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Aging, Neuropsychology, and Cognition
A Journal on Normal and Dysfunctional Development
Volume 28, 2021 - Issue 6
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Original Article

Delayed matching to sample task 48: assessment of malingering with simulating design

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Pages 797-811 | Received 01 Jun 2020, Accepted 17 Sep 2020, Published online: 01 Oct 2020
 

ABSTRACT

The results of neuropsychological tests may be distorted by patients who exaggerate cognitive deficits. Eighty-three patients with cognitive deficit [Amnestic Mild Cognitive Impairment (aMCI), n = 53; Alzheimer’s disease (AD) dementia, n = 30], 44 healthy older adults (HA), and 30 simulators of AD (s-AD) underwent comprehensive neuropsychological assessment. Receiver Operating Characteristic (ROC) analysis revealed high specificity but low sensitivity of the Delayed Matching to Sample Task (DMS48) in differentiating s-AD from AD dementia (87 and 53%, respectively) and from aMCI (96 and 57%). The sensitivity was considerably increased by using the DMS48/Rey Auditory Verbal Learning Test (RAVLT) ratio (specificity and sensitivity 93% and 93% for AD dementia and 96% and 80% for aMCI). The DMS48 differentiates s-AD from both aMCI and AD dementia with high specificity but low sensitivity. Its predictive value greatly increased when evaluated together with the RAVLT.

Acknowledgments

This study was supported by Progress Q27/LF1 and by the project no. LQ1605 from the National Program of Sustainability II (MEYS CR), the Institutional Support of Excellence 2. LF UK grant no. 699012, by the Ministry of Health of the Czech Republic grant no. 19-04-00560, and by the Charles University project GA UK No. 692818.

Disclosure statement

Dr Nikolai, Ms Cechova, Ms Bukacova, Ms Fendrych Mazancova, Dr Markova, Dr Bezdicek and Dr Vyhnalek report no disclosures.

Additional information

Funding

This work was supported by the Ministry of Health of the Czech Republic [19-04-00560]; Charles University [Progress Q27/LF1]; National Program of Sustainability II, Czech republic [LQ1605]; Institutional Support of Excellence 2. LF UK [grant no. 699012].

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