Evidence map›Paper›PMID 36301590›Full record

SynthesisJournal of medical Internet research2022

Effectiveness of Computerized Cognitive Training in Delaying Cognitive Function Decline in People With Mild Cognitive Impairment: Systematic Review and Meta-analysis.

Ran Li, Jiawei Geng, Runze Yang, Yumeng Ge, Therese Hesketh

Registry-linked trialOpen access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06598163 (Efficacy of a Digital Health App Five Lives MED to Improve Cognitive Function in Patients With Mild Cognitive Impairment), which is not on this map. Cited by 37 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 3 pooled it
7.9field-weighted citation impact, top 1% 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.

NCT06598163 narecruitingnot on this mapstarted 2025, after this paper: background citation

Efficacy of a Digital Health App Five Lives MED to Improve Cognitive Function in Patients With Mild Cognitive Impairment: a Randomised Controlled Trial

TypeinterventionalSponsorSharpTxRan2025 to 2026Enrolled170ConditionsMild Cognitive ImpairmentArmsFive Lives MED
3 · Its place in the literature

Who cites it

37 citing papers in PubMed, 3 syntheses or guidelines pooled it, 64 citations in OpenAlex.

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  12. Differential Transfer Effects Across Tasks in Younger and Older Adults Following Executive Function Training.Journal of cognitive enhancement : towards the integration of theory and practice · 2026
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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 at 2 institutions in 2 countries.

Ran Li *Institute for Global Health, University College London, London, United Kingdom.ORCID 0000-0002-8432-9326
Jiawei Geng *Centre for Global Health, School of Public Health, Zhejiang University, Hangzhou Zhejiang, China.ORCID 0000-0002-7622-2692
Runze YangInstitute for Global Health, University College London, London, United Kingdom.ORCID 0000-0002-2032-9757
Yumeng GeCentre for Global Health, School of Public Health, Zhejiang University, Hangzhou Zhejiang, China.ORCID 0000-0003-1448-0116
Therese HeskethInstitute for Global Health, University College London, London, United Kingdom.ORCID 0000-0002-7564-9221
University College London · GBZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith no current cure for mild cognitive impairment (MCI), delaying its progression could significantly reduce the disease burden and improve the quality of life for patients with MCI. Computerized cognitive training (CCT) has recently become a potential instrument for improvement of cognition. However, the evidence for its effectiveness remains limited.

objectiveThis systematic review aims to (1) analyze the efficacy of CCT on cognitive impairment or cognitive decline in patients with MCI and (2) analyze the relationship between the characteristics of CCT interventions and cognition-related health outcomes.

methodsA systematic search was performed using MEDLINE, Cochrane, Embase, Web of Science, and Google Scholar. Full texts of randomized controlled trials of CCT interventions in adults with MCI and published in English language journals between 2010 and 2021 were included. Overall global cognitive function and domain-specific cognition were pooled using a random-effects model. Sensitivity analyses were performed to determine the reasons for heterogeneity and to test the robustness of the results. Subgroup analyses were performed to identify the relationship between the characteristics of CCT interventions and cognition-related effectiveness.

resultsA total of 18 studies with 1059 participants were included in this review. According to the meta-analysis, CCT intervention provided a significant but small increase in global cognitive function compared to that in the global cognitive function of the control groups (standardized mean difference=0.54, 95% CI 0.35-0.73; I

conclusionsThis systematic review suggests that CCT interventions could improve global cognitive function in patients with MCI. Considering the relatively small sample size and the short treatment duration in all the included studies, more comprehensive trials are needed to quantify both the impact of CCT on cognitive decline, especially in the longer term, and to establish whether CCT should be recommended for use in clinical practice.

trial registrationPROSPERO International Prospective Register of Systematic Reviews CRD42021278884; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=278884.

Indexed as

Cognition DisordersCognitive DysfunctionCognitionHumansQuality of LifeTime Factorscomputerized cognitive trainingmild cognitive impairment

Identifiers

PMID36301590
PMCPMC9650579
OpenAlexW4307443718

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.