Hostname: page-component-669899f699-tzmfd Total loading time: 0 Render date: 2025-05-06T20:24:28.773Z Has data issue: false hasContentIssue false
  • English
  • Français

Trajectories of emotional–behavioral difficulty and academic competence: A 6-year, person-centered, prospective study of affluent suburban adolescents

Published online by Cambridge University Press:  22 February 2016

Nadia S. Ansary ,
Thomas J. McMahon  and
Suniya S. Luthar
Nadia S. Ansary*
Affiliation:
Rider University
Thomas J. McMahon
Affiliation:
Yale University School of Medicine
Suniya S. Luthar
Affiliation:
Arizona State University
*
Address correspondence and reprint requests to: Nadia S. Ansary, Rider University, Department of Psychology, 2083 Lawrenceville Road, Lawrenceville, NJ 08648-3099; E-mail: [email protected].
Get access Rights & Permissions [Opens in a new window]

Abstract

This longitudinal study of affluent suburban youth (N = 319) tracked from 6th to 12th grade is parsed into two segments examining prospective associations concerning emotional–behavioral difficulties and academic achievement. In Part 1 of the investigation, markers of emotional–behavioral difficulty were used to cluster participants during 6th grade. Generalized estimating equations were then used to document between-cluster differences in academic competence from 6th to 12th grade. In Part 2 of the study, indicators of academic competence were used to cluster the same students during 6th grade, and generalized estimating equations were used to document between-cluster differences in emotional–behavioral difficulty from 6th to 12th grade. The results from Part 1 indicated that patterns of emotional–behavioral difficulty during 6th grade were concurrently associated with poorer grades and classroom adjustment with some group differences in the rate of change in classroom adjustment over time. In Part 2, patterns of academic competence during 6th grade were concurrently associated with less emotional–behavioral difficulty and some group differences in the rate of change in specific forms of emotional–behavioral difficulty over time. These results suggest that the youth sampled appeared relatively well adjusted and any emotional–behavioral–achievement difficulty that was evident at the start of middle school was sustained through the end of high school.

Type
Regular Articles
Information
Development and Psychopathology , Volume 29 , Special Issue 1: Developmental and Social–Ecological Perspectives on Children, Political Violence, and Armed Conflict , February 2017 , pp. 215 - 234
Copyright
Copyright © Cambridge University Press 2016 

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.)

Article purchase

Temporarily unavailable

References

Ansary, N. S., & Luthar, S. S. (2009). Distress and academic achievement among adolescents of affluence: A study of externalizing and internalizing problem behaviors and school performance. Development and Psychopathology, 21, 319–341. doi:10.1017/S0954579409000182 CrossRefGoogle ScholarPubMed
Ansary, N. S., McMahon, T., & Luthar, S. S. (2012). Socioeconomic context and emotional-behavioral-achievement links: Concurrent and prospective associations among low- and high-income youth. Journal of Research on Adolescence, 22, 14–30. doi:10.1111/j.1532-7795.2011.00747.x CrossRefGoogle Scholar
Beidel, D. C. (1991). Social phobia and overanxious disorder in school age children. Journal of the American Academy of Child & Adolescent Psychiatry, 30, 545–552. doi:10.1097/00004583-199107000-00003 CrossRefGoogle ScholarPubMed
Bergman, L. R. (2001). A person approach in research on adolescence: Some methodological challenges. Journal of Adolescent Research, 16, 28–53. doi:10.1177/0743558401161004 CrossRefGoogle Scholar
Bergman, L. R., & Magnusson, D. (1997). A person-oriented approach in research on developmental psychopathology. Development and Psychopathology, 9, 291–319. doi:10.1017/S095457949700206X CrossRefGoogle ScholarPubMed
Bergman, L. R., Magnusson, D., & El-Khouri, B. M. (2003). Studying individual development in an interindividual context. Mahwah, NJ: Erlbaum.CrossRefGoogle Scholar
Brusco, M. J., & Kohn, H. F. (2008). Optimal partitioning of a dataset based on the p-median model. Psychometrika, 73, 89–105. doi:10.1007/S11336-007-9021-4 CrossRefGoogle Scholar
Bryant, A. L., Schulenberg, J. E., O'Malley, P. M., Bachman, J. G., & Johnston, L. D. (2003). How academic achievement, attitudes, and behaviors relate to the course of substance use during adolescence: A 6-year, multiwave national longitudinal study. Journal of Research on Adolescence, 13, 361–397. doi:10.1111/1532-7795.1303005 CrossRefGoogle Scholar
Bryant, A. L., & Zimmerman, M. A. (2002). Examining the effects of academic beliefs and behaviors on changes in substance use among urban adolescents. Journal of Educational Psychology, 94, 621–637. doi:10.1037/0022-0663.94.3.621 CrossRefGoogle Scholar
Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996). Behavioral observations at age 3 years predict adult psychiatric disorders: Longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53, 1033–1039.CrossRefGoogle ScholarPubMed
Casswell, S., Pledger, M., & Hooper, R. (2003). Socioeconomic status and drinking patterns in young adults. Addiction, 98, 601–610. doi:10.1046/j.1360-0443.2003.00331.x CrossRefGoogle ScholarPubMed
Cicchetti, D., & Rogosch, F. A. (2002). A developmental psychopathology perspective on adolescence. Journal of Consulting and Clinical Psychology, 70, 6–20. doi:10.1037/0022-006X.70.1.6 CrossRefGoogle ScholarPubMed
Craighead, W. E., Curry, J. F., & Hardi, S. S. (1995). Relationship of Children's Depression Inventory factors to major depression among adolescents. Psychological Assessment, 7, 171–176.CrossRefGoogle Scholar
De Clercq, B., Rettew, D., Althoff, R. R., & De Bolle, M. (2012). Childhood personality types: Vulnerability and adaptation over time. Journal of Child Psychology and Psychiatry, 53, 716–722. doi:10.1111/j.1469-7610.2011.02512.x CrossRefGoogle ScholarPubMed
Defoe, I. N., Farrington, D. P., & Loeber, R. (2013). Disentangling the relationship between delinquency and hyperactivity, low achievement, depression, and low socioeconomic status: Analysis of repeated longitudinal data. Journal of Criminal Justice, 41, 100–107. doi:10.1016/j.jcrimjus.2012.12.002 CrossRefGoogle Scholar
Eccles, J. S., Roeser, R., Vida, M., Fredricks, J., & Wigfield, A. (2006). Motivational and achievement pathways through middle childhood. In Balter, L. & Tamis-LeMonda, C. S. (Eds.), Child psychology: A handbook of contemporary issues (2nd ed., pp. 325–356). New York: Psychology Press.Google Scholar
Ellickson, P., Bui, K., Bell, R., & McGuigan, K. A. (1998). Does early drug use increase the risk of dropping out of high school? Journal of Drug Issues, 28, 357–380.CrossRefGoogle Scholar
Elliot, D. S., Dunford, F. W., & Huizinga, D. (1987). The identification and prediction of career offenders utilizing self-reported and official data. In Burchard, J. & Burchard, S. (Eds.), Prevention of delinquent behavior (pp. 90–121). Newbury Park, CA: Sage.Google Scholar
Ensminger, M. E., & Joun, H. S. (1998). Transition to adulthood among high-risk youth. In Jessor, R. (Ed.), New perspectives on adolescent risk behavior (pp. 365–391) New York: Cambridge University Press.Google Scholar
Granleese, J., & Joseph, S. (1993). Factor analysis of the Self-Perception Profile for Children. Personality and Individual Differences, 15, 343–345. doi:10.1016/0191-8869(93)90226-S CrossRefGoogle Scholar
Granleese, J., & Joseph, S. (1994). Further psychometric validation of the Self-Perception Profile for Children. Personality and Individual Differences, 16, 649–651. doi:10.1016/0191-8869(94)90193-7 CrossRefGoogle Scholar
Grossman, I., & Huynh, A. C. (2013). Where is the culture in social class? Psychological Inquiry, 24, 112–119. doi:10.1080/1047840X.2013.792568 CrossRefGoogle Scholar
Hardin, J. W., & Hilbe, J. M. (2003). Generalized estimating equations. London: Chapman & Hall/CRC Press.Google Scholar
Harter, S. (1985). The Self-Perception Profile for Children: Revision of the Perceived Competence Scale for Children. Denver, CO: University of Denver.Google Scholar
Hightower, A. D., Work, W. C., Cowen, E. L., Lotyczewski, B. S., Spinell, A. P., Guare, J. C., et al. (1986). The Teacher–Child Rating Scale: A brief objective measure of elementary children's school problem behaviors and competencies. School Psychology Review, 15, 393–409.CrossRefGoogle Scholar
Huizinga, D., & Elliot, D. S. (1986). Reassessing the reliability and validity of self-report delinquency measures. Journal of Quantitative Criminology, 2, 293–327. doi:10.1007/BF01064258 CrossRefGoogle Scholar
Johnston, L. D., O'Malley, P. M., Bachman, J. G., & Schulenberg, J. E. (2014). Monitoring the Future national survey results on drug use, 1975–2012: Vol. 1. Secondary school students. Ann Arbor, MI: University of Michigan, Institute for Social Research.Google Scholar
Kaufman, L., & Rousseeuw, P. J. (2005). Finding groups in data: An introduction to cluster analysis (9th ed.). New York: Wiley.Google Scholar
Kessler, R. C., Foster, C. L., Saunders, W. B., & Stang, P. E. (1995). Social consequences of psychiatric disorders: I. Educational attainment. American Journal of Psychiatry, 152, 1026–1032.Google ScholarPubMed
Kohn, H. F., Steinley, D., & Brusco, M. J. (2010). The p-median model as a tool for clustering psychological data. Psychological Methods, 15, 87–95. doi:10.1037/a0018535 CrossRefGoogle ScholarPubMed
Kovacs, M. (1992). Children's Depression Inventory manual. New York: Multi-Health Systems.Google Scholar
Kraus, M. W., Tan, J. J. X., & Tannenbaum, M. B. (2013). The social ladder: A rank-based perspective on social class. Psychological Inquiry, 24, 81–96. doi:10.1080/1047840X.2013.778803 CrossRefGoogle Scholar
Last, C. G., Hersen, M., Kazdin, A. E., Orvaschel, H., & Perrin, S. (1991). Anxiety disorders in children and their families. Archives of General Psychiatry, 48, 928–934. doi:10.1001/archpsyc.1991.01810340060008 CrossRefGoogle ScholarPubMed
Lewinsohn, P. M., Roberts, R. E., Seeley, J. R., Rohde, P., Gotlib, I. H., & Hops, H. (1994). Adolescent psychopathology: II. Psychosocial risk factors for depression. Journal of Abnormal Psychology, 103, 302–315. doi:10.1037/0021-843X.103.2.302 CrossRefGoogle ScholarPubMed
Li, Y., & Lerner, R. M. (2011). Trajectories of school engagement during adolescence: Implications for grades, depression, delinquency, and substance use. Developmental Psychology, 47, 233–247. doi:10.1037/a0021307 CrossRefGoogle ScholarPubMed
Lipsey, M. W., & Derzon, J. H. (1998). Predictors of violent or serious delinquency in adolescence and early adulthood: A synthesis of longitudinal research. In Loeber, R. & Farrington, D. P. (Eds.), Serious and violent juvenile offenders (pp. 86–105). Thousand Oaks, CA: Sage.Google Scholar
Loeber, R., Farrington, D. P., Stouthamer-Loeber, M., Moffitt, T. E., Caspi, A., White, H. R., et al. (2003). The development of male offending: Key findings from fourteen years of the Pittsburgh Youth Study. In Thornberry, T. & Krohn, M. (Eds.), Taking stock of delinquency: An overview of findings from contemporary longitudinal studies (pp. 93–136). New York: Kluwer/Plenum Press.CrossRefGoogle Scholar
Ludden, A. B., & Eccles, J. S. (2007). Psychosocial, motivational, and contextual profiles of youth reporting different patterns of substance use during adolescence. Journal of Research on Adolescence, 17, 51–88. doi:10.1111/j.1532-7795.2007.00512.x CrossRefGoogle Scholar
Luthar, S. S., & Ansary, N. S. (2005). Dimensions of adolescent rebellion: Risks for academic failure among high- and low-income youth. Development and Psychopathology, 17, 231–250. doi:10.1017/S0954579405050121 CrossRefGoogle ScholarPubMed
Luthar, S. S., & Barkin, S. H. (2012). Are affluent youth truly “at risk”? Vulnerability and resilience across three diverse samples. Development and Psychopathology, 24, 429–449. doi:10.1017/S0954579412000089 CrossRefGoogle ScholarPubMed
Luthar, S. S., Barkin, S. H., & Crossman, E. J. (2013). “I can, therefore I must”: Fragility in the upper-middle classes. Development and Psychopathology, 25, 1529–1549. doi:10.1017/S0954579413000758 CrossRefGoogle ScholarPubMed
Luthar, S. S., & Becker, B. E. (2002). Privileged but pressured? A study of affluent youth. Child Development, 73, 1593–1610. doi:10.1111/1467-8624.00492 CrossRefGoogle ScholarPubMed
Luthar, S. S., & D'Avanzo, K. (1999). Contextual differences in substance use: A study of suburban and inner-city adolescents. Development and Psychopathology, 11, 845–867.CrossRefGoogle ScholarPubMed
Luthar, S. S., & McMahon, T. J. (1996). Peer reputation among inner-city adolescents: Structure and correlates. Journal of Research on Adolescence, 6, 581–603.Google Scholar
Magnuson, K., Duncan, G. J., & Kalil, A. (2006). The contribution of middle childhood contexts to adolescent achievement and behavior. In Huston, A. C. & Ripke, M. N. (Eds.), Developmental contexts in middle childhood: Bridges to adolescence and adulthood (pp. 150–172). New York: Cambridge University Press.CrossRefGoogle Scholar
Marsee, M. A., Frick, P. J., Barry, C. T., Kimonis, E. R., & Aucoin, K. J. (2014). Profiles of the forms and functions of self-reported aggression in three adolescent samples. Development and Psychopathology, 26, 705–720.CrossRefGoogle ScholarPubMed
Masten, A. S., Burt, K. B., Roisman, G. I., Obradovic, J., Long, J. D., & Tellegen, A. (2004). Resources and resilience in the transition to adulthood: Continuity and change. Development and Psychopathology, 16, 1071–1094. doi:10.1017/S0954579404040143 CrossRefGoogle ScholarPubMed
Masten, A. S., Morison, P., & Pellegrini, D. S. (1985). The revised class play method of peer assessment. Developmental Psychology, 21, 523–533.CrossRefGoogle Scholar
Masten, A. S., Roisman, G. I., Long, J. D., Burt, K. B., Obradovic, J., Riley, J. R., et al. (2005). Developmental cascades: Linking academic achievement and externalizing and internalizing symptoms over 20 years. Developmental Psychology, 41, 733–746. doi:10.1037/0012-1649.41.5.733 CrossRefGoogle ScholarPubMed
McMahon, T. J., & Luthar, S. S. (2006). Patterns and correlates of substance use among affluent, suburban high school students. Journal of Clinical Child and Adolescent Psychology, 35, 72–89. doi:10.1207/s15374424jccp3501_7 CrossRefGoogle ScholarPubMed
Moffitt., T. E., Caspi, A., Rutter, M., & Silva, P. A. (2001). Sex differences in antisocial behaviour: Conduct disorder, delinquency, and violence in the Dunedin Longitudinal Study. New York: Cambridge University Press.CrossRefGoogle Scholar
Muris, P., Meesters, C., & Fijen, P. (2003). The Self-Perception Profile for Children: Further evidence for its factor structure, reliability, and validity. Personality and Individual Differences, 35, 1791–1802. doi:10.1016/S0191-8869(03)00004-7 CrossRefGoogle Scholar
Newcomb, M. D., Abbott, R. D., Catalano, R. F., Hawkins, J. D., Battin-Pearson, S., & Hill, K. (2002). Mediational and deviance theories of late high school failure: Process roles of structural strains, academic competence, and general versus specific problem behaviors. Journal of Counseling Psychology, 49, 172–186. doi:10.1037/0022-0167.49.2.172 CrossRefGoogle Scholar
Newcomb, M. D., & Bentler, P. M. (1988). Consequences of adolescent drug use: Impact on the lives of young adults. Newbury Park, CA: Sage.Google Scholar
Pan, W. (2001). Akaike's information criterion in generalized estimating equations. Biometrics, 57, 120–125. doi:10.1111/j.0006-341X.2001.00120.x CrossRefGoogle ScholarPubMed
Pelkonen, M., Marttunen, M., & Aro, H. (2003). Risk for depression: A 6-year follow-up of Finnish adolescents. Journal of Affective Disorders, 77, 41–51. doi:10.1016/S0165-0327(02)00098-8 CrossRefGoogle ScholarPubMed
Reynolds, C. R., & Richmond, B. O. (1985). Revised Children's Manifest Anxiety Scale. Los Angeles: Western Psychological Services.Google ScholarPubMed
Roeser, R. W., Eccles, J. S., & Strobel, K. R. (1998). Linking the study of schooling and mental health: Selected issues and empirical illustrations at the level of the individual. Educational Psychologist, 33, 153–176. doi:10.1207/s15326985ep3304_2 CrossRefGoogle Scholar
Rubin, K. H., & Cohen, J. S. (1986). The Revised Class Play: Correlates of peer assessed social behaviors in middle childhood. Advances in Behavioral Assessment of Children and Families, 2, 176–206.Google Scholar
SAS Institute (2004). SAS/STAT 9.1 user's guide. Cary, NC: Author.Google Scholar
Schulenberg, J., Bachman, J. G., O'Malley, P. M., & Johnston, L. D. (1994). High school educational success and subsequent substance use: A panel analysis following adolescents into young adulthood. Journal of Health and Social Behavior, 35, 45–62.CrossRefGoogle ScholarPubMed
Stephens, N. M., & Townsend, S. S. M. (2013). Rank is not enough: Why we need a sociocultural perspective to understand social class. Psychological Inquiry, 24, 126–130. doi:10.1080/1047840X.2013.795099 CrossRefGoogle Scholar
Substance Abuse and Mental Health Services Administration. (2013). Results from the 2012 National Survey on Drug Use and Health: Summary of national findings (DHHS Publication SMA 13-4795). Rockville, MD: Author.Google Scholar
Topham, P., & Russell, G. (2012). Social anxiety in higher education. Psychologist, 25, 280–282.Google Scholar
US Census Bureau. (2002). United States Census 2000. Retrieved from http://www.census.gov/main/www/cen2000.html Google Scholar
Woodward, L. J., & Fergusson, D. M. (2001). Life course outcomes of young people with anxiety disorders in adolescence. Journal of American Academy of Child & Adolescent Psychiatry, 40, 1086–1093. doi:10.1097/00004583-200109000-00018 CrossRefGoogle ScholarPubMed
Zimmerman, M. A., & Schmeelk-Cone, K. H. (2003). Longitudinal analysis of adolescent substance use and school motivation among African American youth. Journal of Research on Adolescence, 13, 185–210. doi:10.1111/1532-7795.1302003 CrossRefGoogle Scholar