European Child & Adolescent Psychiatry

, Volume 27, Issue 6, pp 767–774 | Cite as

Predictive value of dysregulation profile trajectories in childhood for symptoms of ADHD, anxiety and depression in late adolescence

  • B. WangEmail author
  • L. G. Brueni
  • C. Isensee
  • T. Meyer
  • N. Bock
  • U. Ravens-Sieberer
  • F. Klasen
  • R. Schlack
  • A. Becker
  • A. Rothenberger
  • The BELLA study group
Original Contribution


We examined whether there are certain dysregulation profile trajectories in childhood that may predict an elevated risk for mental disorders in later adolescence. Participants (N = 554) were drawn from a representative community sample of German children, 7–11 years old, who were followed over four measurement points (baseline, 1, 2 and 6 years later). Dysregulation profile, derived from the parent report of the Strengths and Difficulties Questionnaire, was measured at the first three measurement points, while symptoms of attention deficit hyperactivity disorder (ADHD), anxiety and depression were assessed at the fourth measurement point. We used latent class growth analysis to investigate developmental trajectories in the development of the dysregulation profile. The predictive value of dysregulation profile trajectories for later ADHD, anxiety and depression was examined by linear regression. For descriptive comparison, the predictive value of a single measurement (baseline) was calculated. Dysregulation profile was a stable trait during childhood. Boys and girls had similar levels of dysregulation profile over time. Two developmental subgroups were identified, namely the low dysregulation profile and the high dysregulation profile trajectory. The group membership in the high dysregulation profile trajectory (n = 102) was best predictive of later ADHD, regardless of an individual’s gender and age. It explained 11% of the behavioural variance. For anxiety this was 8.7% and for depression 5.6%, including some gender effects. The single-point measurement was less predictive. An enduring high dysregulation profile in childhood showed some predictive value for psychological functioning 4 years later. Hence, it might be helpful in the preventive monitoring of children at risk.


Dysregulation profile Trajectories Symptoms ADHD Anxiety Depression 



The authors thank all children, adolescents, their parents and young adults who participated in this research for their time and involvement. We would like to thank the Robert Koch Institute for their ongoing support and cooperation. The BELLA study has been financially supported by various grants: Baseline, 1-year follow-up and 2-year follow-up of the BELLA study were financed by the German Science Foundation. The 6-year follow-up was funded by the German Federal Ministry of Health (BMG). BELLA study group: U. Ravens-Sieberer and F. Klasen (Principal Investigators), C. Barkman, M. Bullinger, M. Döpfner, B. Herpertz-Dahlmann, H. Holling, C. Otto, F. Petermann, F Resch, A. Rothenberger, S. Schneider, M. Schulte-Markwort, R. Schlack, F. Verhulst, H.-U. Wittchen.

Compliance with ethical standards

Conflict of interest

All authors declare that they have no conflicts of interest.


  1. 1.
    Achenbach TM, Rescorla LA (2001) Manual for the ASEBA school-age forms & profiles: an integrated system of multi-informant assessment. University of Vermont, Research Center for Children, Youth & Families, BurlingtonGoogle Scholar
  2. 2.
    Althoff RR, Verhulst FC, Rettew DC, Hudziak JJ, van der Ende J (2010) Adult outcomes of childhood dysregulation: a 14-year follow-up study. J Am Acad Child Adolesc Psychiatry 49(11):1105–1116PubMedPubMedCentralGoogle Scholar
  3. 3.
    Asparouhov T, Muthén B (2014) Auxiliary variables in mixture modeling: three-step approaches using M plus. Struct Equ Model A Multidiscip J 21(3):329–341CrossRefGoogle Scholar
  4. 4.
    Bellani M, Negri GA, Brambilla P (2012) The dysregulation profile in children and adolescents: a potential index for major psychopathology? Epidemiol Psychiatr Sci 21(2):155–159CrossRefPubMedGoogle Scholar
  5. 5.
    Birmaher B, Brent DA, Chiappetta L, Bridge J, Monga S, Baugher M (1999) Psychometric properties of the Screen for Child Anxiety Related Emotional Disorders (SCARED): a replication study. J Am Acad Child Adolesc Psychiatry 38(10):1230–1236CrossRefPubMedGoogle Scholar
  6. 6.
    Birmaher B, Khetarpal S, Brent D, Cully M, Balach L, Kaufman J, Neer SM (1997) The screen for child anxiety related emotional disorders (SCARED): scale construction and psychometric characteristics. J Am Acad Child Adolesc Psychiatry 36(4):545–553CrossRefPubMedGoogle Scholar
  7. 7.
    Caye A, Rocha TBM, Anselmi L, Murray J, Menezes AM, Barros FC, Swanson JM et al (2016) Attention-deficit/hyperactivity disorder trajectories from childhood to young adulthood: evidence from a birth cohort supporting a late-onset syndrome. JAMA Psychiatry 73(7):705–712CrossRefPubMedGoogle Scholar
  8. 8.
    Connell AM, Frye AA (2006) Growth mixture modeling in developmental psychology: overview and demonstration of heterogeneity in developmental trajectories of adolescent antisocial behavior. Infant Child Dev 15:609–621CrossRefGoogle Scholar
  9. 9.
    Conners CK (1997) Conners’ Rating Scales-Revised (CRS-R): technical manual. Multi-Health Systems, New YorkGoogle Scholar
  10. 10.
    Conners CK, Sitarenios G, Parker JD, Epstein JN (1998) The revised Conners’ Parent Rating Scale (CPRS-R): factor structure, reliability, and criterion validity. J Abnorm Child Psychol 26(4):257–268CrossRefPubMedGoogle Scholar
  11. 11.
    Faulstich M, Carey M, Ruggiero L, Enyart P, Gresham F (1986) Assessment of depression in childhood and adolescent: an evaluation of the center for Epidemiological Studies Depression Scale for Children (CES-DC). Am J Psychiatry 143:1024–1027CrossRefPubMedGoogle Scholar
  12. 12.
    Feldman BJ, Masyn KE, Conger RD (2009) New approaches to studying problem behaviors: a comparison of methods for modeling longitudinal, categorical adolescent drinking data. Dev Psychol 45(3):652–676CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Goodman R (1997) The Strengths and Difficulties Questionnaire: a research note. J Child Psychol Psychiatry 38(5):581–586CrossRefPubMedGoogle Scholar
  14. 14.
    Hintzpeter B, Klasen F, Schön G, Voss C, Hölling H, Ravens-Sieberer U, BELLA study group (2015) Mental health care use among children and adolescents in Germany: results of the longitudinal BELLA study. Eur Child Adolesc Psychiatry 24(6):705–713CrossRefPubMedGoogle Scholar
  15. 15.
    Holtmann M, Becker A, Banaschewski T, Rothenberger A, Roessner V (2011) Psychometric validity of the strengths and difficulties questionnaire-dysregulation profile. Psychopathology 44(1):53–59CrossRefPubMedGoogle Scholar
  16. 16.
    Holtmann M, Buchmann AF, Esser G, Schmidt MH, Banaschewski T, Laucht M (2011) The Child Behavior Checklist-Dysregulation Profile predicts substance use, suicidality, and functional impairment: a longitudinal analysis. J Child Psychol Psychiatry 52(2):139–147CrossRefPubMedGoogle Scholar
  17. 17.
    Holtmann M, Bölte S, Goth K, Döpfner M, Plück J, Huss M, Fegert JM, Lehmkuhl G, Schmeck K, Poustka F (2007) Prevalence oft he Child Behavior Checklist-pediatric bipolar disorder phenotype in a German general population sample. Bipolar Disord 9(8):895–900CrossRefPubMedGoogle Scholar
  18. 18.
    Jordan P, Rescorla LA, Althoff RR, Achenbach TM (2016) International comparisons of the youth self-report dysregulation profile: latent class analyses in 34 societies. J Am Acad Child Adolesc Psychiatry 55(12):1046–1053CrossRefPubMedGoogle Scholar
  19. 19.
    Jucksch V, Salbach-Andrae H, Lenz K, Goth K, Döpfner M, Poustka F, Holtmann M et al (2011) Severe affective and behavioural dysregulation is associated with significant psychosocial adversity and impairment. J Child Psychol Psychiatry 52(6):686–695CrossRefPubMedGoogle Scholar
  20. 20.
    Jung T, Wickrama KAS (2008) An introduction to latent class growth analysis and growth mixture modeling. Soc Pers Psychol Compass 2(1):302–317CrossRefGoogle Scholar
  21. 21.
    Kim JW, Yu H, Ryan ND, Axelson DA, Goldstein BI, Goldstein TR, Merranko JA et al (2015) Longitudinal trajectories of ADHD symptomatology in offspring of parents with bipolar disorder and community controls. J Clin Psychiatry 76(5):599–606CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Krasner AJ, Turner JB, Feldman JF, Silberman AE, Fisher PW, Workman CC, Posner JE et al (2015) ADHD symptoms in a non-referred low birthweight/preterm cohort: longitudinal profiles, outcomes, and associated features. J Attention Disord. doi: 10.1177/1087054715617532 CrossRefGoogle Scholar
  23. 23.
    Markham JA, Koenig JI (2011) Prenatal stress: role in psychotic and depressive diseases. Psychopharmacology 214(1):89–106CrossRefPubMedGoogle Scholar
  24. 24.
    Muthén LK, Muthén BO (1998–2015). Mplus user’s guide, 7th edn. Muthen & Muthen, Los AngelesGoogle Scholar
  25. 25.
    Nagin DS (1999) Analyzing developmental trajectories: a semiparametric, group-based approach. Psychol Methods 4(2):139–157CrossRefGoogle Scholar
  26. 26.
    Nagin D (2005) Group-based modeling of development. Harvard University Press, CambridgeCrossRefGoogle Scholar
  27. 27.
    Nigg JT (2006) Temperament and developmental psychopathology. J Child Psychol Psychiatry 47(3–4):395–422CrossRefPubMedGoogle Scholar
  28. 28.
    Nylund KL, Asparouhov T, Muthén BO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model 14(4):535–569CrossRefGoogle Scholar
  29. 29.
    Ravens-Sieberer U, Otto C, Kriston L, Rothenberger A, Döpfner M, Herpertz-Dahlmann B, Klasen F et al (2015) The longitudinal BELLA study: design, methods and first results on the course of mental health problems. Eur Child Adolesc Psychiatry 24(6):651–663CrossRefPubMedGoogle Scholar
  30. 30.
    Rettew DC, McKee L (2005) Temperament and its role in developmental psychopathology. Harv Rev Psychiatry 13(1):14–27CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Rohde LA, Biederman J, Busnello EA, Zimmermann H, Schmitz M, Martins S, Tramontina S (1999) ADHD in a school sample of Brazilian adolescents: a study of prevalence, comorbid conditions, and impairments. J Am Acad Child Adolesc Psychiatry 38(6):716–722CrossRefPubMedGoogle Scholar
  32. 32.
    Rothenberger A, Rhode LA, Rothenberger LG (2015) Biomarkers in Child Mental Health: a bio-psycho-social perspective is needed. Behav Brain Funct 11(1):31CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Scheinost D, Sinha R, Cross SN, Kwon SH, Sze G, Constable RT, Ment LR (2016) Does prenatal stress alter the developing connectome? Pediatr Res 81(1–2):214–226PubMedPubMedCentralGoogle Scholar
  34. 34.
    Stringaris A, Maughan B, Copeland WS, Costello EJ, Angold A (2013) Irritable mood as a symptom of depression in youth: prevalence, developmental, and clinical correlates in the Great Smoky Mountains Study. J Am Acad Child Adolesc Psychiatry 52(8):831–840CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Tandon M, Tillman R, Agrawal A, Luby J (2016) Trajectories of ADHD severity over 10 years from childhood into adulthood. ADHD Atten Deficit Hyperact Disord 8(3):121–130CrossRefGoogle Scholar
  36. 36.
    van Lieshout M, Luman M, Twisk JW, Faraone SV, Heslenfeld DJ, Hartman CA, Oosterlaan J et al (2016) Neurocognitive predictors of ADHD outcome: a 6-year follow-up study. J Abnorm Child Psychol 45(2):261–272CrossRefPubMedCentralGoogle Scholar
  37. 37.
    Verhulst FC, van der Ende J, Ferdinand RF, Kasius MC (1997) The prevalence of DSM-III-R diagnoses in a national sample of Dutch adolescents. Arch Gen Psychiatry 54(4):329–336CrossRefPubMedGoogle Scholar
  38. 38.
    Wickrama KK, Lee TK, O’Neal CW, Lorenz FO (2016) Higher-order growth curves and mixture modeling with Mplus: a practical guide. Routledge, LondonCrossRefGoogle Scholar
  39. 39.
    Woerner W, Becker A, Rothenberger A (2004) Normative data and scale properties of the German parent SDQ. Eur Child Adolesc Psychiatry 13:ii3–ii10PubMedGoogle Scholar
  40. 40.
    Yan N, Benner A, Tucker-Drob E, Harden KP (2016) Mothers’ early depressive symptoms and preschoolers’ behavioral problems: the moderating role of genetic influences. Child Psychiatry Hum Dev 48(3):434–443CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  • B. Wang
    • 1
    Email author
  • L. G. Brueni
    • 2
  • C. Isensee
    • 1
  • T. Meyer
    • 6
  • N. Bock
    • 5
  • U. Ravens-Sieberer
    • 3
  • F. Klasen
    • 3
  • R. Schlack
    • 4
  • A. Becker
    • 1
  • A. Rothenberger
    • 1
  • The BELLA study group
  1. 1.Department of Child and Adolescent Psychiatry and PsychotherapyUniversity Medical Center GoettingenGöttingenGermany
  2. 2.Service for Child and Adolescent Psychiatry ThurgauRomanshornSwitzerland
  3. 3.Department of Child and Adolescent Psychiatry and PsychotherapyUniversity Medical Center Hamburg-EppendorfHamburgGermany
  4. 4.Department of Epidemiology and Health MonitoringRobert Koch InstituteBerlinGermany
  5. 5.Vitos Klinik Bad Wilhelmshöhe für Kinder- und Jugendpsychiatrie, Psychosomatik und PsychotherapieBad EmstalGermany
  6. 6.Department of Psychosomatic Medicine and PsychotherapyUniversity Medical Center GoettingenGöttingenGermany

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