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The differential diagnosis between schizophrenia spectrum disorders (SSD) and autism spectrum disorders (ASD) remains an important clinical question, because they have overlap in clinical diagnosis. This study explored the differences between ASD (n = 44) and SSD patients (n = 59), compared to typically developing peers (n = 63), in completing an advanced Theory of Mind (ToM) task. The outcome found several differences between groups. The SSD patients showed greater difficulty in understanding social scenarios, while ASD individuals understood the stories, but did not correctly identify the protagonist's intention. The interesting aspect of the results is that some ToM stories are more informative about the mentalistic reasoning of the two clinical groups, namely, the stories that investigate pretend, persuasion, double bluff and ironic joke constructs.

In recent years, the capabilities of Large Language Models (LLMs), such as ChatGPT, to imitate human behavioral patterns have been attracting growing interest from experimental psychology. Although ChatGPT can successfully generate accurate theoretical and inferential information in several fields, its ability to exhibit a Theory of Mind (ToM) is a topic of debate and interest in literature. Impairments in ToM are considered responsible for social difficulties in many clinical conditions, such as Autism Spectrum Disorder (ASD). Some studies showed that ChatGPT can successfully pass classical ToM tasks, however, the response style used by LLMs to solve advanced ToM tasks, comparing their abilities with those of typical development (TD) individuals and clinical populations, has not been explored. In this preliminary study, we administered the Advanced ToM Test and the Emotion Attribution Task to ChatGPT 3.5 and ChatGPT-4 and compared their responses with those of an ASD and TD group. Our results showed that the two LLMs had higher accuracy in understanding mental states, although ChatGPT-3.5 failed with more complex mental states. In understanding emotional states, ChatGPT-3.5 performed significantly worse than TDs but did not differ from ASDs, showing difficulty with negative emotions. ChatGPT-4 achieved higher accuracy, but difficulties with recognizing sadness and anger persisted. The style adopted by both LLMs appeared verbose, and repetitive, tending to violate Grice's maxims. This conversational style seems similar to that adopted by high-functioning ASDs. Clinical implications and potential applications are discussed. [ABSTRACT FROM AUTHOR]

Awareness of the importance of assessing social cognition skills under conditions showing atypical social behaviours has increased over the years. However, the evaluation of the psychometric properties of the measures and the availability of normative values for the clinical context are still limited. This study aims to revise, provide normative values, and evaluate the clinical validity of the Italian version of three social cognition measures: Advanced Theory of Mind (A-ToM) task, the Emotion Attribution Task (EAT), and the Social Situation Task (SST). Measures were administered to 580 adolescents and adult healthy controls (age range 14–50). We performed differential item functioning and Rasch analysis to revise each task, so normative data of the revised measures were calculated. Moreover, the revised measures were administered to 38 individuals with autism spectrum disorder (ASD) and 35 individuals with schizophrenia spectrum disorders (SSD): ASD and SSD were matched by age, gender, and IQ with a control sample to evaluate clinical validity. ROC analysis showed that the SST is the best measure differentiating between healthy and clinical groups, compared to the A-ToM (AUCASD = 0.70; AUCSSD = 0.65) and EAT (AUCASD = 0.67; AUCSSD = 0.50), which showed poorer performance. For SSD diagnosis, two SST subscales (Violation and Gravity score) indicated the best accuracy (AUCs of 0.88 and 0.84, respectively); for the ASD diagnosis, we propose a combined score between the SST subscale and A-ToM (AUC = 0.86). The results suggest that the proposed measures can be used to support the diagnostic process and clinical practice. [ABSTRACT FROM AUTHOR]

Background/Objectives : The purposes of the present study were to assess gait by using a novel approach that plots two adjacent joint angles and the postural control in individuals with autism (ASD) and individuals with typical neurodevelopmental (TD). Methods : The surface electromyography (sEMG) activity was measured synchronously with the other variables. Twenty young adult men, 10 with TD and 10 with a diagnosis of ASD, took part in this study. Results: There was a significant difference between ASD and TD groups in the area described by the knee-ankle diagram ( p < 0.05). The sEMG activity recorded from the lateral gastrocnemius (LG) during the contact phase of gait was significantly lower in the ASD group compared with the TD group ( p < 0.05). The sEMG activity recorded in the different postural conditions showed differences in LG and tibialis anterior (TA) between the ASD and TD groups ( p < 0.05). Conclusions : The knee-ankle diagram provided a sensitive and specific movement descriptor to differentiate individuals with ASD from individuals with TD. The reduced LG activation is responsible for the reduced area in the knee-ankle diagram and 'toe-walking' in individuals with ASD and represents the common denominator of an altered ankle strategy during locomotion and postural control.