Feasibility and Efficacy of a Virtual Reality Social Prediction Training in Children and Young Adults with Congenital Cerebellar Malformations. - Butti, Niccolò; Biffi, Emilia; Romaniello, Romina; Finisguerra, Alessandra; Valente, Enza Maria; Strazzer, Sandra; Borgatti, Renato; Urgesi, Cosimo (Journal of Autism & Developmental Disorders, 2025)
This study tested the feasibility and efficacy of a Virtual Reality (VR) social prediction training (VR-Spirit) specifically designed for patients with congenital cerebellar malformation. The study is a randomised controlled trial in which 28 cerebellar patients aged 7–25 yo were randomly allocated to the VR-Spirit or to a control intervention in VR. The VR-Spirit required participants to compete with different avatars in scenarios that prompted them to form predictions about avatars' intentions. The control intervention consisted of games currently adopted for motor rehabilitation. Social prediction as well as secondary neuropsychological and behavioural outcomes were assessed at the beginning (T0), at the end (T2) and after 2 months (T3). The experimental group showed a significant increase, compared to the control participants, in social prediction assessed through a VR task. Moreover, at least at T3, the VR-Spirit enhanced the use of contextual predictions in a computer-based action prediction task. Importantly, these effects were generalized to secondary neuropsychological outcomes, specifically theory of mind and, only at T2, inhibition. No differences between the interventions were detected on emotional-behavioural problems. Lastly, both interventions showed high feasibility and acceptability. These findings confirm that it is possible to develop condition-specific rehabilitative training on the basis of neurocognitive functions impaired in case of congenital malformation. The VR-Spirit demonstrated to generalize its effects to theory of mind abilities, and it might be thus extended to other neurodevelopmental disorders that present social perception deficits and alterations of predictive processing. Trial registration: ISRCTN, ID: ISRCTN22332873. Retrospectively registered on 12 March 2018.