We believe we can improve psychiatric treatment by overcoming the mismatch between symptom reduction and more patient oriented goals. To personalize treatment and advance further study, we investigate patient’s needs and identify targetable objectives for individual patients.
In this effort, we use large collections of real-life data collected through patients’ panels to identify lifestyle and other factors that promote recovery. We work to integrate multilevel data (e.g. molecular, cellular, functional, EEG, imaging, clinical characterization, medication, lifestyle, psychotherapy, social interventions) for treatment evaluation and response prediction.
An important way to improve treatment is to develop innovative personalized interventions using e-health, such as apps that can be used for clinical decision making. Such tools can improve patients’ quality of life. We implement these innovations into regional and (inter)national mental health networks.
Examples of projects UMC Utrecht is involved in are:
Weight gain due to antipsychotic use reduces life expectancy and quality of life in people with schizophrenia and bipolar disorder. People who experience weight gain are offered lifestyle sessions as part of their regular treatment. This consists of dietary advice and exercise therapy. In the MELIA trial, we want to find out whether metformin, a drug currently prescribed for diabetes, in combination with lifestyle sessions leads to more weight loss than lifestyle sessions alone. In the trial, we will compare the effect of metformin and lifestyle sessions with a placebo and lifestyle sessions.
Involved PI: Wiepke Cahn
In the Psychosis Prognosis Predictor project, we aim to develop a tool that can predict the individual outcome of people with psychotic disorders. In addition, this predictor aims to calculate the effect of various modifiable factors such as medication and lifestyle. Our goal is to provide patients, their families, and healthcare providers with tools to achieve the best possible prognosis and recovery.
Involved PIs: Edwin van Dellen, Wiepke Cahn
In the MUVA project, we investigate whether a healthy lifestyle can be a catalyst for recovery in people with mental vulnerability. People at risk for mental illness are participating in the MUVA intervention, including exercise activities, the muvaM game, a sleep course, a stop smoking course and information about healthy food. We examine the effects of the MUVA lifestyle interventions on social functioning, and physical and mental health.
Involved PIs: Wiepke Cahn
In healthcare, we collect a lot of data during diagnosis and treatment. We can make much better use of this information. This is the essence of Big Data Psychiatry: using the knowledge hidden in our data to improve care. To do this, we use modern data science techniques and healthcare professionals and data specialists collaborate closely. By analyzing big data, we aim to gain more insight into the causes of mental illness and the effectiveness of treatments. Often, the relationships are complex, as the (social) environment plays a role in addition to behavior and emotions. New technologies allow us to collect new data, for example with wearables that measure heart rate around the clock. With new analysis techniques, we can analyze all these aspects at the same time to uncover (unknown) underlying mechanisms. This should lead to more effective and personalized care for our patients and, even better, prevent people from developing mental health problems.
Involved PIs: Floortje Scheepers, Karin Hagoort
Over the past 50 years, personal experience and the subjective history of the patient have been pushed to the background in psychiatry. The focus has shifted to studying patients at the level of groups and disorders. As a result, care has become increasingly protocolized and tailored to the ‘average’ patient. The Psychiatry Story Bank (in Dutch) aims to change this. Through narrative research, we can gain deeper insights into the lives of people with mental illness and their loved ones. We believe these insights can help improve treatment and care. By creating a scientific database, we aim to generate new knowledge and insights based on personal stories, develop modern methods for analyzing stories, develop initiatives to improve mental health care, and develop training materials for the next generation of healthcare professionals. Moreover, by creating an online platform, we give patients/neighbors/professionals a voice and aim to contribute to the breakdown of taboos and stigma, and to provide comfort, strength and inspiration to others.
Involved PIs: Floortje Scheepers, Fleur Velders