Abstract

AbstractBackgroundDigital memory tests are proposed for the screening of mild cognitive impairment (MCI) and Alzheimer disease (AD). However, previous studies are seldom measuring the time spent of a participant in a memory test. So, it is unclear whether the time spent in a digital memory test can be a predictive factor for the identification of MCI and AD. The objective of this study is to evaluate the diagnostic performance of the digital recognition test, immediate and delayed free recall test in the identification of MCI and AD.MethodsA digital test platform included a recognition test, an immediate and a delayed free recall test was developed. The score and time spent (from participant start to answer the question to finish answering the question) of each memory test were measured. Participants with MCI and AD were consecutive patients in clinics, the controls were recruited from a community elderly center. Regression derived score was calculated using binary logistic regression. Receiver operating characteristic (ROC) curves were used to examine the ability of the memory tests to identify MCI and AD from controls. The area under the curve (AUC) was calculated.ResultsA total of 46 controls, 37 MCI, and 37 AD participants were recruited. In the digital recognition test, the controls had significantly shorter time spent than the MCI participants (mean difference (MD)=‐12.3 seconds, SD=3.64, p=0.001) and MCI participants had significantly shorter time spent than AD participants (MD=‐15.6, SD=6.1, p=0.01). However, no difference in time spent between 3 groups of participants was found in the immediate and delayed free recall test. In the identification of MCI and AD from control, the AUC of time spent and score in digital recognition test were 0.74 and 0.76, respectively. The AUC of regression derived score with taking time spent and the score was 0.85. The AUCs of immediate and delayed free recall tests were 0.71 and 0.76, respectively.ConclusionsThis study showed that both score and time spent in the digital recognition test are predictive factors for the identification of MCI and AD. A combination of score and time spent can enhance the performance of the digital recognition test.

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