Social Communication Research Articles

O LAÇO ENTRE A IGREJA CATÓLICA E A EDUCAÇÃO SOMADO COM A COMUNICAÇÃO SOCIAL

Here we will discuss what social communication can contribute to catechesis or Catholic religious teaching, a form of extreme importance for religious education in the country, a bond is created between social communication and the Catholic Church. TV Aparecida is a great means of communication and serves as a basis for evangelism in the country. It is observed here how social communication, television, radio, newspapers and other means can help spread the Gospel and unique knowledge for Catholic Christians. How Catholic broadcasters can contribute to society will also be discussed in this article.

Sensitive infant care tunes a frontotemporal interbrain network in adolescence

Caregiving plays a critical role in children’s cognitive, emotional, and psychological well-being. In the current longitudinal study, we investigated the enduring effects of early maternal behavior on processes of interbrain synchrony in adolescence. Mother-infant naturalistic interactions were filmed when infants were 3–4 months old and interactions were coded for maternal sensitivity and intrusiveness with the Coding Interactive Behavior Manual. In early adolescence (Mean = 12.30, SD = 1.25), mother-adolescent interbrain synchrony was measured using hyperscanning EEG during a naturalistic interaction of positive valence. Guided by previous hyperscanning studies, we focused on interbrain connections within the right frontotemporal interbrain network. Results indicate that maternal sensitivity in early infancy was longitudinally associated with neural synchrony in the right interbrain frontotemporal network. Post-hoc comparisons highlighted enhancement of mother-adolescent frontal-frontal connectivity, a connection that has been implicated in parent-child social communication. In contrast, maternal intrusiveness in infancy was linked with attenuation of interbrain synchrony in the right interbrain frontotemporal network. Sensitivity and intrusiveness are key maternal social orientations that have shown to be individually stable in the mother-child relationship from infancy to adulthood and foreshadow children’s positive and negative social-emotional outcomes, respectively. Our findings are the first to demonstrate that these two maternal orientations play a role in enhancing or attenuating the child’s interbrain frontotemporal network, which sustains social communication and affiliation. Results suggest that the reported long-term impact of maternal sensitivity and intrusiveness may relate, in part, to its effects on tuning the child’s brain to sociality.

Comparative analysis of machine learning algorithms for sentiment classification in social media text

In the era of social media, sentiment analysis has become crucial for understanding public opinion. This study presents a comparative analysis of five machine learning algorithms for sentiment classification in social media text: Logistic Regression, Support Vector Machines (SVM), Random Forest, Naive Bayes, and Gradient Boosting. Using a dataset of 100,000 tweets collected over three months, we evaluated these algorithm's performance in classifying sentiments as positive, negative, or neutral. The data underwent extensive preprocessing, including cleaning, normalization, and addressing class imbalance using SMOTE. Our results show that Logistic Regression and SVM achieved the highest overall accuracy at 86.22%, demonstrating balanced performance across all sentiment classes. Random Forest followed closely with 82.59% accuracy, while Naive Bayes and Gradient Boosting showed lower but still noteworthy performance at 70.45% and 69.96% respectively. All models exhibited challenges in classifying negative sentiments, suggesting potential areas for improvement. The study provides insights into each algorithm's strengths and weaknesses, offering guidance for practitioners in selecting appropriate methods for sentiment analysis tasks. Our findings contribute to the ongoing research in applying machine learning to the complex task of sentiment analysis in the rapidly evolving landscape of social media communication.

The Role of Thioredoxin System in Shank3 Mouse Model of Autism.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by difficulties in social interaction and communication, repetitive behaviors, and restricted interests. Unfortunately, the underlying molecular mechanism behind ASD remains unknown. It has been reported that oxidative and nitrosative stress are strongly linked to ASD. We have recently found that nitric oxide (NO•) and its products play an important role in this disorder. One of the key proteins associated with NO• is thioredoxin (Trx). We hypothesize that the Trx system is altered in the Shank3 KO mouse model of autism, which may lead to a decreased activity of the nuclear factor erythroid 2-related factor 2 (Nrf2), resulting in oxidative stress, and thus, contributing to ASD-related phenotypes. To test this hypothesis, we conducted in vivo behavioral studies and used primary cortical neurons derived from the Shank3 KO mice and human SH-SY5Y cells with SHANK3 mutation. We showed significant changes in the levels and activity of Trx redox proteins in the Shank3 KO mice. A Trx1 inhibitor PX-12 decreased Trx1 and Nrf2 expression in wild-type mice, causing abnormal alterations in the levels of synaptic proteins and neurotransmission markers, and an elevation of nitrosative stress. Trx inhibition resulted in an ASD-like behavioral phenotype, similar to that of Shank3 KO mice. Taken together, our findings confirm the strong link between the Trx system and ASD pathology, including the increased oxidative/nitrosative stress, and synaptic and behavioral deficits. The results of this study may pave the way for identifying novel drug targets for ASD.

Application of Mixed Reality Technologies in Autism Treatment and Neurodiversity Support

Abstract: This comprehensive review explores the application of Mixed Reality (MR) technologies in treating Autism Spectrum Disorder (ASD) and supporting people with neurodiversity. It examines the potential of MR to create immersive, personalized interventions for social skills training, communication enhancement, and behavioral therapy. The paper discusses the technical considerations in implementing MR systems, including hardware requirements, software development, and user interface design tailored for neurodiverse individuals. It also addresses the challenges and future directions in this field, including ethical considerations, the need for clinical validation, and the integration of MR with existing therapeutic approaches. By synthesizing current research and identifying areas for future investigation, this review highlights the transformative potential of MR in revolutionizing ASD therapy and support.

The Influence of Social Media Strategy, Customer Interaction, and Word of Mouth on E-commerce Purchase Intention

This study investigates the effects of social media strategy, customer interaction, and word of mouth on e-commerce purchase intention. Utilizing a quantitative approach, data were collected from 360 respondents using a structured questionnaire with a Likert scale ranging from 1 to 5. The analysis employed Structural Equation Modeling with Partial Least Squares (SEM-PLS 3) to assess the relationships among the variables. The findings reveal that a well-implemented social media strategy significantly enhances customer interaction and positively influences word of mouth, which in turn drives purchase intention in the e-commerce sector. These results underscore the importance of strategic social media engagement and effective customer communication in fostering consumer intent to purchase online. The study provides valuable insights for e-commerce businesses seeking to optimize their marketing strategies and enhance customer engagement.

Technology as a Threat to Local Values and Culture Among Students: A Case Study in Sabah, Malaysia

The technological and cultural revolution, driven by media manipulation and intensified by social media's cross-border communication, threatens local values and culture (LVC) in any society. In Malaysia, emerging lifestyles significantly challenge LVC, especially among students. Limited research has examined how educators in Sabah perceive the impact of technology on student behaviours related to LVC, leaving a gap in understanding the region's cultural and educational challenges. This study explores educators’ perspectives regarding technological influences in Sabah. Utilising a qualitative case study, nine educators from different educational levels were interviewed individually to explore students’ behaviours in reflecting the LVC in Sabah, Malaysia, particularly in Kota Kinabalu and Tawau. The thematic analysis resulted in four themes, i.e., (a) personality development, (b) technological weakness, (c) emotional intelligence, and (d) suggestions to address student development and digital literacy. The study presented an argument with the previous findings concerning personality disorders in defending LVC due to technological influences. The study suggests the importance of defending LVC in shaping a civilised society. It also contributes new findings on the students' abilities to overcome the challenges of technological influences.

A comprehensive review of neuroimaging-based AI models for autism classification

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by challenges in social interaction, communication, and behavior. Traditional diagnostic methods rely heavily on behavioral assessments, such as the Autism Diagnostic Observation Schedule (ADOS) and Autism Diagnostic Interview-Revised (ADI-R), which are often subjective and limited by the absence of definitive biomarkers. Recent advances in neuroimaging techniques, including structural MRI (sMRI), functional MRI (fMRI), and positron emission tomography (PET), have provided valuable insights into the structural and functional abnormalities associated with ASD. However, the analysis of neuroimaging data is complex, requiring sophisticated machine learning (ML) and artificial intelligence (AI) models. This paper reviews state-of-the-art machine learning approaches, such as Random Forests, Support Vector Machines (SVM), and deep learning models, aimed at improving the diagnostic accuracy of ASD. We particularly focus on multimodal deep learning models that integrate neuroimaging data with behavioral assessments. In this review, we critically evaluate the strengths and limitations of these approaches, and how emerging AI tools not only enhance classification accuracy but also hold potential for identifying biomarkers and tracking the disorder's progression. Our analysis underscores the need for advanced methods that exploit both spatial and temporal features of brain data to better understand ASD, paving the way for improved diagnostics and personalized treatments.

Authenticity and high performance: Nonmarket social, public and media strategies of foreign SMEs during a black swan event

AbstractNonmarket (NM) strategy is an emerging concept, similar to the notion of NM social, public and media strategy (SPMS). Previous literature has predominantly focused on larger corporations, often overlooking smaller enterprises. Additionally, much of the existing research has been centred on developed markets, leaving a gap in qualitative research. The current analysis seeks to elucidate how foreign small and medium‐sized enterprises (FSMEs) in transitional markets, such as Shanghai, adopt specific NM SPMS to mitigate the liability of foreignness (LOF) during a pandemic. The study utilizes a CGT approach, employing semi‐structured interviews with 27 participants, including foreign entrepreneurs and digital marketing specialists. Additionally, qualitative data was analysed comprehensively using Atlas.ti 9 software. The qualitative methodology implementation resulted in the creation of the authenticity and high performance framework from where specific strategies and general implications are presented. The study highlights two principal themes: (1) The need for increased flexibility and speed in social media message communication and (2) Customized FSME strategies through digital marketing—a never‐going‐back market digitalization. The second theme is subdivided into (a) Tailored public relations for FSMEs. (b) An increased need for internal cohesion—fostering a stable mindset and positive rapport among staff. (c) An increased need for trialling new target customers. (d) Creating a relatable story—showing a particular vulnerability can be viral and (e) Maintaining a strong reputation for operational performance.

Transforming the future of nursing care: Artificial intelligence in pediatrics autism nursing care

The advent of artificial intelligence (AI) is revolutionizing various fields, including healthcare. AI's impact is increasingly evident in managing and caring for autistic pediatric patients [1]. The integration of AI into pediatrics autism nursing care is revolutionizing the approach to diagnosis, treatment, and ongoing management of children with autism spectrum disorder (ASD). Through their capacity to process and analyze vast amounts of data, AI technologies offer new possibilities for enhancing the precision, efficiency, and personalization of care for children with autism. ASD presents unique challenges that require specialized, often intensive, care strategies. According to Zhao et al., (2024), integrating AI into nursing care for children with autism offers promising opportunities to enhance diagnostics, personalize treatment plans, and improve overall patient outcomes [2]. This commentary explores how AI is transforming pediatric autism nursing care and the vital role nurses play in this evolving landscape. ASD is a developmental disorder characterized by challenges with social interaction, communication, and repetitive behaviors. Symptoms and their severity vary widely among individuals, making ASD a spectrum disorder. Research indicates that early diagnosis and intervention are crucial for improving outcomes, yet these can be difficult due to the complex and varied presentation of the disorder [3].

Dance Education in Promoting Children's Sociality and Study on the Role and Mechanism of Emotion Development

As a unique form of education, dance education has a significant impact on children's social and emotional development. Through dance activities, while enjoying the charm of art, children can learn social rules and emotional expression through body language and collective interaction, thus enhancing social communication ability and emotional regulation ability. Dance education not only improves children's physical coordination and creativity, but also promotes the cultivation of empathy and the development of self-cognition through non-verbal emotional communication. This study deeply discusses the mechanism of dance education in children's social and emotional development, and provides a valuable reference for preschool education practice.

The Perceived Impact of Social Media on Family and Social Relationships in Saudi Arabia

This article endeavors to investigate the effect of technology adoption on the social changes acknowledged in the realms of Saudi Arabia in the context of the issue that has recently seen a ginormous usage of internet access, particularly in the last decade. Adopting a mixed methods approach, 300 young people aged between 18 and 30 years were sampled from two universities and one high school in Riyadh, Saudi Arabia, who later took part in both questionnaire surveys and in-depth interviews. The objective entailed implying that web browsing caused temporal shifting, thus making real-time social communication distanced, and revealing any changes in the traditional values/norms. The study indicates a significant shift in women's social relations in KSA, with internet usage allowing them to break traditional norms and alter cultural acceptance and social relationships.

Can Avatar Robots Assist Older People and Care Professionals? Evaluation of an Intervention Study in Eight Nursing Homes in Tokyo

Abstract Background Securing human resources to meet increasing demand for older people's care is challenging, particularly in Japan, where the pace of ageing is accelerating. Central and local government have been seeking partial solutions in assistive technologies such as robotics. Against such a background, the study was conducted in 8 nursing care homes in Tokyo, where avatar robots were tested to examine whether and how these robot interventions can affect the daily life of older people and care professionals. Methods Four different types of avatar robot (ORIHIME, NEWME, Piyokame and BOCCO) were introduced to and used in eight nursing care facilities, in order to create conversational opportunities over 12 weeks. Before–after studies were conducted, and a variety of data was collected (interpersonal communication, self-care and depressive tendencies using the International Classification of Functioning, Disability and Health (ICF) and InterRAI assessments). System usability scores (SUS) were collected from care professionals, who also performed a time-on-task analysis. Results Study participants who consented to taking part were 136 older adults (88.4±6.6 years old, 18 men and 118 women) and 63 care professionals. Participants with a high degree of dependency accounted for 31 percent. In total, 136 avatar robots were used. There was an overall, yet marginal, improvement for older people. While the SUS scores were poor, the majority (90 percent) responded that such devices would prove useful in the future. The time-on-task analysis indicates that more time can be secured for ‘person-to-person’ care. Conclusion Positive impacts of avatar robots (to increase the level of social interaction and communication) were observed. However, the results are inconclusive, and more needs to be done with regard to technology skills, competence enhancement and data collection methods for this type of research. The study was funded in part by the Tokyo Metropolitan Government.

Enhancing social presence in online learning through metaverse platform

The rapid growth of online learning has led to the exploration of various strategies for improving its effectiveness. One such strategy is the use of metaverse platforms, which are believed to enhance social communication and presence. This study aimed to investigate the impact of using GatherTown, a metaverse platform, on the social presence of online learning. The study involved a 2-week intervention with 148 students using GatherTown, and data were collected through a pre- and post-intervention questionnaire, as well as interviews with learners. The results indicate that the use of GatherTown positively influences the social presence of online learning. The learners reported higher levels of social presence after using GatherTown, which was attributed to the platform’s ability to facilitate social interaction and personalization of the learning environment. The interviews also revealed that the learners felt more engaged and connected to the learning community as a result of virtual space design. The results of this study shed light on the possible use of metaverse platforms to improve online learning.

Effectiveness of Joint Attention Training on Basic Social Communication, Anxiety and Executive Functions of Children with Autism Spectrum

Introduction: The aim of this study was to investigate the effectiveness of joint attention training on basic social communication, anxiety and executive functions of children with autism. Methods: The research design was quasi-experimental and pre-test and post-test with control group. The statistical populations of children with autism spectrum were referred to the psychiatric and psychological centers in Urmia City during the year 2021-2022. 30 individuals (15 ones from the shared attention group and 15 from the control group) were selected as a statistical sample using the available and targeted method. Data via questionnaires of basic social communication (Zabov, 2010), anxiety (Spence, 1999), executive functions of the parents' brief form (Balster Gerard et al., 2000) were collected during the intervention therapy method of joint attention training (Vakilizad and Abedi, 2015) (12 sessions, 3 days a week, each session was an hour and a half, each session was divided into 3 parts of 25 minutes with a 5 minute break for the child). Then the data were analyzed with Software SPSS V. 16 and multivariate analysis of covariance test. Results: The results showed that joint attention training increased basic social communication and executive functions and reduced anxiety in children with autism spectrum. The differences between the investigated groups and the conducted tests were significant (P≤0.01). Conclusion: Interventional treatment methods such as joint attention training should be developed for the treatment of autistic patients, so that with the help of these methods, the individual and collective life of these patients can be improved.

Study Protocol for a Cluster, Randomized, Controlled Community Effectiveness Trial of the Early Start Denver Model (ESDM) Compared to Community Early Behavioral Intervention (EBI) in Community Programs serving Young Autistic Children: Partnering for Autism: Learning more to improve Services (PALMS)

BackgroundThe rising number of children identified with autism has led to exponential growth in for-profit applied behavior analysis (ABA) agencies and the use of highly structured approaches that may not be developmentally appropriate for young children. Multiple clinical trials support naturalistic developmental behavior interventions (NDBIs) that integrate ABA and developmental science and are considered best practices for young autistic children. The Early Start Denver Model (ESDM) is a comprehensive NDBI shown to improve social communication outcomes for young autistic children in several controlled efficacy studies. However, effectiveness data regarding NDBI use in community-based agencies are limited.MethodsThis study uses a community-partnered approach to test the effectiveness of ESDM compared to usual early behavioral intervention (EBI) for improving social communication and language in autistic children served by community agencies. This is a hybrid type 1 cluster-randomized controlled trial with 2 conditions: ESDM and EBI. In the intervention group, supervising providers will receive training in ESDM; in the control group, they will continue EBI as usual. We will enroll and randomize 100 supervisors (50 ESDM, 50 EBI) by region. Each supervisor enrolls 3 families of autistic children under age 5 (n = 300) and accompanying behavior technicians (n = 200). The primary outcome is child language and social communication at 6 and 12 months. Secondary outcomes include child adaptive behavior, caregiver use of ESDM strategies, and provider intervention fidelity. Child social motivation and caregiver fidelity will be tested as mediating variables. ESDM implementation determinants will be explored using mixed methods.DiscussionThis study will contribute novel knowledge on ESDM effectiveness, the variables that mediate and moderate child outcomes, and engagement of its mechanisms in community use. We expect results from this trial to increase community availability of this model and access to high-quality intervention for young autistic children, especially those who depend on publicly funded intervention services. Understanding implementation determinants will aid scale-up of effective models within communities.Trail registrationClinicaltrials.gov identifier number NCT06005285. Registered on August 21, 2023.Protocol versionIssue date 6 August 2024; Protocol amendment number: 02.

Creative City Brand Building on Social Media Platforms

With the advent of the digital age, social media has become an important tool to shape the image of a city's brand. This paper aims to explore how to use social media platforms to build creative city brands, so as to enhance the attractiveness and competitiveness of cities. Through the study of many successful cases at home and abroad, combined with the theory of social media communication and the theory of urban brand image, this paper analyzes the mechanism of social media in urban brand promotion. The research adopted a combination of quantitative and qualitative methods, including online questionnaire survey, social media data analysis and in-depth interviews, to collect and analyze relevant data. The results show that social media can not only increase the visibility of cities, but also promote cultural exchanges and economic cooperation. In addition, the study found that personalized content creation, interactive user engagement, and sustained brand storytelling are key factors for successful city branding on social media. Finally, this paper puts forward suggestions on social media marketing strategies for different types of cities, and points out that future research should pay attention to the impact of changes in social media platform algorithms on the effectiveness of urban brand communication. This study provides a practical reference for city managers to promote city image more effectively in the new media environment.

Animal Models of Autistic-like Behavior in Rodents: A Scoping Review and Call for a Comprehensive Scoring System

Appropriate animal models of human diseases are a cornerstone in the advancement of science and medicine. To create animal models of neuropsychiatric and neurobehavioral diseases such as autism spectrum disorder (ASD) necessitates the development of sufficient neurobehavioral measuring tools to translate human behavior to expected measurable behavioral features in animals. If possible, the severity of the symptoms should also be assessed. Indeed, at least in rodents, adequate neurobehavioral and neurological tests have been developed. Since ASD is characterized by a number of specific behavioral trends with significant severity, animal models of autistic-like behavior have to demonstrate the specific characteristic features, namely impaired social interactions, communication deficits, and restricted, repetitive behavioral patterns, with association to several additional impairments such as somatosensory, motor, and memory impairments. Thus, an appropriate model must show behavioral impairment of a minimal number of neurobehavioral characteristics using an adequate number of behavioral tests. The proper animal models enable the study of ASD-like-behavior from the etiologic, pathogenetic, and therapeutic aspects. From the etiologic aspects, models have been developed by the use of immunogenic substances like polyinosinic-polycytidylic acid (PolyIC), lipopolysaccharide (LPS), and propionic acid, or other well-documented immunogens or pathogens, like Mycobacterium tuberculosis. Another approach is the use of chemicals like valproic acid, polychlorinated biphenyls (PCBs), organophosphate pesticides like chlorpyrifos (CPF), and others. These substances were administered either prenatally, generally after the period of major organogenesis, or, especially in rodents, during early postnatal life. In addition, using modern genetic manipulation methods, genetic models have been created of almost all human genetic diseases that are manifested by autistic-like behavior (i.e., fragile X, Rett syndrome, SHANK gene mutation, neuroligin genes, and others). Ideally, we should not only evaluate the different behavioral modes affected by the ASD-like behavior, but also assess the severity of the behavioral deviations by an appropriate scoring system, as applied to humans. We therefore propose a scoring system for improved assessment of ASD-like behavior in animal models.

Prospective Interrelation Between Sensory Sensitivity and Fine Motor Skills During the First 18 Months Predicts Later Autistic Features.

Sensory features are included in the diagnostic criteria of autism and atypical sensory responsiveness may produce "cascading effects" on later development. Similarly, autistic individuals often struggle with motor coordination and early delays in the motor domain appear to be linked to later development. However, the longitudinal interrelation between early sensory profiles and motor features on later socio-communicative skills remains to be defined. This study aimed to investigate whether sensory sensitivity impacts fine motor abilities and vice versa from 12 to 18 months of age and to examine how sensory-motor interplay would be associated with later autistic traits at 24-36 months of age. The sample included 118 infant siblings of autistic children recruited at 12 months of age. Sensory sensitivity and eye-hand coordination were assessed at 12 and 18 months of age and autistic traits were evaluated at 24-36 months of age. Cross-lagged panel analysis revealed significant within-domain effects for sensory sensitivity and eye-hand coordination from 12 to 18 months. Furthermore, a significant association between these two domains on later autistic traits was found. In analyzing the longitudinal bidirectional relationship, we found that lower eye-hand coordination skills at 12 months predicted later sensory sensitivity at 18 months, and in turn, social communication skills at 24-36 months. The present study offers new empirical evidence supporting the potential clinical value of including sensory and motor measures besides social communication skills within early autism surveillance programs.

Study protocol of a randomized control trial on the effectiveness of improvisational music therapy for autistic children.

Music therapy is the clinical use of musical interventions to improve mental and physical health across multiple domains, including social communication. Autistic children, who have difficulties in social communication and often increased anxiety, tend to show a strong preference for music, because it can be structured and systematic, and therefore more predictable than social interaction. This makes music therapy a promising medium for therapeutic support and intervention. Previous clinical trials of music therapy compared to traditional therapy for autistic children have shown encouraging but nevertheless mixed results. The primary aim is to conduct a randomised controlled trial (RCT) of improvisational music therapy for autistic children and test its effectiveness in at improving social communication and wellbeing, and to reduce anxiety. The RCT will be conducted with 200 autistic children in the UK aged 7 to 11 years old. Participants will be randomly assigned to either improvisational music therapy or support as usual. The trial will be an assessor-blind, pragmatic two-arm cluster RCT comparing the impact of 12-weeks of improvisational music therapy in addition to support as usual, vs. support as usual for autistic children. Researchers who are blind to which arm the children are in will conduct assessments and obtain data via caregiver reports. The primary outcome will be the absolute change in the total score of the Brief Observation of Social Communication Change (BOSCC) assessed at baseline, T1 (13weeks) and T2 (39weeks) follow-ups. The BOSCC consists of specific items that were developed to identify changes in social-communication behaviours. Secondary outcome measures include: (1) Parent reported anxiety scale for youth with ASD (Note that we do not use the term 'ASD' or Autism Spectrum Disorder, because many autistic people feel it is stigmatising. Instead, we use the term 'autism')(PRAS-ASD) (2) Young Child Outcome Rating Scale, for wellbeing (YCORS), (3) Strengths and Difficulties Questionnaire (SDQ); and (4) Vineland Adaptive Behaviour Scale (VABS). (5) The Children's Communication Checklist-2 (CCC-2) will be completed to evaluate pragmatic speech with fluent speakers only; (6) The Music Engagement Scale (MES); and (7) Assessment of the Quality of Relationship (AQR) will be used to evaluate the child-therapist relationships using video-analysis of music therapy sessions. Additional data will be collected by administering the Wechsler Abbreviated Scale of Intelligence (WASI-II), Music at Home Questionnaire (M@H), and children's versions of the Empathy Quotient (EQ) and Systemizing Quotient (SQ). Audio and video data from the therapy sessions will be collected and analysed (using both human and computer-based feature-coding, e.g., machine learning and AI-driven methods) to identify how music and non-musical interactions foster change throughout the therapy. This study aims to observe if the interactions, engagement, and therapeutic modalities fostered during music therapy sessions can translate to non-musical contexts and improve autistic children's social communication skills, identifying possible mediating factors contributing to the effectiveness of music therapy, potentially informing policy making and governance. This randomised control trial is registered with the NIH U.S. National Library of Medicine: https://clinicaltrials.gov/search?term=NCT06016621 , clinicalTrials.gov Identifier: NCT0601662, Registration Date 19th August 2023.