Evidence map›Paper›PMID 33337341›Full record

ArticleJournal of medical Internet research2020

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

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

Erratum issuedOpen access · goldAbstract readValidation Study
In one paragraph

Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 20 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 2 pooled it
3.0field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 1 institution in 2 countries.

Joyce Y C Chan *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-6329-7727
Adrian Wong *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0002-7859-3956
Brian Yiu *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-8586-5967
Hazel Mok *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0002-7161-0768
Patti Lam *Jockey Club Centre for Osteoporosis Care and Control, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-8634-387X
Pauline Kwan *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-9722-9263
Amany Chan *Jockey Club Centre for Osteoporosis Care and Control, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-8955-8817
Vincent C T Mok *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0002-8102-8835
Kelvin K F Tsoi *Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-5580-7686
Timothy C Y Kwok *Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, Hong Kong.ORCID 0000-0001-9253-3549
Chinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA digital cognitive test can be a useful and quick tool for the screening of cognitive impairment. Previous studies have shown that the diagnostic performance of digital cognitive tests is comparable with that of conventional paper-and-pencil tests. However, the use of commercially available digital cognitive tests is not common in Hong Kong, which may be due to the high cost of the tests and the language barrier. Thus, we developed a brief and user-friendly digital cognitive test called the Electronic Cognitive Screen (EC-Screen) for the detection of mild cognitive impairment (MCI) and dementia of older adults.

objectiveThe aim of this study was to evaluate the performance of the EC-Screen for the detection of MCI and dementia in older adults.

methodsThe EC-Screen is a brief digital cognitive test that has been adapted from the Rapid Cognitive Screen test. The EC-Screen uses a cloud-based platform and runs on a tablet. Participants with MCI, dementia, and cognitively healthy controls were recruited from research clinics and the community. The outcomes were the performance of the EC-Screen in distinguishing participants with MCI and dementia from controls, and in distinguishing participants with dementia from those with MCI and controls. The cohort was randomly split into derivation and validation cohorts based on the participants' disease group. In the derivation cohort, the regression-derived score of the EC-Screen was calculated using binomial logistic regression. Two predictive models were produced. The first model was used to distinguish participants with MCI and dementia from controls, and the second model was used to distinguish participants with dementia from those with MCI and controls. Receiver operating characteristic curves were constructed and the areas under the curves (AUCs) were calculated. The performances of the two predictive models were tested using the validation cohorts. The relationship between the EC-Screen and paper-and-pencil Montreal Cognitive Assessment-Hong Kong version (HK-MoCA) was evaluated by the Pearson correlation coefficient.

resultsA total of 126 controls, 54 participants with MCI, and 63 participants with dementia were included in the study. In differentiating participants with MCI and dementia from controls, the AUC of the EC-Screen in the derivation and validation cohorts was 0.87 and 0.84, respectively. The optimal sensitivity and specificity in the derivation cohorts were 0.81 and 0.80, respectively. In differentiating participants with dementia from those with MCI and controls, the AUC of the derivation and validation cohorts was 0.90 and 0.88, respectively. The optimal sensitivity and specificity in the derivation cohort were 0.83 and 0.83, respectively. There was a significant correlation between the EC-Screen and HK-MoCA (r=-0.67, P<.001).

conclusionsThe EC-Screen is suggested to be a promising tool for the detection of MCI and dementia. This test can be self-administered or assisted by a nonprofessional staff or family member. Therefore, the EC-Screen can be a useful tool for case finding in primary health care and community settings.

Indexed as

AgedCase-Control StudiesCognitive DysfunctionDementiaFemaleHumansMaleMass ScreeningNeuropsychological TestsPublic HealthTechnologycognitive screeningdementiaEC-Screenmild cognitive impairment

Identifiers

PMID33337341
PMCPMC7775823
OpenAlexW3112538355

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.