IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0260788.html
   My bibliography  Save this article

The association between socioeconomic disadvantage and children’s working memory abilities: A systematic review and meta-analysis

Author

Listed:
  • Kate E Mooney
  • Stephanie L Prady
  • Mary M Barker
  • Kate E Pickett
  • Amanda H Waterman

Abstract

Background and objective: Working memory is an essential cognitive skill for storing and processing limited amounts of information over short time periods. Researchers disagree about the extent to which socioeconomic position affects children’s working memory, yet no study has systematically synthesised the literature regarding this topic. The current review therefore aimed to investigate the relationship between socioeconomic position and working memory in children, regarding both the magnitude and the variability of the association. Methods: The review protocol was registered on PROSPERO and the PRISMA checklist was followed. Embase, Psycinfo and MEDLINE were comprehensively searched via Ovid from database inception until 3rd June 2021. Studies were screened by two reviewers at all stages. Studies were eligible if they included typically developing children aged 0–18 years old, with a quantitative association reported between any indicator of socioeconomic position and children’s working memory task performance. Studies were synthesised using two data-synthesis methods: random effects meta-analyses and a Harvest plot. Key findings: The systematic review included 64 eligible studies with 37,737 individual children (aged 2 months to 18 years). Meta-analyses of 36 of these studies indicated that socioeconomic disadvantage was associated with significantly lower scores working memory measures; a finding that held across different working memory tasks, including those that predominantly tap into storage (d = 0.45; 95% CI 0.27 to 0.62) as well as those that require processing of information (d = 0.52; 0.31 to 0.72). A Harvest plot of 28 studies ineligible for meta-analyses further confirmed these findings. Finally, meta-regression analyses revealed that the association between socioeconomic position and working memory was not moderated by task modality, risk of bias, socioeconomic indicator, mean age in years, or the type of effect size. Conclusion: This is the first systematic review to investigate the association between socioeconomic position and working memory in children. Socioeconomic disadvantage was associated with lower working memory ability in children, and that this association was similar across different working memory tasks. Given the strong association between working memory, learning, and academic attainment, there is a clear need to share these findings with practitioners working with children, and investigate ways to support children with difficulties in working memory.

Suggested Citation

  • Kate E Mooney & Stephanie L Prady & Mary M Barker & Kate E Pickett & Amanda H Waterman, 2021. "The association between socioeconomic disadvantage and children’s working memory abilities: A systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 16(12), pages 1-22, December.
  • Handle: RePEc:plo:pone00:0260788
    DOI: 10.1371/journal.pone.0260788
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0260788
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0260788&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0260788?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yekaterina Chzhen & Anna Gromada & Gwyther Rees & Jose Cuesta & Zlata Bruckauf & UNICEF Office of Research - Innocenti, 2018. "An Unfair Start: Inequality in Children's Education in Rich Countries," Papers inreca995, Innocenti Report Card.
    2. John Jerrim & Anna Vignoles, 2013. "Social mobility, regression to the mean and the cognitive development of high ability children from disadvantaged homes," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(4), pages 887-906, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Steve Agnew & Tom Coupé & Cassia-Rose Hingston, 2022. "Predictors of School Exclusion as a Disciplinary Measure in New Zealand: A Maori, Pacific Peoples and Pakeha Comparison," Working Papers in Economics 22/14, University of Canterbury, Department of Economics and Finance.
    2. Emilia Del Bono & Marco Francesconi & Yvonne Kelly & Amanda Sacker, 2016. "Early Maternal Time Investment and Early Child Outcomes," Economic Journal, Royal Economic Society, vol. 126(596), pages 96-135, October.
    3. John Jerrim & Anna Vignoles & Raghu Lingam & Angela Friend, 2013. "The socio-economic gradient in children's reading skills and the role of genetics," DoQSS Working Papers 13-10, Quantitative Social Science - UCL Social Research Institute, University College London.
    4. Ã lvaro Choi & John Jerrim, 2015. "The use (and misuse) of PISA in guiding policy reform: the case of Spain?," DoQSS Working Papers 15-04, Quantitative Social Science - UCL Social Research Institute, University College London.
    5. Claire Crawford & Lindsey Macmillan & Anna Vignoles, 2015. "When and why do initially high attaining poor children fall behind?," DoQSS Working Papers 15-08, Quantitative Social Science - UCL Social Research Institute, University College London.
    6. Hill, Susan M. & Byrne, Matthew F. & Wenden, Elizabeth & Devine, Amanda & Miller, Margaret & Quinlan, Henrietta & Cross, Donna & Eastham, Judy & Chester, Miranda, 2023. "Models of school breakfast program implementation in Western Australia and the implications for supporting disadvantaged students," Children and Youth Services Review, Elsevier, vol. 145(C).
    7. John Jerrim & Sam Sims, 2020. "Grammar schools: Socio-economic differences in entrance rates and the association with socio-emotional outcomes," DoQSS Working Papers 20-11, Quantitative Social Science - UCL Social Research Institute, University College London.
    8. Contini, Dalit & Grand, Elisa, 2013. "On Estimating Achievement Dynamic Models from Repeated Cross-Sections," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201343, University of Turin.
    9. Zlata Bruckauf & Yekaterina Chzhen & UNICEF Innocenti Research Centre, 2016. "Poverty and Children’s Cognitive Trajectories: Evidence from the United Kingdom Millennium Cohort Study," Papers inwopa839, Innocenti Working Papers.
    10. David Madden, 2022. "The socio‐economic gradient of cognitive test scores: evidence from two cohorts of Irish children," Fiscal Studies, John Wiley & Sons, vol. 43(3), pages 265-290, September.
    11. Zlata Bruckauf & Yekaterina Chzhen & UNICEF Innocenti Research Centre, 2016. "Education for All? Measuring inequality of educational outcomes among 15-year-olds across 39 industrialized nations," Papers inwopa843, Innocenti Working Papers.
    12. Alcott, Benjamin & Rose, Pauline, 2017. "Learning in India’s primary schools: How do disparities widen across the grades?," International Journal of Educational Development, Elsevier, vol. 56(C), pages 42-51.
    13. Laura Outhwaite & Jake Anders & Jo Van Herwegen, 2022. "Mathematics Attainment Falls Behind Reading in the Early Primary School Years," CEPEO Working Paper Series 22-06, UCL Centre for Education Policy and Equalising Opportunities, revised May 2022.
    14. Vik, Frøydis Nordgård & Nilsen, Trude & Øverby, Nina Cecilie, 2022. "Aspects of nutritional deficits and cognitive outcomes – Triangulation across time and subject domains among students and teachers in TIMSS," International Journal of Educational Development, Elsevier, vol. 89(C).
    15. repec:esx:essedp:756 is not listed on IDEAS
    16. Marcus Munafò & Neil M. Davies & George Davey Smith, 2020. "Can genetics reveal the causes and consequences of educational attainment?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 681-688, February.
    17. Nicole Black & Danusha Jayawardana & Gawain Heckley, 2023. "Children’s Time Allocation and the Socioeconomic Gap in Human Capital," Papers 2023-06, Centre for Health Economics, Monash University.
    18. Álvaro Choi & John Jerrim, 2015. "The use (and misuse) of Pisa in guiding policy reform: the case of Spain," Working Papers 2015/6, Institut d'Economia de Barcelona (IEB).
    19. repec:cep:spccrp:20 is not listed on IDEAS
    20. Tarshish, Noam, 2019. "How friendly are OECD countries towards children? Conceptualization and measuring issues," Children and Youth Services Review, Elsevier, vol. 103(C), pages 156-165.
    21. Crawford, Claire & Macmillan, Lindsey & Vignoles, Anna F., 2015. "When and why do initially high attaining poor children fall behind?," LSE Research Online Documents on Economics 121535, London School of Economics and Political Science, LSE Library.
    22. Thomas, Michael S.C., 2018. "A neurocomputational model of developmental trajectories of gifted children under a polygenic model: When are gifted children held back by poor environments?," Intelligence, Elsevier, vol. 69(C), pages 200-212.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0260788. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.