IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v68y2018icp58-65.html
   My bibliography  Save this article

The predictive value of developmental assessments at 1 and 2 for intelligence quotients at 6

Author

Listed:
  • Girault, Jessica B.
  • Langworthy, Benjamin W.
  • Goldman, Barbara D.
  • Stephens, Rebecca L.
  • Cornea, Emil
  • Steven Reznick, J.
  • Fine, Jason
  • Gilmore, John H.

Abstract

Intelligence is an important individual difference factor related to mental health, academic achievement, and life success, yet there is a lack of research into its early cognitive predictors. This study investigated the predictive value of infant developmental assessment scores for school-age intelligence in a large, heterogeneous sample of single- and twin-born subjects (N = 521). We found that Early Learning Composite (ELC) scores from the Mullen Scales of Early Learning have similar predictive power to that of other infant tests. ELC scores at age 2 were predictive of Stanford-Binet abbreviated intelligence (ABIQ) scores at age 6 (r = 0.46) even after controlling for sex, gestation number, and parental education. ELC scores at age 1 were less predictive of 6-year ABIQ scores (r = 0.17). When the sample was split to test robustness of findings, we found that results from the full sample replicated in a subset of children born at ≥32 weeks gestation without birth complications (n = 405), though infant cognitive scores did not predict IQ in a subset born very prematurely or with birth complications (n = 116). Scores at age 2 in twins and singletons showed similar predictive ability for scores at age 6, though twins had particularly high correlations between ELC at age 1 and ABIQ at age 6.

Suggested Citation

  • Girault, Jessica B. & Langworthy, Benjamin W. & Goldman, Barbara D. & Stephens, Rebecca L. & Cornea, Emil & Steven Reznick, J. & Fine, Jason & Gilmore, John H., 2018. "The predictive value of developmental assessments at 1 and 2 for intelligence quotients at 6," Intelligence, Elsevier, vol. 68(C), pages 58-65.
    • Handle: RePEc:eee:intell:v:68:y:2018:i:c:p:58-65
    DOI: 10.1016/j.intell.2018.03.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289617302908
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.intell.2018.03.003?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. P. Shaw & D. Greenstein & J. Lerch & L. Clasen & R. Lenroot & N. Gogtay & A. Evans & J. Rapoport & J. Giedd, 2006. "Intellectual ability and cortical development in children and adolescents," Nature, Nature, vol. 440(7084), pages 676-679, March.
    2. Ian J. Deary & Jian Yang & Gail Davies & Sarah E. Harris & Albert Tenesa & David Liewald & Michelle Luciano & Lorna M. Lopez & Alan J. Gow & Janie Corley & Paul Redmond & Helen C. Fox & Suzanne J. Row, 2012. "Genetic contributions to stability and change in intelligence from childhood to old age," Nature, Nature, vol. 482(7384), pages 212-215, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matthew Bluett-Duncan & M Thomas Kishore & Divya M Patil & Veena A Satyanarayana & Helen Sharp, 2021. "A systematic review of the association between perinatal depression and cognitive development in infancy in low and middle-income countries," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-25, June.

    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. Yufik, Yan M., 2013. "Understanding, consciousness and thermodynamics of cognition," Chaos, Solitons & Fractals, Elsevier, vol. 55(C), pages 44-59.
    2. Thomas A. Arcury & Haiying Chen & Sara A. Quandt & Jennifer W. Talton & Kim A. Anderson & Richard P. Scott & Phillip Summers & Paul J. Laurienti, 2023. "Pesticide Exposure among Latinx Children in Rural Farmworker and Urban Non-Farmworker Communities: Associations with Locality and Season," IJERPH, MDPI, vol. 20(9), pages 1-23, April.
    3. Román, Francisco J. & Morillo, Daniel & Estrada, Eduardo & Escorial, Sergio & Karama, Sherif & Colom, Roberto, 2018. "Brain-intelligence relationships across childhood and adolescence: A latent-variable approach," Intelligence, Elsevier, vol. 68(C), pages 21-29.
    4. Silver, Ian A., 2019. "Linear and non-linear: An exploration of the variation in the functional form of verbal IQ and antisocial behavior as adolescents age into adulthood," Intelligence, Elsevier, vol. 76(C), pages 1-1.
    5. Yu, Huihui & McCoach, D. Betsy & Gottfried, Allen W. & Gottfried, Adele Eskeles, 2018. "Stability of intelligence from infancy through adolescence: An autoregressive latent variable model," Intelligence, Elsevier, vol. 69(C), pages 8-15.
    6. Sobia Jamil & Syed Imran Zaman & Yasanur Kayikci & Sharfuddin Ahmed Khan, 2023. "The Role of Green Recruitment on Organizational Sustainability Performance: A Study within the Context of Green Human Resource Management," Sustainability, MDPI, vol. 15(21), pages 1-31, November.
    7. Cherrie, Mark P.C. & Shortt, Niamh K. & Mitchell, Richard J. & Taylor, Adele M. & Redmond, Paul & Thompson, Catharine Ward & Starr, John M. & Deary, Ian J. & Pearce, Jamie R., 2018. "Green space and cognitive ageing: A retrospective life course analysis in the Lothian Birth Cohort 1936," Social Science & Medicine, Elsevier, vol. 196(C), pages 56-65.
    8. Peter M Visscher & Gibran Hemani & Anna A E Vinkhuyzen & Guo-Bo Chen & Sang Hong Lee & Naomi R Wray & Michael E Goddard & Jian Yang, 2014. "Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples," PLOS Genetics, Public Library of Science, vol. 10(4), pages 1-10, April.
    9. van der Linden, Dimitri & Dunkel, Curtis S. & Madison, Guy, 2017. "Sex differences in brain size and general intelligence (g)," Intelligence, Elsevier, vol. 63(C), pages 78-88.
    10. de Souza, Erick Almeida & Silva, Stéphanie Andrade & Vieira, Bruno Hebling & Salmon, Carlos Ernesto Garrido, 2023. "fMRI functional connectivity is a better predictor of general intelligence than cortical morphometric features and ICA parcellation order affects predictive performance," Intelligence, Elsevier, vol. 97(C).
    11. T. Tony Cai & Weidong Liu, 2016. "Large-Scale Multiple Testing of Correlations," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 111(513), pages 229-240, March.
    12. Xinyuan Liang & Lianglong Sun & Xuhong Liao & Tianyuan Lei & Mingrui Xia & Dingna Duan & Zilong Zeng & Qiongling Li & Zhilei Xu & Weiwei Men & Yanpei Wang & Shuping Tan & Jia-Hong Gao & Shaozheng Qin , 2024. "Structural connectome architecture shapes the maturation of cortical morphology from childhood to adolescence," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    13. Drakulich, Stefan & Sitartchouk, Arseni & Olafson, Emily & Sarhani, Reda & Thiffault, Anne-Charlotte & Chakravarty, Mallar & Evans, Alan C. & Karama, Sherif, 2022. "General cognitive ability and pericortical contrast," Intelligence, Elsevier, vol. 91(C).
    14. Cai, T. Tony & Zhang, Anru, 2016. "Inference for high-dimensional differential correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 143(C), pages 107-126.
    15. Cui, Can & Wu, Teresa & Hu, Mengqi & Weir, Jeffery D. & Li, Xiwang, 2016. "Short-term building energy model recommendation system: A meta-learning approach," Applied Energy, Elsevier, vol. 172(C), pages 251-263.
    16. Kocevar, Gabriel & Suprano, Ilaria & Stamile, Claudio & Hannoun, Salem & Fourneret, Pierre & Revol, Olivier & Nusbaum, Fanny & Sappey-Marinier, Dominique, 2019. "Brain structural connectivity correlates with fluid intelligence in children: A DTI graph analysis," Intelligence, Elsevier, vol. 72(C), pages 67-75.

    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:eee:intell:v:68:y:2018:i:c:p:58-65. 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.