Abstract
This investigation examined profiles of individual, academic, and social risks in elementary school, and their association with mental health and academic difficulties in adolescence. Latent profile analyses of data from 574 urban youth revealed three risk classes. Children with the “well-adjusted” class had assets in the academic and social domains, low aggressive behavior, and low depressive symptoms in elementary school, and low rates of academic and mental health problems in adolescence. Children in the “behavior-academic-peer risk” class, characterized by high aggressive behavior, low academic achievement, and low peer acceptance, had conduct problems, academic difficulties, and increased mental health service use in adolescence. Children with the “academic-peer risk” class also had academic and peer problems but they were less aggressive and had higher depressive symptoms than the “behavior-academic-peer risk” class in the first grade; the “academic-peer risk” class had depression, conduct problems, academic difficulties, and increased mental health service use during adolescence. No differences were found between the risk classes with respect to adolescent outcomes.
Similar content being viewed by others
References
Ialongo N, Edelsohn G, Kellam SG (2001) A further look at the prognostic power of young children’s reports of depressed mood. Child Dev 72:736–747
Kellam SG, Rebok GW (1992) Building developmental and etiological theory through epidemiologically based preventive intervention trials. In: McCord J, Tremblay RE (eds) Preventing antisocial behavior: interventions from birth through adolescence. Guilford Press, New York, pp 162–195
Masten AS, Roisman GI, Long JD, Burt KB, Obradovic J, Riley AR et al (2005) Developmental cascades: Linking academic achievement and externalizing and internalizing symptoms over 20 years. Dev Psychol 41:733–746
Eccles JS (1999) The development of children ages 6 to 14. Future Child 9:30–44
Reinke WM, Herman KC, Petras H, Ialongo NS (2008) Empirically derived subtypes of child academic and behavior problems: co-occurrence and distal outcomes. J Abnorm Child Psychol 36:759–770
Carlson EA, Sroufe LA, Collins WA, Jimerson S, Winfield B, Hennighausen K et al (1999) Early environmental support and elementary school adjustment as predictors of school adjustment in middle adolescence. J Adolesc Res 14:72–94
Connor DF (2002) Aggression and antisocial behavior in children and adolescents: research and treatment. Guilford Press, New York
Scholte RHJ, Engels RCME, Overbeek G, de Kemp RAT, Haselager GJT (2007) Stability in bullying and victimization and its association with social adjustment in childhood and adolescence. J Abnorm Child Psychol 35:217–228
Van Lier PAC, Crijnen AAM (2005) Trajectories of peer-nominated aggression: risk status, predictors, and outcomes. J Abnorm Child Psychol 33:99–112
Avenevoli S, Knight E, Kessler RC, Ries Merikangas K (2008) Epidemiology of depression in children and adolescents. In: Abela JRZ, Hankin BL (eds) Handbook of depression in children and adolescents. Guilford Press, New York, pp 6–32
Asher SR (1990) Recent advances in the study of peer rejection. In: Asher SR, Coie JD (eds) Peer rejection in childhood. Cambridge University Press, New York, pp 3–14
Kistner J (2006) Children’s peer acceptance, perceived acceptance, and risk for depression. In: Joiner TE, Brown JS, Kistner J (eds) The interpersonal, cognitive, and social nature of depression. Lawrence Erlbaum Associates, Mahwah, NJ, US, pp 1–21
Pagani L, Tremblay RE, Vitaro F, Boulerice B, McDuff P (2001) Effects of grade retention on academic performance and behavioral development. Dev Psychopathol 13:297–315
Smokowski PR, Mann EA, Reynolds AJ, Fraser MW (2004) Childhood risk and protective factors and late adolescent adjustment in inner city minority youth. Child Youth Serv Rev 26:63–91
Lavin-Loucks D (2006) Research brief: The academic achievement gap. A project of the J. McDonald Williams Institute and the Foundation for Community Empowerment
Bradshaw C, Ialongo N, Schaeffer C, Petras H (2010) Predicting negative life outcomes from early aggressive—disruptive behavior trajectories: gender differences in maladaptation across life domains. J Youth Adolesc 39:953–966
Griffin RS, Gross AM (2004) Childhood bullying: current empirical findings and future directions for research. Aggress Violent Behav 9:379–400
Heijmens Visser J, van der Ende J, Koot HM, Verhulst FC (2003) Predicting change in psychopathology in youth referred to mental health services in childhood or adolescence. J Child Psychol Psychiatr 44:509–519
Berg DH, Klinger DA (2009) Gender differences in the relationship between academic self-concept and self-reported depressed mood in school children. Sex Roles 61:501–509
Hughes JN, Zhang D (2007) Effects of the structure of classmates’ perceptions of peers’ academic abilities on children’s academic self-concept, peer acceptance, and classroom engagement. Contemp Educ Psychol 32:400–419
Fergusson DM, Woodward LJ (2002) Mental health, educational, and social role outcomes of adolescents with depression. Arch Gen Psychiatry 59:225–231
Parra GR, DuBois DL, Sher KJ (2006) Investigation of profiles of risk factors for adolescent psychopathology: a person-centered approach. J Clin Child Adolesc Psychol 35:386–402
Thompson R (2005) The course and correlates of mental health care received by young children: descriptive data from a longitudinal urban high-risk sample. Child Youth Serv Rev 27:39–50
Farmer EM, Burns BJ, Phillips SD, Angold A, Costello EJ (2003) Pathways into and through mental health services for children and adolescents. Psychiatr Serv 54:60–66
Marsh HW, Ludtke O, Trautwein U, Morin JS (2009) Classical latent profile analysis of academic self-concept dimensions: synergy of person- and variable-centered approaches to theoretical models of self-concept. Struct Equ Modeling 16:191–225
Muthén B, Muthén L (2000) Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. Alcohol Clin Exp Res 24:882–891
Lubke GH, Muthen B (2005) Investigating population heterogeneity with factor mixture models. Psychol Methods 10:21–39
Walrath CM, Petras H, Mandell DS, Stephens RL, Holden EW, Leaf PJ (2004) Gender differences in patterns of risk factors among children receiving mental health services: latent class analyses. J Behav Health Serv Res 31:297–311
Rutter M (2001) Psychosocial adversity: risk, resilience, and recovery. In: Richman JM, Fraser MW (eds) The context of youth violence: resilience, risk, and protection. Praeger Publishers, Westport, pp 13–41
Ialongo N, Kellam SG, Poduska J (1999) Manual for the Baltimore how I feel (tech. Rep. No. 2). Johns Hopkins University, Baltimore
Association AmericanPsychiatric (1987) Diagnostic and statistical manual of mental disorders, 3rd edn. Author, Washington, DC
Pekarik E, Prinz R, Leibert C, Weintraub S, Neal J (1976) The pupil evaluation inventory: a sociometric technique for assessing children’s social behavior. J Abnorm Child Psychol 4:83–97
Alberti ET (1990) Comprehensive test of basic skills, 4th edn. CTB/McGraw-Hill, Monterey
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. J Am Acad Child Adolesc Psychiatry 39:28–38
American Psychiatric Association (1994) Diagnostic and statistical manual of mental disorders, 4th edn. Author, Washington, DC
Roberts N, Parker KCH, Dagnone M (2005) Comparison of clinical diagnoses, NIMH-DISC-IV diagnoses and SCL-90-R ratings in an adolescent psychiatric inpatient unit: a brief report. Can Child Adolesc Psychiatry Rev 14:103–105
Kazdin AE (1994) Informant variability in the assessment of childhood depression. In: Reynolds WM, Johnston HF (eds) Handbook of depression in children and adolescents: issues in clinical child psychology. Plenum, New York, pp 249–271
Horwitz SM, Hoagwood K, Stiffman AR, Summerfeld T, Weisz JR, Costello EJ et al (2001) Reliability of the services assessment for children and adolescents. Psychiatr Serv 52:1088–1094
Muthén LK, Muthén BO (1998–2006) Mplus user’s guide, 4th edn. Muthén and Muthén, Los Angeles
Nylund KL, Asparouhov T, Muthén B (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling. A Monte Carlo simulation study. Struct Equ Modeling 14:535–569
Schwartz G (1978) Estimating the dimensions of a model. Ann Stat 6:461–464
Sclove LS (1987) Application of a model-selection criteria to some problems in multivariate analysis. Psychometrika 52:333–343
Lo Y, Mendell NR, Rubin DB (2001) Testing the number of components in a normal mixture. Biometrika 88:767–778
Ramaswamy V, DeSarbo W, Reibstein D, Robinson W (1993) An empirical pooling approach for estimating marketing mix elasticities with PIMS data. Mark Sci 12:103–124
Arbuckle J (1996) Full information estimation in the presence of incomplete data. In: Marcoulides GA, Schumacker RE (eds) Advances in structural equation modeling: issues and techniques. Erlbaum, Mahwah, NJ
Muthén BO, Shedden K (1999) Finite mixture modeling with mixture outcomes using the EM algorithm. Biometrics 6:463–469
Schaefer JL, Graham JW (2002) Missing data: our view of the state of the art. Psychol Methods 7:147–177
Rutter M (1979) Protective factors in children’s response to stress and disadvantage. In: Kent MW, Rolf JE (eds) Primary prevention of psychopathology, vol III, social competence in children. University Press of New England, Hanover
Belle D (1989) Gender differences in children’s social networks and supports. In: Belle D (ed) Children’s social networks and supports. Wiley, New York
Cairns RB, Cairns BD (1994) Lifelines and risks: pathways of youth in our time. Cambridge University Press, Cambridge
Cairns RB, Cairns BD, Neckerman HJ (1989) Early school dropout: configurations and determinants. Child Dev 60:1437–1452
Caspi A, Moffitt TE, Newman DL, Silva PA (1998) Behavioral observations at age 3 years predict adult psychiatric disorders: longitudinal evidence from a birth cohort. Annu Prog Child Psychiatry Child Dev 1997:319–331
Acknowledgments
We thank the Baltimore City Public Schools for their continuing collaborative efforts and the parents, children, teachers, principals, and school psychologists and social workers who participated. We also express our appreciation to Hanno Petras and Scott Hubbard, who made significant contributions to the data analysis and editing of the manuscript. This research was supported by National Institutes of Mental Health Grants RO1 MH42968 (Sheppard Kellam, Principal Investigator) and T-32 MH18834 (Nicholas Ialongo, Principal Investigator) and Centers for Disease Control and Prevention Grant R49/CCR318627–03.
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
See Table 5.
Rights and permissions
About this article
Cite this article
Valdez, C.R., Lambert, S.F. & Ialongo, N.S. Identifying Patterns of Early Risk for Mental Health and Academic Problems in Adolescence: A Longitudinal Study of Urban Youth. Child Psychiatry Hum Dev 42, 521–538 (2011). https://doi.org/10.1007/s10578-011-0230-9
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10578-011-0230-9