Evidence map›Paper›PMID 29721646›Full record

SynthesisNeuropsychology review2018

Meta-Analysis of the Effects of Computerized Cognitive Training on Executive Functions: a Cross-Disciplinary Taxonomy for Classifying Outcome Cognitive Factors.

Shannon L Webb, Vanessa Loh, Amit Lampit, Joel E Bateman, Damian P Birney

Abstract readMeta-AnalysisReview
PubMed Publisher
In one paragraph

Synthesis in Neuropsychology review, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 5 pooled it
–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

38 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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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.

Shannon L WebbSchool of Psychology, University of Sydney, Sydney, NSW, 2006, Australia.
Vanessa LohSchool of Psychology, University of Sydney, Sydney, NSW, 2006, Australia.
Amit LampitSchool of Psychology, University of Sydney, Sydney, NSW, 2006, Australia.
Joel E BatemanSchool of Psychology, University of Sydney, Sydney, NSW, 2006, Australia.
Damian P BirneySchool of Psychology, University of Sydney, Sydney, NSW, 2006, Australia. damian.birney@sydney.edu.au.

Funding

Australian Research Council DP140101147
6 · The paper itself

Abstract

The growing prevalence of neurodegenerative disorders associated with aging and cognitive decline has generated increasing cross-disciplinary interest in non-pharmacological interventions, such as computerized cognitive training (CCT), which may prevent or slow cognitive decline. However, inconsistent findings across meta-analytic reviews in the field suggest a lack of cross-disciplinary consensus and on-going debate regarding the benefits of CCT. We posit that a contributing factor is the lack of a theoretically-based taxonomy of constructs and representative tasks typically used. An integration of the Cattell-Horn-Carroll (CHC) taxonomy of broad and narrow cognitive factors and the Miyake unity-diversity theory of executive functions (EF) is proposed (CHC-M) as an attempt to clarify this issue through representing and integrating the disciplines contributing to CCT research. The present study assessed the utility of this taxonomy by reanalyzing the Lampit et al. (2014) meta-analysis of CCT in healthy older adults using the CHC-M framework. Results suggest that: 1) substantively different statistical effects are observed when CHC-M is applied to the Lampit et al. meta-analytic review, leading to importantly different interpretations of the data; 2) typically-used classification practices conflate Executive Function (EF) tasks with fluid reasoning (Gf) and retrieval fluency (Gr), and Attention with sensory perception; and 3) there is theoretical and practical advantage in differentiating attention and working-memory tasks into the narrow shifting, inhibition, and updating EF domains. Implications for clinical practice, particularly for our understanding of EF are discussed.

Indexed as

CognitionExecutive FunctionNeuropsychological TestsTherapy, Computer-AssistedTreatment OutcomeCognitive DysfunctionHumansModels, TheoreticalCHC theoryCognitive interventionCognitive trainingExecutive functionsNeuropsychological assessmentUnity-diversity of EF

Identifiers

PMID29721646

What OpenQuestion holds

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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.