Screening in toddlers and preschoolers at risk for autism spectrum disorder: Evaluating a novel mobile-health screening tool

2018 ◽  
Vol 11 (7) ◽  
pp. 1038-1049 ◽  
Author(s):  
Stephen M. Kanne ◽  
Laura Arnstein Carpenter ◽  
Zachary Warren
Keyword(s):  
Autism Spectrum Disorder ◽  
At Risk ◽  
Mobile Health ◽  
Screening Tool ◽  
Autism Spectrum ◽  
Health Screening ◽  
Spectrum Disorder

scholarly journals Parent-Mediated Interventions for Infants under 24 Months at Risk for Autism Spectrum Disorder: A Systematic Review of Randomized Controlled Trials

2021 ◽  
Author(s):  
Mei L. Law ◽  
Jatinder Singh ◽  
Mathilde Mastroianni ◽  
Paramala Santosh
Keyword(s):  
Autism Spectrum Disorder ◽  
At Risk ◽  
Randomized Controlled Trials ◽  
Grey Literature ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Controlled Trials ◽  
Intervention Effects ◽  
Level Of Evidence ◽  
Randomized Controlled

AbstractProdromal symptoms of Autism Spectrum Disorder (ASD) have been detected within the first year of life. This review evaluated evidence from randomized controlled trials (RCTs) of parent-mediated interventions for infants under 24 months who are at risk for ASD. Electronic databases, including grey literature, were searched up till November 2019. Seven RCTs were identified. There was substantial heterogeneity in recruitment, outcome measures and effect size calculations. Interventions did not reduce the risk of later ASD diagnosis and post-intervention effects on infant outcomes were inconsistent, with five studies reporting significant improvements across both treatment and control groups. Moderate level of evidence of intervention effects on parental interaction skills and the small number of RCTs, and significant limitations restrict generalizability across studies.

Parent-Mediated Intervention for One-Year-Olds Screened as At-Risk for Autism Spectrum Disorder: A Randomized Controlled Trial

2017 ◽  
Vol 47 (11) ◽  
pp. 3520-3540 ◽  
Author(s):  
Linda R. Watson ◽  
Elizabeth R. Crais ◽  
Grace T. Baranek ◽  
Lauren Turner-Brown ◽  
John Sideris ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
At Risk ◽  
Randomized Controlled Trial ◽  
Controlled Trial ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Randomized Controlled ◽  
One Year

scholarly journals Identification of social engagement indicators associated with autism spectrum disorder using a game-based mobile application

2021 ◽  
Author(s):  
Maya Varma ◽  
Peter Washington ◽  
Brianna Chrisman ◽  
Aaron Kline ◽  
Emilie Leblanc ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Mobile Health ◽  
Social Engagement ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Computational Techniques ◽  
Visual Scanning ◽  
Gaze Fixation ◽  
Healthcare Needs ◽  
Children With Asd

Autism spectrum disorder (ASD) is a widespread neurodevelopmental condition with a range of potential causes and symptoms. Children with ASD exhibit behavioral and social impairments, giving rise to the possibility of utilizing computational techniques to evaluate a child's social phenotype from home videos. Here, we use a mobile health application to collect over 11 hours of video footage depicting 95 children engaged in gameplay in a natural home environment. We utilize automated dataset annotations to analyze two social indicators that have previously been shown to differ between children with ASD and their neurotypical (NT) peers: (1) gaze fixation patterns and (2) visual scanning methods. We compare the gaze fixation and visual scanning methods utilized by children during a 90-second gameplay video in order to identify statistically-significant differences between the two cohorts; we then train an LSTM neural network in order to determine if gaze indicators could be predictive of ASD. Our work identifies one statistically significant region of fixation and one significant gaze transition pattern that differ between our two cohorts during gameplay. In addition, our deep learning model demonstrates mild predictive power in identifying ASD based on coarse annotations of gaze fixations. Ultimately, our results demonstrate the utility of game-based mobile health platforms in quantifying visual patterns and providing insights into ASD. We also show the importance of automated labeling techniques in generating large-scale datasets while simultaneously preserving the privacy of participants. Our approaches can generalize to other healthcare needs.

Response to Joint Attention in Toddlers at Risk for Autism Spectrum Disorder: A Prospective Study

2007 ◽  
Vol 37 (1) ◽  
pp. 37-48 ◽  
Author(s):  
Michelle Sullivan ◽  
Julianna Finelli ◽  
Alison Marvin ◽  
Elizabeth Garrett-Mayer ◽  
Margaret Bauman ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
At Risk ◽  
Prospective Study ◽  
Joint Attention ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Response To Joint Attention ◽  
A Prospective Study
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