Evidence map›Paper›PMID 34880929›Full record

ArticleComputational and mathematical methods in medicine2021

A Novel Game-Based Intelligent Test for Detecting Elderly Cognitive Function Impairment.

Chih-Wei Lin, Tso-Yen Mao, Chun-Feng Huang

RetractedOpen access · hybridAbstract readRetracted Publication
In one paragraph

Article in Computational and mathematical methods in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Chih-Wei LinDepartment of Leisure Services Management, Chaoyang University of Technology, Taichung, Taiwan.ORCID https://orcid.org/0000-0002-7497-7805
Tso-Yen MaoDepartment of Leisure Services Management, Chaoyang University of Technology, Taichung, Taiwan.ORCID https://orcid.org/0000-0001-7133-3257
Chun-Feng HuangDepartment of Leisure Services Management, Chaoyang University of Technology, Taichung, Taiwan.ORCID https://orcid.org/0000-0002-6265-5155
Chaoyang University of Technology · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposesThis research explores the game-based intelligent test (GBIT), predicts the possibilities of Mini-Mental State Examination (MMSE) scores and the risk of cognitive impairment, and then verifies GBIT as one of the reliable and valid cognitive assessment tools.

methodsThis study recruited 117 elderly subjects in Taiwan (average age is 79.92 ± 8.68, average height is 156.91 ± 8.01, average weight is 59.14 ± 9.67, and average MMSE score is 23.33 ± 6.16). A multiple regression model was used to analyze the GBIT parameters of the elderly's reaction, attention, coordination, and memory to predict their MMSE performance. The binary logistic regression was then utilized to predict their risk of cognitive impairment. The statistical significance level was set as

resultsMultiple regression analysis showed that gender, the correct number of reactions, and the correct number of memory have a significantly positive predictive power on MMSE of the elderly (

conclusionsThis study verifies that GBIT is reliable and can effectively predict the cognitive function and risk of cognitive impairment in the elderly. Therefore, GBIT can be used as one of the feasible tools for evaluating older people's cognitive function.

Indexed as

Games, ExperimentalIntelligence TestsMental Status and Dementia TestsVideo GamesAgedAged, 80 and overCognitionCognitive DysfunctionComputational BiologyDementiaFemaleHumansMachine LearningMaleRegression AnalysisTaiwan

Identifiers

PMID34880929
PMCPMC8648469
OpenAlexW3215251098

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.