Determinants of Technological Interventions for Children With Autism - A Systematic Review

Deficits in social cognition underlie many of the profound challenges individuals with autism spectrum disorder face interacting with and understanding others. This study aimed to evaluate abilities predicting behavioral, verbal, and emotional responses during simulated social scenarios in 42 autistic children. Additionally, communication patterns were analyzed across solitary, peer, and group settings. A multifaceted assessment battery including the “prognostic stories” technique, expert observational ratings, cultural congruence metrics, and activity mapping provided insights into participants’ capacity forecasting actions, statements, and feelings in interpersonal situations. Results revealed marked variability across skill domains, with greatest impairments anticipating emotions. Communication quality and self-regulation strongly correlated with predictive accuracy. Cluster analysis indicated four distinct functional profiles (“proactive planners”, “regulatory navigators”, “quiet observers”, and “balanced responders”) highlighting heterogeneous strengths warranting support. Despite challenges inferring psychological states, personalized interventions targeting highly correlated skill deficits offer optimal social adaptation. Findings reiterate calls for balanced approaches recognizing autistic diversity while compassionately addressing barriers to inclusion. With acceptance and opportunity, individuals across the spectrum have much to contribute. Limitations include sample size and gender imbalance. Follow-up longitudinal tracking is warranted.

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Development of personalized profiles of students with autism spectrum disorder for interactive interventions with robots to enhance language and social skills

Herrero-Martín,

Fonseca,

Caro-Via

et al. 2024

Front. Psychiatry

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The inclusion of students with autism spectrum disorder (ASD) in mainstream education (primary and secondary, in the range of 4-5 to 8-10 years old) is a complex task that has long challenged both educators and health professionals. However, the correct use of digital technologies such as personalization settings and interaction with robots has clearly shown how these new technologies can benefit ASD students. However, it is essential to characterize the profile, problems, and needs of each student, since it is not possible to generalize an accessible approach for all users. The work presented shows the creation and validation, through pilot tests, of an instrument that outlines the main needs of a student with ASD, based on behavioral variables. In a later phase, instructional sequences will be designed and adapted through digital tablets and interaction with a robot to improve specific aspects identified in the initial profile. The results demonstrate the method’s ability to assess and prioritize profiles satisfactorily which helps create a design adjusted to each student. The first pilot tests have been well received by ASD students, who have shown increased interest in the contents and methods used in this approach. Motivation levels and engagement have also increased, and social interactions with their peers have improved.

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Determinants of Technological Interventions for Children With Autism - A Systematic Review

Cited by 4 publications

References 141 publications

Integrative Model for Biomarker Identification of Cognitive Learning Barriers in ASD

Integrative Model for Biomarker Identification of Cognitive Learning Barriers in ASD

The ways of communication for children with autism spectrum disorder

Development of personalized profiles of students with autism spectrum disorder for interactive interventions with robots to enhance language and social skills

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