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Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
Videoconference-integrated, computer-assisted cognitive testing improves the remote assessment of processing speed
Jodie E Chapman1, Christoph Helmstaedter2, David F Abbott1,3,4
1https://ror.org/03a2tac74Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia.
Objective:
Remote videoconference neuropsychological assessments offer opportunities that remain under-exploited. We aimed to evaluate teleneuropsychology (TeleNP)-suitable oral and digital versions of the Symbol Digit Modalities Task (SDMT) and Trail Making Test (TMT) - widely used measures of speed and attention - by comparing them to their written counterparts.
Methods:
Three-hundred and twenty-one Australian Epilepsy Project (AEP) adult participants with seizure disorders completed the written SDMT and TMT in-person. One-hundred and forty-four of these participants also completed the oral SDMT and TMT during a remote videoconference-based assessment while 177 completed a novel, examiner-administered digital SDMT analogous measure named Symbol Decoding and a novel digital TMT remotely via custom videoconference-based software.
Results:
Oral SDMT and digital Symbol Decoding strongly correlated with in-person written SDMT (r (133) = .77, p < .001 and r (126) = .76, p < .001, respectively). Oral TMT-B was only moderately associated (r (126) = .52, p < .001) with written TMT-B and, less strongly related to measures of sustained attention and spatial working memory than its written counterpart. Digital TMT better reproduced the written test's properties with improved association with written TMT-B (r (154) = .71, p < .001).
Conclusions:
Oral SDMT and digital Symbol Decoding are strongly correlated with in-person written SDMT. The digital TMT better captures the cognitive demands and performance characteristics of the in-person written form than does oral TMT. Videoconference-integrated digital tasks offer increased standardization and automation in administration and scoring and the potential for rich metadata, making them an attractive area for further development.
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