Psychiatric Quarterly

, Volume 89, Issue 1, pp 219–234 | Cite as

Factor Structure of Teacher Ratings of the ODD Symptoms in Children

  • Rapson Gomez
  • Vasileios Stavropoulos
  • George Van Doorn
Original Paper


This study used confirmatory factor analysis (CFA) to determine the best model for Oppositional Defiant Disorder (ODD) symptoms in children aged 3 to 15 years, as presented in the Disruptive Behavior Rating Scale. Teachers’ ratings of the ODD symptoms of 213 children from general community schools in Australia were obtained. The findings provided most support for a bifactor model based on Stringaris and Goodman’s [1] three-factor model (primary factors for irritable, hurtful, and headstrong). The general factor, but not the group factors in the model, showed high omega hierarchical and explained common variance. Thus, only the general factor in this model can be meaningfully interpreted. Also, the general factor was supported with regard to external validity. Specifically, this factor, but not the group factors, correlated strongly with ADHD inattention and hyperactivity/impulsivity symptom groups, and other measures of behavioural and emotional problems. The taxonomic, diagnostic, practical, and research implications of the findings are discussed.


Oppositional defiant disorder Confirmatory factor analysis Community sample Teacher ratings, bifactor model 


Authors Contributions

Rapson Gomez planning, design and then writing up. Vasileios Stavropoulos literature review, and writing up. George Van Doorn literature review, and writing up.

Role of Funding Source

The study was not funded by any source.

Compliance with Ethical Standards

Conflict of Interest

Authors have no current financial or other interest with any organization currently or in future in terms of the research.

Ethical Statement

All procedures followed for the present study were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000 (5). Informed consent was obtained from all participants for being included in the study. No identifying information is included in this article. No animal or human studies were carried out by the authors for this article.


  1. 1.
    Stringaris A, Goodman R. Three dimensions of oppositionality in youth. J Child Psychol Psychiatry. 2009;50(3):216–23. doi: 10.1097/CHI.0b013e3181984f30.CrossRefPubMedGoogle Scholar
  2. 2.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5®). Washington, DC: American Psychiatric Association; 2013.Google Scholar
  3. 3.
    American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.Google Scholar
  4. 4.
    American Psychiatric Association. Diagnostic and statistical manual. 4th ed. Text Revision (DSM-IV-TR). Washington, DC: American Psychiatric Association; 2000.Google Scholar
  5. 5.
    Krieger FV, Polanczyk GV, Goodman R, Rohde LA, Graeff-Martins AS, Salum G, et al. Dimensions of oppositionality in a Brazilian community sample: testing the DSM-5 proposal and etiological links. Journal of the American Academy of Child & Adolescent Psychiatry. 2013;52(4):389–400. doi: 10.1016/j.jaac.2013.01.004.CrossRefGoogle Scholar
  6. 6.
    Aebi M, Muller UC, Asherson P, Banaschewski T, Buitelaar J, Ebstein R, et al. Predictability of oppositional defiant disorder and symptom dimensions in children and adolescents with ADHD combined type. Psychol Med. 2010;40(12):2089–100. doi: 10.1017/S0033291710000590.CrossRefPubMedGoogle Scholar
  7. 7.
    Burke JD, Waldman I, Lahey BB. Predictive validity of childhood oppositional defiant disorder and conduct disorder: implications for the DSM-V. J Abnorm Psychol. 2010;119(4):739–51. doi: 10.1037/a0019708.CrossRefPubMedGoogle Scholar
  8. 8.
    Rowe R, Costello EJ, Angold A, Copeland WE, Maughan B. Developmental pathways in oppositional defiant disorder and conduct disorder. J Abnorm Psychol. 2010;119(4):726. doi: 10.1037/a0020798.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Burke JD. An affective dimension within oppositional defiant disorder symptoms among boys: personality and psychopathology outcomes into early adulthood. J Child Psychol Psychiatry. 2012;53(11):1176–83. doi: 10.1111/j.1469-7610.2012.02598.x.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Burke JD, Loeber R, Lahey BB, Rathouz PJ. Developmental transitions among affective and behavioral disorders in adolescent boys. J Child Psychol Psychiatry. 2005;46:1200–10. doi: 10.1111/j.1469-7610.2005.00422.x.CrossRefPubMedGoogle Scholar
  11. 11.
    Burke JD, Boylan K, Rowe R, Duku E, Stepp SD, Hipwell AE, et al. Identifying the irritability dimension of ODD: application of a modified bifactor model across five large community samples of children. J Abnorm Psychol. 2014;123(4):841–51.CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Lavigne JV, Bryant FB, Hopkins J, Gouze KR. Dimensions of oppositional defiant disorder in young children: model comparisons, gender and longitudinal invariance. J Abnorm Child Psychol. 2015;43(3):423–39. doi: 10.1007/s10802-014-9919-0.CrossRefPubMedGoogle Scholar
  13. 13.
    Herzhoff K, Tackett JL. Subfactors of oppositional defiant disorder: converging evidence from structural and latent class analyses. J Child Psychol Psychiatry. 2016;57(1):18–29. doi: 10.1111/jcpp.12423.CrossRefGoogle Scholar
  14. 14.
    Ezpeleta L, Granero R, de la Osa N, Penelo E, Domenech JM. Dimensions of oppositional defiant disorder in 3-year-old preschoolers. J Child Psychol Psychiatry. 2012;53(11):1128–38. doi: 10.1111/j.1469-7610.2012.02545.x.CrossRefPubMedGoogle Scholar
  15. 15.
    Goodman R. The strengths and difficulties questionnaire: a research note. J Child Psychol Psychiatry. 1997;38(5):581–6. doi: 10.1111/j.1469-7610.1997.tb01545.x.CrossRefPubMedGoogle Scholar
  16. 16.
    Gomez R. Factor structure of parent and teacher ratings of the ODD symptoms for Malaysian primary school children. Asian J Psychiatr. 2016; doi: 10.1016/j.ajp.2016.10.013.
  17. 17.
    Australian Bureau of Statistics [ABS]. Population census. Canberra: Australian Government Publishing Service; 2007.Google Scholar
  18. 18.
    Australian Bureau of Statistics. Australian standard classification of occupations. Canberra: Australian Government Publishing Service; 1997.Google Scholar
  19. 19.
    Barkley RA, Murphy KR. A clinical workbook: attention-deficit hyperactivity disorder. New York: Guilford; 1998.Google Scholar
  20. 20.
    Goodman R, Meltzer H, Bailey V. The strengths and difficulties questionnaire: a pilot study on the validity of the self-report version. Eur Child Adolesc Psychiatry. 1998;7(3):125–30. doi: 10.1007/s007870050057.CrossRefPubMedGoogle Scholar
  21. 21.
    Muthén LK, Muthén BO. Mplus statistical modeling software: release 7.0. Los Angeles: Muthén & Muthén; 2012.Google Scholar
  22. 22.
    Rhemtulla M, Brosseau-Liard PÉ, Savalei V. When can categorical variables be treated as continuous? A comparison of robust continuous and categorical SEM estimation methods under suboptimal conditions. Psychol Methods. 2012;17(3):354. doi: 10.1037/a0029315.CrossRefPubMedGoogle Scholar
  23. 23.
    Beauducel A, Herzberg PY. On the performance of maximum likelihood versus means and variance adjusted weighted least squares estimation in CFA. Struct Equ Model. 2006;13(2):186–203. doi: 10.1207/s15328007sem1302_2.CrossRefGoogle Scholar
  24. 24.
    Lubke GH, Muthén BO. Applying multigroup confirmatory factor models for continuous outcomes to Likert scale data complicates meaningful group comparisons. Struct Equ Model. 2004;11(4):514–34. doi: 10.1207/s15328007sem1104_2.CrossRefGoogle Scholar
  25. 25.
    Millsap RE, Yun-Tein J. Assessing factorial invariance in ordered-categorical measures. Multivar Behav Res. 2004;39(3):479–515. doi: 10.1207/S15327906MBR3903_4.CrossRefGoogle Scholar
  26. 26.
    Hu LT, Bentler PM. Fit indices in covariance structure modeling: sensitivity to underparameterized model misspecification. Psychol Methods. 1998;3(4):424. doi: 10.1037/1082-989X.3.4.424.CrossRefGoogle Scholar
  27. 27.
    Nye CD, Drasgow F. Assessing goodness of fit: simple rules of thumb simply do not work. Organ Res Methods. 2011;14(3):548–70.CrossRefGoogle Scholar
  28. 28.
    Revelle W, Zinbarg RE. Coefficients alpha, beta, omega, and the glb: comments on Sijtsma. Psychometrika. 2009;74(1):145–54. doi: 10.1007/s11336-008-9102-z.CrossRefGoogle Scholar
  29. 29.
    Zinbarg RE, Yovel I, Revelle W, McDonald RP. Estimating generalizability to a latent variable common to all of a scale's indicators: a comparison of estimators for ωh. Appl Psychol Meas. 2006;30(2):121–44.CrossRefGoogle Scholar
  30. 30.
    Bonifay WE, Reise SP, Scheines R, Meijer RR. When are multidimensional data unidimensional enough for structural equation modeling? An evaluation of the DETECT multidimensionality index. Struct Equ Model Multidiscip J. 2015;22(4):504–16. doi: 10.1080/10705511.2014.938596.CrossRefGoogle Scholar
  31. 31.
    Hancock GR, Mueller RO. Rethinking construct reliability within latent variable systems. In: Structural equation modeling: Present and Future. 2001. pp. 195–216.Google Scholar
  32. 32.
    Reise SP, Bonifay WE, Haviland MG. Scoring and modeling psychological measures in the presence of multidimensionality. J Pers Assess. 2013;95(2):129–40. doi: 10.1080/00223891.2012.725437.CrossRefPubMedGoogle Scholar
  33. 33.
    Zinbarg RE, Revelle W, Yovel I, Li W. Cronbach’s α, Revelle’s β, and McDonald’s ω H: their relations with each other and two alternative conceptualizations of reliability. Psychometrika. 2005;70(1):123–33. doi: 10.1007/s11336-003-0974-7.CrossRefGoogle Scholar
  34. 34.
    Brunner M, Nagy G, Wilhelm O. A tutorial on hierarchically structured constructs. J Pers. 2012;80(4):796–846. doi: 10.1111/j.1467-6494.2011.00749.x.CrossRefPubMedGoogle Scholar
  35. 35.
    McDonald RP. Test theory: a unified approach. New Jersey: Lawrence Erlbaum Associates; 1999.Google Scholar
  36. 36.
    Reise SP. The rediscovery of bifactor measurement models. Multivar Behav Res. 2012;47(5):667–96.CrossRefGoogle Scholar
  37. 37.
    Rodriguez A, Reise SP, Haviland MG. Applying bifactor statistical indices in the evaluation of psychological measures. J Pers Assess. 2016;98(3):223–37. doi: 10.1080/00223891.2015.1089249.CrossRefPubMedGoogle Scholar
  38. 38.
    Cohen J. A power primer. Psychol Bull. 1992;112:155–9.CrossRefPubMedGoogle Scholar
  39. 39.
    Field A. Discovering statistics using IBM SPSS statistics (4th revised edition). London: Sage Publications Ltd.; 2013.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Rapson Gomez
    • 1
  • Vasileios Stavropoulos
    • 1
    • 2
  • George Van Doorn
    • 1
  1. 1.School of Health Sciences and PsychologyFederation University AustraliaBallaratAustralia
  2. 2.University of AthensAthensGreece

Personalised recommendations