IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v98y2023ics0160289623000351.html
   My bibliography  Save this article

Maternal supportiveness is predictive of childhood general intelligence

Author

Listed:
  • Dunkel, Curtis S.
  • van der Linden, Dimitri
  • Kawamoto, Tetsuya

Abstract

Data from the Early Head Start Research and Evaluation Project (N = 1075) were used to test the hypothesis that maternal supportiveness (measured at three waves from 14 to 36 months) is positively and prospectively associated with a child's general intelligence (measured at five waves from 14 months to 10 years). Bivariate correlations showed that maternal supportiveness was consistently and positively associated with a child's general intelligence. For example, maternal supportiveness as measured at 14 months was correlated with a child's general intelligence at age 10; r = 0.35. Results of autoregressive cross-lagged panel models showed maternal supportiveness directly predicted future general intelligence through age four and indirectly, via age four general intelligence, up to age 10. Additional analyses verified that the effect of maternal supportiveness was on general intelligence and not specific abilities. The results point to the importance of maternal supportiveness on general intelligence in the first decade of life.

Suggested Citation

  • Dunkel, Curtis S. & van der Linden, Dimitri & Kawamoto, Tetsuya, 2023. "Maternal supportiveness is predictive of childhood general intelligence," Intelligence, Elsevier, vol. 98(C).
  • Handle: RePEc:eee:intell:v:98:y:2023:i:c:s0160289623000351
    DOI: 10.1016/j.intell.2023.101754
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289623000351
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intell.2023.101754?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    2. Guang Guo & Kathleen Harris, 2000. "The mechanisms mediating the effects of poverty on children’s intellectual development," Demography, Springer;Population Association of America (PAA), vol. 37(4), pages 431-447, November.
    3. repec:mpr:mprres:5983 is not listed on IDEAS
    4. Ledyard Tucker & Charles Lewis, 1973. "A reliability coefficient for maximum likelihood factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 38(1), pages 1-10, March.
    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. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    2. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    3. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    4. Nuanphromsakul, Kajohnjak & Szczepańska-Woszczyna, Katarzyna & Kot, Sebastian & Chaveesuk, Singha & Chaiyasoonthorn, Wornchanok, 2022. "Sustainability of Rubber Farmers Cooperatives: Empirical Evaluation of Determining Factors," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 14(4), December.
    5. Mark Shevlin & David Boyda & James Houston & Jamie Murphy, 2015. "Measurement of the psychosis continuum: Modelling the frequency and distress of subclinical psychotic experiences," Psychosis, Taylor & Francis Journals, vol. 7(2), pages 108-118, April.
    6. Ibrahim A. Elshaer & Alaa M. S. Azazz & Yahdih Semlali & Mahmoud A. Mansour & Mohammed N. Elziny & Sameh Fayyad, 2024. "The Nexus between Green Transformational Leadership, Employee Behavior, and Organizational Support in the Hospitality Industry," Administrative Sciences, MDPI, vol. 14(6), pages 1-22, May.
    7. E. Huebner & Rich Gilman & James Laughlin, 1999. "A Multimethod Investigation of the Multidimensionality of Children's Well-Being Reports: Discriminant Validity of Life Satisfaction and Self-Esteem," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 46(1), pages 1-22, January.
    8. Ali Safarnejad & Jose-Antonio Izazola-Licea, 2017. "Direct and indirect effects of enablers on HIV testing, initiation and retention in antiretroviral treatment and AIDS related mortality," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-15, February.
    9. Lili Tian & Li Zhang & E. Scott Huebner & Xiaoting Zheng & Wang Liu, 2016. "The Longitudinal Relationship Between School Belonging and Subjective Well-Being in School Among Elementary School Students," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 11(4), pages 1269-1285, December.
    10. Ronald S. Burt, 1973. "Confirmatory Factor-Analytic Structures and the Theory Construction Process," Sociological Methods & Research, , vol. 2(2), pages 131-190, November.
    11. Christopher J Greenwood & George J Youssef & Primrose Letcher & Jacqui A Macdonald & Lauryn J Hagg & Ann Sanson & Jenn Mcintosh & Delyse M Hutchinson & John W Toumbourou & Matthew Fuller-Tyszkiewicz &, 2020. "A comparison of penalised regression methods for informing the selection of predictive markers," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    12. Liangyuan Hu & Lihua Li, 2022. "Using Tree-Based Machine Learning for Health Studies: Literature Review and Case Series," IJERPH, MDPI, vol. 19(23), pages 1-13, December.
    13. Norah Alyabs & Sy Han Chiou, 2022. "The Missing Indicator Approach for Accelerated Failure Time Model with Covariates Subject to Limits of Detection," Stats, MDPI, vol. 5(2), pages 1-13, May.
    14. Sulaiman Olusegun Atiku & Ziska Fields & Ethel Abe, 2017. "Cultural Values and Human Resource Outcomes in the Nigerian Banking Industry," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 67(2), pages 26-46, April-Jun.
    15. Feldkircher, Martin, 2014. "The determinants of vulnerability to the global financial crisis 2008 to 2009: Credit growth and other sources of risk," Journal of International Money and Finance, Elsevier, vol. 43(C), pages 19-49.
    16. Evangeline I. Chirayil & Claire L. Thompson & Sue Burney, 2014. "Predicting Human Papilloma Virus Vaccination and Pap Smear Screening Intentions Among Young Singaporean Women Using the Theory of Planned Behavior," SAGE Open, , vol. 4(4), pages 21582440145, October.
    17. Chong, Melody P.M. & Muethel, Miriam & Richards, Malika & Fu, Ping Ping & Peng, Tai-Kuang & Shang, Yu Fan & Caldas, Miguel P., 2013. "Influence behaviors and employees’ reactions: An empirical test among six societies based on a transactional–relational contract model," Journal of World Business, Elsevier, vol. 48(3), pages 373-384.
    18. Jon W. Hoelter, 1983. "The Analysis of Covariance Structures," Sociological Methods & Research, , vol. 11(3), pages 325-344, February.
    19. Bach Quang Ho & Yuki Inoue, 2020. "Driving Network Externalities in Education for Sustainable Development," Sustainability, MDPI, vol. 12(20), pages 1-16, October.
    20. Eunsil Seok & Akhgar Ghassabian & Yuyan Wang & Mengling Liu, 2024. "Statistical Methods for Modeling Exposure Variables Subject to Limit of Detection," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 16(2), pages 435-458, July.

    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:eee:intell:v:98:y:2023:i:c:s0160289623000351. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    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.