Relapse identification in Severe Mental Illness using smartphone app

Severe psychiatric disorders are among the most important medical causes of disability and reduced life expectancy. These disorders, such as schizophrenia, bipolar disorder or major depression, usually have an episodic progression, characterized by periods with few or no symptoms and followed by relapses. In the case of schizophrenia, for example, about 80% of people treated for a first episode will have relapsed within five years. In the case of bipolar disorder, one third of patients who are not correctly treated relapse within a year. In the case of depression, relapses most often occur within three years of the first depressive episode, and after three depressive episodes, the risk of further relapse is 90%. Moreover, relapses seem to cause neurobiological changes, which increase the probability of further relapses in the future.

Currently available observation and monitoring methods are very expensive, rely on retrospective evaluations that often do not reflect the actual disease functioning and progression, and require an investment that patients are often unable to make. The intervention with the best empirical evidence involves an increase in short-term medication, as well as continuous maintenance medication without the dose reductions wich would prevent relapse, thereby increasing the risk of medication side effects such as weight gain and diabetes. For all these reasons, a treatment strategy that uses continuous monitoring has the potential to contribute to safer and more acceptable treatment strategies for people with serious mental illness.

In this project, the aim of our researchers is to initiate a study to develop an application that supports the relapse prevention approach by monitoring early warning signs on a day-to-day basis. Additionaly, they aim to improve to improve the follow-up strategy for patients in the daily clinical practice. Unobtrusive monitoring helps patients and caregivers become aware of the increased risk of relapse and and helps to activate a rapid and appropriate treatment strategy. Within the framework of this project, our scientists are actively collaborating with the mental health network of Fribourg.