Table 1.

Accuracy and validity metrics of the included digital biomarker apps for autism classification.

App name	Sample size, n	Autism prevalence (%)	Accuracy (%)	Sensitivity (%)	Specificity (%)	PPVa (%)	NPVb (%)	Comparator
Canvas Dx	425	28.7	28c	51.6d	18.5d	20.3c	48.7c	ECDe
Guess What?f	49	57.1	73	76	69c	76.6c	68.3c	Parent-reported diagnosis
START	131	36.6	61.6	Unable to calculate	Unable to calculate	Unable to calculate	Unable to calculate	ECD
SenseToKnow	475	10.3	80.6c	81.6	80.5	32.5c	97.4c	ECD

^aPPV: positive predictive value.

^bNPV: negative predictive value.

^cCalculated using the following formulas: accuracy = (sensitivity) × (prevalence) + (specificity) × (1 – prevalence); PPV = (sensitivity × prevalence) / {(sensitivity × prevalence) + ([1 – specificity] × [1 – prevalence])}; and NPV = (specificity × [1 – prevalence]) / {(specificity × [1 – prevalence]) + ([1 – sensitivity] × prevalence)}.

^dFor 3 classes (autism, uncertain, and nonautism) classification. If participants who received an uncertain or indeterminate class decided by the classifier were removed, for the remaining 31.8% (135/425) of participants who received a determinate output (autism or nonautism), sensitivity and specificity increased to 98.4% and 78.9%, respectively.

^eExpert clinician diagnosis.

^fMetrics from the feasibility study. Ongoing study for the validation of the GuessWhat? app (registered trial NCT04739982 [20])