Evidence map›Paper›PMID 31507406›Full record

ArticleFrontiers in aging neuroscience2019

Discourse Measures to Differentiate Between Mild Cognitive Impairment and Healthy Aging.

Bo Seon Kim, Yong Bum Kim, HyangHee Kim

Open access · goldAbstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

28 citing papers in PubMed, 1 synthesis or guideline pooled it, 57 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
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  11. Review
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  14. Article
  15. Language Differences Among Individuals with Normal Cognition, Amnestic and Non-Amnestic MCI, and Alzheimer's Disease.Archives of clinical neuropsychology : the official journal of the National Academy of Neuropsychologists · 2023
    Article
  16. DementiaBank: Theoretical Rationale, Protocol, and Illustrative Analyses.American journal of speech-language pathology · 2023
    Article
  17. Review
  18. Article
  19. Toward harmonization of strategies for investigating lucidity in AD/ADRD: A preliminary research framework.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2023
    Article
  20. Clinical Guidelines for Eliciting Discourse Using the RHDBank Protocol.American journal of speech-language pathology · 2022
    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

3 authors at 2 institutions in 1 country.

Bo Seon KimGraduate Program in Speech-Language Pathology, Yonsei University, Seoul, South Korea.
Yong Bum KimDepartment of Neurology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea.
HyangHee KimGraduate Program in Speech-Language Pathology, Yonsei University, Seoul, South Korea.
Yonsei University · KRSungkyunkwan University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although subtle discourse declines in people with mild cognitive impairment (MCI) have been reported, heterogeneous measures and tasks among the MCI discourse studies have yielded widely varying outcomes. The present study aimed to first, identify discourse measures that aid the differentiation among people with amnestic MCI (aMCI), people with non-amnestic MCI (naMCI), and cognitively healthy control (HC) participants, and second, delineate the cognitive functions related to such discourse measures. Three discourse tasks (an episodic narrative, a planning task, and a picture description) were performed by 30 aMCI, 22 naMCI, and 21 HC participants. Samples were analyzed using six categories of 15 measures, namely coherence, cohesion, proposition, grammaticality, lexicality, and fluency. The statistical analyses included (1) a multivariate analysis of variance for group comparison; (2) binary simple logistic regression and receiver operating characteristic curve analysis for differentiation between two groups; (3) binary multiple logistic regression for being diagnosed with naMCI or aMCI with the minimum number of predictors; and (4) Pearson correlation analysis for identifying the cognitive functions associated with the discourse measures. The proportion of cohesive words and propositional density in aMCI participants were worse than those in naMCI participants. Global coherence, the proportion of cohesive words, and the proportion of dysfluencies and pauses in naMCI participants were lower than those in the HC participants. Global and local coherence and the proportion of cohesive words, cohesive ties per utterances, propositional density, and dysfluencies and pauses in aMCI participants were worse than those in the HC participants. The aforementioned measures were demonstrated to be effective predictors for classifying groups by receiver operating characteristic curve analysis. In addition, the proportions of cohesive words and pauses were common discourse measures for differentiation between naMCI and HC participants or between aMCI and HC participants using binary multiple logistic regression. According to the correlation analysis, memory and executive functions are needed for coherent, cohesive, and efficient discourse productions in MCI. The detailed description of discourse performances in this study will aid the characterization of the declined language abilities of MCI participants and also the understanding of the cognitive functions involved in discourse performance in MCI.

Indexed as

cognitiondiscourselanguage impairmentmeasuresmild cognitive impairment

Identifiers

PMID31507406
PMCPMC6714864
OpenAlexW2965752664

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.