An exploratory network analysis to investigate schizotypy’s structure using the ‘Multidimensional Schizotypy Scale’ and ‘Oxford-Liverpool Inventory’ in a healthy cohort

Schizophrenia spectrum disorders and schizotypy share traits across positive, negative, and disorganised domains. Instruments like the Multidimensional Schizotypy Scale (MSS) and the Oxford-Liverpool Inventory (O-LIFE) offer nuanced perspectives on schizotypy, including its expression as a personality trait and its potential clinical outcomes. This study investigates the structure of schizotypy using exploratory graph analysis (EGA) to analyse how the MSS and O-LIFE operationalise the construct in the same sample of German speakers. This approach allows comparison of their factorial structures from both statistical and clinical perspectives, while also assessing cross-cultural validity. 1059 German-speaking, healthy participants completed the MSS and O-LIFE questionnaires. EGA was conducted to identify dimensional structures within each scale, utilising the graphical lasso algorithm for network estimation and the Walktrap community detection method for clustering. Confirmatory factor analysis was used to assess model fit and reliability, using indices such as the comparative fit index and root mean square error of approximation. EGA of the MSS revealed three primary dimensions and an additional 'dissociated' domain. This four-dimensional model showed improved fit and reliability compared to the original model. For the O-LIFE, EGA identified a refined four-factor structure comprising: 'cognitive and behavioural disorganisation,' 'introversion', 'unusual experiences', and 'environmental valence', all validated by confirmatory analyses. This study supports the multidimensional view of schizotypy, introducing new factor structures in the MSS and O-LIFE that emphasise the previously unexplored domains 'dissociated' and 'environmental valence.' These findings highlight the value of culturally adaptive tools in enhancing schizotypy assessment and intervention strategies.