Evidence map›Paper›PMID 25762931›Full record

ArticleFrontiers in aging neuroscience2015

Visuospatial characteristics of an elderly Chinese population: results from the WAIS-R block design test.

Shufei Yin, Xinyi Zhu, Xin Huang, Juan Li

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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

14 citing papers in PubMed.

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  14. Correlates of Visuospatial Ability among Older People in Indonesia.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shufei YinCenter on Ageing Psychology, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences Beijing, China ; University of Chinese Academy of Sciences Beijing, China.
Xinyi ZhuCenter on Ageing Psychology, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences Beijing, China.
Xin HuangCenter on Ageing Psychology, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences Beijing, China ; University of Chinese Academy of Sciences Beijing, China.
Juan LiCenter on Ageing Psychology, Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visuospatial deficits have long been recognized as a potential predictor of dementia, with visuospatial ability decline having been found to accelerate in later stages of dementia. We, therefore, believe that the visuospatial performance of patients with mild cognitive impairment (MCI) and dementia (Dem) might change with varying visuospatial task difficulties. This study administered the Wechsler Adult Intelligence Scale-Revised (WAIS-R) Block Design Test (BDT) to determine whether visuospatial ability can help discriminate between MCI patients from Dem patients and normal controls (NC). Results showed that the BDT could contribute to the discrimination between MCI and Dem. Specifically, simple BDT task scores could best distinguish MCI from Dem patients, while difficult BDT task scores could contribute to discriminating between MCI and NC. Given the potential clinical value of the BDT in the diagnosis of Dem and MCI, normative data stratified by age and education for the Chinese elderly population are presented for use in research and clinical settings.

Indexed as

dementiamild cognitive impairmentnormative datavisuospatial characteristicsWAIS-R block design test

Identifiers

PMID25762931
PMCPMC4340228

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Registered trials

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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.