BACKGROUND: Signs of autism are present in the first 2 years of life, but the average age of diagnosis lags far behind. Instruments that improve detection of autism risk in infancy are needed. This study developed and tested the psychometric properties of a novel video-based approach to detecting ASD in infancy. METHODS: A prospective longitudinal study of children at elevated or lower risk for autism spectrum disorder was conducted. Participants were 76 infants with an older sibling with ASD and 37 infants with no known family history of autism. The Video-referenced Infant Rating System for Autism (VIRSA) is a web-based application that presents pairs of videos of parents and infants playing together and requires forced-choice judgments of which video is most similar to the child being rated. Parents rated participants on the VIRSA at 6, 9, 12, and 18 months of age. We examined split-half and test-retest reliability; convergent and discriminant validity; and sensitivity, specificity, and negative and positive predictive value for concurrent and 36-month ASD diagnoses. RESULTS: The VIRSA demonstrated satisfactory reliability and convergent and discriminant validity. VIRSA ratings were significantly lower for children ultimately diagnosed with ASD than children with typical development by 12 months of age. VIRSA scores at 18 months identified all children diagnosed with ASD at that age, as well as 78% of children diagnosed at 36 months. CONCLUSIONS: This study represents an initial step in the development of a novel video-based approach to detection of ASD in infancy. The VIRSA's psychometric properties were promising when used by parents with an older affected child, but still must be tested in community samples with no family history of ASD. If results are replicated, then the VIRSA's low-burden, web-based format has the potential to reduce disparities in communities with limited access to screening.
BACKGROUND: Signs of autism are present in the first 2 years of life, but the average age of diagnosis lags far behind. Instruments that improve detection of autism risk in infancy are needed. This study developed and tested the psychometric properties of a novel video-based approach to detecting ASD in infancy. METHODS: A prospective longitudinal study of children at elevated or lower risk for autism spectrum disorder was conducted. Participants were 76 infants with an older sibling with ASD and 37 infants with no known family history of autism. The Video-referenced Infant Rating System for Autism (VIRSA) is a web-based application that presents pairs of videos of parents and infants playing together and requires forced-choice judgments of which video is most similar to the child being rated. Parents rated participants on the VIRSA at 6, 9, 12, and 18 months of age. We examined split-half and test-retest reliability; convergent and discriminant validity; and sensitivity, specificity, and negative and positive predictive value for concurrent and 36-month ASD diagnoses. RESULTS: The VIRSA demonstrated satisfactory reliability and convergent and discriminant validity. VIRSA ratings were significantly lower for children ultimately diagnosed with ASD than children with typical development by 12 months of age. VIRSA scores at 18 months identified all children diagnosed with ASD at that age, as well as 78% of children diagnosed at 36 months. CONCLUSIONS: This study represents an initial step in the development of a novel video-based approach to detection of ASD in infancy. The VIRSA's psychometric properties were promising when used by parents with an older affected child, but still must be tested in community samples with no family history of ASD. If results are replicated, then the VIRSA's low-burden, web-based format has the potential to reduce disparities in communities with limited access to screening.
Authors: Lonnie Zwaigenbaum; Margaret L Bauman; Deborah Fein; Karen Pierce; Timothy Buie; Patricia A Davis; Craig Newschaffer; Diana L Robins; Amy Wetherby; Roula Choueiri; Connie Kasari; Wendy L Stone; Nurit Yirmiya; Annette Estes; Robin L Hansen; James C McPartland; Marvin R Natowicz; Alice Carter; Doreen Granpeesheh; Zoe Mailloux; Susanne Smith Roley; Sheldon Wagner Journal: Pediatrics Date: 2015-10 Impact factor: 7.124
Authors: Natasha Marrus; Anne L Glowinski; Theodore Jacob; Ami Klin; Warren Jones; Caroline E Drain; Kieran E Holzhauer; Vaishnavi Hariprasad; Robert T Fitzgerald; Erika L Mortenson; Sayli M Sant; Lyndsey Cole; Satchel A Siegel; Yi Zhang; Arpana Agrawal; Andrew C Heath; John N Constantino Journal: J Child Psychol Psychiatry Date: 2015-02-11 Impact factor: 8.982
Authors: Ana B Sánchez-García; Purificación Galindo-Villardón; Ana B Nieto-Librero; Helena Martín-Rodero; Diana L Robins Journal: J Autism Dev Disord Date: 2019-05
Authors: Maria Jesus Herrero; Dmitry Velmeshev; David Hernandez-Pineda; Saarthak Sethi; Shawn Sorrells; Payal Banerjee; Catherine Sullivan; Abha R Gupta; Arnold R Kriegstein; Joshua G Corbin Journal: Mol Autism Date: 2020-05-27 Impact factor: 7.509