Digital interventions using mobile technologies for life skills development of learners with autism spectrum disorder: a scoping review

Abstract

Providing essential information for digital health human-computer interaction designers, this scoping review identified the most utilized features of digital evidence-based interventions in prototyped mobile technologies for autism spectrum disorder (ASD), to lay the groundwork for designing user-focused mobile assistive technologies for learners with ASD. The review systematically categorized the features and capabilities of mobile applications that teach, support, and maintain life skills. Synthesizing and analysing 42 studies using thematic analysis, it was found that mobile applications hold the potential to support the uniqueness and varying needs of learners with ASD. This is achieved through personalization in the user interface and user experience, coupled with customizations on learning content. The scoping review also found that mobile applications can assist learners with ASD by breaking down tasks into smaller steps, incorporating pictures, illustrations, videos, sounds, pre-recorded instructions, and just-in-time prompting. In a broader context, mobile technologies can not only enhance life skills learning but also contribute to routine-building for individuals with ASD. This is possible if interventions taught in school are continued at home and integrated with daily home activities, aiming to enhance learning, daily practice, and maintenance of life skills. Future work focuses on making evidence-based interventions readily available and accessible to learners, parents, caregivers, and educators to support the overall well-being of learners with ASD.

Keywords:

• Digital assistive technology
• autism spectrum disorder
• participatory design
• UI/UX
• codesign
• qualitative research

Acknowledgements

The authors would like to acknowledge the support of Prof. Daniel Amyot for his help with the methodology and review of research drafts.

Data availability statement

The submission contains the complete dataset in the main paper. No separate dataset is required.

Disclosure statement

No potential conflicts of interest were reported by the authors.

Additional information

Funding

Genevieve R. Villamin is supported by the University of Ottawa Graduate School scholarship.