Clinical Research Directory

Precision Subclassification of Mental Health in Diabetes: Digital Twins for Precision Mental Health to Track Subgroups

Mental conditions and disorders (e.g. distress, depressive, anxiety, and eating disorders) are more prevalent in people with diabetes (PWD) and associated with reduced quality of life and impaired glycaemic outcomes. Evidence supports a complex network between psychosocial factors and glycaemic control that can be highly variable between persons. It is assumed that subgroups exist that show different trajectories of glycaemia and mental health. Belonging to a particular subgroup may be linked with a higher risk of developing mental health problems compared to others. This suggests that it is possible to treat individuals in different subgroups in a manner that optimizes their treatment and can improve health outcomes. Accurate characterisation can inform more individualized care. This calls for a more personalised approach considering the idiosyncrasies of different subgroups. Over 3 years, the investigators have established the basis of a precision mental health approach for diabetes using n-of-1 analyses. By utilizing combined ecological momentary assessment (EMA: repeated daily sampling of psychosocial factors in everyday life) and continuous glucose monitoring (CGM), intensive longitudinal data per person could be collected. This enables the analysis of individual associations between glycaemic parameters and psychosocial variables and identification of individual sources of diabetes distress in each person. The objective of the present study is to use of the n-of-1 approach to identify subgroups of PWD who share common characteristics in the associations between glucose and psychosocial variables. The identified subgroups shall be used to develop a digital twin for precision mental health in diabetes. The digital twin serves as representation of a real person, allowing to make simulations and predictions of the course of mental health and glycaemia. These predictions can inform diabetes care and lead to more precise, personalised treatment decisions. To achieve this, a longitudinal panel including over 1,400 PWD who continuously complete EMA and questionnaire surveys and measure glucose levels using CGM was developed. Over 1000 clinical interviews to diagnose mental disorders have been conducted to identify major mental health conditions and map mental outcomes. To identify subgroups and develop the digital twin, the sampling will be expanded aiming at a total of 1,809 PWD. Incidence and remission of mental disorders will be determined via repeated interviews. The complex networks between clinical, metabolic, and psychosocial data will be analysed using machine learning, leading to new insights with the potential to shape future guidelines. These results will be used by the digital twin to predict courses of glycaemic control and mental health, translating the individual evidence into direct treatment suggestions.

A Single-session Intervention Adaptation of the Habit Framework for the Prevention of Eating Disorders

The purpose of this proposal is to launch the first trial of a single-session intervention (SSI) specifically for the prevention of eating disorders (EDs).

Effectiveness of Group EFT for Transdiagnostic Eating Disorders/Difficulties Within Student Counselling Services.

What is the purpose of the study? Emotion-Focused Therapy (EFT) is a therapeutic approach that helps individuals identify, explore, and transform difficult emotions to improve emotional wellbeing and resolve psychological issues. While there is a growing body of evidence for the effectiveness of both individual and group EFT with a range of difficulties, including eating disorders, this has not yet been sufficiently explored within university counselling services. The purpose of this study is to assess the feasibility, acceptability, and preliminary effectiveness of a group EFT intervention for students experiencing eating disorders or concerns related to eating, weight, and shape. The study aims to determine whether this type of therapy can be effectively delivered within a university counselling service, and if it could potentially improve participants' mental health and wellbeing.

Family-Based Treatment at Home in Adolescents With Eating Disorders and Co-occurring Mental Health Conditions

The significant impact of eating disorders on adolescents necessitates the evaluation of current treatments. Family-based Treatment (FBT) is the standard treatment but has modest remission rates, highlighting the need for improvements. Assessing its effectiveness in adolescents with co-occurring mental health conditions is also crucial. In the Netherlands, there is a growing focus on home-based treatment. This study aims to enhance remission rates in FBT by adapting it for use in a home setting (FBT-H).