The Arabic Discourse Assessment Tool (ADAT) can diagnose aphasia and fluency status following brain damage.

The Arabic Discourse Assessment Tool (ADAT) is a newly developed, standardised, and norm-referenced tool comprising three discourse tasks, eight high-quality discourse measures, and two transcription-less assessment approaches. ADAT can accurately differentiate discourse responses produced by people with aphasia (PwA) from those of neurotypical adults. In this study, we examined the diagnostic accuracy of ADAT in patients with brain damage. We addressed key methodological limitations in the existing literature by: (a) using ADAT to distinguish brain damaged PwA from those without aphasia; (b) diagnosing fluency status among PwA using ADAT; (c) testing the predictive validity of the tool in out-of-sample data; and (d) assessing whether transcription-less discourse assessment approaches can produce similar diagnostic accuracy to traditional, time-consuming discourse sampling. We examined 100 patients with brain damage using ADAT; 50 of whom were diagnosed with aphasia (28 fluent and 22 non-fluent aphasia). Using random-permutation nested cross-validation and bootstrapping, the study demonstrates that the combination of eight ADAT discourse measures can predict aphasia status in brain damaged patients with 90% accuracy, and the two transcription-less, clinically-friendly discourse assessment approaches can predict aphasia status with 88% accuracy. Furthermore, ADAT's discourse measures can diagnose fluency status in PwA with 81% accuracy, and the two transcription-less approaches can diagnose fluency status with 88% accuracy. The findings provide evidence that ADAT, including its discourse measures and transcription-less approaches, can be used to diagnose aphasia in brain damaged individuals and fluency status in PwA with very high accuracy, thus offering clinical applications for early identification and targeted interventions.