IDEAS home Printed from https://ideas.repec.org/a/eee/intell/v98y2023ics0160289623000326.html
   My bibliography  Save this article

The cross-cultural generalizability of cognitive ability measures: A systematic literature review

Author

Listed:
  • Wilson, Christopher J.
  • Bowden, Stephen C.
  • Byrne, Linda K.
  • Joshua, Nicole R.
  • Marx, Wolfgang
  • Weiss, Lawrence G.

Abstract

Examining factorial invariance provides the strongest test of the generalizability of psychological constructs across populations and should be investigated prior to cross-cultural interpretation of cognitive assessments. The aim of this systematic review was to critically evaluate the current evidence regarding the factorial invariance and the generalizability of cognition models across cultures. The review was structured using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search identified 57 original studies examining the factorial invariance of cognitive ability assessments across cultures. The results were strongly supportive of the cross-cultural generalizability of the underlying cognitive model. Ten studies found configural invariance, 20 studies found weak or partial weak factorial invariance, 12 found strong or partial strong factorial invariance, and 13 found strict factorial invariance. However, the quality of the factorial invariance analyses varied between studies, with some analyses not adopting the hierarchical approach to factorial invariance analysis, leading to ambiguous results. No study that provided interpretable results in terms of the hierarchical approach to factorial invariance found a lack of factorial invariance. Overall, the results of this review suggest that i) the factor analytic models of cognitive abilities generalize across cultures, ii) the use of the hierarchical approach to factorial invariance is likely to find strong or strict factorial invariance, iii) the results are compatible with well-established Cattell-Horn-Carroll constructs being invariant across cultures. Future research into factorial invariance should follow the hierarchical analytic approach so as not to misestimate factorial invariance. Studies should also use the Cattell-Horn-Carroll taxonomy to systematize intelligence research.

Suggested Citation

  • Wilson, Christopher J. & Bowden, Stephen C. & Byrne, Linda K. & Joshua, Nicole R. & Marx, Wolfgang & Weiss, Lawrence G., 2023. "The cross-cultural generalizability of cognitive ability measures: A systematic literature review," Intelligence, Elsevier, vol. 98(C).
  • Handle: RePEc:eee:intell:v:98:y:2023:i:c:s0160289623000326
    DOI: 10.1016/j.intell.2023.101751
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0160289623000326
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intell.2023.101751?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. William Meredith, 1964. "Notes on factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 177-185, June.
    2. Jasmin T Gygi & Elodie Fux & Alexander Grob & Priska Hagmann-von Arx, 2016. "Measurement Invariance and Latent Mean Differences in the Reynolds Intellectual Assessment Scales (RIAS): Does the German Version of the RIAS Allow a Valid Assessment of Individuals with a Migration B," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-13, November.
    3. William Meredith, 1993. "Measurement invariance, factor analysis and factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 58(4), pages 525-543, December.
    4. Charlotte Wray & Alysse Kowalski & Feziwe Mpondo & Laura Ochaeta & Delia Belleza & Ann DiGirolamo & Rachel Waford & Linda Richter & Nanette Lee & Gaia Scerif & Aryeh D Stein & Alan Stein & COHORTS, 2020. "Executive functions form a single construct and are associated with schooling: Evidence from three low- and middle- income countries," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-14, November.
    5. William Meredith, 1964. "Rotation to achieve factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 29(2), pages 187-206, June.
    6. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    7. Caemmerer, Jacqueline M. & Keith, Timothy Z. & Reynolds, Matthew R., 2020. "Beyond individual intelligence tests: Application of Cattell-Horn-Carroll Theory," Intelligence, Elsevier, vol. 79(C).
    8. A. Nayena Blankson & John J. McArdle, 2015. "Measurement Invariance of Cognitive Abilities Across Ethnicity, Gender, and Time Among Older Americans," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 70(3), pages 386-397.
    9. Bryan, Victoria M. & Mayer, John D., 2020. "A meta-analysis of the correlations among broad intelligences: Understanding their relations," Intelligence, Elsevier, vol. 81(C).
    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. Adam Carle, 2010. "Interpreting the results of studies using latent variable models to assess data quality: an empirical example using confirmatory factor analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 44(3), pages 483-497, April.
    2. Hao Wu & Ryne Estabrook, 2016. "Identification of Confirmatory Factor Analysis Models of Different Levels of Invariance for Ordered Categorical Outcomes," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 1014-1045, December.
    3. Johan Oud & Manuel Voelkle, 2014. "Do missing values exist? Incomplete data handling in cross-national longitudinal studies by means of continuous time modeling," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(6), pages 3271-3288, November.
    4. Bruce Bloxom, 1972. "Alternative approaches to factorial invariance," Psychometrika, Springer;The Psychometric Society, vol. 37(4), pages 425-440, December.
    5. Ji Hoon Ryoo & Sunhee Park & Hongwook Suh & Jaehwa Choi & Jongkyum Kwon, 2022. "Development of a New Measure of Cognitive Ability Using Automatic Item Generation and Its Psychometric Properties," SAGE Open, , vol. 12(2), pages 21582440221, April.
    6. Kano, Yutaka & Takai, Keiji, 2011. "Analysis of NMAR missing data without specifying missing-data mechanisms in a linear latent variate model," Journal of Multivariate Analysis, Elsevier, vol. 102(9), pages 1241-1255, October.
    7. K. Jöreskog, 1971. "Simultaneous factor analysis in several populations," Psychometrika, Springer;The Psychometric Society, vol. 36(4), pages 409-426, December.
    8. Vieira, Bruno Hebling & Pamplona, Gustavo Santo Pedro & Fachinello, Karim & Silva, Alice Kamensek & Foss, Maria Paula & Salmon, Carlos Ernesto Garrido, 2022. "On the prediction of human intelligence from neuroimaging: A systematic review of methods and reporting," Intelligence, Elsevier, vol. 93(C).
    9. Scholderer, Joachim & Grunert, Klaus G. & Brunso, Karen, 2005. "A procedure for eliminating additive bias from cross-cultural survey data," Journal of Business Research, Elsevier, vol. 58(1), pages 72-78, January.
    10. Roger Millsap, 2007. "Invariance in Measurement and Prediction Revisited," Psychometrika, Springer;The Psychometric Society, vol. 72(4), pages 461-473, December.
    11. Jeanne A. Teresi & Chun Wang & Marjorie Kleinman & Richard N. Jones & David J. Weiss, 2021. "Differential Item Functioning Analyses of the Patient-Reported Outcomes Measurement Information System (PROMIS®) Measures: Methods, Challenges, Advances, and Future Directions," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 674-711, September.
    12. Piia Seppälä & Saija Mauno & Taru Feldt & Jari Hakanen & Ulla Kinnunen & Asko Tolvanen & Wilmar Schaufeli, 2009. "The Construct Validity of the Utrecht Work Engagement Scale: Multisample and Longitudinal Evidence," Journal of Happiness Studies, Springer, vol. 10(4), pages 459-481, August.
    13. Cernat, Alexandru, 2015. "Using equivalence testing to disentangle selection and measurement in mixed modes surveys," Understanding Society Working Paper Series 2015-01, Understanding Society at the Institute for Social and Economic Research.
    14. İlkay Unay-Gailhard & Mark A. Brennen, 2022. "How digital communications contribute to shaping the career paths of youth: a review study focused on farming as a career option," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 39(4), pages 1491-1508, December.
    15. Mahin Ghafari & Vali Baigi & Zahra Cheraghi & Amin Doosti-Irani, 2016. "The Prevalence of Asymptomatic Bacteriuria in Iranian Pregnant Women: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-10, June.
    16. Elizabeth T Cafiero-Fonseca & Andrew Stawasz & Sydney T Johnson & Reiko Sato & David E Bloom, 2017. "The full benefits of adult pneumococcal vaccination: A systematic review," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-23, October.
    17. Santos Urbina & Sofía Villatoro & Jesús Salinas, 2021. "Self-Regulated Learning and Technology-Enhanced Learning Environments in Higher Education: A Scoping Review," Sustainability, MDPI, vol. 13(13), pages 1-12, June.
    18. Oded Berger-Tal & Alison L Greggor & Biljana Macura & Carrie Ann Adams & Arden Blumenthal & Amos Bouskila & Ulrika Candolin & Carolina Doran & Esteban Fernández-Juricic & Kiyoko M Gotanda & Catherine , 2019. "Systematic reviews and maps as tools for applying behavioral ecology to management and policy," Behavioral Ecology, International Society for Behavioral Ecology, vol. 30(1), pages 1-8.
    19. Nadine Desrochers & Adèle Paul‐Hus & Jen Pecoskie, 2017. "Five decades of gratitude: A meta‐synthesis of acknowledgments research," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2821-2833, December.
    20. Alene Sze Jing Yong & Yi Heng Lim & Mark Wing Loong Cheong & Ednin Hamzah & Siew Li Teoh, 2022. "Willingness-to-pay for cancer treatment and outcome: a systematic review," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 1037-1057, August.

    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:s0160289623000326. 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.