Structure-Informed Cognitive Representation Improves Prediction of Real-World Functioning in Schizophrenia: A Comparison with Conventional Domain Scores

Predicting real-world functional outcomes in schizophrenia (SCZ) remains a clinical priority, but existing models are limited by methodological constraints and a lack of established clinical utility. Cognition is a commonly used predictor, and the Normative Latent Cognitive Structure (N-LCS) approach provides a structure-informed representation that may address limitations of conventional domain-level scores. Data from two merged COBRE cohorts (163 SCZ, 180 healthy controls) were used to develop ridge regression models for economic (EF), occupational (OF), and social (SF) functioning, using N-LCS deviation metrics alongside a priori selected demographic and clinical predictors. Score-based m