Project
Advanced Network Approaches to Enhance Youth Mental Health

This project focuses on developing and applying psychometric network models to address mental health challenges in adolescence. Adolescence is marked by heightened susceptibility to mental health issues. However, despite extensive research, identifying underlying causes for mental disorders has been largely unsuccessful (Fried, 2015). In addition, the reliability and validity of mental health measurements have raised concerns (Flake & Fried, 2020), and diagnosing mental disorders remains to be challenging (Mai et al., 2020). The main reason is that the comprehensive understanding of the interplay between manifestations of symptoms is lacking. The goal of the current project is to utilize advanced network approaches to investigate dynamic symptom development and interdependence, and subsequently inform targeted interventions. Using time series data and diverse participant conditions, this project aims to gain insight into comorbidity development and symptom dynamics for different mental health issues among adolescents.

Psychometric network approaches are underpinned by a new theoretical framework to explain the existence and development of mental disorders; namely, disorders are conceptualized as systems of interacting symptoms. This contrasts with the traditional perspective, where symptoms are assumed to result from an underlying, latent cause (Cramer et al., 2010; Fried, 2015). Instead, according to the network approach, symptoms can causally influence one another. This implies that the causes of the disorder lie in the symptoms and their interactions, not an underlying common cause. Additionally, the network framework is able to provide a new perspective on why mental disorders co-occur. If two disorders share a symptom, this symptom could operate as a bridge connecting the two networks into a single system (Fried, 2015). This implies that comorbidity is an inherent feature of mental disorders (Roefs et al., 2022). In other words, network models are by default transdiagnostic, as different disorders can share symptoms.

The goal of the current project is to acquire new insights into psychopathology by uncovering dynamic symptom development, interdependence between disorders and comorbidity development and inform new targeted interventions based on insights from these developments.

Supervisors
Prof. Dr. Gonneke Stevens
Prof. Dr. Daniel Oberski  
Dr. Mahdi Shafiee Kamalabad
Dr. Gerdien van Eersel

Financed by
Utrecht University – Starter Grant

Period
30 October 2024 – 30 April 2029