TY - JOUR
T1 - The Factor Structure of Social Cognition in Schizophrenia
T2 - A Focus on Replication With Confirmatory Factor Analysis and Machine Learning
AU - Riedel, Philipp
AU - Horan, William P.
AU - Lee, Junghee
AU - Hellemann, Gerhard S.
AU - Green, Michael F.
N1 - Publisher Copyright:
© The Author(s) 2020.
PY - 2021/1
Y1 - 2021/1
N2 - Social cognition has become a major focus in psychosis research aimed at explaining heterogeneity in functional outcome and developing interventions oriented to functional recovery. However, there is still no consensus on the structure of social cognition in psychosis, and research in this area has been plagued by lack of replication. Our first goal was to replicate the factor structure of social cognition using nearly identical tasks in independent samples. Our second goal was to externally validate the factors as they relate to nonsocial cognition and various symptoms in the prediction of functioning using machine learning. Confirmatory factor analyses validated a three-factor model for social cognition in psychosis (low-level, high-level, attributional bias factor). A least absolute shrinkage and selection operator regression and cross-validation provided evidence for external validity of data-driven linear models including the social-cognitive factors, nonsocial cognition, and symptoms. We addressed the replicability problems that have impeded research in this area, and our results will guide future psychosis studies.
AB - Social cognition has become a major focus in psychosis research aimed at explaining heterogeneity in functional outcome and developing interventions oriented to functional recovery. However, there is still no consensus on the structure of social cognition in psychosis, and research in this area has been plagued by lack of replication. Our first goal was to replicate the factor structure of social cognition using nearly identical tasks in independent samples. Our second goal was to externally validate the factors as they relate to nonsocial cognition and various symptoms in the prediction of functioning using machine learning. Confirmatory factor analyses validated a three-factor model for social cognition in psychosis (low-level, high-level, attributional bias factor). A least absolute shrinkage and selection operator regression and cross-validation provided evidence for external validity of data-driven linear models including the social-cognitive factors, nonsocial cognition, and symptoms. We addressed the replicability problems that have impeded research in this area, and our results will guide future psychosis studies.
KW - factor structure
KW - machine learning
KW - psychosis
KW - replication
KW - social cognition
UR - http://www.scopus.com/inward/record.url?scp=85092127762&partnerID=8YFLogxK
U2 - 10.1177/2167702620951527
DO - 10.1177/2167702620951527
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AN - SCOPUS:85092127762
SN - 2167-7026
VL - 9
SP - 38
EP - 52
JO - Clinical Psychological Science
JF - Clinical Psychological Science
IS - 1
ER -