevention
Disease prevention has proved to be particularly effective in the adolescent age group
Our research looks at how apps may be used to detect mental health illness in this age group
Studies from the past two decades have made it clear that the prevention of mental health disorders is a public health priority. The economic and social costs of mental health illnesses are vast and long-lasting, and treatment effectiveness and coverage are significantly limited. Arguably, the only sustainable way of reducing the burden caused by mental disorders is investing in primary and secondary prevention. In general, prevention focuses on modifying risk factors. Primary prevention focuses on the disease determinants, and secondary prevention focuses on early detection of disease and intervention.
Although prevention seems effective, and although stakeholders give the highest priority to research on the topic, the resources dedicated to it are still low. Therefore, pressure on stakeholders must increase so primary and secondary prevention become a priority. Our research focuses on finding innovative solutions to making prevention more effective, efficient and wide-reaching. Specifically, we explore how mental health apps on smartphones can improve the early detection of mental disorders.
Our main goal is to boost early detection during puberty and adolescence, which is the stage when treatment can have its biggest impact. Major mental disorders usually begin to show symptoms in puberty, and the first serious episodes usually occur in adolescence. Treatments at these early stages are very effective; they suppress symptoms and prevent reoccurrence. In contrast, a lack of early diagnosis and treatment tends to lead to deterioration, often resulting in a complex morbid state that modern treatments cannot yet effectively target. Puberty and adolescence are therefore critical phases for early detection because it is the best window in which to intervene. Increasingly, mental health apps are being considered as a way of extending the reach of mental health care across the population. Hence, our research focuses on how mental health apps can contribute to early detection in puberty and adolescence.
The literature on mental health apps is scarce, and few apps have actually been professionally validated. Furthermore, mental health apps have many pitfalls: they are often designed to be an adjunct for therapy rather than stand-alone, and they have low rates on personal support, motivation for use and credibility. However, the evidence from mental health apps that have been tested in clinical trials is encouraging. Passive and active tracking features are a promising way to monitor and predict changes in mood states. This data can be used to improve case detection and mental health literacy (i.e. the ability to recognize mental health problems, helpful interventions and outcomes). The challenge, therefore, is to find a way of taking advantage of mental health apps’ tracking and predicting uses, while compensating for their pitfalls.
Our research explores two concrete ways in which this can be done. The first is to use mental health apps as an aid for mental health literacy programmes at schools; the second is to use them to expand the technology-enabled care services (services that use telehealth, telecare, and telecoaching) to cover early detection in puberty and adolescence. These suggestions bring up a number of concerns that require careful consideration. First, there are issues about how to use apps to improve early detection whilst taking global apps use into account. Second, there are issues about how data use and privacy should be regulated. Despite these challenges, we think that if the right angle can be found, the use of mental health apps to complement mental health literacy programmes at schools and technology-enabled health services, could contribute to improve early detection in puberty and adolescence.
Further reading
Andrews G, Issakidis C, Sanderson K, Corry J, Lapsley H: Utilising survey data to inform public policy: comparison of the cost-effectiveness of treatment of ten mental disorders. Br J Psychiatry 2004, 184:526–533.
Munoz RF, Beardslee WR, Leykin Y: Major depression can be prevented. Am Psych 2012, 67:285–295.
Mihalopoulos C, Vos T, Pirkis J, Carter R: The economic analysis of prevention in mental health programs. Ann Rev Clin Psyc 2011, 7:169–201.
Van Ameringen M, Turna J, Khalesi Z, Pullia K, Patterson B. There’s an app for that! The current state of mobile applications (apps) for DSM-5 obsessive-compulsive disorder, posttraumatic stress disorder, anxiety and mood disorders. Depress Anxiety. 2017,34,526– 539. https://doi.org/10.1002/da.22657
WHO, Prevention of Mental Disorders: Effective Interventions and Policy Options, 2004.
About the authors
Juliana finished the BPhil in Philosophy at Oxford in February 2018. She is currently working at the Colombian Nursing Collegiate Organization (Organizacion Colegial de Enfermeria), developing the research and projects department.
Hadassah is starting Graduate-Entry Medicine at Oxford after completing a BA in Neuroscience. She has also led the development of an app to help people manage self-harm.
Dominic is studying for a BA in Biomedical Sciences at New College, Oxford. He is currently the Vice-President of the Oxford University Society of Biomedical Sciences (OUSBMS).
Thomas is in his second rear of reading Medicine at Oriel College, Oxford. He is passionate about providing a voice to students, having integrated talks across the region by founding Thames Valley Medical Society.