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Genetic differential susceptibility in literacy-delayed children: A randomized controlled trial on emergent literacy in kindergarten

Published online by Cambridge University Press:  02 February 2015

Rachel D. Plak ,
Cornelia A. T. Kegel  and
Adriana G. Bus
Rachel D. Plak
Affiliation:
Leiden University
Cornelia A. T. Kegel
Affiliation:
Leiden University
Adriana G. Bus*
Affiliation:
Leiden University
*
Address correspondence and reprint requests to: Adriana G. Bus, Department of Education and Child Studies, Leiden University, Wassenaarseweg 52, PO Box 9555, 2300 RB Leiden, The Netherlands; E-mail: [email protected].
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Abstract

In this randomized controlled trial, 508 5-year-old kindergarten children participated, of whom 257 were delayed in literacy skills because they belonged to the lowest quartile of a national standard literacy test. We tested the hypothesis that some children are more susceptible to school-entry educational interventions than their peers due to their genetic makeup, and thus whether the dopamine receptor D4 gene moderated intervention effects. Children were randomly assigned to a control condition or one of two interventions involving computer programs tailored to the literacy needs of delayed pupils: Living Letters for alphabetic knowledge and Living Books for text comprehension. Effects of Living Books met the criteria of differential susceptibility. For carriers of the dopamine receptor D4 gene seven-repeat allele (about one-third of the delayed group), the Living Books program was an important addition to the common core curriculum in kindergarten (effect size d = 0.56), whereas the program did not affect the other children (d = –0.09). The same seven-repeat carriers benefited more from Living Letters than did the noncarriers, as reflected in effect sizes of 0.63 and 0.34, respectively, although such differences did not fulfill the statistical criteria for differential susceptibility. The implications of differential susceptibility for education and regarding the crucial question “what works for whom?” are discussed.

Type
Special Section Articles
Information
Development and Psychopathology , Volume 27 , Issue 1: What Works for Whom? Genetic Moderation of Intervention Efficacy , February 2015 , pp. 69 - 79
Copyright
Copyright © Cambridge University Press 2015 

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References

Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2006). Gene–environment interaction of the dopamine D4 receptor (DRD4) and observed maternal insensitivity predicting externalizing behavior in pre-schoolers. Developmental Psychobiology, 48, 406–409. doi:10.1002/dev.20152CrossRefGoogle Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to rearing environment depending on dopamine-related genes: New evidence and a meta-analysis. Development and Psychopathology, 23, 39–52. doi:10.1017/S0954579410000635Google Scholar
Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (in press). The hidden efficacy of interventions: Gene × Environment experiments from a differential susceptibility perspective. Annual Review of Psychology.Google Scholar
Barnett, W., Jung, K., Yarosz, D., Thomas, J., Hornbeck, A., Stechuk, R., et al. (2008). Educational effects of the Tools of the Mind curriculum: A randomized trial. Early Childhood Research Quarterly, 23, 299–313. doi:10.1016/j.ecresq.2008.03.001Google Scholar
Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2007). For better and for worse: Differential susceptibility to environmental influences. Current Directions in Psychological Science, 16, 300–304. doi:10.1111/j.1467-8721.2007.00525.xGoogle Scholar
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummet, B., & Williams, R. (2009). Vulnerability genes or plasticity genes? Molecular Psychiatry, 14, 746–754. doi:10.1038/mp.2009.44Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis–stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. doi:10.1037/a0017376Google Scholar
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience and dysregulation: Phenotypic plasticity and human development. Development and Psychopathology, 25, 1243–1261. doi:10.1017/S095457941300059XGoogle Scholar
Belsky, J., Pluess, M., & Widaman, K. F. (2013). Confirmatory and competitive evaluation of alternative gene–environment interaction hypotheses. Journal of Child Psychology and Psychiatry, 54, 1135–1143. doi:10.1111/jcpp.12075CrossRefGoogle ScholarPubMed
Bodrova, E., & Leong, D. J. (2006). Vygotskian perspectives on teaching and learning early literacy. In Dickinson, D. K. & Neuman, S. B. (Eds.), Handbook of early literacy research (Vol. 2, pp. 243–256). New York: Guilford Press.Google Scholar
Both-De Vries, A. C., & Bus, A. G. (2008). Name writing: A first step to phonetic writing? Does the name have a special role in understanding the symbolic function of writing? Literacy Teaching and Learning, 12, 37–55.Google Scholar
Both-De Vries, A. C., & Bus, A. G. (2010). The proper name as starting point for basic reading skills. Reading and Writing, 23, 173–187. doi:10.1007/s11145-008-9158-2Google Scholar
Bus, A. G., Takacs, Z. K., & Kegel, C. A. T. (in press). Affordances and limitations of electronic storybooks for young children's literacy: Consequences for engineering apps. Developmental Review.Google Scholar
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.Google Scholar
Cronbach, L. J., & Snow, R. E. (1977). Aptitudes and instructional methods. New York: Irvington.Google Scholar
Ellis, B. J., Boyce, W. T., Belsky, J., Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2011). Differential susceptibility to the environment: An evolutionary–neurodevelopmental theory. Development and Psychopathology, 23, 7–28. doi:10.1017/S0954579410000611Google Scholar
Ferreiro, E., & Teberosky, A. (1982). Literacy before schooling. Exeter, NH: Heinemann.Google Scholar
Goswami, U., & Bryant, P. E. (1990). Phonological skills and learning to read. Hillsdale, NJ: Erlbaum.Google Scholar
Howe, G. W., Beach, S. R. H., & Brody, G. H. (2010). Microtrial methods for translating gene–environment dynamics into preventive interventions. Prevention Science, 11, 343–354. doi:10.1007/s11121-010-0177-2Google Scholar
Hsiung, G. Y. R., Kaplan, B. J., Petryshen, T. L., Lu, S., & Field, L. L. (2004). A dyslexia susceptibility locus (DYX7) linked to dopamine D4 receptor (DRD4) region on chromosome 11p15.5. American Journal of Medical Genetics, 125B, 112–119. doi:10.1002/ajmg.b.20082Google Scholar
Hulme, C., Bowyer-Crane, C., Carroll, J. M., Duff, F. J., & Snowling, M. (2012). The causal role of phoneme awareness and letter–sound knowledge in learning to read: Combining intervention studies with mediation analysis. Psychological Science, 23, 572–577. doi:10.1177/0956797611435921Google Scholar
Justice, L. M., Chow, S. M., Capellini, C., Flanigan, K., & Colton, S. (2003). Emergent literacy intervention for vulnerable preschoolers: Relative effects of two approaches. American Journal of Speech–Language Pathology, 12, 320–332. doi:10.1044/1058-0360(2003/078)Google Scholar
Kamil, M. L., Intrator, S. M., & Kim, H. S. (2000). The effects of other technologies on literacy and literacy learning. In Kamil, M. L., Mosenthal, P. B., Pearson, P. D., & Barr, R. (Eds.), Handbook of reading research (Vol. 3, pp. 771–778). Mahwah, NJ: Erlbaum.Google Scholar
Kegel, C. A. T., & Bus, A. G. (2012). Online tutoring as a pivotal quality of web-based early literacy programs. Journal of Educational Psychology, 104, 182–192. doi:10.1037/a0025849Google Scholar
Kegel, C. A. T., & Bus, A. G. (2013). Links between DRD4, executive attention, and alphabetic skills in a nonclinical sample. Journal of Child Psychology and Psychiatry, 54, 305–312. doi:10.1111/j.1469-7610.2012.02604.xGoogle Scholar
Kegel, C. A. T., Bus, A. G., & van IJzendoorn, M. H. (2011). Differential susceptibility in early literacy instruction through computer games: The role of the dopamine D4 receptor gene (DRD4). Mind, Brain, and Education, 5, 71–78. doi:10.1111/j.1751-228X.2011.01112.xGoogle Scholar
Kegel, C. A. T., Van der Kooy-Hofland, V. A. C., & Bus, A. G. (2009). Improving early phoneme skills with a computer program: Differential effects of regulatory skills. Learning and Individual Differences, 19, 549–554. doi:10.1016/j.lindif.2009.07.002Google Scholar
Keller, M. C. (2014). Gene × Environment interaction studies have not properly controlled for potential confounders: The problem and the (simple) solution. Biological Psychiatry, 75, 18–42. doi:10.1016/j.biopsych.2013.09.006Google Scholar
Lansink, N., & Hemker, B. (2012). Wetenschappelijke verantwoording van de toetsen Taal voor Kleuters voor groep 1 en 2 uit het Cito volgsysteem primair onderwijs [Scientific justification of literacy tests for the kindergarten years]. Arnhem, The Netherlands: Cito.Google Scholar
Levin, I., Both-De Vries, A. C., Aram, D., & Bus, A. G. (2005). Writing starts with own name writing: From scribbling to conventional spelling in Israeli and Dutch children. Applied Psycholinguistics, 26, 463–477. doi:10.1017/S0142716405050253Google Scholar
Lonigan, C. J., Farver, J. M., Phillips, B. M., & Clancy-Menchetti, J. (2011). Promoting the development of preschool children's emergent literacy skills: A randomized evaluation of a literacy-focused curriculum and two professional development models. Reading and Writing, 24, 305–337. doi:10.1007/s11145-009-9214-6Google Scholar
Luke, D. A. (2004). Multilevel modeling. Thousand Oaks, CA: Sage.Google Scholar
National Center for Family Literacy. (2008). Developing early literacy: Report of the National Early Literacy Panel: A scientific synthesis of early literacy development and implications for intervention. Washington, DC: National Institute for Literacy.Google Scholar
Obradović, J., Bush, N. R., Stamperdahl, J., Adler, N. E., & Boyce, W. T. (2010). Biological sensitivity to context: The interactive effects of stress reactivity and family adversity on socio-emotional behavior and school readiness. Child Development, 81, 270–289. doi:10.1111/j.1467-8624.2009.01394.xGoogle Scholar
Paris, S. G. (2005). Reinterpreting the development of reading skills. Reading Research Quarterly, 40, 184–202. doi:10.1598/RRQ.40.2.3Google Scholar
Robbins, T. W., & Everitt, B. J. (1999). Drug addiction: Bad habits add up. Nature, 398, 567–570. doi:10.1038/19208Google Scholar
Snow, C. E., Burns, M. S., & Griffin, P. (Eds.). (1998). Preventing reading difficulties in young children. Washington, DC: National Academy Press.Google Scholar
Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360–407. doi:10.1598/RRQ.21.4.1Google Scholar
Tripp, G., & Wickens, J. R. (2008). Dopamine transfer deficit: A neurobiological theory of altered reinforcement mechanisms in ADHD. Child Psychology and Psychiatry, 49, 691–704. doi:10.1111/j.1469-7610.2007.01851.xGoogle Scholar
van Breukelen, G. J. P., & van Dijk, K. R. A. (2007). Use of covariates in randomized controlled trials. Journal of the International Neuropsychological Society, 13, 903–904. doi:10.10170S1355617707071147Google Scholar
van den Berg, H., & Bus, A. G. (in press). Beneficial effects of BookStart in temperamentally highly reactive infants. Learning and Individual Differences.Google Scholar
van der Kooy-Hofland, V. A. C., Bus, A. G., & Roskos, K. A. (2012). Effects of a brief but intensive remedial computer intervention in a sub-sample of kindergartners with early literacy delays. Reading and Writing, 25, 1479–1497. doi:10.1007/s11145-011-9328-5Google Scholar
van IJzendoorn, M. H., & Bakermans-Kranenburg, M. J. (2012). Differential susceptibility experiments: Going beyond correlational evidence: Comment on beyond mental health, differential susceptibility articles. Developmental Psychology, 48, 769–774. doi:10.1037/a0027536Google Scholar
van IJzendoorn, M. H., & Bakermans-Kranenburg, M. J. (2015). Genetic differential susceptibility on trial: Meta-analytic support from randomized controlled experiments. Development and Psychopathology, 27, 151–162.Google Scholar
van IJzendoorn, M., Bakermans-Kranenburg, M., Belsky, J., Beach, S., Brody, G., Dodge, K., et al. (2011). Gene-by-environment experiments: A new approach to find missing heritability. Nature Reviews Genetics, 12, 881. doi:10.1038/nrg2764-c1Google Scholar
Wasserman, T., & Drucker Wasserman, L. (2012). The sensitivity and specificity of neuropsychological tests in the diagnosis of attention deficit hyperactivity diagnosis. Applied Neuropsychology: Child, 1, 90–99. doi:10.1080/21622965.2012.702025Google Scholar
Widaman, K. F., Helm, J. L., Castro-Schilo, L., Pluess, M., Stallings, M. C., & Belsky, J. (2012). Distinguishing ordinal and disordinal interactions. Psychological Methods, 17, 615–622. doi:10.1037/a0030003Google Scholar