Background: The increasing prevalence of autism spectrum disorder (ASD) has driven research interest on the therapy of individuals with autism, especially children, as early diagnosis and appropriate treatment can lead to improvement in the condition. With the widespread availability of virtual reality, augmented reality (AR), and mixed reality technologies to the public and the increasing popularity of mobile devices, the interest in the use of applications and technologies to provide support for the therapy of children with autism is growing. Objective: This study aims to describe the literature on the potential of virtual reality, AR, and mixed reality technologies in the context of therapy for children with ASD. We propose to investigate and analyze the temporal distribution of relevant papers, identify the target audience for studies related to extended reality apps in ASD therapy, examine the technologies used in the development of these apps, assess the skills targeted for improvement in primary studies, explore the purposes of the proposed solutions, and summarize the results obtained from their application. Methods: For the systematic literature review, 6 research questions were defined in the first phase, after which 5 international databases (Web of Science, Scopus, ScienceDirect, IEEE Xplore Digital Library, and ACM Digital Library) were searched using specific search strings. Results were centralized, filtered, and processed applying eligibility criteria and using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The results were refined using a technical and IT-oriented approach. The quality criteria assessed whether the research addressed ASDs, focused on children’s therapy, involved targeted technologies, deployed solutions on mobile devices, and produced results relevant to our study. Results: In the first step, 179 publications were identified in Zotero reference manager software (Corporation for Digital Scholarship). After excluding articles that did not meet the eligibility or quality assessment criteria, 28 publications were finalized. The analysis revealed an increase in publications related to apps for children with autism starting in 2015 and peaking in 2019. Most studies (22/28, 79%) focused on mobile AR solutions for Android devices, which were developed using the Unity 3D platform and the Vuforia engine. Although 68% (19/28) of these apps were tested with children, 32% (9/28) were tested exclusively by developers. More than half (15/28, 54%) of the studies used interviews as an evaluation method, yielding mostly favorable although preliminary results, indicating the need for more extensive testing. Conclusions: The findings reported in the studies highlight the fact that these technologies are appropriate for the therapy of children with ASD. Several studies showed a distinct trend toward the use of AR technology as an educational tool for people with ASD. This trend entails multidisciplinary cooperation and an integrated research approach, with an emphasis on comprehensive empirical evaluations and technology ethics.

Decentralized databases have gained popularity in the last few years in different areas, such as: traceability, supply chains or finance. Leveraging this type of emerging technology will improve knowledge sharing, as well as the transparency and traceability of the data for digital systems. In a similar way, the characteristics are advertised by the centralized ledger technologies, which are manufactured by large cloud service providers such as Amazon. The present study analyzes the performance of two ledger technologies: BigchainDB (i.e., the decentralized blockchain database) and Amazon QLDB (i.e., the centralized ledger database with transparent and immutable characteristics). For the purposes of comparison, we have integrated these technologies into our traceability platform, which is called the Smart Tracking Platform (STP), and performed a series of experiments enabling us to acquire data for different metrics, such as CPU or memory usage for both the reading and writing operations. The findings of the present study show that QLDB has an overall better performance compared to BigchainDB, based on the metrics that have been considered. From the perspective of database ledger implementation, Amazon QLDB proved to be an integrated solution, easier to use, while BigchainDB comprises a more complex system to be implemented and developed, but is more flexible. Although both systems are almost ready to use solutions for local environments, when it comes to configuration and setting up the communication between nodes within a production environment, BigchainDB adds a layer of complexity from a DevOps perspective, while Amazon QLDB completely overcomes it. Depending on the area considered and the identified needs, both BigchainDB and Amazon QLDB can be considered as suitable solutions for a ledger database.

Caregivers of children with Autism Spectrum Disorder (ASD) frequently experience chronic psychological stress, thereby necessitating accessible support. Although artificial intelligence (AI)-based assisted technologies have the potential to reduce caregiver workload, most existing solutions lack robust privacy control and clinical interoperability, which significantly limits their adoption in regulated healthcare environments. To address these challenges, this paper proposes a Privacy-by-Design (PbD) multi-agent architecture that enables consent-aware, auditable, and privacy-preserving AI-assisted support for caregivers of children with ASD. The effectiveness of the proposed architecture was evaluated using two datasets: one focusing on clinically grounded autism-related knowledge and another reflecting naturalistic caregiver observation language. System performance was assessed using a Retrieval-Augmented Generation Assessment (RAGAs)-based framework with a Large Language Model (LLM)-as-a-Judge approach implemented via a locally deployed Llama 3 8B model. The system achieved answer relevancy scores of 0.767 for the clinical dataset and 0.750 for the observational dataset, with corresponding Recall@K values of 0.400 and 0.742, respectively. Context precision ranged from 0.599 to 0.631, and no harmful content was detected. Overall, the proposed architecture demonstrates secure caregiver–specialist collaboration through consent-aware routing, anonymised data storage, and controlled data reconstruction, providing a regulation-aligned design option for privacy-preserving AI integration in assisted care platforms.

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder characterized by persistent impairments in communication, social interaction and learning (Hodges et al., 2020). Because of its heterogeneous nature, ASD presents complex challenges, including social exclusion, school abandonment and limited access to health care. Technologies offer a pragmatic solution to overcome these limitations and to deliver therapeutic interventions in both physical and online environments. Studies have demonstrated that technology-mediated interventions (TMIs) have a positive impact on the development of capabilities of individuals with ASD. However, according to the European Parliament's Research Service technologies for ASDs are less mature (European Parliament. Directorate General for Parliamentary Research Services., 2018) and the causes and effects of TMIs in ASD should be better understood. Present study aimed to investigate the psychological variables related to TMIs in ASD. The study employed a survey research method with a between-subjects design involving 61 adult participants comprising therapists, teachers and parents of children with ASD and it examined psychological variables related to children with ASD, factors of technology usage, and parental and educators' experiences. The analysis of the data obtained from the questionnaire focused on correlations and differences between groups, and was carried out using nonparametric tests. Kendall's Tau B test was used to explore the relationships between variables. The Mann-Whitney nonparametric test was employed to identify differences between groups. The findings revealed numerous relationships between variables and meaningful differences between the groups investigated in terms of how technologies are perceived by stakeholders involved in ASD interventions.

BACKGROUND The increasing prevalence of autism spectrum disorder (ASD) has driven research interest on the therapy of individuals with autism, especially children, as early diagnosis and appropriate treatment can lead to improvement in the condition. With the widespread availability of virtual reality, augmented reality (AR), and mixed reality technologies to the public and the increasing popularity of mobile devices, the interest in the use of applications and technologies to provide support for the therapy of children with autism is growing. OBJECTIVE This study aims to describe the literature on the potential of virtual reality, AR, and mixed reality technologies in the context of therapy for children with ASD. We propose to investigate and analyze the temporal distribution of relevant papers, identify the target audience for studies related to extended reality apps in ASD therapy, examine the technologies used in the development of these apps, assess the skills targeted for improvement in primary studies, explore the purposes of the proposed solutions, and summarize the results obtained from their application. METHODS For the systematic literature review, 6 research questions were defined in the first phase, after which 5 international databases (Web of Science, Scopus, ScienceDirect, IEEE Xplore Digital Library, and ACM Digital Library) were searched using specific search strings. Results were centralized, filtered, and processed applying eligibility criteria and using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. The results were refined using a technical and IT-oriented approach. The quality criteria assessed whether the research addressed ASDs, focused on children’s therapy, involved targeted technologies, deployed solutions on mobile devices, and produced results relevant to our study. RESULTS In the first step, 179 publications were identified in Zotero reference manager software (Corporation for Digital Scholarship). After excluding articles that did not meet the eligibility or quality assessment criteria, 28 publications were finalized. The analysis revealed an increase in publications related to apps for children with autism starting in 2015 and peaking in 2019. Most studies (22/28, 79%) focused on mobile AR solutions for Android devices, which were developed using the Unity 3D platform and the Vuforia engine. Although 68% (19/28) of these apps were tested with children, 32% (9/28) were tested exclusively by developers. More than half (15/28, 54%) of the studies used interviews as an evaluation method, yielding mostly favorable although preliminary results, indicating the need for more extensive testing. CONCLUSIONS The findings reported in the studies highlight the fact that these technologies are appropriate for the therapy of children with ASD. Several studies showed a distinct trend toward the use of AR technology as an educational tool for people with ASD. This trend entails multidisciplinary cooperation and an integrated research approach, with an emphasis on comprehensive empirical evaluations and technology ethics.