Hostname: page-component-8448b6f56d-wq2xx Total loading time: 0 Render date: 2024-04-19T22:51:24.875Z Has data issue: false hasContentIssue false
  • English
  • Français

The effects of the interplay of genetics and early environmental risk on the course of internalizing symptoms from late childhood through adolescence

Published online by Cambridge University Press:  04 May 2015

Rashelle J. Musci ,
Katherine E. Masyn ,
Kelly Benke ,
Brion Maher ,
George Uhl  and
Nicholas S. Ialongo
Rashelle J. Musci*
Affiliation:
Johns Hopkins University Bloomberg School of Public Health
Katherine E. Masyn
Affiliation:
Harvard University Graduate School of Education
Kelly Benke
Affiliation:
Johns Hopkins University Bloomberg School of Public Health
Brion Maher
Affiliation:
Johns Hopkins University Bloomberg School of Public Health
George Uhl
Affiliation:
NIH-IRP NIDA Molecular Neurobiology Branch
Nicholas S. Ialongo
Affiliation:
Johns Hopkins University Bloomberg School of Public Health
*
Address correspondence and reprint requests to: Rashelle J. Musci, Bloomberg School of Public Health, Johns Hopkins University, 624 North Broadway, Room 841, Baltimore, MD 21205; E-mail: rmusci1@jhu.edu.
Get access Rights & Permissions [Opens in a new window]

Abstract

Internalizing symptoms during adolescence and beyond is a major public health concern, particularly because severe symptoms can lead to the diagnosis of a number of serious psychiatric conditions. This study utilizes a unique sample with a complex statistical method in order to explore Gene × Environment interactions found in internalizing symptoms during adolescence. Data for this study were drawn from a longitudinal prevention intervention study (n = 798) of Baltimore city school children. Internalizing symptom data were collected using self-report and blood or saliva samples genotyped using Affymetrix 6.0 microarrays. A major depression polygenic score was created for each individual using information from the major depressive disorder Psychiatric Genetics Consortium and used as a predictor in a latent trait–state–occasion model. The major depressive disorder polygenic score was a significant predictor of the stable latent trait variable, which captures time-independent phenotypic variability. In addition, an early childhood stressor of death or divorce was a significant predictor of occasion-specific variables. A Gene × Environment interaction was not a significant predictor of the latent trait or occasion variables. These findings support the importance of genetics on the stable latent trait portion of internalizing symptoms across adolescence.

Type
Regular Articles
Information
Development and Psychopathology , Volume 28 , Issue 1 , February 2016 , pp. 225 - 237
Copyright
Copyright © Cambridge University Press 2015 

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

Abramson, L., Seligman, M., & Teasdale, J. D. (1978). Learned helplessness in humans: Critique and reformulation. Journal of Abnormal Psychology, 37, 49–74.Google Scholar
Adam, E. K., & Chase-Landsdale, L. P. (2002). Home sweet home(s): Parental separations, residential moves and adjustment projects in low income adolescent girls. Developmental Psychology, 38, 792–805.CrossRefGoogle Scholar
Amato, P. R. (2000). The consequences of divorce for adults and children. Journal of Marriage and Family, 62, 1269–1287.Google Scholar
American Psychiatric Association. (1978). Diagnosis and statistical manual of mental disorders (3rd rev. ed.). Washington, DC: Author.Google Scholar
Amin, N., van Duijin, C. M., & Janssens, A. C. J. W. (2009). Genetic scoring analysis: A way forward in genomewide association studies? European Journal of Epidemiology, 24, 585–587. doi:10.1007/s10654-009-9387-y Google Scholar
Anderson, C. A., Pettersson, F. H., Clarke, G. M., Cardon, L. R., Morris, A. P., & Zondervan, K. T. (2010). Data quality control in genetic case-control association studies. Nature Protocols, 5, 1564–1573. doi:10.1038/nprot.2010.116 Google Scholar
Asarnow, J. R., & Carlson, G. A. (1985). Depression self-rating scale: Utility with child psychiatric inpatients. Journal of Consulting Psychology, 53, 491–499 Google Scholar
Bartels, M., Rietveld, M. J. H., Van Baal, G. C. M., & Boomsma, D. I. (2002). Genetic and environmental influences on the development of intelligence. Behavior Genetics, 32, 237–249.Google Scholar
Battaglia, M., Pesenti-Gritti, P., Medland, S. E., Ogliari, A., Tambs, K., & Spatola, C. A. (2009). A genetically informed study of the association between childhood separation anxiety, sensitivity to CO(2), panic disorder, and the effect of childhood parental loss. Archives of General Psychiatry, 66, 64–71. doi:10.1001/archgenpsychiatry.2008.513 Google Scholar
Beach, S., Brody, G., Lei, M. K., Sangjin, K., Kui, J., & Philibert, R. (2014). Is serotonin transporter genotype associated with epigenetic susceptibility or vulnerability? Examination of the impact of socioeconomic status risk on African American youth. Development and Psychopathology, 26, 1–16.CrossRefGoogle ScholarPubMed
Belden, A., Barch, D. M., Oakberg, T. J., April, L. M., Harms, M. P., Botteron, K. N., et al. (in press). Anterior insula volume and guilt: Neurobehavioral markers of recurrence after early childhood major depressive disorder. JAMA Psychiatry.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, 300–304. doi:10.1111/j.1467-8721.2007.00525.x Google Scholar
Belsky, J., & Pluess, M. (2009). Beyond diathesis stress: Differential susceptibility to environmental influences. Psychological Bulletin, 135, 885–908. doi:10.1037/a0017376 Google Scholar
Benke, K. S., Nivard, M. G., Velders, F. P., Walters, R. K., Pappa, I., Scheet, P. A., et al. (in press). Genome-wide association meta-analysis of preschool internalizing problems. Journal of the American Academy of Child & Adolescent Psychiatry.Google Scholar
Boomsma, D. I., Van Beijsterveldt, C. E. M., & Hudziak, J. J. (2005). Genetic and environmental influences on anxious/depression during childhood: A study from the Netherlands Twin Register. Genes, Brain and Behavior, 4, 466–481.Google Scholar
Booth, A., Rustenbach, E., & McHale, S. (2008). Early family transitions and depressive symptom changes from adolescence to early adulthood. Journal of Marriage and Family, 70, 3–14.Google Scholar
Brady, E. U., & Kendall, P. C. (1992). Comorbidity of anxiety and depression in children and adolescents. Psychological Bulletin, 111, 244–255.Google Scholar
Brody, G. H., Yu, T., Beach, S., & Philibert, R. (in press). Prevention effects ameliorate the prospective association between non-supportive parenting and diminished telomere length. Prevention Science.Google Scholar
Caspi, A., Sugden, K., Moffitt, T. E., Taylor, A., Craig, I. W., Harrington, H., et al. (2003). Influence of life stress on depression: Moderation by a polymorphism in the 5-HTT gene. Science, 301, 386–389.Google Scholar
Cicchetti, D., & Schneider-Rosen, K. (1984). Toward a transactional model of childhood depression. In Cicchetti, D. & Schneider-Rosen, K. (Eds.), Childhood depression a developmental perspective (pp. 5–28). San Francisco, CA: Jossey–Bass.Google Scholar
Cole, D. A., Martin, N. C., & Steiger, J. H. (2005). Empirical and conceptual problems with longitudinal trait–state models: Introducing a trait-state-occasion model. Psychological Methods, 10, 3–20. doi:10.1037/1082-989X.10.1.3 Google Scholar
Cole, D. A., & Rehm, L. (1986). Family interaction patterns and childhood depression. Journal of Abnormal Child Psychology, 14, 297–314.Google Scholar
Deary, I. J., Spinath, F. M., & Bates, T. C. (2006). Genetics of intelligence. European Journal of Human Genetics, 14, 690–700.Google Scholar
DeCoster, J., Iselin, A. R., & Gallucci, M. (2009). A conceptual and empirical examination of justifications for dichotomization. Psychological Methods, 14, 349–366.Google Scholar
D'Onofrio, B. M., Turkheimer, E., Emery, R., Maes, H. H., Silberg, J., & Eaves, L. J. (2007). A children of twins study of parental divorce and offspring psychpathology. Journal of Child Psychology and Psychiatry, 48, 667–675. doi:10.1111/j.1469-7610.2007.01741.x CrossRefGoogle Scholar
D'Onofrio, B. M., Turkheimer, E., Emery, R. E., Slutske, W. S., Heath, A. C., Madden, P. A., et al. (2005). A genetically informed study of marital instability and its association with offspring psychopathology. Journal of Abnormal Psychology, 114, 570–586. doi:10.1037/0021-843X.114.4.570 Google Scholar
Duncan, L. E., Pollastri, A. R., & Smoller, J. W. (2014). Mind the gap: Why many geneticists and psychological scientists have discrepant views about gene-environment interaction (GxE) research. American Journal of Psychology, 69, 249–268. doi:10.1037/a0036320 Google Scholar
Dunn, E., Uddin, M., Subramanian, S. V., Smoller, J. W., Galea, S., & Koenen, K. (2011). Research Review: Gene–environment interaction research in youth depression—A systematic review with recommendations for future research. Journal of Child Psychology and Psychiatry, 52, 1223–1238.Google Scholar
Edelsohn, G., Ialongo, N., Wethamer-Larsson, L., Crockett, L., & Kellam, S. (1992). Self- reported depressive symptoms in first-grade children: Developmentally transient phenomena? Journal of the American Academy of Child & Adolescent Psychiatry, 31, 282–290.Google Scholar
Ensminger, M. E., Forrest, C. B., Riley, A. W., Kang, M., Green, B. F., & Starfield, B. (2000). The validity of measures of socioeconomic status of adolescents. Journal of Adolescent Research, 15, 392–419. doi: 10.1177/0743558400153005 CrossRefGoogle Scholar
Ferentinos, P., Rivera, M., Ising, M., Spain, S. L., Cohen-Woods, S., Butler, A. W., et al. (2013). Investigating the genetic variation underlying episodicity in major depressive disorder: Suggestive evidence for a bipolar contribution. Journal of Affective Disorders, 155, 81–89.Google Scholar
Garber, J., & Weersing, V. R. (2010). Comorbidity of anxiety and depression in youth: Implications for treatment and prevention. Clinical Psychology: Science and Practice, 17, 293–306.Google Scholar
Gheyara, S., Klump, K. L., McGue, M., Iacono, W. G., & Burt, S. A. (2011). The death(s) of close friends and family moderate genetic influences on symptoms of major depressive disorder. Psychological Medicine, 41, 721–730.CrossRefGoogle ScholarPubMed
Hatton, H., Donnellan, M. B., Masyn, K., Feldman, B. J., Larsen-Rife, D., & Conger, R. D. (2008). Family and individual difference predictors of trait aspects of negative interpersonal behaviors during emerging adulthood. Journal of Family Psychology, 22, 448–455. doi:10.1037/0893-3200.22.3.448 Google Scholar
Ialongo, N., Edelsohn, G., Werthamer-Larsson, L., Crockett, L., & Kellam, S. (1994). The significance of self-reported anxious symptoms in first grade children. Journal of Abnormal Child Psychology, 22, 441–456.Google Scholar
Ialongo, N., Edelsohn, G., Werthamer-Larsson, L., Crockett, L., & Kellam, S. (1995). The significance of self-reported anxious symptoms in first grade children: Prediction to anxious symptoms and adaptive functioning in fifth grade. Journal of Child Psychology and Psychiatry, 36, 427–437.Google Scholar
Ialongo, N., Edelsohn, G., Werthamer-Larsson, L., Crockett, L., & Kellam, S. (1996). Cognitive and social impairment in first graders with anxious and depressive symptoms. Journal of Clinical Child Psychology, 25, 15–24.Google Scholar
Ialongo, N., Poduska, J., Werthamer, L., & Kellam, S. (2001). The distal impact of two first grade preventive interventions on conduct problems and disorder in early adolescence. Journal of Emotional and Behavioral Disorders, 9, 146–160.Google Scholar
Ialongo, N. S., Werthamer, L., Kellam, S. G., Brown, C. H., Wang, S., & Lin, Y. (1999). Proximal impact of two first-grade preventive interventions on the early risk behaviors for later substance abuse, depression, and antisocial behavior. American Journal of Community Psychology, 27, 599–641. doi:10.1023/A:1022137920532.Google Scholar
Jaffee, S. R., Moffitt, T. E., Caspi, A., Fombonne, E., Poulton, R., & Martin, J. (2002). Differences in early childhood risk factors for juvenile-onset and adult-onset depression. Archives of General Psychiatry, 58, 215–222.Google Scholar
Kang, S. J., Larkin, E. K., Song, Y., Barnholtz-Sloan, J., Baechle, D., Feng, T., et al. (2009). Assessing the impact of global vs. local ancestry in association studies. BMC Proceedings, 3, S107. doi:10.1186/1753-6561-3-S7-S107 Google Scholar
Karg, K., Burmeister, M., Shedden, K., & Sen, S. (2011). The serotonin transporter variant (5HTTLPR), stress, and depression meta-analysis revisited. Archives of General Psychiatry, 68, 444–454.CrossRefGoogle ScholarPubMed
Kazdin, A. E., Rodgers, A., & Colbus, D. (1986). The hopelessness scale for children: Psychometric characteristics and concurrent validity. Journal of Consulting Psychology, 54, 241–245.Google Scholar
Kellam, S., & Rebok, G. (1992). Building developmental and etiological theory through epidemiologically based preventive intervention trials. In McCord, J. & Tremblay, R. E. (Eds.), Preventing antisocial behavior: Interventions from birth through adolescence (pp. 162–195). New York: Neale Watson Academic Publishers.Google Scholar
Kendler, K. S., Heath, A. C., Martin, N. G., & Eaves, L. J. (1987). Symptoms of anxiety and symptoms of depression: Same genes, different environments? Archives of General Psychiatry, 44, 451–457.Google Scholar
Kendler, K. S, Kessler, R. C., Walters, E. E., MacLean, C., Neale, M. C., Heath, A. C., et al. (1995). Stressful life events, genetic liability, and onset of an episode of major depression in women. American Journal of Psychiatry, 152, 833–842.Google Scholar
Kendler, K. S., Neale, M. C., Kessler, R. C., Heath, A. C., & Eaves, L. J. (1992). Childhood parental loss and adult psychopathology in women: A twin study perspective. Archives of General Psychiatry, 49, 109–116.Google Scholar
Kovacs, M. (1983). The Children's Depression Inventory: A self-rated depression scale for school-age youngsters. Unpublished manuscript, University of Pittsburgh.Google Scholar
Lambert, S. F., McCreary, B. T., Joiner, T. E., Schmidt, N. B., & Ialongo, N. S. (2004). Structure of anxiety and depression in urban youth: An examination of the tripartite model. Journal of Consulting and Clinical Psychology, 72, 904–908.Google Scholar
Little, T. D., Cunningham, W. A., Shahar, G., & Widaman, K. F. (2002). To parcel or not to parcel: Exploring the question, weighing the merits. Structural Equation Modeling, 9, 151–173. doi:10.1207/S15328007SEM0902_1 Google Scholar
Little, T. D., Rhemtulla, M., Gibson, K., & Schoemann, A. M. (in press). Why the items versus parcels controversy needn't be one. Pyschological Methods. Google Scholar
Liu, J., Lewinger, J. P., Gilliland, F. D., Gauderman, W. J., & Conti, D. V. (2013). Confounding and heterogeneity in genetic associations with admixed populations. American Journal of Epidemiology, 177, 351–360. doi:10.1093/aje/kws234 Google Scholar
Luby, J. (2010). Preschool depression the importance of identification of depression early in development. Current Directions in Psychological Science, 19, 91–95.Google Scholar
Luby, J. L., Belden, A., Botteron, K., Marrus, N., Harms, M. P., Babb, C., et al. (2013). The effects of poverty on childhood brain development: The mediating effect of caregiving and stressful life events. JAMA Pediatrics, 167, 1135–1142.Google Scholar
Luby, J. L., Gaffrey, M. S., Tillman, R., April, L. M., & Belden, A. C. (in press). Trajectories of preschool disorders to full DSM depression at school age and early adolescence: Continuity of preschool depression. American Journal of Psychiatry.Google Scholar
Luecken, L. J., Hagan, M. J., Sandler, I. N., Tein, J. Y, Ayers, T. S., & Wolchik, S. (2014). Longitudinal mediators of a randomized prevention program effect on cortisol for youth from parentally bereaved families. Prevention Science, 15, 224–232.Google Scholar
McCutcheon, V. V., Heath, A. C., Nelson, E. C., Bucholz, K. K., Madden, P. A. F., & Martin, N. G. (2009). Accumulation of trauma over time and risk for depression in a twin sample. Psychological Medicine, 39, 431–441.Google Scholar
Melhem, N. M., Walker, M., Moritz, G., & Brent, D. A. (2008). Antecedents and sequelae of sudden parental death in offspring and surviving caregivers. Archives of Pediatric and Adolescent Medicine, 162, 403–410.Google Scholar
Montana, G., & Pritchard, J. K. (2004). Statistical tests for admixture maping with case-control and cases only. American Journal of Human Genetics, 75, 771–789.Google Scholar
Moos, R. H., Cronkite, R. L., Billings, A. G., & Finney, J. W. (1987). Revised health and daily living form manual. Palo Alto, CA: Veterans Administration and Stanford University Medical Centers.Google Scholar
Muthén, B., & Muthén, L. (1998–2012). Mplus user's guide. Los Angeles: Author.Google Scholar
Muthén, B., & Shedden, K. (1999). Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics, 55, 463–469. doi:10.1111/j.0006-341X.1999.00463.x Google Scholar
O'Connor, T. G., Caspi, A., DeFries, J. C., & Plomin, R. (2000). Are associations between parental divorce and children's adjustment genetically mediated? An adoption study. Developmental Psychology, 36, 429–437. doi:10.1037/0012-1649.36.4.429 Google Scholar
Olatunji, B. O, & Cole, D. A. (2009). The longitudinal structure of general and specific anxiety dimensions in children: Testing a latent trait-state-occasion model. Psychological Assessment, 21, 412–424. doi:10.1037/a0016206 Google Scholar
Ouellet-Morin, I., Boivin, M., Dionne, G., Lupien, S. J., Arsenault, L., Barr, R. G., et al. (2008). Variations in heritability of cortisol reactivity to stress as a function of early familial adversity among 19-month-old twins. Archives of General Psychiatry, 65, 211–218.CrossRefGoogle ScholarPubMed
Persico, A. M., Bird, G., Gabbay, F. H., & Uhl, G. R. (1996). D2 dopamine receptor gene taqI A1 and B1 restriction fragment length polymorphisms: Enhanced frequencies in psychostimulant-preferring polysubstance abusers. Journal of Biological Psychiatry, 40, 776–784. doi:10.1016/0006-3223(95)00483-1 Google Scholar
Plomin, R., & Spinath, F. M. (2004). Intelligence: Genetics, genes, and genomics. Journal of Personality and Social Psychology, 86, 112–129.Google Scholar
Pritchard, J. K., & Rosenberg, N. A. (1999). Use of unlinked genetic markers to detect population stratification in association studies. American Journal of Human Genetics, 65, 220–228. doi:10.1086/302449 Google Scholar
Psychiatric Genomics Consortium. (2013). A mega-analysis of genome-wide association studies for major depressive disorder. Molecular Psychiatry, 18, 497–511.Google Scholar
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., et al. (2007). PLINK: A tool set for whole-genome association and population-based linkage analyses. American Journal of Human Genetics, 81, 559–575. doi:10.1086/519795 Google Scholar
Qin, H., Morris, N., Kang, S. J., Li, M., Tayo, B., Lyon, H., et al. (2010). Interrogating local population structure for fine mapping in genome-wide association studies. Bioinformatics, 26, 2961–2968. doi:10.1093/bioinformatics/btq560 Google Scholar
Radke-Yarrow, M., Belmont, B., Nottlemann, E., & Bottomly, L. (1990). Young children's self-conceptions: Origins in the natural discourse of depressed and normal mothers and their children. In Cicchetti, D. & Beeghly, M. (Eds.), The self in transition: Infancy to childhood (pp. 345–361). Chicago: University of Chicago Press.Google Scholar
Rescorla, L., Ivanova, M. Y., Achenbach, T. M., Begovac, I., Chahed, M., Druglo, M. B., et al. (2012). International epidemiology of child and adolescent psychopathology: II. Integration and applications of dimensional findings from 44 societies. Journal of the American Academy of Child & Adolescent Psychiatry, 51, 1273–1283.Google Scholar
Reuter, M. A., Scaramella, L., Wallace, L. E., & Conger, R. D. (1999). First onset of depressive or anxiety disorders predicted by the longitudinal course of internalizing symptoms and parent-adolescent disagreements. Archives of General Psychiatry, 56, 726–732. doi:10.1001/archpsyc.56.8.726 Google Scholar
Reynolds, C. R., & Richmond, B. O. (1985). Revised Children's Manifest Anxiety Scale (RCMAS) manual. Los Angeles: Western Psychological Services.Google Scholar
Rice, F., van den Bree, M., & Thapar, A. (2004). A population-based study of anxiety as a precursor for depression in childhood and adolescence. BMC Psychiatry, 4, 43.Google Scholar
Risch, N., Herrell, R., Lehner, T., Liang, K. Y., Eaves, L., Hoh, J., et al. (2009). Interaction between the serotonin transporter gene (5-HTTLPR), stressful life events, and risk of depression: A meta-analysis. Journal of the American Medical Association, 301, 2462–2471.Google Scholar
Sankararaman, S., Sridhar, S., Kimmel, G., & Halperin, E. (2008). Estimating local ancestry in admixed populations. American Journal of Human Genetics, 82, 290–303. doi:10.1016/j.ajhg.2007.09.022 Google Scholar
Schafer, J. L., & Graham, J. W. (2002). Missing data: Our view of the state of the art. Psychological Methods, 7, 147–177. doi:10.1037/1082-989X.7.2.147 Google Scholar
Shaffer, D., Fisher, P., Lucas, C., Dulcan, M., & Schwab-Stone, M. (2000). NIMH Diagnostic Interview Schedule for Children Version IV (NIMH DISC-IV): Description, differences from previous versions, and reliability of some common diagnoses. Journal of the American Academy of Child & Adolescent Psychiatry, 39, 28–38.Google Scholar
Silberg, J. L., Rutter, M., & Eaves, L. (2001). Genetic and environmental influences on the temporal association between earlier anxiety and later depression in girls. Biological Psychiatry, 49, 1040–1049.Google Scholar
Streiner, D. L. (2002). Breaking up is hard to do: The heartbreak of dichotomizing continuous data. Canadian Journal of Psychiatry, 47, 262–266.Google Scholar
Thompson, P. M., Cannon, T. D., Narr, K. L., van Erp, T., Poutanen, V., Huttunen, M., et al. (2001). Genetic influences on brain structure. Nature Neuroscience, 4, 1253–1258.Google Scholar
Trouton, A., Spinath, F. M., & Plomin, R. (2002). Twins Early Development Study (TEDS): A multivariate, longitudinal genetic investigation of language, cognition and behavior problems in childhood. Twin Research, 5, 444–448.Google Scholar
Tucker-Drob, E., Briley, D. A., & Harden, K. P. (2013). Genetic and environmental influences on cognition across development and context. Current Directions in Psychological Science, 22, 349–355.Google Scholar
Vélez, C. E., Wolchik, S. A., Tein, J. Y., & Sandler, I. (2011). Protecting children from the consequences of divorce: A longitudinal study of the effects of parenting on children's coping processes. Child Development, 82, 2244–2257.Google Scholar
Wang, M., & Saudino, K. J. (2013). Genetic and environmental influences on individual differences in emotion regulation and its relation to working memory in toddlerhood. Emotion, 13, 1055–1067.Google Scholar
Waszczuk, M. A., Zavos, H. M., Gregory, A. M., & Eley, T. C. (2014). The phenotypic and genetic structure of depression and anxiety disorder symptoms in childhood, adolescence, and young adulthood. JAMA Psychiatry, 71, 905–916.Google Scholar
Whalley, H. C., Sprooten, E., Hackett, S., Hall, L., Blackwood, D. H., Glahn, D. C., et al. (2013). Polygenic risk and white matter integrity in individuals at high risk of mood disorder. Biological psychiatry, 74, 280–286.Google Scholar
Wolchik, S. A., Sandler, I. N., Tein, J. Y., Mahrer, N., Millsap, R., Winslow, E., et al. (2013). Fifteen-year follow-up of a randomized trial of a preventive intervention for divorced families: Effects on mental health and substance use outcomes in young adulthood. Journal of Consulting and Clinical Psychology, 81, 660–673.Google Scholar