Skip to main content Accessibility help
Hostname: page-component-768dbb666b-sz752 Total loading time: 0.565 Render date: 2023-02-02T03:21:30.843Z Has data issue: true Feature Flags: { "useRatesEcommerce": false } hasContentIssue false

Parenting × Brain Development interactions as predictors of adolescent depressive symptoms and well-being: Differential susceptibility or diathesis-stress?

Published online by Cambridge University Press:  04 February 2019

Camille Deane
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, Australia
Nandita Vijayakumar
Department of Psychology, University of Oregon, Eugene, OR, USA
Nicholas B. Allen
Department of Psychology, University of Oregon, Eugene, OR, USA Melbourne School of Psychological Sciences, University of Melbourne, MelbourneAustralia
Orli Schwartz
Melbourne School of Psychological Sciences, University of Melbourne, MelbourneAustralia Orygen, The National Centre of Excellence in Youth Mental Health, Melbourne, Australia Centre of Youth Mental Health, University of Melbourne, Melbourne, Australia
Julian G. Simmons
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, Australia Melbourne School of Psychological Sciences, University of Melbourne, MelbourneAustralia
Chad A. Bousman
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, Australia Departments of Medical Genetics, Psychiatry, and Physiology & Pharmacology, University of Calgary, Calgary, Canada Alberta Children's Hospital Research Institute, Calgary, Canada Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Canada
Christos Pantelis
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, Australia
Sarah Whittle*
Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne & Melbourne Health, Melbourne, Australia Melbourne School of Psychological Sciences, University of Melbourne, MelbourneAustralia
Author for correspondence: Sarah Whittle, Melbourne Neuropsychiatry Centre, Department of Psychiatry, Level 3, Alan Gilbert Building, 161 Barry St, Carlton, VIC 3053; E-mail:


It is unclear how individual differences in parenting and brain development interact to influence adolescent mental health outcomes. This study examined interactions between structural brain development and observed maternal parenting behavior in the prediction of adolescent depressive symptoms and psychological well-being. Whether findings supported diathesis-stress or differential susceptibility frameworks was tested. Participants completed observed interactions with their mothers during early adolescence (age 13), and the frequency of positive and aggressive maternal behavior were coded. Adolescents also completed structural magnetic resonance imaging scans at three time points: mean ages 13, 17, and 19. Regression models analyzed interactions between maternal behavior and longitudinal brain development in the prediction of late adolescent (age 19) outcomes. Indices designed to distinguish between diathesis-stress and differential susceptibility effects were employed. Results supported differential susceptibility: less thinning of frontal regions was associated with higher well-being in the context of low levels of aggressive maternal behavior, and lower well-being in the context of high levels of aggressive maternal behavior. Findings suggest that reduced frontal cortical thinning during adolescence may underlie increased sensitivity to maternal aggressive behavior for better and worse and highlight the importance of investigating biological vulnerability versus susceptibility.

Regular Articles
Copyright © Cambridge University Press 2019

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.)


Bakermans-Kranenburg, M. J., & van IJzendoorn, M. H. (2015). The hidden efficacy of interventions: Gene × Environment experiments from a differential susceptibility perspective. Annual Review of Psychology, 66, 381409. doi:10.1146/annurev-psych-010814-015407CrossRefGoogle Scholar
Beck, A. T., Brown, G., Epstein, N., & Steer, R. A. (1988). An inventory for measuring clinical anxiety: Psychometric properties. Journal of Consulting and Clinical Psychology, 56, 893897. doi:10.1037/0022-006X.56.6.893CrossRefGoogle ScholarPubMed
Belsky, J. (1997). Variation in susceptibility to environmental influence: An evolutionary argument. Psychological Inquiry, 8, 182186.CrossRefGoogle Scholar
Belsky, J., Jonassaint, C., Pluess, M., Stanton, M., Brummett, B., & Williams, R. (2009). Vulnerability genes or plasticity genes? Molecular Psychiatry, 14, 746754. doi:10.1038/mp.2009.44CrossRefGoogle ScholarPubMed
Belsky, J., Newman, J., Widaman, D., Rodkin, K., Pluess, P., Fraley, M., … Roisman, G. I. (2014). Differential susceptibility to effects of maternal sensitivity? A study of candidate plasticity genes. Development and Psychopathology, 27, 725746.CrossRefGoogle ScholarPubMed
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885908. doi:10.1037/a0017376CrossRefGoogle ScholarPubMed
Belsky, J., & Widaman, K. (2018). Editorial perspective: Integrating exploratory and competitive-confirmatory approaches to testing person × environment interactions. Journal of Child Psychology and Psychiatry and Allied Disciplines, 59, 296298. doi:10.1111/jcpp.12824CrossRefGoogle ScholarPubMed
Bos, M. G. N., Peters, S., Van de Kamp, F. C., Crone, E. A., & Tamnes, C. K. (2018). Emerging depression in adolescence coincides with accelerated frontal cortical thinning. Journal of Child Psychology and Psychiatry, 59, 19. doi:10.1111/jcpp.12895CrossRefGoogle ScholarPubMed
Cannon, T. D., Chung, Y., He, G., Sun, D., Jacobson, A., Van Erp, T. G. M., … Heinssen, R. (2015). Progressive reduction in cortical thickness as psychosis develops: A multisite longitudinal neuroimaging study of youth at elevated clinical risk. Biological Psychiatry, 77, 147157. doi:10.1016/j.biopsych.2014.05.023CrossRefGoogle ScholarPubMed
Capaldi, D. M., & Rothbart, M. K. (1992). Development and validation of an early adolescent temperament measure. Journal of Early Adolescence, 12, 153173. doi:10.1177/0272431692012002002CrossRefGoogle Scholar
Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review, 28, 6277. doi:10.1016/j.dr.2007.08.003CrossRefGoogle ScholarPubMed
Chen, H., Cohen, P., Kasen, S., Gordan, K., Dufur, R., & Smailes, E. (2004). Construction and validation of a quality of life instrument for young adults. Quality of Life Research, 13, 747759.CrossRefGoogle ScholarPubMed
Cicchetti, D., & Natsuaki, M. N. (2014). Multilevel developmental perspectives toward understanding internalizing psychopathology: Current research and future directions. Development and Psychopathology, 26, 11891190. doi:10.1017/S0954579414000959CrossRefGoogle ScholarPubMed
Clos, M., Amunts, K., Laird, A. R., Fox, P. T., & Eickhoff, S. B. (2013). Tackling the multifunctional nature of Broca's region meta-analytically: Co-activation-based parcellation of area 44. NeuroImage, 83, 174188. doi:10.1016/j.neuroimage.2013.06.041CrossRefGoogle ScholarPubMed
Cole, D. A., Tram, J. M., Martin, J. M., Hoffman, K. B., Ruiz, M. D., Jacquez, F. M., & Maschman, T. L. (2002). Individual differences in the emergence of depressive symptoms in children and adolescents: A longitudinal investigation of parent and child reports. Journal of Abnormal Psychology, 111, 156165. doi:10.1037//0021-843X.111.1.156CrossRefGoogle ScholarPubMed
Del Giudice, M. (2017). Statistical tests of differential susceptibility: Performance, limitations, and improvements. Development and Psychopathology, 29, 12671278. doi:10.1017/S0954579416001292CrossRefGoogle ScholarPubMed
Dennison, M. J., Sheridan, M. A., Busso, D. S., Jenness, J. L., Peverill, M., Rosen, M. L., & McLaughlin, K. A. (2016). Neurobehavioral markers of resilience to depression amongst adolescents exposed to child abuse. Journal of Abnormal Psychology, 125, 12011212. doi:10.1037/abn0000215CrossRefGoogle ScholarPubMed
Ducharme, S., Albaugh, M. D., Hudziak, J. J., Botteron, K. N., Nguyen, T. V., Truong, C., … Karama, S. (2014). Anxious/depressed symptoms are linked to right ventromedial prefrontal cortical thickness maturation in healthy children and young adults. Cerebral Cortex, 24, 29412950. doi:10.1093/cercor/bht151CrossRefGoogle ScholarPubMed
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/S0954579410000611CrossRefGoogle Scholar
Ellis, B. J., Essex, M. J., & Boyce, W. T. (2005). Biological sensitivity to context: II. Empirical explorations of an evolutionary-developmental theory. Development and Psychopathology, 17, 303328. doi:10.1017/S0954579405050157CrossRefGoogle ScholarPubMed
Ellis, B. J., & Rothbart, M. K. (2001). Revision of the early adolescent temperament questionnaire. Poster presented at the biennial meeting of the Society for Research in Child Development, Minneapolis.Google Scholar
Ent, D., Braber, A., Baselmans, B. M. L., Brouwer, R. M., Dolan, C. V, Hulshoff Pol, H. E., … Bartels, M. (2017). Associations between subjective well-being and subcortical brain volumes. Scientific Reports, 7, 112. doi:10.1038/s41598-017-07120-zGoogle Scholar
Field, A. (2009). Discovering statistics using SPSS (3rd ed.). London: Sage.Google Scholar
Forbes, E. E., Ryan, N. D., Phillips, M. L., Manuck, S. B., Worthman, C. M., Moyles, D. L., … Dahl, R. E. (2010). Healthy adolescents’ neural response to reward: Associations with puberty, positive affect, and depressive symptoms. Journal of the American Academy of Child & Adolescent Psychiatry, 49, 162172. doi:10.1097/00004583-201002000-00010Google ScholarPubMed
Friedel, S., Whittle, S. L., Vijayakumar, N., Simmons, J. G., Byrne, M. L., Schwartz, O. S., & Allen, N. B. (2015). Dispositional mindfulness is predicted by structural development of the insula during late adolescence. Developmental Cognitive Neuroscience, 14, 6270. doi:10.1016/j.dcn.2015.07.001CrossRefGoogle ScholarPubMed
Friedrich, R. J. (1982). In defense of multiplicative terms in multiple regression equations. American Journal of Political Science, 26, 797833.CrossRefGoogle Scholar
Fuhrmann, D., Knoll, L. J., & Blakemore, S. J. (2015). Adolescence as a sensitive period of brain development. Trends in Cognitive Sciences, 19, 558566. doi:10.1016/j.tics.2015.07.008CrossRefGoogle ScholarPubMed
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., … Thompson, P. M. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences of the United States of America, 101, 81748179. doi:10.1073/pnas.0402680101CrossRefGoogle ScholarPubMed
Goldin, P. R., McRae, K., Ramel, W., & Gross, J. J. (2008). The neural bases of emotion regulation: Reappraisal and suppression of negative emotion. Biological Psychiatry, 63, 577586. doi:10.1016/j.biopsych.2007.05.031CrossRefGoogle ScholarPubMed
Gottman, J., Coan, J., Carrere, S., & Swanson, C. (1998). Predicting marital happiness and stability from newlywed interactions. Journal of Marriage and the Family, 60, 522.CrossRefGoogle Scholar
Herting, M. M., Johnson, C., Mills, K. L., Vijayakumar, N., Dennison, M., Liu, C., … Tamnes, C. K. (2018). Development of subcortical volumes across adolescence in males and females: A multisample study of longitudinal changes. NeuroImage, 172, 194205. doi:10.1016/j.neuroimage.2018.01.020CrossRefGoogle ScholarPubMed
Hops, H., Davis, B., & Longoria, N. (1995). Methodological issues in direct observation: Illustrations with the Living in Familial Environments (LIFE) coding system. Journal of Clinical Child Psychology, 24, 193203. doi:10.1207/s15374424jccp2402_7CrossRefGoogle Scholar
Hulvershorn, L. A., Cullen, K., & Anand, A. (2011). Toward dysfunctional connectivity: A review of neuroimaging findings in pediatric major depressive disorder. Brain Imaging and Behavior, 5, 307328. doi:10.1007/s11682-011-9134-3CrossRefGoogle ScholarPubMed
Katz, L. F., & Hunter, E. C. (2007). Maternal meta-emotion philosophy and adolescent depressive symptomatology. Social Development, 16, 343360. doi:10.1111/j.1467-9507.2007.00388.xCrossRefGoogle 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/S0954579411000071CrossRefGoogle ScholarPubMed
Kok, R., Thijssen, S., Bakermans-Kranenburg, M. J., Jaddoe, V. W. V., Verhulst, F. C., White, T., … Tiemeier, H. (2015). Normal variation in early parental sensitivity predicts child structural brain development. Journal of the American Academy of Child & Adolescent Psychiatry, 54, 824831. doi:10.1016/j.jaac.2015.07.009CrossRefGoogle ScholarPubMed
Kong, F., Ding, K., Yang, Z., Dang, X., Hu, S., Song, Y., & Liu, J. (2015). Examining gray matter structures associated with individual differences in global life satisfaction in a large sample of young adults. Social Cognitive and Affective Neuroscience, 10, 952960. doi:10.1093/scan/nsu144CrossRefGoogle Scholar
Kong, F., Wang, X., Hu, S., & Liu, J. (2015). Neural correlates of psychological resilience and their relation to life satisfaction in a sample of healthy young adults. NeuroImage, 123, 165172. doi:10.1016/j.neuroimage.2015.08.020CrossRefGoogle Scholar
Kringelbach, M. L. (2005). The human orbitofrontal cortex: Linking reward to hedonic experience. Nature Reviews Neuroscience, 6, 691702. doi:10.1038/nml748CrossRefGoogle ScholarPubMed
Lekes, N., Gingras, I., Philippe, F. L., Koestner, R., & Fang, J. (2010). Parental autonomy-support, intrinsic life goals, and well-being among adolescents in China and North America. Journal of Youth and Adolescence, 39, 858869. doi:10.1007/s10964-009-9451-7CrossRefGoogle ScholarPubMed
Lewis, G. J., Kanai, R., Rees, G., & Bates, T. C. (2014). Neural correlates of the “good life”: Eudaimonic well-being is associated with insular cortex volume. Social Cognitive and Affective Neuroscience, 9, 615618. doi:10.1093/scan/nst032CrossRefGoogle Scholar
Liakakis, G., Nickel, J., & Seitz, R. J. (2011). Diversity of the inferior frontal gyrus—A meta-analysis of neuroimaging studies. Behavioural Brain Research, 225, 341347. doi:10.1016/j.bbr.2011.06.022CrossRefGoogle ScholarPubMed
Luby, J. L., Barch, D. M., Belden, A., Gaffrey, M. S., Tillman, R., Babb, C., … Botteron, K. N. (2012). Maternal support in early childhood predicts larger hippocampal volumes at school age. Proceedings of the National Academy of Sciences of the United States of America, 109, 28542859. doi:10.1073/pnas.1118003109CrossRefGoogle ScholarPubMed
Macphillamy, D. J., & Lewinsohn, P. M. (1982). The pleasant events schedule: Studies on reliability, validity, and scale intel-correlation. Journal of Consulting and Clinical Psychology, 50, 363380.CrossRefGoogle Scholar
McLeod, B. D., Weisz, J. R., & Wood, J. J. (2007). Examining the association between parenting and childhood depression: A meta-analysis. Clinical Psychology Review, 27, 9861003. doi:10.1016/j.cpr.2007.03.001CrossRefGoogle ScholarPubMed
Mills, K. L., Goddings, A. L., Clasen, L. S., Giedd, J. N., & Blakemore, S. J. (2014). The developmental mismatch in structural brain maturation during adolescence. Developmental Neuroscience, 36, 147160. doi:10.1159/000362328CrossRefGoogle ScholarPubMed
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//0033-2909.110.3.406CrossRefGoogle ScholarPubMed
Monroe, S. M., Slavich, G., & Gotlib, I. H. (2014). Life stress and family history for depression: The moderating role of past depressive episodes. Journal of Psychiatric Research, 49, 9095. doi:10.1016/j.jpsychires.2013.11.005CrossRefGoogle ScholarPubMed
Mutlu, A. K., Schneider, M., Debbané, M., Badoud, D., Eliez, S., & Schaer, M. (2013). Sex differences in thickness, and folding developments throughout the cortex. NeuroImage, 82, 200207. doi:10.1016/j.neuroimage.2013.05.076CrossRefGoogle ScholarPubMed
Narum, S. R. (2006). Beyond bonferroni: Less conservative analyses for conservation genetics. Conservation Genetics, 7, 783787. doi:10.1007/s10592-005-9056-yCrossRefGoogle Scholar
Nelson, E. E., Leibenluft, E., McClure, E., & Pine, D. S. (2005). The social re-orientation of adolescence: A neuroscience perspective on the process and its relation to psychopathology. Psychological Medicine, 35, 163174. doi:10.1017/S0033291704003915CrossRefGoogle ScholarPubMed
Pine, D. S., Cohen, P., Gurley, D., Brook, J., & Ma, Y. (1998). The risk for early-adulthood anxiety and depressive disorders in adolescents with anxiety and depressive disorders. Archives of General Psychiatry, 55, 5664. doi:10.1001/archpsyc.55.1.56CrossRefGoogle ScholarPubMed
Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2018). nlme: Linear and nonlinear mixed effects models [Software]. Retrieved from Scholar
Prinz, R. J., Foster, S., Kent, R. N., & O'Leary, K. D. (1979). Multivariate assessment of conflict in distressed and nondistressed mother-adolescent dyads. Journal of Applied Behavior Analysis, 12, 691700. doi:10.1901/jaba.1979.12-691PCrossRefGoogle ScholarPubMed
Qiu, L., Lui, S., Kuang, W., Huang, X., Li, J., Li, J., … Gong, Q. (2014). Regional increases of cortical thickness in untreated, first-episode major depressive disorder. Translational Psychiatry, 4, 17. doi:10.1038/tp.2014.18CrossRefGoogle ScholarPubMed
Radloff, L. (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385401.CrossRefGoogle Scholar
Raznahan, A., Shaw, P. W., Lerch, J. P., Clasen, L. S., Greenstein, D., Berman, R., … Giedd, J. N. (2014). Longitudinal four-dimensional mapping of subcortical anatomy in human development. Proceedings of the National Academy of Sciences, 111, 15921597. doi:10.1073/pnas.1316911111CrossRefGoogle ScholarPubMed
R Development Core Team. (2008). R: A language and environment for statistical computing [Software]. Vienna: R Foundation for Statistical Computing. Retrieved from http://www.r-project.orgGoogle Scholar
Reuter, M., & Fischl, B. (2011). Avoiding asymmetry-induced bias in longitudinal image processing. Neuroimage, 57, 1921. doi:10.1016/j.neuroimage.2011.02.076CrossRefGoogle ScholarPubMed
Reuter, M., Rosas, H. D., & Fischl, B. (2010). Highly accurate inverse consistent registration: A robust approach. Neuroimage, 53, 11811196. doi:10.1016/j.neuroimage.2010.07.020CrossRefGoogle ScholarPubMed
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012). Within-subject template estimation for unbiased longitudinal image analysis. Neuroimage, 61, 14021418. doi:10.1016/j.neuroimage.2012.02.084CrossRefGoogle ScholarPubMed
Rioux, C., Castellanos-Ryan, N., Parent, S., Vitaro, F., Tremblay, R. E., & Séguin, J. R. (2015). Differential susceptibility to environmental influences: Interactions between child temperament and parenting in adolescent alcohol use. Development and Psychopathology, 28, 111. doi:10.1017/S0954579415000437Google ScholarPubMed
Robins, R. W., Trzesniewski, K. H., Tracy, J. L., Gosling, S. D., & Potter, J. (2002). Global self-esteem across the life span. American Psychological Association, 17, 423434. doi:10.1037//0882-7974.17.3.423Google ScholarPubMed
Roisman, G. I., Newman, D. A., Fraley, R. 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
Schriber, R. A., Anbari, Z., Robins, R. W., Conger, R. D., Hastings, P. D., & Guyer, A. E. (2017). Hippocampal volume as an amplifier of the effect of social context on adolescent depression. Clinical Psychological Science, 5, 632649. doi:10.1177/2167702617699277CrossRefGoogle ScholarPubMed
Schriber, R. A., & Guyer, A. E. (2016). Adolescent neurobiological susceptibility to social context. Developmental Cognitive Neuroscience, 19, 118. doi:10.1016/j.dcn.2015.12.009CrossRefGoogle ScholarPubMed
Schwartz, O. S., Byrne, M. L., Simmons, J. G., Whittle, S., Dudgeon, P., Yap, M. B. H., … Allen, N. B. (2013). Parenting during early adolescence and adolescent-onset major depression: A 6-year prospective longitudinal study. Clinical Psychological Science, 1, 115. doi:10.1177/2167702613505531Google Scholar
Schwartz, O. S., Dudgeon, P., Sheeber, L. B., Yap, M. B. H., Simmons, J. G., & Allen, N. B. (2011). Observed maternal responses to adolescent behaviour predict the onset of major depression. Behaviour Research and Therapy, 49, 331338. doi:10.1016/j.brat.2011.02.008CrossRefGoogle ScholarPubMed
Schwartz, O. S., Simmons, J. G., Whittle, S., Byrne, M. L., Yap, M. B. H., Sheeber, L. B., & Allen, N. B. (2017). Affective parenting behaviors, adolescent depression, and brain development: A review of findings from the Orygen Adolescent Development Study. Child Development Perspectives, 11, 9096. doi:10.1111/cdep.12215CrossRefGoogle Scholar
Sellström, E., & Bremberg, S. (2006). The significance of neighbourhood context to child and adolescent health and well-being: A systematic review of multilevel studies. Scandinavian Journal of Public Health, 34, 544554. doi:10.1080/14034940600551251CrossRefGoogle ScholarPubMed
Skuse, D. H., & Gallagher, L. (2009). Dopaminergic-neuropeptide interactions in the social brain. Trends in Cognitive Sciences, 13, 2735. doi:10.1016/j.tics.2008.09.007CrossRefGoogle ScholarPubMed
Takeuchi, H., Taki, Y., Nouchi, R., Hashizume, H., Sassa, Y., Sekiguchi, A., … Kawashima, R. (2014). Anatomical correlates of quality of life: Evidence from voxel-based morphometry. Human Brain Mapping, 35, 18341846. doi:10.1002/hbm.22294CrossRefGoogle ScholarPubMed
Vijayakumar, N., Allen, N. B., Dennison, M., Byrne, M. L., Simmons, J. G., & Whittle, S. (2017). Cortico-amygdalar maturational coupling is associated with depressive symptom trajectories during adolescence. NeuroImage, 156, 403411. doi:10.1016/j.neuroimage.2017.05.051CrossRefGoogle ScholarPubMed
Vijayakumar, N., Allen, N. B., Youssef, G., Dennison, M., Yücel, M., Simmons, J. G., & Whittle, S. (2016). Brain development during adolescence: A mixed-longitudinal investigation of cortical thickness, surface area, and volume. Human Brain Mapping, 37, 20272038. doi:10.1002/hbm.23154CrossRefGoogle ScholarPubMed
Vijayakumar, N., Whittle, S., Yücel, M., Dennison, M., Simmons, J., & Allen, N. B. (2014). Thinning of the lateral prefrontal cortex during adolescence predicts emotion regulation in females. Social Cognitive and Affective Neuroscience, 9, 18451854. doi:10.1093/scan/nst183CrossRefGoogle ScholarPubMed
Wechsler, D. (2003). Wechsler Intelligence Scale for Children—Fourth edition (WISC-IV). San Antonio, TX: Psychological Corporation.Google Scholar
Whittle, S., Lichter, R., Dennison, M., Vijayakumar, N., Schwartz, O., Byrne, M. L., … Alle, N. B. (2014). Structural brain development and depression onset during adolescence: A prospective longitudinal study. American Journal of Psychiatry, 171, 564571. doi:10.1176/appi.ajp.2013.13070920CrossRefGoogle ScholarPubMed
Whittle, S., Vijayakumar, N., Dennison, M., Schwartz, O., Simmons, J. G., Sheeber, L., & Allen, N. B. (2016). Observed measures of negative parenting predict brain development during adolescence. PLOS ONE, 11, 116. doi:10.1371/journal.pone.0147774CrossRefGoogle ScholarPubMed
Whittle, S., Yap, M. B. H., Sheeber, L., Dudgeon, P., Yücel, M., Pantelis, C., … Allen, N. B. (2011). Hippocampal volume and sensitivity to maternal aggressive behavior: A prospective study of adolescent depressive symptoms. Development and Psychopathology, 23, 115129. doi:10.1017/S0954579410000684CrossRefGoogle ScholarPubMed
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/a0030003CrossRefGoogle ScholarPubMed
Wierenga, L. M., Bos, M. G. N., Schreuders, E., Peper, J. S., Tamnes, C. K., & Crone, E. A. (2018). Unraveling age, puberty and testosterone effects on subcortical brain development across adolescence. Psychoneuroendocrinology, 91, 105114. doi:10.1016/j.psyneuen.2018.02.034CrossRefGoogle ScholarPubMed
Yap, M. B. H., Allen, N. B., Shea, M. O., Parsia, D. I., Simmons, J. G., & Sheeber, L. (2011). Early adolescents’ temperament, emotion regulation during mother-child interactions, and depressive symptomatology. Development and Psychopathology, 23, 267282. doi:10.1017/S0954579410000787CrossRefGoogle ScholarPubMed
Yap, M. B. H., Pilkington, P. D., Ryan, S. M., Kelly, C. M., & Jorm, A. F. (2014). Parenting strategies for reducing the risk of adolescent depression and anxiety disorders: A Delphi consensus study. Journal of Affective Disorders, 156, 6775. doi:10.1016/j.jad.2013.11.017CrossRefGoogle ScholarPubMed
Yap, M. B. H., Whittle, S., Yücel, M., Sheeber, L., Pantelis, C., Simmons, J. G., & Allen, N. B. (2008). Interaction of parenting experiences and brain structure in the prediction of depressive symptoms in adolescents. Archives of General Psychiatry, 65, 13771385. doi:10.1001/archpsyc.65.12.1377CrossRefGoogle ScholarPubMed
Supplementary material: File

Deane et al. supplementary material

Tables S1-S4 and Figures S1-S2

Download Deane et al. supplementary material(File)
File 5 MB
Cited by

Save article to Kindle

To save this article to your Kindle, first ensure is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the or variations. ‘’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Parenting × Brain Development interactions as predictors of adolescent depressive symptoms and well-being: Differential susceptibility or diathesis-stress?
Available formats

Save article to Dropbox

To save this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Dropbox account. Find out more about saving content to Dropbox.

Parenting × Brain Development interactions as predictors of adolescent depressive symptoms and well-being: Differential susceptibility or diathesis-stress?
Available formats

Save article to Google Drive

To save this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your Google Drive account. Find out more about saving content to Google Drive.

Parenting × Brain Development interactions as predictors of adolescent depressive symptoms and well-being: Differential susceptibility or diathesis-stress?
Available formats

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *