Evidence map›Paper›PMID 23977183›Full record

ArticlePloS one2013

The use of bayesian latent class cluster models to classify patterns of cognitive performance in healthy ageing.

Patrício Soares Costa, Nadine Correia Santos, Pedro Cunha, Joana Almeida Palha, Nuno Sousa

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Article
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  3. Using Mixture Modeling to Construct Subgroups of Cognitive Aging in the Wisconsin Longitudinal Study.The journals of gerontology. Series B, Psychological sciences and social sciences · 2021
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  4. Article
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  7. The Cognitive Connectome in Healthy Aging.Frontiers in aging neuroscience · 2021
    Article
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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

5 authors.

Patrício Soares CostaLife and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal ; ICVS/3B's, PT Government Associate Laboratory, Braga/Guimarães, Portugal.
Nadine Correia Santos
Pedro Cunha
Joana Almeida Palha
Nuno Sousa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The main focus of this study is to illustrate the applicability of latent class analysis in the assessment of cognitive performance profiles during ageing. Principal component analysis (PCA) was used to detect main cognitive dimensions (based on the neurocognitive test variables) and Bayesian latent class analysis (LCA) models (without constraints) were used to explore patterns of cognitive performance among community-dwelling older individuals. Gender, age and number of school years were explored as variables. Three cognitive dimensions were identified: general cognition (MMSE), memory (MEM) and executive (EXEC) function. Based on these, three latent classes of cognitive performance profiles (LC1 to LC3) were identified among the older adults. These classes corresponded to stronger to weaker performance patterns (LC1>LC2>LC3) across all dimensions; each latent class denoted the same hierarchy in the proportion of males, age and number of school years. Bayesian LCA provided a powerful tool to explore cognitive typologies among healthy cognitive agers.

Indexed as

Models, PsychologicalAgedAged, 80 and overAgingBayes TheoremCluster AnalysisCognitionExecutive FunctionFemaleHealthHumansMaleMarkov ChainsMemoryMiddle AgedMonte Carlo Method

Identifiers

PMID23977183
PMCPMC3748115

What OpenQuestion holds

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LicenceCC BY
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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.