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Examination of the accuracy of Cogniciti’s self‐administered, online, Brain Health Assessment in detecting amnestic mild cognitive impairment
Author(s) -
Paterson Theone S.E.,
Sivajohan Brintha,
Gardner Sandra,
Binns Malcolm,
Stokes Kathryn A.,
Freedman Morris,
Levine Brian,
Troyer Angela
Publication year - 2021
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.057507
Subject(s) - logistic regression , psychology , population , gold standard (test) , neuropsychology , neuropsychological assessment , cognition , test (biology) , clinical psychology , medicine , psychiatry , paleontology , environmental health , biology
Background Our need for easily administered online assessments sensitive to mild cognitive difficulties is increasing as our population ages. Our team has recently presented data indicating the accuracy of an online, publicly available, self‐administered screening measure, Cogniciti’s Brain Health Assessment (BHA), in the detection of amnestic mild cognitive impairment (aMCI) in a sample of community dwelling older adults. This current work extends those findings by further examining diagnostic accuracy of this measure. Method Using a cross‐sectional design, community‐dwelling older adults aged 60‐89 completed a gold standard neuropsychological assessment to determine a diagnosis of normal cognition (NC) or aMCI (by consensus of 3 staff neuropsychologists). Each participant also completed the BHA. Penalized logistic regression (PLR) analyses were used to examine which specific BHA tasks and measured demographic variables contributed to this test’s predictive utility in detecting aMCI. Diagnostic accuracy of the PLR model was compared with a logistic regression (LR) model examining BHA total score accuracy. Result 91 participants met inclusion criteria (51 aMCI, 40 NC). PLR modelling for the BHA indicated that of the tasks and variables measured by the BHA, the Face‐Name Association and Spatial Working Memory tasks predicted aMCI, with age also accounted for in the model (ROC‐AUC = 0.76; 95%CI: 0.66, 0.86). Based on this model, optimal performance cut‐points were determined, which resulted in 21% of the sample being classified as aMCI (positive), 23% as negative, and 56% as inconclusive. Projected general population classification rates are also presented to provide an estimate of how the BHA may perform in the broader population. Conclusion Results support that validity of the BHA as a screening measure for aMCI, and provide indication of the tasks within this measure that contribute to its utility in screening for this specific type of cognitive decline. Given the BHA is an online, self‐administered task, this measure has the potential to not only decrease unnecessary referrals for comprehensive assessment to determine presence of aMCI, but also to save practitioners time over commonly used paper and pencil screeners.