Separate scoring algorithms for specific identification priorities optimize the screening properties of the Screening Tool for Autism in Toddlers (STAT).
Shana M Attar, Lisa V Ibanez, Wendy L Stone
PMID 36073529WHAT IT FOUND
Adding examiner ratings of social engagement and atypical behavior to the STAT screening tool increased sensitivity for identifying autism risk in two-year-olds.
This approach helps catch more at-risk children but lowers specificity, meaning more false positives.
Key findings
01The expanded STAT-E with original scoring had lower sensitivity (0.67) and specificity (0.66) in this sample compared to previous validation studies.
02Adding social engagement and atypical behavior ratings significantly increased sensitivity to 0.77, though specificity dropped to 0.62.
03Novice assessors trained via a web module achieved reasonable screening properties, suggesting broader implementation is feasible.
STILL TO COME
How it was doneWhat they foundWhat it means for SLPs
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What it does not show
The sample was predominantly White and male, limiting generalizability across race, ethnicity, and sex. Reliability checks were not performed on the new social engagement and atypical behavior ratings. The study combined novice assessors with experimental ratings, making it unclear if the results apply to experienced clinicians. The atypical behavior rating was rarely endorsed, which may be because these behaviors emerge later in childhood.
Declared interests
WS is an author of the STAT and receives an author's share of royalties from Vanderbilt University for sales.
The easy way to misread this
Do not assume the new scoring algorithm is superior for all contexts. It increases sensitivity but decreases specificity, meaning it will identify more children as at-risk who do not have autism. This trade-off may overwhelm referral systems if not managed carefully.