The purpose of this study was to identify evidenced-based, focused intervention practices for children and youth with autism spectrum disorder. This study was an extension and elaboration of a previous evidence-based practice review reported by Odom et al. (Prev Sch Fail 54:275–282, 2010b, doi:
 10.1080/10459881003785506
 ). In the current study, a computer search initially yielded 29,105 articles, and the subsequent screening and evaluation process found 456 studies to meet inclusion and methodological criteria. From this set of research studies, the authors found 27 focused intervention practices that met the criteria for evidence-based practice (EBP). Six new EBPs were identified in this review, and one EBP from the previous review was removed. The authors discuss implications for current practices and future research.

Evidence-Based Practices for Children, Youth, and Young Adults with Autism Spectrum Disorder: A Comprehensive Review.

Determining the integrity of emotion recognition in autistic spectrum disorder is important to our theoretical understanding of autism and to teaching social skills. Previous studies have reported both positive and negative results. Here, we take a formal meta-analytic approach, bringing together data from 48 papers testing over 980 participants with autism. Results show there is an emotion recognition difficulty in autism, with a mean effect size of 0.80 which reduces to 0.41 when a correction for publication bias is applied. Recognition of happiness was only marginally impaired in autism, but recognition of fear was marginally worse than recognition of happiness. This meta-analysis provides an opportunity to survey the state of emotion recognition research in autism and to outline potential future directions.

/pdf/recognition-of-emotions-in-autism-a-formal-meta-analysis-58ul6qkd5g.pdf

Recognition of Emotions in Autism: A Formal Meta-Analysis.

Kaufman Brief Intelligence Test

This article reports the results of a meta-analysis of technology-based intervention studies for children with autism spectrum disorders. We conducted a systematic review of research that used a pre-post design to assess innovative technology interventions, including computer programs, virtual reality, and robotics. The selected studies provided interventions via a desktop computer, interactive DVD, shared active surface, and virtual reality. None employed robotics. The results provide evidence for the overall effectiveness of technology-based training. The overall mean effect size for posttests of controlled studies of children with autism spectrum disorders who received technology-based interventions was significantly different from zero and approached the medium magnitude, d = 0.47 (confidence interval: 0.08-0.86). The influence of age and IQ was not significant. Differences in training procedures are discussed in the light of the negative correlation that was found between the intervention durations and the studies' effect sizes. The results of this meta-analysis provide support for the continuing development, evaluation, and clinical usage of technology-based intervention for individuals with autism spectrum disorders.

Innovative technology-based interventions for autism spectrum disorders: A meta-analysis

Background: Embodied conversational agents (ECAs) are computer-generated characters that simulate key properties of human face-to-face conversation, such as verbal and nonverbal behavior. In Internet-based eHealth interventions, ECAs may be used for the delivery of automated human support factors. Objective: We aim to provide an overview of the technological and clinical possibilities, as well as the evidence base for ECA applications in clinical psychology, to inform health professionals about the activity in this field of research. Methods: Given the large variety of applied methodologies, types of applications, and scientific disciplines involved in ECA research, we conducted a systematic scoping review. Scoping reviews aim to map key concepts and types of evidence underlying an area of research, and answer less-specific questions than traditional systematic reviews. Systematic searches for ECA applications in the treatment of mood, anxiety, psychotic, autism spectrum, and substance use disorders were conducted in databases in the fields of psychology and computer science, as well as in interdisciplinary databases. Studies were included if they conveyed primary research findings on an ECA application that targeted one of the disorders. We mapped each study’s background information, how the different disorders were addressed, how ECAs and users could interact with one another, methodological aspects, and the study’s aims and outcomes. Results: This study included N=54 publications (N=49 studies). More than half of the studies (n=26) focused on autism treatment, and ECAs were used most often for social skills training (n=23). Applications ranged from simple reinforcement of social behaviors through emotional expressions to sophisticated multimodal conversational systems. Most applications (n=43) were still in the development and piloting phase, that is, not yet ready for routine practice evaluation or application. Few studies conducted controlled research into clinical effects of ECAs, such as a reduction in symptom severity. Conclusions: ECAs for mental disorders are emerging. State-of-the-art techniques, involving, for example, communication through natural language or nonverbal behavior, are increasingly being considered and adopted for psychotherapeutic interventions in ECA research with promising results. However, evidence on their clinical application remains scarce. At present, their value to clinical practice lies mostly in the experimental determination of critical human support factors. In the context of using ECAs as an adjunct to existing interventions with the aim of supporting users, important questions remain with regard to the personalization of ECAs’ interaction with users, and the optimal timing and manner of providing support. To increase the evidence base with regard to Internet interventions, we propose an additional focus on low-tech ECA solutions that can be rapidly developed, tested, and applied in routine practice. [J Med Internet Res 2017;19(5):e151]

https://findresearcher.sdu.dk:8443/ws/files/125085260/Embodied_Conversational_Agents_in_Clinical_Psychology.pdf

Embodied Conversational Agents in Clinical Psychology: A Scoping Review

This study assessed the efficacy of FaceSay, a computer-based social skills training program for children with Autism Spectrum Disorders (ASD). This randomized controlled study (N = 49) indicates that providing children with low-functioning autism (LFA) and high functioning autism (HFA) opportunities to practice attending to eye gaze, discriminating facial expressions and recognizing faces and emotions in FaceSay’s structured environment with interactive, realistic avatar assistants improved their social skills abilities. The children with LFA demonstrated improvements in two areas of the intervention: emotion recognition and social interactions. The children with HFA demonstrated improvements in all three areas: facial recognition, emotion recognition, and social interactions. These findings, particularly the measured improvements to social interactions in a natural environment, are encouraging.

https://link.springer.com/content/pdf/10.1007%2Fs10803-011-1179-z.pdf

Avatar assistant: improving social skills in students with an ASD through a computer-based intervention.

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Avatar assistant: improving social skills in students with an ASD through a computer-based intervention.