Investigating the gap between research and practice in Robot-Based therapy for Autism Spectrum Disorder

Abstract

The use of social robots as therapeutic tools for children with Autism Spectrum Disorder (ASD) has emerged as a promising area of research in recent years. Numerous studies have demonstrated the potential of these robots to support the development of social skills, including improvements in eye contact, verbal and physical communication, joint attention, and other interpersonal behaviors. Researchers such as Dautenhahn, Dickstein-Fisher, and initiatives like AskNAO have documented positive short- and medium-term outcomes across diverse populations and robotic systems. Despite this growing body of evidence, the real-world adoption of social robots in clinical or home-based ASD therapy remains limited. This study investigates the barriers that hinder the practical implementation of social robots in ASD care by analyzing current research trends and comparing them with the perspectives of key stakeholders — namely, clinicians and parents of children with ASD. We employed a mixed-methods approach to gain a multidimensional understanding of these challenges. First, a systematic literature review was conducted using major academic databases, including PubMed, IEEE Xplore, and Scopus. Studies published between January 2016 and December 2024 were examined, focusing specifically on robot-child interaction and therapeutic application in the context of ASD. Our review revealed that although all studies reported measurable benefits for children, none of the robot systems had been systematically integrated into regular therapeutic practices. Several limitations were identified, including a general lack of user testing—most studies involved fewer than ten participants—variation in robot appearance and behavior due to the absence of a standardized design framework, and inconsistent metrics used to assess therapeutic effectiveness. To complement the literature review and gain insight into real-world expectations and constraints, we conducted semi-structured interviews with clinicians and distributed surveys to parents. These qualitative and quantitative methods allowed us to explore stakeholders’ attitudes toward social robots, identify their practical concerns, and gather suggestions for how these technologies could be improved for clinical use. Preliminary findings highlight concerns about inconsistent robotic design, including differences in personality, appearance, and level of customization. In addition, participants cited the lack of intuitive interfaces for therapists and caregivers as a significant obstacle to implementation. Many also pointed to the absence of evidence-based clinical guidelines that would support decision-making and evaluation in real-world therapy settings. Through this research, we aim to bridge the gap between research success and real-life clinical integration by identifying key areas where standardization and clearer communication with users could improve both the research process and product development. Specifically, future work can focus on establishing core therapeutic activities that robots can support, ensuring robots are adaptable and customizable to meet individual needs, defining cost-effectiveness benchmarks to guide adoption decisions, and promoting the development of ASD-specific robotic solutions. The findings from this study offer a roadmap for researchers, designers, and healthcare providers to collaboratively address the challenges preventing broader adoption of social robots in autism care. By aligning technological innovation with stakeholder needs, this work contributes to a more realistic and practical understanding of how to transition social robotics from research labs into everyday therapeutic contexts.