Hostname: page-component-cd9895bd7-jn8rn Total loading time: 0 Render date: 2024-12-26T09:10:58.489Z Has data issue: false hasContentIssue false

Statistical tests of differential susceptibility: Performance, limitations, and improvements

Published online by Cambridge University Press:  05 January 2017

Marco Del Giudice*
Affiliation:
University of New Mexico
*
Address correspondence and reprint requests to: Marco Del Giudice, Department of Psychology, University of New Mexico, Logan Hall, 2001 Redondo Drive NE, Albuquerque, NM 87131; E-mail: marcodg@unm.edu.

Abstract

Statistical tests of differential susceptibility have become standard in the empirical literature, and are routinely used to adjudicate between alternative developmental hypotheses. However, their performance and limitations have never been systematically investigated. In this paper I employ Monte Carlo simulations to explore the functioning of three commonly used tests proposed by Roisman et al. (2012). Simulations showed that critical tests of differential susceptibility require considerably larger samples than standard power calculations would suggest. The results also showed that existing criteria for differential susceptibility based on the proportion of interaction index (i.e., values between .40 and .60) are especially likely to produce false negatives and highly sensitive to assumptions about interaction symmetry. As an initial response to these problems, I propose a revised test based on a broader window of proportion of interaction index values (between .20 and .80). Additional simulations showed that the revised test outperforms existing tests of differential susceptibility, considerably improving detection with little effect on the rate of false positives. I conclude by noting the limitations of a purely statistical approach to differential susceptibility, and discussing the implications of the present results for the interpretation of published findings and the design of future studies in this area.

Type
Regular Articles
Copyright
Copyright © Cambridge University Press 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Beaver, K. M., Hartman, S., & Belsky, J. (2015). Differential susceptibility to parental sensitivity based on early-life temperament in the prediction of adolescent affective psychopathic personality traits. Criminal Justice and Behavior, 42, 546565. doi:10.1177/0093854814553620 Google Scholar
Belsky, J. (1997). Variation in susceptibility to rearing influences: An evolutionary argument. Psychological Inquiry, 8, 182186. doi:10.1207/s15327965pli0803_3 CrossRefGoogle Scholar
Belsky, J. (2005). Differential susceptibility to rearing influences: An evolutionary hypothesis and some evidence. In Ellis, B. & Bjorklund, D. (Eds.), Origins of the social mind: Evolutionary psychology and child development (pp. 139163). New York: Guilford Press.Google 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, 300304. doi:10.1111/j.1467-8721.2007.00525.x Google Scholar
Belsky, J., Newman, D. A., Widaman, K. F., Rodkin, P., Pluess, M., Fraley, R. C., … Roisman, G. I. (2015). Differential susceptibility to effects of maternal sensitivity? A study of candidate plasticity genes. Development and Psychopathology, 27, 725746. doi:10.1017/S0954579414000844 Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885908. doi:10.1037/a0017376 Google Scholar
Belsky, J., & Pluess, M. (2013). Beyond risk, resilience, and dysregulation: Phenotypic plasticity and human development. Development and Psychopathology, 25, 12431261. doi:10.1017/S095457941300059X Google Scholar
Belsky, J., & Pluess, M. (2016). Differential susceptibility to environmental influences. In Cicchetti, D. (Ed.), Developmental psychopathology: Vol. 2. Developmental neuroscience (3rd ed., pp. 59106). Hoboken, NJ: Wiley.Google 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, 11351143. doi:10.1111/jcpp.12075 CrossRefGoogle ScholarPubMed
Boyce, W. T., Chesney, M., Alkon, A., Tschann, J. M., Adams, S., Chesterman, B., … Wara, D. (1995). Psychobiologic reactivity to stress and childhood respiratory illnesses: Results of two prospective studies. Psychosomatic Medicine, 57, 411422.CrossRefGoogle ScholarPubMed
Brett, Z. H., Humphreys, K. L., Smyke, A. T., Gleason, M. M., Nelson, C. A., Zeanah, C. H., … Drury, S. S. (2015). Serotonin transporter linked polymorphic region (5-HTTLPR) genotype moderates the longitudinal impact of early caregiving on externalizing behavior. Development and Psychopathology, 27, 718. doi:10.1017/S0954579414001266 Google Scholar
Bush, N. R., & Boyce, W. T. (2016). Differential sensitivity to context: Implications for developmental psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology: Vol. 2. Developmental neuroscience (3rd ed., pp. 107137). Hoboken, NJ: Wiley.Google Scholar
Chabris, C. F., Lee, J. J., Cesarini, D., Benjamin, D. J., & Laibson, D. I. (2015). The fourth law of behavior genetics. Current Directions in Psychological Science, 24, 304312. doi:10.1177/0963721415580430 Google Scholar
Dalton, E. D., Hammen, C. L., Najman, J. M., & Brennan, P. A. (2014). Genetic susceptibility to family environment: BDNF Val66met and 5-HTTLPR influence depressive symptoms. Journal of Family Psychology, 28, 947956. doi:10.1037/fam0000032 Google Scholar
Davies, P., Cicchetti, D., & Hentges, R. F. (2015). Maternal unresponsiveness and child disruptive problems: The interplay of uninhibited temperament and dopamine transporter genes. Child Development, 86, 6379. doi:10.1111/cdev.12281 Google Scholar
Del Giudice, M. (in press). The evolution of interaction shape in differential susceptibility. Child Development.Google Scholar
Del Giudice, M., & Ellis, B. J. (2016). Evolutionary foundations of developmental psychopathology. In Cicchetti, D. (Ed.), Developmental psychopathology: Vol. 2. Developmental neuroscience (3rd ed., pp. 158). Hoboken, NJ: Wiley.Google Scholar
Dick, D. M., Agrawal, A., Keller, M. C., Adkins, A., Aliev, F., Monroe, S., … Sher, K. J. (2015). Candidate gene-environment interaction research: Reflections and recommendations. Perspectives on Psychological Science, 10, 3759. doi:10.1177/1745691614556682 Google Scholar
Duncan, L., & Keller, M. C. (2011). A critical review of the first ten years of measured gene-by-environment interaction research in psychiatry. American Journal of Psychiatry, 168, 10411049. doi:10.1176/appi.ajp.2011.11020191 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, 728. doi:10.1017/S0954579410000611 CrossRefGoogle Scholar
Elmore, A. L., Nigg, J. T., Friderici, K. H., Jernigan, K., & Nikolas, M. A. (2016). Does 5HTTLPR genotype moderate the association of family environment with child attention-deficit hyperactivity disorder symptomatology? Journal of Clinical Child and Adolescent Psychology, 45, 348360. doi:10.1080/15374416.2014.979935 CrossRefGoogle ScholarPubMed
Gallitto, E. (2015). Temperament as a moderator of the effects of parenting on children's behavior. Development and Psychopathology, 27, 757773. doi:10.1017/S0954579414000753 CrossRefGoogle ScholarPubMed
Gottesman, I., & Shields, J. (1972). Schizophrenia and genetics: A twin study vantage point. New York: Academic Press.Google Scholar
Hankin, B. L., & Abela, J. R. Z. (2005). Development and psychopathology: A vulnerability-stress perspective. Thousand Oaks, CA: Sage.Google Scholar
Kochanska, G., Kim, S., Barry, R. A., & Philibert, R. A. (2011). Children's genotypes interact with maternal responsive care in predicting children's competence: Diathesis–stress or differential susceptibility? Development and Psychopathology, 23, 605616. doi:10.1017/S0954579411000071 Google Scholar
Kogan, S. M., Lei, M. K., Beach, S. R., Brody, G. H., Windle, M., Lee, S., … Chen, Y. F. (2014). Dopamine receptor gene D4 polymorphisms and early sexual onset: Gender and environmental moderation in a sample of African-American youth. Journal of Adolescent Health, 55, 235240.Google Scholar
Lee, S., Lei, M. K., & Brody, G. H. (2015). Confidence intervals for distinguishing ordinal and disordinal interactions in multiple regression. Psychological Methods, 20, 245258. doi:10.1037/met0000033 CrossRefGoogle ScholarPubMed
McClelland, G. H., & Judd, C. M. (1993). Statistical difficulties of detecting interactions and moderator effects. Psychological Bulletin, 114, 376390. doi:10.1037/0033-2909.114.2.376 Google Scholar
Monroe, S. M., & Simons, A. D. (1991). Diathesis-stress theories in the context of life stress research: Implications for the depressive disorders. Psychological Bulletin, 110, 406425. doi:10.1037/0033-2909.110.3.406 Google Scholar
Montirosso, R., Provenzi, L., Tavian, D., Morandi, F., Bonanomi, A., Missaglia, S., … Borgatti, R. (2015). Social stress regulation in 4-month-old infants: Contribution of maternal social engagement and infants’ 5-HTTLPR genotype. Early Human Development, 91, 173179. doi:10.1016/j.earlhumdev.2015.01.010 Google Scholar
Pluess, M. (2015). Individual differences in environmental sensitivity. Child Development Perspectives, 9, 138143. doi:10.1111/cdep.12120 Google Scholar
Pluess, M., & Belsky, J. (2013). Vantage sensitivity: Individual differences in response to positive experiences. Psychological Bulletin, 139, 901916. doi:10.1037/a0030196 Google Scholar
R Core Team. (2013). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from http://www.R-project.org Google Scholar
Roisman, G. I., Newman, D. A., Fraley, C., Haltigan, J. D., Groh, A. M., & Haydon, K. C. (2012). Distinguishing differential susceptibility from diathesis–stress: Recommendations for evaluating interaction effects. Development and Psychopathology, 24, 389409. doi:10.1017/S0954579412000065CrossRefGoogle ScholarPubMed
Sameroff, A. J. (1983). Development systems: Contexts and evolution. In Mussen, P. (Ed.), Handbook of child psychology (4th ed., pp. 237294). New York: Wiley.Google Scholar
Sumner, J. A., McLaughlin, K. A., Walsh, K., Sheridan, M. A., & Koenen, K. C. (2015). Caregiving and 5-HTTLPR genotype predict adolescent physiological stress reactivity: Confirmatory tests of Gene × Environment interactions. Child Development, 86, 985994. doi:10.1111/cdev.12357 Google Scholar
Thibodeau, E. L., Cicchetti, D., & Rogosch, F. A. (2015). Child maltreatment, impulsivity, and antisocial behavior in African American children: Moderation effects from a cumulative dopaminergic gene index. Development and Psychopathology, 27, 16211636. doi:10.1017/S095457941500098X Google 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, 151162. doi:10.1017/S0954579414001369 CrossRefGoogle ScholarPubMed
van IJzendoorn, M. H., Belsky, J., & Bakermans-Krananburg, M. J. (2012). Serotonin transporter genotype 5HTTLPR as a marker of differential susceptibility? A meta-analysis of child and adolescent gene-by-environment studies. Translational Psychiatry, 2, e147. doi:10.1038/tp.2012.73 Google Scholar
Visscher, P. M., & Posthuma, D. (2010). Statistical power to detect genetic loci affecting environmental sensitivity. Behavior Genetics, 40, 728733. doi:10.1007/s10519-010-9362-0 Google 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, 615622. doi:10.1037/a0030003 Google Scholar
Zhang, W., Cao, Y., Wang, M., Ji, L., Chen, L., & Deater-Deckard, K. (2015). The dopamine D2 receptor polymorphism (DRD2 TaqIA) interacts with maternal parenting in predicting early adolescent depressive symptoms: Evidence of differential susceptibility and age differences. Journal of Youth and Adolescence, 44, 14281440. doi:10.1007/s10964-015-0297-x CrossRefGoogle ScholarPubMed