Cited by 371Cognitive Abilities and TestingCognitive Functions and MemoryNeural and Behavioral Psychology Studies

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index; 13 of the 50 sources its claims cite were checked for support.

Working memory training revisited: A multi-level meta-analysis of n-back training studies

Open access
Soveri, Anna, Antfolk, Jan, Karlsson, Linda, Salo, Benny, Laine, Matti·2017·Psychonomic Bulletin & Review

Published version of a preprint

Abstract

The efficacy of working memory (WM) training has been a controversial and hotly debated issue during the past years. Despite a large number of training studies and several meta-analyses, the matter has not yet been solved. We conducted a multi-level meta-analysis on the cognitive transfer effects in healthy adults who have been administered WM updating training with n-back tasks, the most common experimental WM training paradigm. Thanks to this methodological approach that has not been employed in previous meta-analyses in this field, we were able to include effect sizes from all relevant tasks used in the original studies. Altogether 203 effect sizes were derived from 33 published, randomized, controlled trials. In contrast to earlier meta-analyses, we separated task-specific transfer (here untrained n-back tasks) from other WM transfer tasks. Two additional cognitive domains of transfer that we analyzed consisted of fluid intelligence (Gf) and cognitive control tasks. A medium-sized transfer effect was observed to untrained n-back tasks. For other WM tasks, Gf, and cognitive control, the effect sizes were of similar size and very small. Moderator analyses showed no effects of age, training dose, training type (single vs. dual), or WM and Gf transfer task contents (verbal vs. visuospatial). We conclude that a substantial part of transfer following WM training with the n-back task is task-specific and discuss the implications of the results to WM training research.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This multi-level meta-analysis of 33 randomized controlled n-back training studies in healthy adults found a medium-sized transfer effect to untrained n-back tasks but only very small effects to other WM, cognitive control, and fluid intelligence tasks. The authors conclude that much of n-back training transfer is task-specific rather than evidence of broad working memory improvement.

Key findings

  • Across 203 effect sizes (190 after data screening) from 33 studies, 41 experiments, and 2,105 participants, transfer was largest to untrained n-back tasks: g = 0.62 [0.44, 0.81], p < .001; other WM tasks: g = 0.24 [0.16, 0.32], p < .001; cognitive control: g = 0.16 [0.05, 0.27], p < .001; and Gf: g = 0.16 [0.08, 0.24], p < .001. The n-back effect differed from all other domains (all ps < .001), while the other domains did not differ from each other (all ps ≥ .134).
  • Moderator analyses showed no effects of age, training dose (sessions or hours), training type (single vs. dual n-back), or WM/Gf transfer task materials (verbal vs. nonverbal); for example, training type: QM(1) = 2.19, g = 0.09 [−0.03, 0.21], p = .139; age: QM(1) = 0.07, g = 0.03 [−0.17, 0.22], p = .794.
  • Within studies that used both control types, active and passive control groups did not differ in pre-post change, g = 0.03 [−0.07, 0.12], p = .429. When control type was included as a covariate, passive-control studies showed a slightly higher estimated training effect, g = 0.11 [0.00, 0.22], p = .048; after controlling, n-back remained g = 0.59, WM g = 0.18, cognitive control g = 0.08 (p = .202), and Gf g = 0.11 (p > .05).
  • A reanalysis of healthy-adult data from Melby-Lervåg et al. (2016) found that untrained versions of the training tasks showed a stronger effect, g = 0.62 [0.38, 0.86], than other WM tasks, g = 0.21 [0.08, 0.33], QM(1) = 8.89, p < .01.

Methods

  • Multi-level meta-analysis of randomized, controlled trials of n-back training in healthy adults. Searches of PubMed, PsycINFO, Google Scholar, Google, and ERIC (initial February 2015; updated July 2015, February 2016, October 2016) required pretest-posttest designs, n-back-only training, active control training not targeting WM, and transfer measures in n-back, WM, Gf, or cognitive control. Final sample: 33 studies, 41 experiments, 103 groups, 2,105 participants, and 203 training effects (190 after screening).
  • Effect sizes were within-group pre-post standardized mean changes (SMCR) converted to between-group training effects (g_BETWEEN). A three-level model included random intercepts for experiment and for measure within experiment (ICC = 0.499); pre-post correlations were available for 406 of 507 within-sample comparisons, deduced or conservatively estimated for 80 of the remaining 101, and set to 0 when unavailable. Moderators included control type, training type, training dose, transfer materials, and age. Publication bias was assessed with contour-enhanced funnel plots, residual funnel plots, and PET-PEESE regressions.

Limitations

  • Stated: the meta-analysis focused on only one WM training type (n-back), limiting conclusions to n-back training; the limited number of available studies prevented investigating transfer to other cognitive domains and all moderator analyses for all four domains (e.g., material-specific transfer was investigated only for WM and Gf); interactions between moderators were not investigated.
  • Evident from the text: the sample was restricted to healthy adults, so findings may not generalize to clinical samples, children, or other WM training paradigms; reliance on author-provided or estimated pre-post correlations for many effect sizes may affect precision; and publication-bias assessment was complicated by dependent effect sizes and the multilevel structure, leading the authors to use visual inspection and PET-PEESE rather than p-curve or trim-and-fill.

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Integrity signals

Registry

Crossref · 10.3758/s13423-016-1217-0

Cites

85 of 85 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

59 Own result · 17 Own method · 17 Own interpretation · 14 No full text of the sources · 7 No basis given · 6 Partly supported · 5 Sources not found · 3 Supported so far · 2 Supported · 1 Not supported · accuracy not yet measured

  • Probably not a substantial claim. 22
  • It may state two separate claims as one. 27
46 of 46
  • The paper relies on this without support.

    n-back tasks are the most commonly used computerized experimental WM training paradigm.

    “the most commonly used computerized experimental WM training paradigm, namely with n-back tasks”
  • The paper relies on this without support.

    The n-back task is one of the most commonly used working memory training paradigms.

    “We examined the efficacy of one of the most commonly used WM training paradigms, namely the n-back task.”
  • The authors state this as an assumption.

    Experiments within the same study can be treated as independent samples.

    “for the sake of parsimony we did not model the dependency between experiments within the same study, but treated all 41 experiments as independent samples”
  • The authors state this as an assumption.

    Missing pre-post correlations can be set to zero, treating pre- and posttest measures as independent groups.

    “Where we were unable to estimate the correlation, we entered 0 as a correlation, essentially treating the pre-and posttest measures as independent groups.”
  • The paper relies on this without support.

    Task-specific improvement can enhance performance only on tasks with a similar structure where the same strategies can be successfully employed.

    “This is because taskspecific improvement can enhance performance only on tasks with a similar structure where the same strategies can be succesfully employed.”
  • The paper relies on this without support.

    The transfer tasks categorized as measuring working memory, fluid intelligence, or cognitive control validly measure those constructs.

    “Transfer effects to other tasks (whether they measure WM, Gf, or cognitive control), albeit being observable, are small and apparently of little practical significance.”
6 of 6

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Citations

Cites

Show all 83 references

Research works printed but not linked: 3

  1. *Heffernan, A. E. (2014). The generalizability of dual n-back training in younger adults (Master’s thesis). Retrieved from http://hdl.handle.net/10222/56021
  2. NIMH Research Domain Criteria Workshop (2010). Working memory: Workshop proceedings. Downloaded November 8, 2016 from https://www.nimh.nih.gov/research-priorities/rdoc/working-memory-workshop-proceedings.shtml
  3. *Prandl, A. (2012). Visual memory improvement in recognition (Bachelor’s thesis). Retrieved from http://ro.ecu.edu.au/theses_hons/59/

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Metadata

Authors
Soveri, A., Antfolk, J., Karlsson, L., Salo, B., & Laine, M.
Affiliations
  • Åbo Akademi University (FI)
  • University of Turku (FI)
Corresponding author
Soveri, Anna
Venue
Psychonomic Bulletin & Review
Published
2017-01-23
Volume
24
Issue
4
Pages
1077-1096
ISSN
  • 1069-9384 (ISSN-L)
  • 1531-5320
OpenAlex
W2582113845
Cited by
371
References
83
Citations by year
2026: 22 · 2025: 36 · 2024: 46 · 2023: 28 · 2022: 40 · 2021: 46 · 2020: 53 · 2019: 48 · 2018: 39 · 2017: 13
FWCI
5.36
Type
journal article
Language
en
Open access
Locations
  • Psychonomic Bulletin & Review (publishedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion, cc-by)
  • PubMed (publishedVersion)
  • Åbo Akademi University Research Portal (submittedVersion)
  • PsyArXiv (OSF Preprints) (submittedVersion)
Topics
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Abilities and Testing
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Cognitive Functions and Memory
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
Keywords
working memory training, n-back task, transfer of learning, fluid intelligence, cognitive control, training dose, dual-task training
MeSH terms
Cognition, Humans, Learning, Memory, Short-Term, Executive Function

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