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Journal of Abnormal Child Psychology

, Volume 47, Issue 5, pp 765–778 | Cite as

Using Early Childhood Behavior Problems to Predict Adult Convictions

  • Francesca KassingEmail author
  • Jennifer Godwin
  • John E. Lochman
  • John D. Coie
  • Conduct Problems Prevention Research Group
Article

Abstract

The current study examined whether teacher and parent ratings of externalizing behavior during kindergarten and 1st grade accurately predicted the presence of adult convictions by age 25. Data were collected as part of the Fast Track Project. Schools were identified based on poverty and crime rates in four locations: Durham, NC, Nashville, TN, Seattle, WA, and rural, central PA. Teacher and parent screening measures of externalizing behavior were collected at the end of kindergarten and 1st grade. ROC curves were used to visually depict the tradeoff between sensitivity and specificity and best model fit was determined. Five of the six combinations of screen scores across time points and raters met both the specificity and sensitivity cutoffs for a well-performing screening tool. When data were examined within each site separately, screen scores performed better in sites with high base rates and models including single teacher screens accurately predicted convictions. Similarly, screen scores performed better and could be used more parsimoniously for males, but not females (whose base rates were lower in this sample). Overall, results indicated that early elementary screens for conduct problems perform remarkably well when predicting criminal convictions 20 years later. However, because of variations in base rates, screens operated differently by gender and location. The results indicated that for populations with high base rates, convictions can be accurately predicted with as little as one teacher screen taken during kindergarten or 1st grade, increasing the cost-effectiveness of preventative interventions.

Keywords

Screening Preventative intervention Convictions Base rates 

Notes

Acknowledgments

This work was supported by National Institute of Mental Health (NIMH) grants R18 MH48043, R18 MH50951, R18 MH50952, R18 MH50953, K05MH00797 and K05MH01027; Department of Education grant S184 U30002; and NIDA grants DA16903, DA017589, K05DA015226, and P30DA023026. The Center for Substance Abuse Prevention and the National Institute on Drug Abuse also provided support through a memorandum of agreement with the NIMH. Additional support for the preparation of this work was provided by a LEEF B.C. Leadership Chair award, Child & Family Research Institute Investigator Salary and Investigator Establishment Awards, and a Canada Foundation for Innovation award to Robert J. McMahon. Funders provided financial support, but responsibility for the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, and approval of the manuscript rests solely with the authors. We are grateful for the close collaboration of the Durham Public Schools, the Metropolitan Nashville Public Schools, the Bellefonte Area Schools, the Tyrone Area Schools, the Mifflin County Schools, the Highline Public Schools, and the Seattle Public Schools. We greatly appreciate the hard work and dedication of the many staff members who implemented the project, collected the evaluation data, and assisted with data management and analyses.

The Conduct Problems Prevention Research Group includes (alphabetically): Karen L. Bierman, Ph.D., Pennsylvania State University; John D. Coie, Ph.D., Duke University; Kenneth A. Dodge, Ph.D., Duke University; Mark T. Greenberg, Ph.D., Pennsylvania State University; John E. Lochman, Ph.D., University of Alabama; Robert J. McMahon, Ph.D., Simon Fraser University and B.C. Children’s Hospital; and Ellen E. Pinderhughes, Ph.D., Tufts University.

Compliance with Ethical Standards

Conflict of Interest

Drs. Bierman, Coie, Dodge, Greenberg, Lochman, McMahon, and Pinderhughes are the principal investigators on the Fast Track Project and have a publishing agreement with Guilford Publications, Inc. Royalties from that agreement will be donated to a professional organization. They are also authors of the PATHS curriculum and donate all royalties from Channing-Bete, Inc. to a professional organization. Dr. Greenberg is a developer of the PATHS curriculum and has a separate royalty agreement with Channing-Bete, Inc. Bierman, Coie, Dodge, Greenberg, Lochman, and McMahon are the developers of the Fast Track curriculum and have publishing and royalty agreements with Guilford Publications, Inc. Dr. McMahon is a coauthor of Helping the Noncompliant Child and has a royalty agreement with Guilford Publications, Inc.

Ethical Approval

All procedures were approved by the Institutional Review Boards of participating universities (i.e., Duke University, University of Washington, Vanderbilt University, and Penn State University).

Informed Consent

Written informed consent from parents and oral assent from children were obtained for the collection of demographic and screening variables. Additional informed consent was not required for the collection of adult conviction data, given the public accessibility of these data.

References

  1. Achenbach, T. M. (1982). Developmental psychopathology (2nd ed.). New York: Wiley.Google Scholar
  2. Achenbach, T. M. (1991). Manual for the child behavior checklist/4–18 and 1991 profile. Department of Psychiatry: University of Vermont.Google Scholar
  3. Baker, C. N., Tichovolsky, M. H., Kupersmidt, J. B., Voegler-Lee, M. E., & Arnold, D. H. (2015). Teacher (mis)perceptions of preschoolers’ academic skills: Predictors and associations with longitudinal outcomes. Journal of Educational Psychology, 107, 805–820.  https://doi.org/10.1037/edu0000008.CrossRefGoogle Scholar
  4. Bennett, K. J., & Offord, D. R. (2001). Screening for conduct problems: Does the predictive accuracy of conduct disorder symptoms improve with age? Journal of the American Academy of Child and Adolescent Psychiatry, 40, 1418–1425.  https://doi.org/10.1097/00004583-200112000-00012.CrossRefGoogle Scholar
  5. Bennett, K. J., Lipman, E. L., Racine, Y., & Offord, D. (1998). Do measures of externalizing behavior in normal populations predict later outcome? Implications for targeted interventions to prevent conduct disorder. Journal of Child Psychology and Psychiatry, 39, 1059–1070.CrossRefGoogle Scholar
  6. Bennett, K. J., Lipman, E. L., Brown, S., Racine, Y., Boyle, M. H., & Offord, D. R. (1999). Predicting conduct problems: Can high-risk children be identified in kindergarten and grade 1? Journal of Consulting and Clinical Psychology, 67, 470–480.  https://doi.org/10.1037/0022-006X.67.4.470.CrossRefGoogle Scholar
  7. Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods & Research, 33, 261–304.CrossRefGoogle Scholar
  8. Coie, J. D., Watt, N. F., West, S. G., Hawkins, J. D., Asarnow, J. R., Markman, H. J., et al. (1993). The science of prevention: A conceptual framework and some directions for a national research program. The American Psychologist, 48, 1013–1022.CrossRefGoogle Scholar
  9. Conduct Problems Prevention Research Group. (1992). A developmental and clinical model for the prevention of conduct disorder: The FAST track program. Development and Psychopathology, 4, 509–527.  https://doi.org/10.1017/S0954579400004855.CrossRefGoogle Scholar
  10. Conduct Problems Prevention Research Group. (1999). Initial impact of the Fast track prevention trial for conduct problems: I. the high-risk sample. Journal of Consulting and Clinical Psychology, 67, 631–647.CrossRefGoogle Scholar
  11. Conduct Problems Prevention Research Group. (2000). Merging universal and indicated prevention programs: The Fast track model. Addictive Behaviors, 25, 913–927.CrossRefGoogle Scholar
  12. De Los Reyes, A., Augenstein, T. M., Wang, M., Thomas, S. A., Drabick, D. A. G., Burgers, D. E., & Rabinowitz, J. (2015). The validity of the multi-informant approach to assessing child and adolescent mental health. Psychological Bulletin, 141, 858–900.  https://doi.org/10.1037/a0038498.CrossRefGoogle Scholar
  13. Drabick, D. A. G., Bubier, J., Chen, D., Price, J., & Lanza, H. I. (2011). Source-specific oppositional defiant disorder among inner-city children: Prospective prediction and moderation. Journal of Clinical Child & Adolescent Psychology, 40, 23–35.  https://doi.org/10.1080/15374416.2011.533401.CrossRefGoogle Scholar
  14. Elwood, R. W. (1993). Psychological tests and clinical discriminations: Beginning to address the base rate problem. Clinical Psychology Review, 13, 409–419.  https://doi.org/10.1016/0272-7358(93)90012-B.CrossRefGoogle Scholar
  15. Goulter, N., Godwin, J., & Conduct Problems Prevention Research Group. (2018). Person-oriented analyses of Fast Track effects: Typologies of adult criminal convictions. Poster presented at the Banff international conference on behavioral science, Banff, BC, Canada.Google Scholar
  16. Heller, T. L., Baker, B. L., Henker, B., & Hinshaw, S. P. (1996). Externalizing behavior and cognitive functioning from preschool to first grade: Stability and predictors. Journal of Clinical Child Psychology, 25, 376–387.  https://doi.org/10.1207/s15374424jccp2504_3.CrossRefGoogle Scholar
  17. Hill, L. G., Coie, J. D., Lochman, J. E., & Greenberg, M. T. (2004). Effectiveness of early screening for externalizing problems: Issues of screening accuracy and utility. Journal of Consulting and Clinical Psychology, 72, 809–820.  https://doi.org/10.1037/0022-006X.72.5.809.CrossRefGoogle Scholar
  18. Jones, D., Dodge, K. A., Foster, E. M., Nix, R., & Conduct Problems Prevention Research Group. (2002). Early identification of children at risk for costly mental health service use. Prevention Science: The Official Journal of the Society for Prevention Research, 3, 247–256.CrossRefGoogle Scholar
  19. Jones, D. E., Greenberg, M., & Crowley, M. (2015). Early social-emotional functioning and public health: The relationship between kindergarten social competence and future wellness. American Journal of Public Health, 105, 2283–2290.  https://doi.org/10.2105/AJPH.2015.302630.CrossRefGoogle Scholar
  20. Kaplow, J. B., Curran, P. J., Dodge, K. A., & Conduct Problems Prevention Research Group. (2002). Child, parent, and peer predictors of early-onset substance use: A multisite longitudinal study. Journal of Abnormal Child Psychology, 30, 199–216.CrossRefGoogle Scholar
  21. Lochman, J. E., & Conduct Problems Prevention Research Group. (1995). Screening of child behavior problems for prevention programs at school entry. Journal of Consulting and Clinical Psychology, 63, 549–559.CrossRefGoogle Scholar
  22. Martel, M. M. (2013). Sexual selection and sex differences in the prevalence of childhood externalizing and adolescent internalizing disorders. Psychological Bulletin, 139, 1221–1259.  https://doi.org/10.1037/a0032247.CrossRefGoogle Scholar
  23. Matthys, W., & Lochman, J. E. (2010). Oppositional defiant disorder and conduct disorder in childhood. Oxford: Wiley-Blackwell.Google Scholar
  24. McNeilis, J., Maughan, B., Goodman, R., & Rowe, R. (2017). Comparing the characteristics and outcomes of parent- and teacher-reported oppositional defiant disorder: Findings from a national sample. Journal of Child Psychology and Psychiatry, 59, 659–666.  https://doi.org/10.1111/jcpp.12845.CrossRefGoogle Scholar
  25. Meehl, P. E., & Rosen, A. (1955). Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychological Bulletin, 52, 194–216.CrossRefGoogle Scholar
  26. Nagelkerke, N. J. D. (1991). A note on a general definition of the coefficient of determination. Biometrika, 78, 691–692.CrossRefGoogle Scholar
  27. Nix, R. L. (2001). Child Behavior Checklist (Technical report). https://doi.org/http://www.fasttrackproject.org/technical-reports.php.
  28. Okado, Y., & Bierman, K. L. (2014). Differential risk for late adolescent conduct problems and mood dysregulation among children with early externalizing behavior problems. Journal of Abnormal Child Psychology, 43, 735–747.  https://doi.org/10.1007/s10802-014-9931-4.CrossRefGoogle Scholar
  29. Pasalich, D. S., Witkiewitz, K., McMahon, R. J., Pinderhughes, E. E., & Conduct Problems Prevention Research Group. (2015). Indirect effects of the Fast track intervention on conduct disorder symptoms and callous-unemotional traits: Distinct pathways involving discipline and warmth. Journal of Abnormal Child Psychology, 44, 587–597.  https://doi.org/10.1007/s10802-015-0059-y.CrossRefGoogle Scholar
  30. Petras, H., Chilcoat, H. D., Leaf, P. J., Ialongo, N. S., & Kellam, S. G. (2004a). Utility of TOCA-R scores during the elementary school years in identifying later violence among adolescent males. Journal of the American Academy of Child & Adolescent Psychiatry, 43, 88–96.  https://doi.org/10.1097/00004583-200401000-00018.CrossRefGoogle Scholar
  31. Petras, H., Schaeffer, C. M., Ialongo, N., Hubbard, S., Muthén, B., Lambert, S. F., et al. (2004b). When the course of aggressive behavior in childhood does not predict antisocial outcomes in adolescence and young adulthood: An examination of potential explanatory variables. Development and Psychopathology, 16, 919–941.CrossRefGoogle Scholar
  32. Sawyer, A. C. P., Chittlrborough, C. R., Lynch, J. W., Baghurst, P., Mittiny, M. N., Kaim, A. L. E., & Sawyer, M. G. (2014). Can screening 4-5 year olds accurately identify children who will have teacher-reported mental health problems when children are aged 6-7 years? Australian and New Zealand Journal of Psychiatry, 48, 554–563.CrossRefGoogle Scholar
  33. Stormont, M. (2000). Early child risk factors for externalizing and internalizing behaviors: A 5-year follow-forward assessment. Journal of Early Intervention, 23, 180–190.  https://doi.org/10.1177/10538151000230030701.CrossRefGoogle Scholar
  34. Stormshak, E. A., Bierman, K. L., & Conduct Problems Prevention Research Group. (1998). The implications of different developmental patterns of disruptive behavior problems for school adjustment. Development and Psychopathology, 10, 451–467.CrossRefGoogle Scholar
  35. Welsh, B. C., Loeber, R., Stevens, B. R., Stouthamer-Loeber, M., Cohen, M. A., & Farrington, D. P. (2008). Costs of juvenile crime in urban areas: A longitudinal perspective. Youth Violence and Juvenile Justice, 6, 3–27.  https://doi.org/10.1177/1541204007308427.CrossRefGoogle Scholar
  36. Werthamer-Larsson, L., Kellam, S., & Wheeler, L. (1991). Teacher observation of classroom adaptation--revised. PsycTESTS.  https://doi.org/10.1037/t31163-000.
  37. Wichstrøm, L., Skogen, K., & Oia, T. (1996). Increased rate of conduct problems in urban areas: What is the mechanism? Journal of the American Academy of Child and Adolescent Psychiatry, 35, 471–479.CrossRefGoogle Scholar
  38. Yates, T. M., & Marcelo, A. K. (2014). Through race-colored glasses: Preschoolers’ pretend play and teachers’ ratings of preschooler adjustment. Early Childhood Research Quarterly, 29, 1–11.  https://doi.org/10.1016/j.ecresq.2013.09.003.CrossRefGoogle Scholar
  39. Zoccolillo, M., Tremblay, R., & Vitaro, F. (1996). DSM-III-R and DSM-III criteria for conduct disorder in preadolescent girls: Specific but insensitive. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 461–470.  https://doi.org/10.1097/00004583-199604000-00012.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of PsychologyThe University of AlabamaTuscaloosaUSA
  2. 2.Center for Child and Family PolicyDuke UniversityDurhamUSA

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