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CC BY-NC-ND 4.0 · Appl Clin Inform 2021; 12(05): 1030-1040
DOI: 10.1055/s-0041-1736626
Research Article

A Mobile Game Platform for Improving Social Communication in Children with Autism: A Feasibility Study

Yordan Penev
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Kaitlyn Dunlap
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Arman Husic
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Cathy Hou
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Peter Washington
4   Department of Bioengineering, Stanford University, Stanford, California, United States
,
Emilie Leblanc
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Aaron Kline
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
John Kent
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Anthony Ng-Thow-Hing
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Bennett Liu
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Christopher Harjadi
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Meagan Tsou
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Manisha Desai
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
,
Dennis P. Wall
1   Department of Pediatrics (Systems Medicine), Stanford University, Stanford, California, United States
2   Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, United States
3   Department of Biomedical Data Science, Stanford University, Stanford, California, United States
› Author Affiliations Funding The work was supported in part by funds to DPW from the National Institutes of Health (1R01EB025025–01, 1R21HD091500–01, 1R01LM013083), the National Science Foundation (Award 2014232), The Hartwell Foundation, Bill and Melinda Gates Foundation, Coulter Foundation, Lucile Packard Foundation, the Weston Havens Foundation, and program grants from Stanford's Human Centered Artificial Intelligence Program, Precision Health and Integrated Diagnostics Center (PHIND), Beckman Center, Bio-X Center, Predictives and Diagnostics Accelerator (SPADA) Spectrum, Spark Program in Translational Research, MediaX, and from the Wu Tsai Neurosciences Institute's Neuroscience: Translate Program. P.W. would like to acknowledge support from the Stanford Interdisciplinary Graduate Fellowship (SIGF).
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Abstract

Background Many children with autism cannot receive timely in-person diagnosis and therapy, especially in situations where access is limited by geography, socioeconomics, or global health concerns such as the current COVD-19 pandemic. Mobile solutions that work outside of traditional clinical environments can safeguard against gaps in access to quality care.

Objective The aim of the study is to examine the engagement level and therapeutic feasibility of a mobile game platform for children with autism.

Methods We designed a mobile application, GuessWhat, which, in its current form, delivers game-based therapy to children aged 3 to 12 in home settings through a smartphone. The phone, held by a caregiver on their forehead, displays one of a range of appropriate and therapeutically relevant prompts (e.g., a surprised face) that the child must recognize and mimic sufficiently to allow the caregiver to guess what is being imitated and proceed to the next prompt. Each game runs for 90 seconds to create a robust social exchange between the child and the caregiver.

Results We examined the therapeutic feasibility of GuessWhat in 72 children (75% male, average age 8 years 2 months) with autism who were asked to play the game for three 90-second sessions per day, 3 days per week, for a total of 4 weeks. The group showed significant improvements in Social Responsiveness Score-2 (SRS-2) total (3.97, p <0.001) and Vineland Adaptive Behavior Scales-II (VABS-II) socialization standard (5.27, p = 0.002) scores.

Conclusion The results support that the GuessWhat mobile game is a viable approach for efficacious treatment of autism and further support the possibility that the game can be used in natural settings to increase access to treatment when barriers to care exist.

Keywords

digital therapeutics - mobile game - mobile health - AI-medicine - autism spectrum disorder - developmental disorders - behavioral therapy - clinical testing - smartphone - patient population - mental health

Protection of Human and Animal Subjects

The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects and was reviewed by Stanford University's Institutional Review Board.


Supplementary Material



Publication History

Received: 13 June 2021

Accepted: 21 September 2021

Article published online:
17 November 2021

© 2021. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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