(2022) 22:457
Kouzuki et al. BMC Neurology
https://doi.org/10.1186/s12883-022-02997-4

Open Access

RESEARCH

Validation of a novel computerized cognitive
function test for the rapid detection of mild
cognitive impairment
Minoru Kouzuki1*, Madoka Miyamoto2, Nobuto Tanaka2 and Katsuya Urakami2

Abstract
Background: In the present study, we examined the distinguishing ability of a mild cognitive impairment (MCI)
assessment tool for rapid screening using a computer (MARC) for Alzheimer’s disease dementia (ADD), MCI, and nondemented controls (NDC) with no cognitive impairment, as well as its validity and reliability, as part of a preliminary
trial for the development of the tool.
Methods: A total of 64 participants (23 in the ADD group, 17 in the MCI group, and 24 in the NDC group) wereanalyzed. The participants were administered MARC and a pre-existing computerized Alzheimer’s dementia screening test (MSP), and 31 participants (14 in the MCI group, 17 in the NDC group) were readministered MARC within
4 months from the first test.
Results: The median (interquartile range) test time for MARC was 401 (350–453) s. Total MARC scores were significantly worse in the MCI and ADD groups than in the NDC group (p < 0.05 and p < 0.01, respectively). In the receiver
operating characteristic (ROC) analysis, the area under the ROC curve (AUC) when comparing the NDC and MCI
groups was 0.866 (95% CI, 0.759–0.974), when comparing the NDC and AD groups was 0.989 (95% CI, 0.970–1.000),
and when comparing the MCI and AD groups was 0.889 (95% CI, 0.790–0.988). Furthermore, there was a significant
correlation with the results of the existing test, MSP (r = 0.839, p < 0.001). In addition, the intraclass correlation coefficient (ICC) (1,1) when the first and second MARC scores were compared was 0.740 (95% CI, 0.529–0.865; p < 0.001).
Conclusions: MARC is considered capable of distinguishing MCI with high accuracy. The tool has good validity andreliability, and it can be administered in a short period of time without the need for a specialist.
Keywords: Mild cognitive impairment, Alzheimer’s disease dementia, Computerized cognitive assessment battery,
Neuropsychological test
Background
Dementia is thought to develop from a normal state ofcognitive function, by going through the stage of mild
cognitive impairment (MCI) [1]. There is growing interest in early detection and intervention at the MCI stage.
*Correspondence: kouzuki@tottori-u.ac.jp
1
Department of Biological Regulation, School of Health Science, Facultyof Medicine, Tottori University, 86 Nishi‑cho, Yonago 683‑8503, Japan
Full list of author information is available at the end of the article

While previous population-based studies have shownthat the prevalence of MCI in people aged 65 years andolder ranges from a few percent at the lower end to 42%
at the higher end, most of the results fall between 5 and
30% [2, 3]. In Japan, an epidemiological survey conductedby the Ministry of Health, Labour and Welfare of Japan
reported in March 2013 that the estimated prevalenceof MCI was 13% among individuals aged 65 years andover [4]. In addition, the results of a population based
prospective cohort study of dementia conducted with© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​
mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Kouzuki et al. BMC Neurology(2022) 22:457

approximately 10,000 individuals aged 65 years and aboveat eight different locations in Japan showed that the prevalence of MCI was 17.0% [5]. Since there are potentiallya large number of people with MCI, it is important toestablish a system that enables people to have check-ups
in their local area and undergo examinations at medical institutions nearby [6, 7] so that they may be evaluated regularly. While the annual conversion rate from
MCI to dementia is thought to be approximately 5–15%
based on the observation of two review articles [3, 8],
MCI does not always exacerbate progressively, and cognitive function may return to normal levels after MCI. It
has been shown that, on average, approximately 20% ofparticipants with MCI improve over time [3]. It has beenreported that certain active lifestyles may be a contributing factor in the return of cognitive function to normal levels after MCI [9], and the likelihood of cognitive
function returning to normal is higher in elderly with
MCI who maintain or start multidomain lifestyle activities than those who discontinue or do not engage in suchactivities [10]. Cognitive function improved in elderly
individuals with suspected mild cognitive decline byimplementing a program incorporating exercise, cognitive training, and education about dementia and lifestyle
habits [11]. These findings suggest that early detection ofdementia at the MCI stage and implementation of interventions may reduce the incidence of dementia.
The Montreal Cognitive Assessment (MoCA) was
developed as a neuropsychological test for the detectionof MCI [12, 13]. It is covered by health insurance in Japanand used as a part of routine clinical practice. MoCA isknown for its high sensitivity (90%) and specificity (87%)
for detecting MCI in individuals with normal cognitive
function, when the cut-off value is set at 25/26 points[12]. The Japanese version of MoCA has also been shown
to produce similar results with a sensitivity of 93% andspecificity of 89% [13]. However, normative studies using
population-based samples showed high false-positive
rates by classification using the cut-off value of 26 [14].
Research groups in several countries have conductednormative studies on MoCA, and it has been proposedthat the cut-off value should take demographic factors into consideration [14]. The usefulness of MoCA issuggested by the various verifications described above.
However, there are difficulties involved in implementing
MoCA in local-area check-ups, which requires evaluation of a large number of cases; as MoCA is an individualinterview-based test, it is preferable to be administeredby a professional with specialized knowledge. On theother hand, while a variety of computerized screening
tools have been developed for the detection of MCI, thetest time of computerized tests, whose reliability andvalidity measures were reported in a review by Tsoy et al.

Page 2 of 10[15], was 10 minutes or longer, although they showed
high sensitivity and specificity for detecting MCI. In
addition, many of the computerized tests shown in otherreviews also take more than 10 minutes to complete [16,17]. Subjects may experience psychological stress and it
may be too long to be used for screening at the local-areacheck-ups. Several computer-based tests that can be performed in a short period of time have also been reported
in Japan and other countries [18–21]. Although the accuracy for identifying dementia is sufficient, the accuracy
for identifying MCI has not been verified nor is higher
than the detection ability for dementia, so there is room
for improvement. We thought that this problem could be
solved by devising a new computer-based test by taking
advantage of the information about tests that have beendeveloped so far.
Therefore, the purpose of the present study was to prepare questions based on previously developed tests fordementia and MCI and perform a preliminary trial forthe development of an MCI assessment tool for rapid
screening using a computer (MARC), which could be
used in local-area check-ups without the need for a specialized examiner and administered in a short periodof time with high accuracy. MARC was performed for
Alzheimer’s disease dementia (ADD), MCI, and nondemented controls (NDC) with no cognitive impairment
to examine its distinguishing ability, to evaluate its validity and reliability, and for its verification.

Methods
Patients

A total of 66 outpatients (25 with ADD, 17 MCI, and 24
NDC) aged 65 years or above that visited Shinsei Hospital(Kurayoshi, Japan) between July 2021 and December 2021
were included. All participants were recruited from thehospital’s forgetfulness outpatient department. All participants were diagnosed by experienced neurologists basedon medical history, the results of general physical andneurological examinations, laboratory tests, brain imaging tests such as brain computed tomography, magnetic
resonance imaging, and/or single photon emission computed tomography, and neuropsychological tests suchas the Geriatric Depression Scale 15-item version, theMini-Mental State Examination, the Alzheimer’s Disease
Assessment Scale-Cognitive Subscale, and/or the Touch
Panel-type Dementia Assessment Scale [22]. Participants
meeting the diagnostic criteria of the National Instituteon Aging-Alzheimer’s Association Work groups (NIAAA) [23] were diagnosed with ADD. However, patientswith ADD undergoing treatment with anti-dementia
drugs (donepezil, rivastigmine, galantamine, or memantine) were included in the study only if they had reachedthe maintenance dose for at least 38 weeks. Patients

Kouzuki et al. BMC Neurology(2022) 22:457

with MCI were those who met the diagnostic criteriaof Petersen et al. [24] and whose global score based onclinical dementia rating (CDR) [25] was 0.5. Those who
did not meet the diagnostic criteria of NIA-AA or that ofPetersen et al. and were diagnosed as having no cognitive
impairment were assigned to the NDC group. The exclusion criterion was visual impairment that would present
difficulty when performing MARC.
The present study was approved by the ethics committee of Tottori University Faculty of Medicine (No.
20A228). Prior to conducting the research, the participants and those concerned (consent was also obtained
from those concerned only if the participants were suffering from ADD or MCI) were informed about the aimsof the research and their consent was obtained in writing.
Procedures

Information including age, sex, years of education, andglobal CDR score [25] was obtained in interviews or bysurveying medical chart data. Following this, the participants of the study were given MARC, as shown below,
and an existing computerized test battery for Alzheimer’s
disease screening (developed by Nihon Kohden Corporation with the product name “monowasure soudan proguramu (MSP)” (which means forgetfulness consultation

Page 3 of 10

program)) [18] on the same day. Regarding MARC, toconfirm reproducibility, a second trial was performed
with participants who visited the hospital less than
4 months after the first MARC and consented to a second
test.
Administration of MARC​

We examined the contents of MSP [18], MoCA [12, 13],
touch panel-type dementia assessment scale [22], andvisuo-spatial memory test [26], and literature on aphasia testing [27] to prepare questions for MARC. MARC
comprises nine tasks (immediate recognition task, timeorientation task, digit span forward and backward task,
visuo-spatial perception task, visual retention task, digit
and letter order task, visuo-spatial memory task, object
recognition task, and delayed recognition task) witha maximum score of 20 (Table 1). The questions wereprepared using Microsoft PowerPoint (PPT) on a computer (Additional file 1: Fig. S1), and the question sentences were recorded. The actual steps of MARC wereas follows. The participants were asked to sit in front ofa monitor and wear headphones. Next, the questions
and choices prepared using PPT were displayed on themonitor, and the pre-recorded question sentences wereread out loud to the participants. Because we could

Table 1 Detailed explanation of the computerized cognitive assessment battery
Tasks

Contents

Maximum score Numberof slides

Immediate recognition task

The participant memorizes four words (pine, cow, train, and desk), which aredisplayed in order at 4 s intervals, and selects the four words they memorizedfrom 12 words.

No points

7

Time orientation task

The participant is asked what day, date, month, and year it is, and selects fromthe choices.

4

4

Digit span forward and backward task Counting forward task: five numbers (9, 5, 7, 8, and 3) are read out loud, and theparticipant selects the numbers in order from a choice of 1 to 9.
Counting backward task: three numbers (9, 4, and 1) are read out loud, and theparticipant selects in reverse order from a choice of 1 to 9.

2

4

Visuo-spatial perception task

A cube is displayed at the top of the screen, and the participant selects, fromfive choices shown at the bottom of the screen, the choice that matches the
cube as seen from a different angle. A question about a triangular prism is thenpresented in a similar format.

22Visual retention task

A figure consisting of orange, yellow, and blue rectangles overlapping with awhite square is displayed on the screen for 5 s, during which the participant
memorizes the figure. The participant has to choose the figure they memorizedfrom three choices.

1

3

Digit and letter order task

1

2

Visuo-spatial memory task

The participant selects randomly placed numbers (1, 2, 3) and hiragana (a, i, u) in
the following order: “1 → a → 2 → i → 3 → u”.

The participant memorizes a circle with randomly placed numbers (1, 2) andhiragana (a, i), which is displayed for 8 s. After that, the participant selects in theorder of “1 → a → 2 → i” from the screen where only a circle is displayed with thenumbers and hiragana removed.

1

3

Object recognition task

A picture of a shovel is displayed, and the participant selects its name from six
choices.

1

1

Delayed recognition task

The participant selects from 12 choices the four words that they memorized in
the immediate recognition task.

81

Kouzuki et al. BMC Neurology(2022) 22:457

not develop a software version of MARC, there was no
response when the screen was touched, MARC was
administered in a semi-automated manner where theparticipants were asked to select a choice from the screenby pointing at it, and the examiner recorded their choice
on a scoring form. After the participant responded toa question by pointing at a choice, the examiner would
immediately press the “next page” button. All the questions were presented to the participants in this manner.
The examiner measured the response time using a stopwatch. The test was performed by researchers (MK, MM,
or NT) who are also biomedical laboratory scientists. The
examiners were not necessarily the same for the first andsecond examinations. However, in response to the questions from the examinees, the examiners did not explain
with any additional information other than what was
shown on the computer screen and the explanation of thevoice from the headphones.
Implementation of the MSP

MSP is a computerized test battery for ADD screening that was created based on the revised Hasegawa’s
Dementia Scale [28]. In the test, the subject performs on
their own following the instructions given by the computer (MSP-1100; Nihon Kohden Corporation, Tokyo,
Japan) [18]. It comprises four evaluation items: threeword memory test, temporal orientation test, threedimensional visual-spatial perception test, and delayedrecall test. The maximum score is 15 points for answering all questions correctly and the minimum score is
0 points for answering all questions incorrectly. It wasreported that the sensitivity and specificity for distinguishing between healthy control and ADD were 96 and86%, respectively, when the cut-off value was set to 12/13
points [18].
Statistical analysis

The sample size was based on a previous study that verified the Japanese version of MoCA [13], and was originally defined as 150 patients (50 each in ADD, MCI, and
NDC groups), which is slightly larger than that in theprevious study. However, because of difficulties in the
recruitment process, the sample size was reduced to 66.
MARC’s questions were uniquely devised, and we wereunable to infer the effect size in the calculation of thesample size due to the lack of similar previous research.
Therefore, we did not perform a power analysis in thisstudy.
SPSS version 27 was used for statistical analysis. Alldata were tested for normality using the Shapiro–Wilk
test. The Fisher’s exact test, one-way analysis of variance(ANOVA), or the Kruskal–Wallis test were used to compare demographic characteristics. The Tukey method orPage 4 of 10

Bonferroni method was used for subsequent multiple
comparison tests. ANOVA or the Kruskal-Wallis wasused to evaluate the results of MARC for the ADD, MCI
and NDC groups, and the Tukey method or Bonferroni
method was used for subsequent multiple comparison
tests. Moreover, the receiver operating characteristic(ROC) curve was plotted and the area under the ROC
curve (AUC) and 95% confidence interval (CI) were calculated. In addition, cut-off values, sensitivity, specificity,
positive predictive value (PPV), and negative predictive
value (NPV) were calculated. Regarding the validity of
MARC, the association between MARC and MSP was
evaluated by calculating Spearman’s rank correlation
coefficient. The internal consistency of MARC was evaluated by calculating the coefficient of Cronbach’s alpha.
The reproducibility of MARC was evaluated by calculating the intraclass correlation coefficient (ICC (1, 1)) and
95% CI using the results of those who were able to perform the MARC twice. All statistics were two-tailed andp < 0.05 was considered significant.

Results
Participant data are shown in Table 2. In the present
study, two patients with ADD who were unable to complete MARC were excluded from the 66 participants
enrolled, and 64 participants were analyzed (23 participants in the ADD group, 17 participants in the MCI
group, and 24 participants in the NDC group). Age wassignificantly higher, and years of education was significantly lower in the ADD group than in the NDC group(both p < 0.01). With regard to CDR, all participants in
the NDC group had no dementia with a CDR of 0, allparticipants in the MCI group had questionable dementia with a CDR of 0.5, and in the ADD group, five participants had mild dementia with a CDR of 1 and 18
participants had moderate dementia with a CDR of 2.
Figure 1A shows a comparison of MARC scoresamong the three groups. The MCI group and the ADD
group scored significantly worse than the NDC group(p < 0.05 and p < 0.01, respectively), and the ADD
group scored significantly worse than the MCI group(p < 0.01). The median time (interquartile range) thatthe participants required to complete the test was 401(350–453) s. The breakdown by group was 371 (304–405) s for the NDC group, 403 (355–479) s for the MCI
group, and 443 (385–511) s for the ADD group. The
examination time was significantly longer (p < 0.01) in
the ADD group than the NDC group. In an ROC analysis conducted to examine the extent to which MARC
distinguished the NDC group from the MCI or ADD
group, the AUC in the comparison between the NDC
and MCI groups was 0.866 (95% CI, 0.759–0.974), thatin the comparison between the NDC and ADD groupsKouzuki et al. BMC Neurology(2022) 22:457

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Table 2 Characteristics of patients
NDC

MCI

ADD

(n = 24)(n = 17)(n = 23)

P-valueSex (M:F)

7:17

9:8

8:15

0.302

Age (years)

79.5 (75.8–82.0)

82.0 (79.0–85.0)

85.0 (80.0–88.5)< 0.001 a

Education (years)

12.0 (11.5–13.3)

12.0 (9.0–12.0)

9.0 (9.0–12.0)

0.008 aCDR staging (0/0.5/1/2)

24/0/0/0

0/17/0/0

0/0/5/18–

Data are presented as numbers or medians (interquartile range)
Sex was analyzed using the Fisher’s exact test. Age was compared using a one-way analysis of variance followed by the Tukey test. Education was compared using the
Kruskal–Wallis test followed by the Bonferroni correction
CDR clinical dementia rating, NDC non-demented controls, ADD Alzheimer’s disease dementia, MCI mild cognitive impairmentaSignificant difference between ADD and NDC (p < 0.01)

Fig. 1 Diagnostic performance of the MARC. A The score of MARC in patients with ADD, MCI, and NDC. The MCI and ADD groups scoredsignificantly worse than the NDC group (p < 0.05 and p < 0.01, respectively), and the ADD group scored significantly worse than the MCI group(p < 0.01). B ROC analysis in patients with ADD, MCI, and NDC. The AUC was 0.866 for NDC versus the MCI group, 0.989 for NDC versus the ADD
group, and 0.889 for MCI versus the ADD group. The data was compared using the Kruskal–Wallis test, followed by the Bonferroni correction. *p < 0.05, ** p < 0.01. NDC, non-demented controls; ADD, Alzheimer’s disease dementia; MCI, mild cognitive impairment; MARC, mild cognitive
impairment assessment tool for rapid screening using a computer; ROC, receiver operating characteristic; AUC, area under the receiver operating
characteristic curve

was 0.989 (95% CI, 0.970–1.000), and in the comparison between the MCI and ADD groups was 0.889 (95%CI, 0.790–0.988) (Fig. 1B). Table 3 shows the sensitivity, specificity, PPV, and NPV for each cut-off value.
The optimal cut-off value as suggested by the Youden
index was 11/12 points for distinguishing both the MCI
group from the NDC group and the ADD group fromthe NDC group. Further, the participants were stratified by age into groups of 65–74 years, 75–84 years, and85 years or above (Additional file 1: Table S1), in orderconsider the effects of age. The analysis results areshown in Additional file 1: Fig. S2. Because the number of participants between the ages of 65 and 74 years
and those aged 85 years or above was small, we did notconduct a comparison of the three groups by statistical analysis. However, as with the examination of allparticipants, examination of the participants between
the ages of 75–84 showed that the MCI and ADD
groups scored significantly worse than the NDC group(p < 0.01 and p < 0.01, respectively), while the ADD
group scored significantly worse than the MCI group(p < 0.01). In addition, the comparison results among
the three groups of the MARC subtest are shown in
Additional file 1: Table S2. Items in which the MCI
group scored significantly lower compared to the NDCgroup were time orientation task, visuo-spatial memory task, delayed recognition task (all p < 0.05), and
the ADD group scored lower than the NDC group inKouzuki et al. BMC Neurology(2022) 22:457

Page 6 of 10

Table 3 Results of sensitivity, specificity, PPV, and NPV in distinguishing MCI and ADD from NDS
Cut-off value

NDC vs MCI
Sen

NDC vs ADD
Spe

PPV

NPV

Sen

Spe

PPV

NPV

7/8

23.5

100

100

64.9

78.3

100

100

82.8

8/9

29.4

95.8

83.3

65.7

91.3

95.8

95.5

92.0

9 / 10

41.2

91.7

77.8

68.8

95.7

91.7

91.7

95.7

10 / 11

64.7

87.5

78.6

77.8

95.7

87.5

88.0

95.5

11 / 12

70.6

87.5

80.0

80.8

100

87.5

88.5

100

12 / 13

76.5

79.2

72.2

82.6

100

79.2

82.1

100

13 / 14

76.5

75.0

68.4

81.8

100

75.0

79.3

100

14 / 15

82.4

66.7

63.6

84.2

100

66.7

74.2

100

15 / 16

100

58.3

63.0

100

100

58.3

69.7

100

Data are presented as percentages (%)
NDC non-demented controls, ADD Alzheimer’s disease dementia, MCI mild cognitive impairment, Sen sensitivity, Spe specificity, PPV positive predictive value, NPV
negative predictive value

the time orientation task, digit span forward and backward task, visuo-spatial perception task, digit and letterorder task, and delayed recognition task (all p < 0.05).
We conducted a correlation analysis with an existing
test, MSP, to examine the validity, and a significant correlation was observed (r = 0.839, p < 0.001) (Fig. 2A).
The Cronbach’s alpha coefficient calculated to examineinternal consistency was 0.618. MARC was performed
twice with 31 participants (14 in the MCI group and 17
in the NDC group) to study the reproducibility (mediantime elapsed before re-examination (interquartile range)
was 77 (77–77) days). When the first and second MARCscores were compared, the ICC (1,1) was 0.740 (95% CI,
0.529–0.865; p < 0.001) (Fig. 2B).

Discussion
MARC was shown to be a valid evaluation method forcognitive function as it demonstrated a correlation withan existing test, MSP. The reliability was also substantial with an ICC of 0.740 for the first and second tests.
Internal consistency was somewhat low with a Cronbach’s alpha coefficient of 0.618, but this is thought to bebecause various cognitive functions including memory,
visuospatial cognition, attention, and executive function

Fig. 2 Assessing the validity and reliability of MARC. A Scatter plot for the scores in MARC and MSP, an existing computerized cognitive test battery.
There was a significant correlation between MARC and MSP (r = 0.839, p < 0.001). (B) Scatter plot of the first and second MARC scores with a median77-day interval. The ICC between the first and second test was 0.740 (p < 0.001). A circle indicates 1 person, square indicates 2 people, and triangle
refers to 4 people. Correlation analyses were conducted using Spearman’s correlation coefficient. To assess test–retest reliability, ICC were calculated
between scores at the first and second tests. MARC, mild cognitive impairment assessment tool for rapid screening using a computer; ICC, intraclasscorrelation coefficient; MSP, a computerized test battery for Alzheimer’s disease screening (produced by Nihon Kohden Corporation, named“monowasure soudan proguramu” (forgetfulness consultation program))Kouzuki et al. BMC Neurology(2022) 22:457

were measured. Although MARC could be performedin most of the subjects, two patients with ADD wereunable to complete MARC. This suggests that this test
may not be possible for people with advanced cognitive impairment to complete. Additionally, it has beenshown that the rate of internet usage decreases with age[29], and there is a possibility that many elderly people
are unfamiliar with computers. Other cognitive assessments using mobile devices have also shown that there
were cases where the test could not be completed inolder adult population [30]. Careful instructions on how
to operate the machine are necessary when conducting
computerized test.
When the MARC cut-off value was set at 11/12,
MARC was able to accurately distinguish between the
NDC and ADD groups with a sensitivity and specificity of 100 and 87.5%, respectively. However, it should be
noted that approximately 78% of the participants in the
ADD group had a CDR of 2, indicating moderate ADD. If
most of the participants in the ADD group had a CDR of
1, the distinguishing ability of the MARC between NCD
and ADD as well as between ADD and MCI is probably
lower. Therefore, care should be taken when analyzing
the results. On the other hand, the sensitivity and thespecificity were 70.6 and 87.5%, respectively, when the
cut-off value for distinguishing the MCI group from the
NDC group was set at 11/12. The sensitivity was somewhat low because a few patients in the MCI group hadhigh scores. The present study provides the results foreach cut-off value (Table 3). We recommend the selection of a cut-off value with high sensitivity according topurpose when using MARC as a screening test for cognitive function impairment in local area check-ups. In
addition, the MARC total scores between the MCI and
ADD groups were significantly different. However, many
patients from both groups scored between 4 and 11
points. Since MARC is a highly difficult test created forthe purpose of detecting MCI, low scores of 4–11 points
were seen in the MCI group. The overall median test
time was 401 s, with the ADD group requiring the longest test time. However, most of the participants finishedthe test within 10 min. Several computerized cognitive
tests validated for MCI, as reviewed by Tsoy et al. [15],have test time of 12–30 minutes, sensitivity of 41–90%,
specificity of 64–94%, and the test with the highest sensitivity and specificity required more than 20 minutes. On
the other hand, in recent years, there have been several
reports of computer-based examinations that have beenverified for MCI in Japan as well [19, 31–33]. Althoughmany of these tests have shorter test times than MARC,
the specificity and AUC of MARC were the highest(Additional file 1: Table S3). From the above evidence,
tests with a higher distinguishing ability for diseases than

Page 7 of 10

MARC are thought to take longer for testing, while tests
with a shorter test time than MARC are thought to havea slightly inferior distinguishing ability than MARC. As
such, MARC is moderate in terms of its distinguishingability and test time, which positions it in the middle
among other tests. In recent years, an increasing number of studies have been utilizing mobile devices for thecognitive assessment of the elderly [30], and there is a
growing interest. In view of studies conducted worldwide
on computerized cognitive function tests, it is desirable
to examine the use of a test based on test time and diagnostic performance. We believe that 10 minutes is acceptable in screening, and MARC is considered to have highperformance in distinguishing MCI given that it can becompleted within 10 minutes. Currently, a software version of the MARC was developed based on the verification results of the present study. It is a test that can be
performed by anyone who owns a computer and does not
require the purchase of special equipment. In addition to
the advantage of being easy to introduce in terms of cost,it can reduce the burden on the examiner.
The costs and social support associated with dementia
increase as the severity of it increases [34, 35]. Additionally, it has been reported that early symptomatic treatment of dementia is cost-effective [36]. In other words,
early detection and implementation of appropriate measures are not only important for reducing the burdenof care and social costs, but are also beneficial for thepatients themselves. However, it has been reported thatmild anosognosia is observed in MCI and severe anosognosia in dementia [37]. In other words, subjective evaluation alone (for example, self-report) may not be sufficient
as a means for early detection and, therefore, objective
evaluation is important. In a study involving a questionnaire survey with elderly individuals, more than half ofthe respondents were unwilling or undecided regarding
regular dementia screening tests. The primary reasons
were “bothersome to visit the clinic” and “do not know
which doctors can be consulted” [38]. Because there arepeople who feel resistance towards hospital visits, we
believe that, in addition to recommending hospital visits, it is effective for early detection to provide a venue
in local areas where people can casually visit to receivea check-up. Furthermore, past studies have shown thatparticipants in home-visit surveys were more likely toexperience cognitive decline than those in venue surveys[39], suggesting the importance of home-visit surveys.
Thus, approaches including community check-ups andhome-visit surveys are necessary for the early detectionof cognitive function decline, and a tool that enables
evaluation in a short period of time without the need fora specialist is desirable in such settings. We, therefore,
believe that the use of computerized tests such as MARCKouzuki et al. BMC Neurology(2022) 22:457

provides high value. In addition, research is ongoing to
examine whether preclinical AD can be identified andrisk of cognitive decline and ADD can be predicted byadministering a new online test, TAS Test, that assesses
a range of motor-cognitive functions using a laptop or
desktop computer with a webcam and microphone [40],and it is expected that patients in the pre-MCI stage may
be detected with the use of computers in the future.
Because MARC is a test prepared in Japanese, it cannot
be used with people who do not understand Japanese.
However, we believe the questions can be directly translated without any problems, since the MARC questions
do not include any cultural questions (that is, questions
that only the Japanese people can understand). It should
be noted that the words used in the delayed recognition
task were chosen from words which the Japanese elderly
recalled frequently as presented in a previous study [41],within the categories of animals, vehicles, plants, andfurniture. Directly translating these words will result inchanges in familiarity with them due to cultural differences. It has been shown that memory performance varies between familiar words and unfamiliar words [42],and this may alter the difficulty of a question. Therefore,words which can be easily recalled by the elderly in eachcountry should be selected from four different categories
without changing the concept of question preparation.
Finally, we discuss some of the limitations of the present study. First, the sample size was small. The numberof patients in the MCI group was smaller than those in
the NDC and ADD groups. In addition, the numberof participants between the age of 65 and 74 years was
small. Measures for patients during this chronologicalperiod are very important to prevent the developmentof dementia. Furthermore, this is a single-centre study;
a multicentre joint study with a larger number of cases
which also includes participants between 65 and 74 age
is necessary to draw a conclusion. Second, a software version of the test was not available. Although the examiners in this study were specialists, they did not provide
more than the necessary explanations, so it is unlikelythat the presence of the examiners affected the results.
However, non-software version of the test resulted in theparticipants not receiving any response after selecting ananswer on the screen. It is possible that this bewildered
the participants and affected their performance. We speculate that those who scored particularly low in the NDCgroup may have been affected by this. This is a weaknessof the study. A software version of the test was developed
based on the verification results of the present study. We
believe it is important to check the consistency of theresults by re-examination. Third, only participants with
ADD were tested in the present study and patients withother types of dementia were not evaluated. It is unclear

Page 8 of 10

whether other types dementia can be detected as was
possible with ADD because the cognitive areas affectedvary by the type of dementia. Examination of MCI, whichis broadly divided into the amnestic type with memory
impairment and non-amnestic type without memory
impairment [1], by subtype was also not performed.
Although MARC includes questions that assess cognitive
functions other than memory, there are many memoryfocused questions. Therefore, this test may potentially failto classify non-amnestic patients. A previous study using
MoCA showed that the classification accuracy for nonamnestic MCI was lower than that for amnestic MCI,
and there was a difference in the detection rate of MCI
subtypes [43]. We believe that an accuracy application of
MARC can be found by examining dementia other thanADD and exploring MCI by subtype.

Conclusions
MARC is a computer-assisted test which can be performed in less than 10 minutes without the need for a
specialist. It has high validity in relation to existing tests
and high reliability, as evaluated by retesting. This evaluation method is characterized by its ability to distinguish
MCI with high accuracy. We believe that MARC can beused as a tool for the early detection of cognitive decline
during community check-ups, where many individuals
need to be evaluated within a short period of time, as
well as home-visit surveys. In addition, computer-based
examinations, not person-to-person examinations, areuseful in countermeasures against infectious diseases
caused by droplet infection, such as the coronavirus disease 2019. In this study, verification was performed by asemi-automated method, but since the software versionof MARC has already been developed, we believe that useof the software version of MARC can make the most of
the above advantages.
Abbreviations
ADD: Alzheimer’s disease dementia; MCI: mild cognitive impairment; NDC:
non-demented controls; MoCA: Montreal cognitive assessment; MARC​: mild
cognitive impairment assessment tool for rapid screening using a computer;
CDR: clinical dementia rating; ROC: receiver operating characteristic; AUC​: area
under the receiver operating characteristic curve; CI: confidence interval; ICC:
intraclass correlation coefficients; ANOVA: analysis of variance; MSP: a computerized test battery for Alzheimer’s disease screening (produced by Nihon
Kohden Corporation, named “monowasure soudan proguramu” (forgetfulness
consultation program)).

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s12883-​022-​02997-4.
Additional file 1: Table S1. Characteristics of patients in the 65–74,
75–84, and over 85 years old groups. Table S2. Comparison of the score ofKouzuki et al. BMC Neurology(2022) 22:457

subtests in the MARC. Table S3. Overview of the psychometric properties
of Japanese computerized cognitive function test verified for MCI. Figure
S1. Samples of the representative tests on the MARC. Figure S2. The scoreof MARC in the 65–74, 75–84, and over 85 years old groups.
Acknowledgements
We thank the patients who participated in our study and their families. We
also thank the staff at Shinsei Hospital (Kurayoshi, Japan) who cooperated withthis study. We also thank Editage (www.​edita​ge.​com) for English language
editing.
Authors’ contributions
MK, MM and KU designed the study. MK, MM, and NT implemented the tests.
MK and MM analyzed and MK, MM, and KU interpreted the data. MK wrote thefirst draft of the manuscript, and MM, NT, and KU reviewed the manuscript. All
authors read and approved the final manuscript.
Funding
This work was supported by JSPS KAKENHI (Grant Number JP19K19460). The
funding body had no role in the design of the study, data collection, analysis
or interpretation of data, or writing of the manuscript.
Availability of data and materials
The datasets used and/or analyzed during the current study are available fromthe corresponding author on reasonable request, subject to the approval of
all authors and the ethics committee. Additionally, a software version of MARC
(in Japanese) is available free of charge from the corresponding author on
reasonable request.

Page 9 of 10

4.

5.

6.
7.
8.
9.
10.
11.
12.
13.

Declarations
Ethics approval and consent to participate
The ethics committee of Tottori University faculty of Medicine (Yonago, Japan)
approved the design of this study (number: 20A228), conducted by following
the tenets of the Declaration of Helsinki. We explained the research protocol
to the patients and guardians as necessary, who provided written informed
consent for participation.

14.

Consent for publication
Not applicable.

16.

Competing interests
MK, MM, and NT have no conflicts of interest to declare. KU owns a patent on
the computerized test battery for Alzheimer’s disease screening (produced by
Nihon Kohden Corporation, named “monowasure soudan proguramu (MSP)”(forgetfulness consultation program)), and receives royalties from Nihon
Kohden Corporation.

17.

Author details
1
Department of Biological Regulation, School of Health Science, Facultyof Medicine, Tottori University, 86 Nishi‑cho, Yonago 683‑8503, Japan. 2 Department of Dementia Prevention, School of Health Science, Faculty of Medicine,
Tottori University, 86 Nishi‑cho, Yonago 683‑8503, Japan.

15.

18.

19.

20.
21.

Received: 27 September 2022 Accepted: 1 December 2022
22.
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