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The main purpose was to examine if the algorithmic changes increase identification of children later diagnosed with ASD, and to examine if there is a trade\u2010off when changing algorithms. We included 54,463 screened cases from the Norwegian Mother and Child Cohort Study. Children were screened using the 23 items of the M\u2010CHAT at 18\u2009months. Further, the performance of the M\u2010CHAT\u2010R algorithm was compared to the M\u2010CHAT algorithm on the 23\u2010items. In total, 337 individuals were later diagnosed with ASD. Using M\u2010CHAT\u2010R algorithm decreased the number of correctly identified ASD children by 12 compared to M\u2010CHAT, with no children with ASD screening negative on the M\u2010CHAT criteria subsequently screening positive utilizing the M\u2010CHAT\u2010R algorithm. A nonparametric McNemar's test determined a statistically significant difference in identifying ASD utilizing the M\u2010CHAT\u2010R algorithm. The present study examined the application of 20\u2010item MCHAT\u2010R scoring criterion to the 23\u2010item MCHAT. We found that this resulted in decreased sensitivity and increased specificity for identifying children with ASD, which is a trade\u2010off that needs further investigation in terms of cost\u2010effectiveness. However, further research is needed to optimize screening for ASD in the early developmental period to increase identification of false negatives.<\/jats:p>","DOI":"10.1002\/aur.2643","type":"journal-article","created":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T07:29:56Z","timestamp":1637998196000},"page":"296-304","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["What are we optimizing for in autism screening? 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