Comparison of validity between spatial memory test （SMT） and Montreal cognitive assessment （MoCA） for screening mild cognitive impairment in Chinese elderly population

doi:10.16150/j.1671-2870.2026.02.007

Abstract

Abstract:

Objective To evaluate the screening performance of the Spatial Memory Test (SMT) in identifying mild cognitive impairment (MCI) among the elderly population in China, and to compare it with the Montreal Cognitive Assessment (MoCA), in order to provide a foundation for individualized MCI screening in China. Methods The data for this study were derived from the Shanghai Elderly Brain Health Cohort Study, including 415 community-dwelling older adults consecutively enrolled from January 2023 to January 2024, comprising 88 cognitively normal (NC) individuals, 188 with subjective cognitive decline (SCD), and 139 individuals with mild cognitive impairment (MCI). All participants completed SMT and MoCA assessments. SCD and NC were served as the control groups and MCI as the case group, and receiver operating characteristic (ROC) curve analysis was employed to compare the screening performance of the two tools. Furthermore, the correlation between SMT scores and various neuropsychological tests was explored, and stratified and interaction analyses were conducted to examine the effects of age and education level on the screening performance of SMT. Results Both SMT and MoCA effectively identified MCI, with SMT demonstrating superior overall screening performance. When distingui-shing SCD from MCI, the area under the receiver operating characteristic curve (AUC) of MoCA was slightly higher than that of SMT (0.925 vs. 0.885). However, SMT showed higher specificity (91.06%) and positive predictive value (84.89%) at the commonly used international cutoff point (≤8), with an overall accuracy of 80.0%, outperforming MoCA across different cutoff values. Correlation analysis indicated that SMT was not only positively correlated with the total MoCA score (r=0.612, P<0.001), but also closely associated with cognitive domains sensitive to early AD, such as delayed recall and visuospatial reasoning (all P<0.01). Stratified analysis revealed that among individuals aged ≥75 years, the AUC for distinguishing SCD from MCI was comparable between SMT and MoCA (0.917 vs. 0.910, P=0.802); among those with education >9 years, the performance of the two tests in distinguishing SCD from MCI was similar (AUC: 0.924 vs. 0.904, P=0.358). Interaction analysis further indicated that only in the subgroup with education >9 years and age ≥75 years did MoCA slightly outperform SMT in distinguishing SCD from MCI (AUC: 0.942 vs. 0.864, P<0.05) and NC from MCI (AUC: 0.99 vs. 0.90, P<0.05). Conclusion As a digital screening tool for early cognitive impairment, SMT demonstrates superior overall performance compared to MoCA in screening for MCI, with advantages of high specificity and ease of use, and is more suitable for large-scale community screening and rapid preliminary assessment in the elderly population.

Key words: Mild cognitive impairment, Spatial memory test, Montreal cognitive assessment, Elderly population, Screening tools

CLC Number:

R441
R749.16

WANG Jiayue, XIONG Wenkui, JIANG Weiyun, WANG Jian, ZENG Naiyan, YUE Ling. Comparison of validity between spatial memory test （SMT） and Montreal cognitive assessment （MoCA） for screening mild cognitive impairment in Chinese elderly population[J]. Journal of Diagnostics Concepts & Practice, 2026, 25(02): 165-173.

Figures/Tables 6

Table 1

Demographic and clinical information of participants

Variables	NC（n=88）	SCD（n=188）	MCI（n=139）	F/H/χ²	P	Post-comparison
Age (year)	73.07±6.17	73.77±6.49	73.78±6.94	0.399	0.672
Gender (Male/Female)	24(7/17)	60(19/41)	51(19/32)	2.237	0.136
Education (year)	10(9,121)	12(9,12)	11(9,14)	1.461	0.482
Smoke (year)	19（21.6%）	26（13.8%）	21（15.1%）	2.799	0.247
Drink (year)	16（18.2%）	19（10.1%）	19（13.7%）	3.533	0.171
Hypertension [n(%)]	42（47.7%）	115（61.2%）	88（63.3%）	6.057	0.048
Diabetes [n(%)]	18（20.5%）	52（27.7%）	49（35.3%）	5.942	0.051
CHD [n(%)]	7（8%）	38（20.2%）	31（22.3%）	8.244	0.016
Hyperlipidemia [n(%)]	22（25%）	87（46.3%）	53（38.1%）	11.475	0.003
Cerebral hemorrhage [n(%)]	2（2.3%）	7（3.8%）	2（1.4%）	1.724	0.422
Stroke [n(%)]	7（8%）	30（16%）	23（16.5%）	3.842	0.146
MoCA [M (P25, P75)]	25（23,27）	25（22,26）	19（17,21）^a,b	201.037	0.000	MCI<NC, SCD
SMT [M (P25, P75)]	10（9,11）	10（9,11）	6（5,8）^a,b	166.462	0.000	MCI<NC, SCD
Digit span
Forward [M (P25, P75)]	10（8,12）	9（8,11）	10（7,11）	2.973	0.226
Backward [M (P25, P75)]	5（4,7）	5（4,6）	5（4,6）	1.320	0.517
Visual recognition
Functional [M (P25, P75)]	4（4,4）	4（4,4）	4（3,4）^a,b	14.020	0.001	MCI<NC, SCD
Semantic [M (P25, P75)]	3（3,4）	4（3,4）	3（3,4）	1.552	0.460
Correct [M (P25, P75)]	5（4,6）	5（4,6）	5（4,6）	1.090	0.580
Mistake [M (P25, P75)]	1（0,1）	1（0,1）	1（0,1）	0.614	0.736
Visual matching and reasoning [M (P25, P75)]	5（4,7）	5（3,7）	5（3,7）	1.824	0.402
Verbal fluency [M (P25, P75)]	15（13,18）	15（13,17）	15（12,17）	0.779	0.677
Trails-A [M (P25, P75)]	56（46,72）	54（44,69）	59（49,69）	2.889	0.236
Trails-B	122（95,165）	120（95,152）	120（95,161）	0.364	0.833
HVLT
Learning tests [M (P25, P75)]	14（11,18）	14（11,17）	14（11,17）	1.302	0.522
Delayed recall test [M (P25, P75)]	5（3,7）	5（3,6）	5（3,6）	1.706	0.426
Recognition test [M (P25, P75)]	5（2,7）	4（2,6）	4（2,6）	2.345	0.310

Table 1

Figure 1

Table 2

Figure 2

Figure 3

Table 3

References 29

[1]	首都医科大学宣武医院国家神经疾病医学中心, 中国疾病预防控制中心慢性非传染性疾病预防控制中心, 国家卫生健康委能力建设和继续教育中心, 等. 中国阿尔茨海默病蓝皮书(精简版)[J]. 中华医学杂志, 2024, 104(29):2701-2727.
	National Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University; National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention; National Health Commission Capacity Building and Continuing Education Center, et al. Blue paper on Alzheimer′s disease in China(simplified version)[J]. Natl Med J China, 2024, 104(29):2701-2727.
[2]	岳玲, 江叶昊. 阿尔茨海默病诊断和分期新标准:生物标志物引领的精准医疗时代[J]. 神经病学与神经康复学杂志, 2025, 21(1):1-5.
	YUE L, JIANG Y H. New diagnostic and staging criteria for Alzheimer's disease:the era of precision medicine led by biomarkers[J]. J Neurol Neurorehabil, 2025, 21(1):1-5.
[3]	RABIN L A, SMART C M, AMARIGLIO R E. Subjective cognitive decline in preclinical Alzheimer’s disease[J]. Annu Rev Clin Psychol, 2017,13:369-396.
[4]	SANFORD A M. Mild cognitive impairment[J]. Clin Geria-tr Med, 2017, 33(3):325-337.
[5]	马瑾瑾, 肖卫忠. 阿尔茨海默病早期诊断方法[J]. 中国临床研究, 2024, 37(7):1113-1119.
	MA J J, XIAO W Z. Early diagnosis of Alzheimer's di-sease[J]. Chin J Clin Res, 2024, 37(7):1113-1119.
[6]	初曙光, 王刚. 淀粉样蛋白相关影像学异常:一种与阿尔茨海默病治疗相关的具有影像学特征和诊断特异性的MRI表现[J]. 神经病学与神经康复学杂志, 2025, 21(1):6-11.
	CHU S G, WANG G. Amyloid-related imaging abnormalities:an MRI manifestation associated with Alzheimer's disease-targeted therapy with imaging characteristics and diagnostic specificit[J]. J Neurol Neurorehabil, 2025, 21(1):6-11.
[7]	JIA X, WANG Z, HUANG F, et al. A comparison of the Mini-mental state examination (MMSE) with the Montreal cognitive assessment (MoCA) for mild cognitive impairment screening in Chinese middle-aged and older population: A cross-sectional study[J]. BMC Psychiatry, 2021, 21(1):485. doi: 10.1186/s12888-021-03495-6 pmid: 34607584
[8]	AMRO I, AL HAMADI A M, EL SALEM A A, et al. Population-based norms for the Montreal cognitive assessment in Arab adults[J]. Brain Behav, 2025, 15(2):e70287. doi: 10.1002/brb3.v15.2 URL
[9]	夏安琪, 李军, 岳玲, 等. 蒙特利尔认知评估量表在中国社区老人中的应用[J]. 上海交通大学学报(医学版), 2021, 41(12):1661-1667.
	XIA A Q, LI J, YUE L, et al. Application of Montreal cognitive assessment scale to the elderly in Chinese community[J]. J Shanghai Jiao Tong Univ(Med Sci), 2021, 41(12):1661-1667.
[10]	ISLAM N, HASHEM R, GAD M, et al. Accuracy of the Montreal Cognitive Assessment tool for detecting mild cognitive impairment: A systematic review and meta-analysis[J]. Alzheimers Dement, 2023, 19(7):3235-3243. doi: 10.1002/alz.13040 pmid: 36934438
[11]	VORA N, PATEL P, MARSOOL M D M, et al. Atypical Alzheimer’s dementia: Addressing the subtypes, epide-miology, atypical presentations, diagnostic biomarkers, and treatment updates[J]. Dis a Mon, 2025, 71(5):101863.
[12]	SANTAGATA F, CAPPA S F, PRESTA R, et al. Visuospatial impairment in dementia: A new index to improve the clinical diagnosis of Alzheimer’s disease[J]. Aging Clin Exp Res, 2025, 37(1):127. doi: 10.1007/s40520-025-03028-1
[13]	WANG H, FAN Z, SHI C, et al. Consensus statement on the neurocognitive outcomes for early detection of mild cognitive impairment and Alzheimer dementia from the Chinese Neuropsychological Normative (CN-NORM) Project[J]. J Glob Health, 2019, 9(2):020320. doi: 10.7189/jogh.09.020320 URL
[14]	JESSEN F, AMARIGLIO R E, VAN BOXTEL M, et al. A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease[J]. Alzheimers Dement, 2014, 10(6):844-852. doi: 10.1016/j.jalz.2014.01.001 URL
[15]	PETERSEN R C, DOODY R, KURZ A, et al. Current concepts in mild cognitive impairment[J]. Arch Neurol, 2001, 58(12):1985. doi: 10.1001/archneur.58.12.1985 URL
[16]	ZHANG S, QIU Q, QIAN S, et al. Determining appropriate screening tools and cutoffs for cognitive impairment in the Chinese elderly[J]. Front Psychiatry, 2021,12:773281.
[17]	MICHALLAT-BRAGG G, BENNETT M, FLEWITT B I, et al. Exploring the sensitivity of episodic and spatial memory tests to healthy and pathological cognitive aging[J]. Front Aging Neurosci, 2025,17:1547834.
[18]	HARTLEY T, BIRD C M, CHAN D, et al. The hippocampus is required for short-term topographical memory in humans[J]. Hippocampus, 2007, 17(1):34-48. doi: 10.1002/hipo.20240 pmid: 17143905
[19]	HONG Y, ZENG X, ZHU C W, et al. Evaluating the Beijing version of Montreal cognitive assessment for identification of cognitive impairment in monolingual Chinese American older adults[J]. J Geriatr Psychiatry Neurol, 2022, 35(4):586-593.[LinkOut] doi: 10.1177/08919887211036182 URL
[20]	PARRA-RODRÍGUEZ L, SILVA-PEREYRA J, SÁNCHEZ-GARCÍA S, et al. Normative data for the Montreal cognitive assessment (MoCA) in Mexican adults: A regression-based approach[J]. Diagnostics, 2025, 15(22):2920. doi: 10.3390/diagnostics15222920 URL
[21]	肖世富, 徐巍, 姚培芬. 世界卫生组织老年认知功能评价成套神经心理测验的临床初步应用[J]. 中华精神科杂志, 1999, 32(4):230.
	XIAO S F, XV W, YAO P F. The preliminary clinical use of the World Health Organization battery of cognitive assessment instruments for elderly[J]. Chin J Psychiatry, 1999, 32(4):230.
[22]	YOSHIMURA T, OSAKA M, OSAWA A, et al. The classical backward digit span task detects changes in working memory but is unsuitable for classifying the severity of dementia[J]. Appl Neuropsychol Adult, 2023, 30(5):528-534. doi: 10.1080/23279095.2021.1961774 URL
[23]	LLINÀS-REGLÀ J, VILALTA-FRANCH J, LÓPEZ-POUSA S, et al. The trail making test: Association with other neuropsychological measures and normative values for adults aged 55 years and older from a Spanish-speaking population-based sample[J]. Assessment, 2017, 24(2):183-196. doi: 10.1177/1073191115602552 URL
[24]	CAI Y, YANG T, YU X, et al. The alternate-form reliabi-lity study of six variants of the brief visual-spatial memory test-revised and the Hopkins verbal learning test-revised[J]. Front Public Health, 2023,11:1096397.
[25]	CHEN K L, XU Y, CHU A Q, et al. Validation of the Chinese Version of Montreal cognitive assessment basic for screening mild cognitive impairment[J]. J Am Geriatr Soc, 2016, 64(12):e285-e290.
[26]	SONG C S, LEE H S, CHUN B Y. Comparison of Montreal cognitive assessment in Korean version for predic-ting mild cognitive assessment in 65-year and over indi-viduals[J]. Occup Ther Int, 2022,2022:4108434.
[27]	CLASSON E, VAN DEN HURK W, LYTH J, et al. Montreal cognitive assessment: Normative data for cognitively healthy Swedish 80- to 94-year-olds[J]. J Alzheimers Dis, 2022, 87(3):1335-1344. doi: 10.3233/JAD-215629 pmid: 35431248
[28]	CHAN D, GALLAHER L M, MOODLEY K, et al. The 4 mountains test: A short test of spatial memory with high sensitivity for the diagnosis of pre-dementia Alzheimer’s disease[J]. J Vis Exp, 2016,116:54454.
[29]	IWATSUBO T, SPERLING R A, ALGECIRAS-SCHIMNICH A, et al. Modernizing diagnosis of Alzheimer's disease: A review of global trends and Asia-specific perspectives[J]. Alzheimers Dement, 2025, 21(8):e70536. doi: 10.1002/alz.v21.8 URL

Diagnostic indicators	SMT≤8	MoCA≤26	MoCA≤25	MoCA≤24
Sensitivity	65.56%	100%	44.84%	52.08%
Specificity	91.06%	23.90%	100.00%	99.33%
Positive predictive value	84.89%	39.80%	100.00%	99.28%
Negative predictive value	77.54%	100.00%	38.40%	53.99%
Precision	80.00%	49.40%	58.50%	69.16%

Item	Education≤9 years and Age<75 years		Education≤9 years and Age≥75 years		Education>9 years and Age<75 years		Education>9 years and Age≥75 years
Item	MoCA	SMT	MoCA	SMT	MoCA	SMT	MoCA	SMT
NC vs. MCI	NC=28 vs. MCI=33	NC=28 vs. MCI=33	NC=14 vs. MCI=24	NC=14 vs. MCI=24	NC=21 vs. MCI=46	NC=21 vs. MCI=46	NC=24 vs. MCI=36	NC=24 vs. MCI=36
Sensitivity	0.91	0.85	0.96	0.92	0.94	0.87	0.97	0.67
Specificity	0.79	0.82	0.79	0.08	0.76	0.76	0.92	0.96
Cut-off	22.50	8.50	22.50	8.5	22.5	8.5	22.5	7.5
AUC（95％CI）	0.93 (0.84-0.99)	0.86 (0.77-0.96)	0.87 （0.71-1.00）	0.88 （0.76-1.00）	0.88 （0.77-0.99）	0.87 （0.77-0.97）	0.99 （0.98-1.00）^*	0.90 （0.82-0.98)
SCD vs. MCI	SCD=49 vs. MCI=33	SCD=49 vs. MCI=33	SCD=17 vs. MCI=24	SCD=17 vs. MCI=24	SCD=60 vs. MCI=46	SCD=60 vs. MCI=46	SCD=57 vs. MCI=36	SCD=57 vs. MCI=36
Sensitivity	0.74	0.74	0.82	0.82	0.87	0.85	0.97	0.88
Specificity	0.91	0.85	0.96	0.75	0.8	0.87	0.75	0.67
Cut-off	22.50	8.50	22.50	7.5	21.5	8.5	20.5	7.5
AUC（95％CI）	0.91 (0.84-0.97)	0.84 (0.75-0.94)	0.95 （0.89-1.00）	0.86 （0.74-0.98）	0.91 （0.86-0.96）	0.94 （0.89-0.98）	0.94 （0.90-0.99）^*	0.86 （0.79-0.94）