Automated movement analysis predicts transition to non-psychotic disorders in individuals at ultra-high risk for psychosis

Objective: Ultra-high risk criteria were developed to identify prodromal symptoms of psychosis, although the transition does not occur in most individuals. This highlights the need to identify transition markers, such as movement analysis. In the first stage of our study, movement analysis was used to differentiate controls from ultra-high risk patients, who had reduced movement and increased erraticism. We aimed to determine whether these variables can predict ultra-high risk outcomes after follow-up. Methods: Ultra-high risk individuals were recorded while performing two speech tasks at baseline. The videos were analyzed using motion energy analysis for head and torso movements (mean amplitude, frequency, and variability) and were manually coded for gesticulation. During follow-up, seven participants transitioned to psychosis, 21 to other DSM-5 disorders (called the general disorder group), and 18 did not transition to psychosis. Results: The general disorders group showed lower torso frequency and higher variability in both regions than the psychosis group, as well as greater torso variability than the non-transition group. No differences were found between the psychosis and non-transition groups. Gesticulation did not significantly differ between groups. Conclusions: Baseline movement variability distinguishes ultra-high risk transition outcomes, with higher variability in those who transitioned to non-psychotic disorders. This demonstrates the importance of movement analysis as a potential transition marker and suggests that treating ultra-high risk individuals as a single group may overlook important information.