Synchrony in psychotherapy: High physiological positive concordance predicts symptom reduction and negative concordance predicts symptom aggravation

Objective Therapeutic alliance is often considered as a predictor for therapeutic success. This study explored dyadic synchrony of skin conductance response (SCR) during naturalistic therapeutic interactions and investigated its potential as an objective biomarker for predicting therapy effectiveness. Methods In this proof-of-concept study, skin conductance from both dyad members was continuously measured via wristbands during psychotherapy. Patients and therapists completed post-session reports capturing their subjective appraisal of therapeutic alliance. Additionally, patients completed symptom questionnaires. Each therapeutic dyad was recorded twice in a follow-up design. The first session of the follow-up group was assessed for physiological synchrony (Single Session Index (SSI)). Therapy outcome was captured by the difference between symptom severity scores over time. Results SCR synchrony significantly predicted the outcome variable of change in patients' global severity index (GSI). High positive SCR concordance was linked to a reduction in patients' GSI, while negative or small positive SSI values were linked to an increase in patients' GSI. Conclusion The results demonstrate the presence of SCR synchrony in clinical interactions. Skin conductance response synchrony was a significant predictor for change in patients' symptom severity index, emphasizing its potential as an objective biomarker in the context of evidence-based psychotherapy

INTRASync_Python_andR_Scripts

Python scripts that were used for data recording in study 1 of the project 'INTRApersonal synchrony in adults with and without ASD' R script that was used for data analysis

Automated extraction of speech and turn-taking parameters in autism allows for diagnostic classification using a multivariable prediction model

Speech, if present, is usually affected in terms of how people speak as a central symptom of autism spectrum disorder (ASD). Additionally, autistic people report having difficulties with small talk. Since small talk specifically, and conversations in general, are essential for building connections with others, it is important to understand how autistic and non-autistic verbal behaviour differs. In this study, we recorded dyadic conversations and used automated extraction of speech and interactional turn-taking features of 54 non-autistic and 26 autistic participants. Using Bayesian mixed ANOVAs, we found differences in speech, such that autistic interaction partners talked slower and in a more monotonous manner than non-autistic interaction partners. Turn-taking parameters also differed between homogeneous non-autistic dyads and heterogeneous (autistic and non-autistic) dyads. Specifically, heterogeneous dyads had increased periods of silence, and the intensity, i.e., loudness, of their speech was more synchronous. The extracted speech and turn-taking parameters showed high potential as a diagnostic marker. A linear support vector machine was able to predict the dyad type with 76.2% balanced accuracy (sensitivity: 73.8%, specificity: 78.6%), suggesting that digitally assisted diagnostics could significantly enhance the current clinical diagnostic process due to their objectivity and scalability

An evaluation of the German version of the Sensory Perception Quotient from an expert by experience perspective

Sensory processing is often altered in individuals with autism; thus, it is essential to develop reliable measurement tools to assess sensory perception. The Sensory Perception Quotient (SPQ) quantifies basic sensory sensitivities in adults via self-report. Adopting an expert by experience perspective, this study aimed to evaluate a German translation of the SPQ for its use in clinical and research applications, especially for autistic adults. 108 adults (n = 54 autistic) completed the German SPQ in an online assessment. A 92-item and a 35-item version of the German SPQ were analyzed for group differences and internal consistency. Our results show that adults with autism reported greater sensory sensitivity compared to non-autistic adults. Results further suggest good to excellent internal consistency for the 95-item and 35-item SPQ translations. This finding was supported by the correlative relationship between sensory sensitivity and autistic traits. These findings confirm the reliability of our SPQ translation, making it a suitable German assessment tool for basic sensory sensitivity in autistic adults

Data_Sheet_1_An evaluation of the German version of the Sensory Perception Quotient from an expert by experience perspective.docx

Sensory processing is often altered in individuals with autism; thus, it is essential to develop reliable measurement tools to assess sensory perception. The Sensory Perception Quotient (SPQ) quantifies basic sensory sensitivities in adults via self-report. Adopting an expert by experience perspective, this study aimed to evaluate a German translation of the SPQ for its use in clinical and research applications, especially for autistic adults. 108 adults (n = 54 autistic) completed the German SPQ in an online assessment. A 92-item and a 35-item version of the German SPQ were analyzed for group differences and internal consistency. Our results show that adults with autism reported greater sensory sensitivity compared to non-autistic adults. Results further suggest good to excellent internal consistency for the 95-item and 35-item SPQ translations. This finding was supported by the correlative relationship between sensory sensitivity and autistic traits. These findings confirm the reliability of our SPQ translation, making it a suitable German assessment tool for basic sensory sensitivity in autistic adults.</p

Machine learning classification of autism spectrum disorder based on reciprocity in naturalistic social interactions

Abstract Autism spectrum disorder is characterized by impaired social communication and interaction. As a neurodevelopmental disorder typically diagnosed during childhood, diagnosis in adulthood is preceded by a resource-heavy clinical assessment period. The ongoing developments in digital phenotyping give rise to novel opportunities within the screening and diagnostic process. Our aim was to quantify multiple non-verbal social interaction characteristics in autism and build diagnostic classification models independent of clinical ratings. We analyzed videos of naturalistic social interactions in a sample including 28 autistic and 60 non-autistic adults paired in dyads and engaging in two conversational tasks. We used existing open-source computer vision algorithms for objective annotation to extract information based on the synchrony of movement and facial expression. These were subsequently used as features in a support vector machine learning model to predict whether an individual was part of an autistic or non-autistic interaction dyad. The two prediction models based on reciprocal adaptation in facial movements, as well as individual amounts of head and body motion and facial expressiveness showed the highest precision (balanced accuracies: 79.5% and 68.8%, respectively), followed by models based on reciprocal coordination of head (balanced accuracy: 62.1%) and body (balanced accuracy: 56.7%) motion, as well as intrapersonal coordination processes (balanced accuracy: 44.2%). Combinations of these models did not increase overall predictive performance. Our work highlights the distinctive nature of non-verbal behavior in autism and its utility for digital phenotyping-based classification. Future research needs to both explore the performance of different prediction algorithms to reveal underlying mechanisms and interactions, as well as investigate the prospective generalizability and robustness of these algorithms in routine clinical care

Interpersonal synchrony modulates neural processing in the Action Observation Network and is spared in autism

Interpersonal synchrony (IPS) is the mutual coordination of individuals’ behaviors during social interaction. Behavioral IPS has been studied increasingly in various contexts, such as a feature of the social interaction difficulties inherent to autism. To fully understand the dynamics of behavioral IPS, or reductions thereof in autism, the neural basis of IPS perception needs to be established, as it is an arguably essential ingredient to achieve IPS when engaging in social interactions. Thus, the current study’s aim was twofold: to establish the basic neuro-perceptual processing of IPS in typical observers and to test whether it might differ in autistic individuals. In a task-based fMRI paradigm, participants viewed short, silent video vignettes of humans during social interactions featuring a variation of behavioral IPS. The results show that IPS modulates the Action Observation Network. Interestingly, autistic participants showed the same IPS modulation of neural activation patterns as non-autistic participants, suggesting that IPS perception is spared and likely not underlying reduced behavioral IPS in autism. Nevertheless, a general difference of processing social interactions was found in autistic observers characterized by decreased neural activation in the right middle frontal gyrus, angular gyrus, and superior temporal areas. This may implicate frontoparietal regions as a source of attenuation for integrating top-down modulation during social interactions. As such, the attenuated production of behavioral IPS and subsequently social interaction difficulties in autism may not stem from differences in perceiving the timing of other’s behavior, but rather from altered integration thereof into the temporal coordination of behavior when interacting with others

Examining Perceived Stereotype Threat among Overweight/Obese Adults Using a Multi-Threat Framework

Objective: The Multi-Threat Framework accounts for potentially different forms of stereotype threat that differ in target (i.e., the individual or the group) and source (i.e., the self or others). This investigation examined how these different forms of perceived stereotype threat were related to concepts, such as group identity, stereotype endorsement, stigma consciousness, etc., among overweight and obese individuals. Method: 216 adults completed an online survey. Participants' mean age was 23.6 (SD 10.1; range 18-64) years and mean BMI was 31.6 (SD 7.5) kg/m2. Results: Participants reported a history of feeling threatened by stereotypes related to weight. When reflecting on past experiences of perceived stereotype threat, participants reported greater levels of self/own stereotype threat compared to group stereotype threat. Level of stereotype threat was related to a number of personal characteristics (i.e., sex, BMI) and individual factors (i.e., group identity, stigma consciousness, fear of fat). Conclusion: Individuals who are overweight report a history of being threatened by negative stereotypes. The findings support the Multi-Threat Framework for stereotype threat based on body weight. Overweight individuals' susceptibility to stereotype threat may vary systematically depending on several factors. Future research should examine weight-related stereotypes' impact on cognitive and behavioral outcomes