Updating patient perceptions with intensive longitudinal data for enhanced case conceptualizations: An approach with Bayesian informative priors.
Saskia Scholten, Lars Klintwall, Julia Anna Glombiewski, Julian Burger
Abstract
= 935), resulting in personalized "posterior networks." Both Perceived Causal Networks and longitudinal assessments were evaluated as feasible and acceptable. Face validity was scored highest for the posterior networks. Patients emphasized the personal relevance of these networks, while therapists noted their value in guiding the therapeutic process. However, prior, posterior, and data networks showed significant dissimilarities. These differences may stem from patients' limited insight into symptom interactions, insufficient power in the longitudinal data, or variations in self-perception. Despite some inconsistencies, the study shows potential for combining two methods to create personalized models of psychopathology, highlighting the need for future research to refine this formalization process into a more rigorous theoretical-empirical cycle to test these models. (PsycInfo Database Record (c) 2025 APA, all rights reserved).