Digital tools for direct assessment of autism risk during early childhood: A systematic review

Abstract

Current challenges in early identification of autism spectrum disorder lead to significant delays in starting interventions, thereby compromising outcomes. Digital tools can potentially address this barrier as they are accessible, can measure autism-relevant phenotypes and can be administered in children’s natural environments by non-specialists. The purpose of this systematic review is to identify and characterise potentially scalable digital tools for direct assessment of autism spectrum disorder risk in early childhood. In total, 51,953 titles, 6884 abstracts and 567 full-text articles from four databases were screened using predefined criteria. Of these, 38 met inclusion criteria. Tasks are presented on both portable and non-portable technologies, typically by researchers in laboratory or clinic settings. Gamified tasks, virtual-reality platforms and automated analysis of video or audio recordings of children’s behaviours and speech are used to assess autism spectrum disorder risk. Tasks tapping social communication/interaction and motor domains most reliably discriminate between autism spectrum disorder and typically developing groups. Digital tools employing objective data collection and analysis methods hold immense potential for early identification of autism spectrum disorder risk. Next steps should be to further validate these tools, evaluate their generalisability outside laboratory or clinic settings, and standardise derived measures across tasks. Furthermore, stakeholders from underserved communities should be involved in the research and development process. Lay abstract The challenge of finding autistic children, and finding them early enough to make a difference for them and their families, becomes all the greater in parts of the world where human and material resources are in short supply. Poverty of resources delays interventions, translating into a poverty of outcomes. Digital tools carry potential to lessen this delay because they can be administered by non-specialists in children’s homes, schools or other everyday environments, they can measure a wide range of autistic behaviours objectively and they can automate analysis without requiring an expert in computers or statistics. This literature review aimed to identify and describe digital tools for screening children who may be at risk for autism. These tools are predominantly at the ‘proof-of-concept’ stage. Both portable (laptops, mobile phones, smart toys) and fixed (desktop computers, virtual-reality platforms) technologies are used to present computerised games, or to record children’s behaviours or speech. Computerised analysis of children’s interactions with these technologies differentiates children with and without autism, with promising results. Tasks assessing social responses and hand and body movements are the most reliable in distinguishing autistic from typically developing children. Such digital tools hold immense potential for early identification of autism spectrum disorder risk at a large scale. Next steps should be to further validate these tools and to evaluate their applicability in a variety of settings. Crucially, stakeholders from underserved communities globally must be involved in this research, lest it fail to capture the issues that these stakeholders are facing.

Using mobile health technology to assess childhood autism in low-resource community settings in India: An innovation to address the detection gap

“…To our knowledge, this is the first demonstration of a multi-measure digital platform to assess autism-related symptoms by non-specialists in a low-resource setting. It adds to the growing number of international efforts towards digital assessments of autism (Dawson & Sapiro, 2019; D. Mukherjee et al, 2023).…”

“…To our knowledge, this is the first demonstration of a multi-measure digital platform to assess autism-related symptoms by non-specialists in a low-resource setting. It adds to the growing number of international efforts towards digital assessments of autism ( Dawson & Sapiro, 2019 ; D. Mukherjee et al, 2023 ). The largely non-verbal nature of the app’s directly assessed behavioural tasks makes it applicable in principle to other global settings without significant alteration.…”

Diagnosing Autism Spectrum Disorder in Pediatric Patients via Gait Analysis using ANN and SVM with Electromyography Signals

“…In some cases, children with ASD may exhibit toe-walking tendencies, which are more closely associated with motor behavior than language development. Therefore, early detection of ASD can rely on motor indicators [5][6]. Children with ASD may experience motor delays in gross and fine motor skills, affecting their locomotion [2,7].…”

Shifting the centre of gravity: Towards a truly global representation in autism research

“…This included research in exploring autism community priorities for autism research and capacity building in low-resource contexts ( Lee et al, 2022 ; Perez Liz et al, 2023 ), developing and evaluating interventions (e.g. Brandi Gomes Godoy et al, 2023 ; Schlebusch et al, 2022 ) and applying novel technologies to facilitate autism assessment ( Lockwood Estrin et al, 2023 ; Mukherjee et al, 2022 ). It is also interesting to see how research is being replicated across countries and regions, recognising that contextual factors play an important role ( Garcia Torres et al, 2023 ; Zerihun et al, 2023 ).…”