Within, between and beyond heterogeneity Uncovering individual differences using network models

Traditional approaches in psychology often rely on aggregate models to study the human psyche, overlooking the complexity of individual experiences. By exploring mental disorders through the lens of person-specific network models, this thesis contributes to the growing shift toward a more idiographic approach. A key challenge herein is to effectively capture and quantify individual differences within these networks, distinguishing true heterogeneity from statistical noise. By intergrating methodological innovations with theoretical insights, this work advances our understanding of the unique dynamic processes underlying psychophatology and emphasizes the importance of developing more precise and individualized models to deepen our knowledge of the systems driving mental health.