How to Select Technologies for Autistic Users: A Co-Developed Evidence-Based Framework
When seeking technology-based interventions, a particular challenge for members of the autistic community is identifying which of the multitude of digital technologies available is most appropriate. What kind of evidence do the autistic community use to inform their decisions regarding technology-based interventions? And to what extent does this match with any evidence provided by those developing or evaluating the digital interventions? This study is part of a project aiming to integrate the perspectives of the autistic, practitioner, developer and researcher communities as to what constitutes evidence for technology-based interventions.
To develop an agreed framework, shared among all relevant stakeholders, for good practice with regard to the provision of accessible evidence for technology-based interventions for autism.
We carried out a Delphi-inspired qualitative study adopting Delphi methodology’s iterative nature, participant anonymity and online communication (Hasson et al. 2000; Boulkedid et al., 2011) and performing a thematic analysis on the aggregated data. An international panel of 23 specialists (researchers, practitioners, developers, autistic community) in autism and digital technologies completed a four-phase Delphi consultation initially informed by a systematic literature review. Suggestions for evidence usage in technology-based interventions for autism were elicited from the panel, grouped and reviewed by a moderator and rated by the panel at every phase.
Three separate and distinct requirements emerged for technology-based interventions for autism, namely: reliability, engagement and efficiency. Four sources of evidence were consistently considered high-value by our expert panel, namely: hands-on experience, academic sources, expert views and online reviews. The relative weighting of the importance of each source of evidence varied between reliability, engagement and efficiency. For example, hands-on experience was thought to provide the strongest evidence for reliability and engagement, whereas academic sources were thought to provide the strongest evidence for efficiency. The panel also identified need for caution in relation to some sources of evidence, such as information provided by product developers themselves, as well as a detailed list of resources for digital products for the autism community.
For the first time, a framework for considering the evidence for technology-based interventions for autism has been developed. The framework has been co-developed by all the relevant stakeholders and is an accessible guide to the available evidence. It can be quickly and easily applied to technology-based interventions for autism by the members of the autism community. This framework can be used as a guide when selecting or recommending a technology-based intervention for autistic people.