Literature DB >> 29921507

Comparison of Computerized and Paper-and-Pencil Memory Tests in Detection of Mild Cognitive Impairment and Dementia: A Systematic Review and Meta-analysis of Diagnostic Studies.

Joyce Y C Chan1, Joey S W Kwong2, Adrian Wong1, Timothy C Y Kwok1, Kelvin K F Tsoi3.   

Abstract

OBJECTIVES: To compare the diagnostic performance of computerized and paper-and-pencil memory tests in detection of mild cognitive impairment (MCI) and dementia.
DESIGN: Diagnostic studies comparing computerized or paper-and-pencil memory tests with the standard diagnostic criterion for MCI or dementia were identified from OVID databases. The primary outcome was the diagnostic performance of memory tests for detection of MCI, and detection of dementia was the secondary outcome. Risk of bias and reporting quality in included studies was assessed. SETTING AND PARTICIPANTS: Participants with MCI and dementia in any kind of setting. MEASURES: Bivariate random-effects models were used to combine the diagnostic performance of memory tests and presented with a summary receiver-operating characteristic curve.
RESULTS: A total of 58 studies with 18,450 participants with mean age ranging from 55 to 84 years were included. For the verbal memory tests on patients with MCI, computerized tests showed diagnostic accuracy of 0.89 sensitivity (95% confidence interval [CI] 0.69-0.97) and 0.82 specificity (95% CI 0.70-0.90), whereas paper-and-pencil tests showed diagnostic accuracy of 0.86 sensitivity (95% CI 0.82-0.90) and 0.82 specificity (95% CI 0.76-0.86). For the visual memory tests on MCI patients, computerized tests showed diagnostic accuracy of 0.79 sensitivity (95% CI 0.71-0.84) and 0.80 specificity (95% CI 0.71-0.86), whereas paper-and-pencil tests showed diagnostic accuracy of 0.80 sensitivity (95% CI 0.67-0.89) and 0.68 specificity (95% CI 0.51-0.81). The findings were also comparable to those with dementia. CONCLUSIONS/IMPLICATIONS: Both verbal and visual computerized memory tests showed comparable diagnostic performance to the paper-and-pencil tests. Computerized cognitive tests show a great potential to use as an alternative to paper-and-pencil tests. When the records can be digitalized, long-term monitoring of cognitive function will be feasible for better management of dementia.
Copyright © 2018 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Computerized test; dementia; mild cognitive impairment; verbal memory; visual memory

Mesh:

Year:  2018        PMID: 29921507     DOI: 10.1016/j.jamda.2018.05.010

Source DB:  PubMed          Journal:  J Am Med Dir Assoc        ISSN: 1525-8610            Impact factor:   4.669


  4 in total

1.  Electronic Cognitive Screen Technology for Screening Older Adults With Dementia and Mild Cognitive Impairment in a Community Setting: Development and Validation Study.

Authors:  Joyce Y C Chan; Adrian Wong; Brian Yiu; Hazel Mok; Patti Lam; Pauline Kwan; Amany Chan; Vincent C T Mok; Kelvin K F Tsoi; Timothy C Y Kwok
Journal:  J Med Internet Res       Date:  2020-12-18       Impact factor: 5.428

2.  A voice recognition-based digital cognitive screener for dementia detection in the community: Development and validation study.

Authors:  Xuhao Zhao; Ruofei Hu; Haoxuan Wen; Guohai Xu; Ting Pang; Xindi He; Yaping Zhang; Ji Zhang; Christopher Chen; Xifeng Wu; Xin Xu
Journal:  Front Psychiatry       Date:  2022-07-22       Impact factor: 5.435

Review 3.  Evaluation of Digital Drawing Tests and Paper-and-Pencil Drawing Tests for the Screening of Mild Cognitive Impairment and Dementia: A Systematic Review and Meta-analysis of Diagnostic Studies.

Authors:  Joyce Y C Chan; Baker K K Bat; Adrian Wong; Tak Kit Chan; Zhaohua Huo; Benjamin H K Yip; Timothy C Y Kowk; Kelvin K F Tsoi
Journal:  Neuropsychol Rev       Date:  2021-10-16       Impact factor: 6.940

4.  Supervised Digital Neuropsychological Tests for Cognitive Decline in Older Adults: Usability and Clinical Validity Study.

Authors:  Francesca Lunardini; Matteo Luperto; Marta Romeo; Nicola Basilico; Katia Daniele; Domenico Azzolino; Sarah Damanti; Carlo Abbate; Daniela Mari; Matteo Cesari; Nunzio Alberto Borghese; Simona Ferrante
Journal:  JMIR Mhealth Uhealth       Date:  2020-09-21       Impact factor: 4.773

  4 in total

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