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Journal of Youth and Adolescence

, Volume 48, Issue 1, pp 43–55 | Cite as

Structural Home Environment Effects on Developmental Trajectories of Self-Control and Adolescent Risk Taking

  • Christopher HolmesEmail author
  • Alexis Brieant
  • Rachel Kahn
  • Kirby Deater-Deckard
  • Jungmeen Kim-Spoon
Empirical Research

Abstract

Extant literature has demonstrated that self-control is critical for health and adjustment in adolescence. Questions remain regarding whether there are individuals that may be most vulnerable to impaired self-control development and whether aspects of the structural home environment may predict membership in these subgroups, as well as the behavioral consequences of impaired self-control trajectories. The present study utilized growth mixture modeling and data from 1083 individuals (50% female, 82% White) from age 8.5 to 15 years to identify four latent classes of self-control development. Additionally, higher household chaos and lower socioeconomic status at age 8.5 were associated with maladaptive trajectories of self-control at ages 8.5–11.5. In turn, maladaptive self-control trajectories at ages 8.5–11.5 were associated with higher risk taking at age 15. The results highlight the importance of increased structure and support for at-risk youth.

Keywords

SES Household chaos Self-control Risk taking Adolescence 

Notes

Acknowledgements

This work was supported by grants from the National Institute on Drug Abuse awarded to Jungmeen Kim-Spoon/Brooks King-Casas (DA 036017) and Gene Brody (DA 027827), and from the National Institute of Child Health and Human Development awarded to Kirby Deater-Deckard (HD 054481). We thank Kathy Faris for reviewing literature relevant to the current study and Eileen Neubaum Carlan for editorial assistance. The Study of Early Child Care and Youth Development was conducted by the NICHD Early Child Care Research Network, and was supported by NICHD through a cooperative agreement that calls for scientific collaboration between the grantees and the NICHD staff. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development or the National Institutes of Health. The authors thank the study participants and research staff.

Authors’ Contributions

C.H. conceived of the study, participated in its design, performed the statistical analyses and drafted the manuscript; A.B. performed statistical analyses, edited the manuscript, and substantially contributed to the revisions of the manuscript; R.K. participated in the design of the study and helped to draft the manuscript; K.D.D. conceived of the study, participated in the design and interpretation of the data, and edited the manuscript; J.K.S. conceived of the study, participated in the design and interpretation of the data, and edited the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by grants from the National Institute on Drug Abuse awarded to Jungmeen Kim-Spoon/Brooks King-Casas (DA 036017) and Gene Brody (DA 027827), and from the National Institute of Child Health and Human Development awarded to Kirby Deater-Deckard (HD 054481).

Data Sharing and Declaration

The datasets generated and/or analyzed during the current study are available from the Study of Early Child Care and Youth Development within the National Institute of Child Health and Human Development at https://www.icpsr.umich.edu/icpsrweb/ICPSR/series/00233.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Berry, D., McCartney, K., Petrill, S., Deater‐Deckard, K., & Blair, C. (2014). Gene–environment interaction between DRD4 7‐repeat VNTR and early child‐care experiences predicts self‐regulation abilities in prekindergarten. Developmental Psychobiology, 56, 373–391.  https://doi.org/10.1002/dev.21105.CrossRefGoogle Scholar
  2. Blair, C., & Ursache, A. (2011). A bidirectional model of executive functions and self-regulation. In K. D. Vohs & R. F. Baumeister (Eds.), Handbook of self-regulation: research, theory, and applications. 2nd ed. New York, NY: Guilford.Google Scholar
  3. Boelema, S. R., Harakeh, Z., Ormel, J., & Hartman, C. A. (2014). Executive functioning shows differential maturation from early to late adolescence: longitudinal findings from a TRAILS study. Neuropsychology, 28, 177–187.  https://doi.org/10.1037/neu0000049.CrossRefGoogle Scholar
  4. Brody, G. H., Flor, D. L., & Morgan Gibson, N. (1999). Linking maternal efficacy beliefs, developmental goals, parenting practices, and child competence in rural single‐parent African American families. Child Development, 70, 1197–1208.  https://doi.org/10.1111/1467-8624.00087.CrossRefGoogle Scholar
  5. Bronfenbrenner, U. (2001). Growing chaos in the lives of children, youth, and families: how can we turn it around? In J. C. Westman (Ed.), Parenthood in America (pp. 197–210). Madison, WI: University of Wisconsin Press.Google Scholar
  6. Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review, 28, 62–77.  https://doi.org/10.1016/j.dr.2007.08.003.CrossRefGoogle Scholar
  7. Conger, R. D., & Elder, Jr, G. H. (1994). Families in troubled times: adapting to change in rural America. Social Institutions and social change. New York, NY: Aldine de Gruyter.Google Scholar
  8. Crandall, A. A., Magnusson, B. M., & Novilla, M. L. B. (2017). Growth in adolescent self-regulation and impact on sexual risk-taking: a curve-of-factors analysis. Journal of Youth and Adolescence, 47, 1–14.  https://doi.org/10.1007/s10964-017-0706-4.Google Scholar
  9. Evans, G. W. (2006). Child development and the physical environment. Annual Review of Psychology, 57, 423–451.  https://doi.org/10.1146/annurev.psych.57.102904.190057.CrossRefGoogle Scholar
  10. Evans, G. W. & Wachs, T. D. (Eds.) (2010). Chaos and its influence on children’s development. Washington, DC: American Psychological Association.Google Scholar
  11. Evans, G. W., Eckenrode, J., & Marcynyszyn, L. A. (2010). Chaos and the macrosetting: the role of poverty and socioeconomic status. In G. W. Evans & T. D. Wachs (Eds.), Chaos and its influence on children’s development: an ecological perspective (pp. 225-238). 10.1037/12057-014Google Scholar
  12. Evans, G. W., Gonnella, C., Marcynyszyn, L. A., Gentile, L., & Salpekar, N. (2005). The role of chaos in poverty and children’s socioemotional adjustment. Psychological Science, 16, 560–565.  https://doi.org/10.1111/j.0956-7976.2005.01575.x.CrossRefGoogle Scholar
  13. Fabes, R. A., Martin, C. L., & Hanish, L. D. (2009). Children’s behaviors and interactions with peers. In K. H. Rubin, W. M. Bukowski & B. Laursen (Eds.), Handbook of peer interactions, relationships, and groups (pp. 45–62). New York, NY: Guilford.Google Scholar
  14. Fosco, G. M., Frank, J. L., Stormshak, E. A., & Dishion, T. J. (2013). Opening the “Black Box”: family check-up intervention effects on self-regulation that prevents growth in problem behavior and substance use. Journal of School Psychology, 51, 455–468.  https://doi.org/10.1016/j.jsp.2013.02.001.CrossRefGoogle Scholar
  15. Frankenhuis, W. E., Panchanathan, K., & Nettle, D. (2016). Cognition in harsh and unpredictable environments. Current Opinion in Psychology, 7, 76–80.  https://doi.org/10.1016/j.copsyc.2015.08.011.CrossRefGoogle Scholar
  16. Fuller‐Rowell, T. E., Evans, G. W., Paul, E., & Curtis, D. S. (2015). The role of poverty and chaos in the development of task persistence among adolescents. Journal of Research on Adolescence, 25, 606–613.  https://doi.org/10.1111/jora.12157.CrossRefGoogle Scholar
  17. Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Stanford, CA: Stanford University Press.Google Scholar
  18. Gresham, F. M., & Elliott, S. N. (1990). Social skills rating system: manual. Circle Pines, MN: American Guidance Service.Google Scholar
  19. Hardaway, C. R., Wilson, M. N., Shaw, D. S., & Dishion, T. J. (2012). Family functioning and externalizing behaviour among low‐income children: self‐regulation as a mediator. Infant and Child Development, 21, 67–84.  https://doi.org/10.1002/icd.765.CrossRefGoogle Scholar
  20. Holmes, C. J., Kim-Spoon, J., & Deater-Deckard, K. (2016). Linking executive function and peer problems from early childhood through middle adolescence. Journal of Abnormal Child Psychology, 44, 31–42.  https://doi.org/10.1007/s10802-015-0044-5.CrossRefGoogle Scholar
  21. Hughes, C., Ensor, R., Wilson, A., & Graham, A. (2009). Tracking executive function across the transition to school: A latent variable approach. Developmental Neuropsychology, 35, 20–36.  https://doi.org/10.1080/87565640903325691.CrossRefGoogle Scholar
  22. Kahn, R. E., Holmes, C., Farley, J. P., & Kim-Spoon, J. (2015). Delay discounting mediates parent–adolescent relationship quality and risky sexual behavior for low self-control adolescents. Journal of Youth and Adolescence, 44, 1674–1687.  https://doi.org/10.1007/s10964-015-0332-y.CrossRefGoogle Scholar
  23. Kim-Spoon, J. & Grimm, K. J. (2016). Latent growth modeling and developmental psychopathology. In D. Cicchetti (Ed.), Development and psychopathology : Vol. I Theory and Method, 3rd edn (pp. 986–1041). New York: John Wiley & Sons.Google Scholar
  24. Kim-Spoon, J., Holmes, C., & Deater-Deckard, K. (2015). Attention regulates anger and fear to predict adolescent risk-taking behaviors. Journal of Child Psychology and Psychiatry, 56, 756–765.  https://doi.org/10.1111/jcpp.12338.CrossRefGoogle Scholar
  25. King, K. M., Lengua, L. J., & Monahan, K. C. (2013). Individual differences in the development of self-regulation during pre-adolescence: connections to context and adjustment. Journal of Abnormal Child Psychology, 41, 57–69.  https://doi.org/10.1007/s10802-012-9665-0.CrossRefGoogle Scholar
  26. Kline, R. B. (2011). Principles and practice of structural equation modeling. 3rd edn. New York, NY: Guildford Press.Google Scholar
  27. Ladd, G.W. (2005). Children’s peer relations and social competence: a century of progress. New Haven, Connecticut: Yale University Press.Google Scholar
  28. Lengua, L. J., Honorado, E., & Bush, N. R. (2007). Contextual risk and parenting as predictors of effortful control and social competence in preschool children. Journal of Applied Developmental Psychology, 28, 40–55.  https://doi.org/10.1016/j.appdev.2006.10.001.CrossRefGoogle Scholar
  29. Lo, Y., Mendell, N. R., & Rubin, D. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88, 757–778.  https://doi.org/10.1093/biomet/88.3.767.CrossRefGoogle Scholar
  30. Magar, E. C., Phillips, L. H., & Hosie, J. A. (2008). Self-regulation and risk-taking. Personality and Individual Differences, 45, 153–159.  https://doi.org/10.1016/j.paid.2008.03.014.CrossRefGoogle Scholar
  31. Masten, A. S., & Cicchetti, D. (2010). Developmental cascades. Development and Psychopathology, 22, 491–495.  https://doi.org/10.1017/S0954579410000222.CrossRefGoogle Scholar
  32. Matheny, A. P., Wachs, T. D., Ludwig, J. L., & Phillips, K. (1995). Bringing order out of chaos: psychometric characteristics of the confusion, hubbub, and order scale. Journal of Applied Developmental Psychology, 16, 429–444.  https://doi.org/10.1016/0193-3973(95)90028-4.CrossRefGoogle Scholar
  33. Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H., & Caspi, A. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108, 2693–2698.  https://doi.org/10.1073/pnas.1010076108.
  34. Mullainathan, S., & Shafir, E. (2013). Scarcity: why having too little means so much. New York, NY: Time Books.Google Scholar
  35. Muthén, L. K., & Muthén, B. O. (1998). Mplus User’s Guide. 7th edn. Los Angeles, CA: Muthén & Muthén. 2012.Google Scholar
  36. Nigg, J. T. (2017). Annual research review: on the relations among self‐regulation, self‐control, executive functioning, effortful control, cognitive control, impulsivity, risk‐taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, 58, 361–383.  https://doi.org/10.1111/jcpp.12675.CrossRefGoogle Scholar
  37. Ordaz, S. J., Foran, W., Velanova, K., & Luna, B. (2013). Longitudinal growth curves of brain function underlying inhibitory control through adolescence. Journal of Neuroscience, 33, 18109–18124.  https://doi.org/10.1523/JNEUROSCI.1741-13.2013.CrossRefGoogle Scholar
  38. Pianta, R. (1992). Student-teacher relationship scale. Charlottesville, VA: University of Virginia.Google Scholar
  39. Romer, D., Betancourt, L. M., Brodsky, N. L., Giannetta, J. M., Yang, W., & Hurt, H. (2011). Does adolescent risk taking imply weak executive function? A prospective study of relations between working memory performance, impulsivity, and risk taking in early adolescence. Developmental Science, 14, 1119–1133.  https://doi.org/10.1111/j.1467-7687.2011.01061.x.CrossRefGoogle Scholar
  40. Sclove, L. S. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 53, 333–343.  https://doi.org/10.1007/BF02294360.CrossRefGoogle Scholar
  41. Steinberg, L. (2007). Risk taking in adolescence new perspectives from brain and behavioral science. Current Directions in Psychological Science, 16, 55–59.  https://doi.org/10.1111/j.1467-8721.2007.00475.x.CrossRefGoogle Scholar
  42. Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78–106.  https://doi.org/10.1016/j.dr.2007.08.002.CrossRefGoogle Scholar
  43. Tofighi, D., & Enders, C. K. (2007). Identifying the correct number of classes in growth mixture models. In G. R. Hancock (Ed.), Advances in latent variable mixture models. Charlotte, NC: Information Age.Google Scholar
  44. Ursache, A., & Noble, K. G. (2016). Neurocognitive development in socioeconomic context: multiple mechanisms and implications for measuring socioeconomic status. Psychophysiology, 53, 71–82.  https://doi.org/10.1111/psyp.12547.CrossRefGoogle Scholar
  45. Vazsonyi, A. T., & Huang, L. (2010). Where self-control comes from: on the development of self-control and its relationship to deviance over time. Developmental Psychology, 46, 245–257.  https://doi.org/10.1037/a0016538.CrossRefGoogle Scholar
  46. Vazsonyi, A. T., Roberts, J. W., Huang, L., & Vaughn, M. G. (2015). Why focusing on nurture made and still makes sense: the biosocial development of self-control. The Routledge international handbook of biosocial criminology (pp. 263–279). New York, NY: Routledge.Google Scholar
  47. Vernon-Feagans, L., Willoughby, M., & Garrett-Peters, P. (2016). Predictors of behavioral regulation in kindergarten: household chaos, parenting, and early executive functions. Developmental Psychology, 52, 430–441.  https://doi.org/10.1037/dev0000087.CrossRefGoogle Scholar
  48. Wachs, T. D., & Evans, G. W. (2010). Chaos in context. In G. W. Evans & T. D. Wachs (Eds.), Chaos and its influence on children’s development: an ecological perspective (pp. 3–13). Washington, DC: American Psychological Association.  https://doi.org/10.1037/12057-001. CrossRefGoogle Scholar
  49. Wickrama, K. A. S., O’Neal, C. W., & Holmes, C. (2017). Towards a heuristic research model linking early socioeconomic adversity and youth cumulative disease risk: an integrative review. Adolescent Research Review, 2, 161–179.  https://doi.org/10.1007/s40894-017-0054-3.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Christopher Holmes
    • 1
    Email author
  • Alexis Brieant
    • 2
  • Rachel Kahn
    • 3
  • Kirby Deater-Deckard
    • 4
  • Jungmeen Kim-Spoon
    • 2
  1. 1.Center for Family ResearchUniversity of GeorgiaAthensUSA
  2. 2.Virginia TechBlacksburgUSA
  3. 3.Sand Ridge Secure Treatment CenterMaustonUSA
  4. 4.University of MassachusettsAmherstUSA

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