Specialized self-report questionnaires have been developed for detection of symptoms indicative of psychosis risk. The identification of at-risk individuals is typically based on sum scores, which assume equal severity and discriminability of all symptoms, and a single dimension of illness. Our aim was to test whether separable dimensions of risk could be identified in the general population.
We explored the latent structure of one such questionnaire using full-information item factor analysis, deriving exploratory models from the PROD-Screen questionnaire responses of the adolescent general population based on the Northern Finland 1986 Birth Cohort (n=6611).
A three-dimensional factor structure of positive, negative and general symptoms emerged. The factor structure, the appropriateness of the statistical model and the application of the results to the detection of heightened psychosis risk are discussed.
In explicitly taking into account the multidimensionality and varying symptom severity of the included items, the current model provides an improvement in questionnaire-based assessment of psychosis risk.