The future of case formulation in clinical psychology: advancements in network modeling and simulation-based science

Case formulations are explanations co-created by clinician and client for the client’s psychological, social, and behavioral problems. In clinical practice, case formulations are used to tailor interventions to the specific problems, needs, and resources of the client. However, the process of creating case formulations is complex and requires integrating a broad range of information about the client’s experiences. The PhD thesis therefore aims to facilitate and advance this process by using statistical network models of psychological symptoms and computer simulations. It discusses how statistical networks are estimated from smartphone data, how clinical reasoning and theory are integrated with such networks, and demonstrates how these models can be used to inform case formulations. It showcases how computer simulations can be used to improve the accuracy and predictions of case formulations. The thesis applies these methods to a range of psychological problems, including depression, generalized anxiety disorder, eating disorder, obsessive-compulsive disorder, and panic disorder. It ends with a discussion on the feasibility of these methods in clinical practice, and the steps that are required to introduce them into therapy.