Multidimensional Predictors of Treatment Outcome in Usual Care for Adolescent Conduct Problems and Substance Use

  • Aaron HogueEmail author
  • Craig E. Henderson
  • Adam T. Schmidt
Original Article


This study investigated baseline client characteristics that predicted long-term treatment outcomes among adolescents referred from school and community sources and enrolled in usual care for conduct and substance use problems. Predictor effects for multiple demographic (age, sex, race/ethnicity), clinical (baseline symptom severity, comorbidity, family discord), and developmental psychopathology (behavioral dysregulation, depression, peer delinquency) characteristics were examined. Participants were 205 adolescents (52 % male; mean age 15.7 years) from diverse backgrounds (59 % Hispanic American, 21 % African American, 15 % multiracial, 6 % other) residing in a large inner-city area. As expected, characteristics from all three predictor categories were related to various aspects of change in externalizing problems, delinquent acts, and substance use at one-year follow-up. The strongest predictive effect was found for baseline symptom severity: Youth with greater severity showed greater clinical gains. Higher levels of co-occurring developmental psychopathology characteristics likewise predicted better outcomes. Exploratory analyses showed that change over time in developmental psychopathology characteristics (peer delinquency, depression) was related to change in delinquent acts and substance use. Implications for serving multiproblem adolescents and tailoring treatment plans in routine care are discussed.


Outcome predictors Adolescent mental health treatment Adolescent substance use treatment Usual care 



This study was supported by the National Institute on Drug Abuse (R01DA019607). The authors would like acknowledge the dedicated work of the CASALEAP research staff: Cynthia Arnao, Molly Bobek, Daniela Caraballo, Benjamin Goldman, Diana Graizbord, Jacqueline Horan, Candace Johnson, Emily Lichvar, Emily McSpadden, Catlin Rideout, and Jeremy Sorgen. We are grateful to Sarah Dauber for her expert research support and to the partnering treatment sites for their generous cooperation.


  1. Achenbach, T. M., & Rescorla, L. A. (2001). ASEBA school age forms and profiles. Burlington: ASEBA.Google Scholar
  2. American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (Vol. 4). Washington, DC: APA.Google Scholar
  3. American Society on Addiction Medicine. (2001). ASAM patient placement criteria for the treatment of substance related disorders (Vol. 2). Chevy Chase: American Society of Addiction Medicine Inc.Google Scholar
  4. Baldwin, S. A., Christian, S., Berkeljon, A., Shadish, W., & Bean, R. (2012). The effects of family therapies for adolescent delinquency and substance abuse: A meta-analysis. Journal of Marital and Family Therapy, 38, 281–304. doi: 10.1111/j.1752-0606.2011.00248.x.CrossRefPubMedGoogle Scholar
  5. Becker, S. J., Curry, J. F., & Yang, C. (2011). Factors that influence trajectories of change in frequency of substance use and quality of life among adolescents receiving a brief intervention. Journal of Substance Abuse Treatment, 41, 294–304. doi: 10.1016/j.jsat.2011.04.004.CrossRefPubMedGoogle Scholar
  6. Boxer, P. (2011). Negative peer involvement in multisystemic therapy for the treatment of youth problem behavior: Exploring outcome and process variables in “real-world” practice. Journal of Clinical Child and Adolescent Psychology, 40, 848–854. doi: 10.1080/15374416.2011.614583.CrossRefPubMedGoogle Scholar
  7. Brown, E. C., Catalano, R. F., Fleming, C. B., Haggerty, K. P., & Abbott, R. D. (2005). Adolescent substance use outcomes in the Raising Healthy Children project: A two-part latent growth curve analysis. Journal of Consulting and Clinical Psychology, 73, 699–710. doi: 10.1037/0022-006X.73.4.699.CrossRefPubMedGoogle Scholar
  8. Brunelle, N., Bertrand, K., Beaudoin, I., Ledoux, C., Gendron, A., & Arseneault, C. (2013). Drug trajectories among youth undergoing treatment: The influence of psychological problems and delinquency. Journal of Adolescence, 36, 705–716. doi: 10.1016/j.adolescence.2013.05.009.CrossRefPubMedGoogle Scholar
  9. Bukstein, O. G., Cornelius, J., Trunzo, A. C., Kelly, T. M., & Wood, D. S. (2005). Clinical predictors of treatment in a population of adolescents with alcohol use disorders. Addictive Behaviors, 30, 1663–1673. doi: 10.1016/j.addbeh.2005.07.013.CrossRefPubMedGoogle Scholar
  10. Chorpita, B. F., & Daleiden, E. L. (2014). Structuring the collaboration of science and service in pursuit of a shared vision. Journal of Clinical Child and Adolescent Psychology, 43, 323–338. doi: 10.1080/15374416.2013.828297.CrossRefPubMedGoogle Scholar
  11. Chorpita, B. F., Bernstein, A., Daleiden, E. L., & Research Network on Youth Mental Health. (2008). Driving with roadmaps and dashboards: Using information resources to structure the decision models in service organizations. Administration and Policy in Mental Health and Mental Health Services Research, 35, 114–123. doi: 10.1007/s10488-007-0151-x.CrossRefPubMedGoogle Scholar
  12. Clair, M., Stein, L. A. R., Soenksen, S., Martin, R. A., Lebeau, R., & Golembeske, C. (2013). Ethnicity as a moderator of motivational interviewing for incarcerated adolescents after release. Journal of Substance Abuse Treatment, 45, 370–375. doi: 10.1016/j.jsat.2013.05.006.CrossRefPubMedPubMedCentralGoogle Scholar
  13. Clark, D. B., Chung, T., Thatcher, D. L., Pajtek, S., & Long, E. C. (2012). Psychological dysregulation, white matter disorganization and substance use disorders in adolescence. Addiction, 107, 206–214. doi: 10.1111/j.1360-0443.2011.03566.x.CrossRefPubMedGoogle Scholar
  14. Cooper, H., & Patall, E. A. (2009). The relative benefits of meta-analysis conducted with individual participant data versus aggregated data. Psychological Methods, 14, 165–176. doi: 10.1037/a0015565.CrossRefPubMedGoogle Scholar
  15. Curran, P. J., & Hussong, A. M. (2003). The use of latent trajectory models in psychopathology research. Journal of Abnormal Psychology, 112, 526–544. doi: 10.1037/0021-843X.112.4.526.CrossRefPubMedPubMedCentralGoogle Scholar
  16. Diamantopoulou, S., Verhulst, F. C., & van der Ende, J. (2011). Gender differences in the development and adult outcome of co-occurring depression and delinquency in adolescence. Journal of Abnormal Psychology, 120, 644–655. doi: 10.1037/a0023669.CrossRefPubMedGoogle Scholar
  17. Dishion, T. J., & Dodge, K. A. (2005). Peer contagion in interventions for children and adolescents: Moving towards an understanding of the ecology and dynamics of change. Journal of Abnormal Child Psychology, 33, 395–400. doi: 10.1007/s10802-005-3579-z.CrossRefPubMedPubMedCentralGoogle Scholar
  18. Dishion, T. J., & Tipsord, J. M. (2011). Peer contagion in child and adolescent social and emotional development. Annual Review of Psychology, 62, 189–214. doi: 10.1146/annurev.psych.093008.100412.CrossRefPubMedPubMedCentralGoogle Scholar
  19. Elliott, D. S., Huizinga, D., & Ageton, S. S. (1985). Explaining delinquency and drug use. Beverly Hills: Sage Publications.Google Scholar
  20. Evans-Chase, M., Kim, M., & Zhou, H. (2013). Risk-taking and self-regulation: A systematic review of the analysis of delinquency outcomes in the juvenile justice intervention literature 1996-2009. Criminal Justice and Behavior, 40, 608–628. doi: 10.1177/0093854812469608.CrossRefGoogle Scholar
  21. Fosco, G., Frank, J., Stormshak, E., & Dishion, T. J. (2013). Opening the “Black Box”: Family check-up intervention effects on self-regulation that prevents growth in problem behavior and substance use. Journal of School Psychology, 51, 455–468. doi: 10.1016/j.jsp.2013.02.001.CrossRefPubMedPubMedCentralGoogle Scholar
  22. Garland, A. F., Hough, R. L., McCabe, K. M., Yeh, M., Wood, P. A., & Aarons, G. A. (2001). Prevalence of psychiatric disorders in youths across five sectors of care. Journal of the American Academy of Child and Adolescent Psychiatry, 40, 409–418. doi: 10.1097/00004583-200104000-00009.CrossRefPubMedGoogle Scholar
  23. Garland, A. F., Hurlburt, M. S., Brookman-Frazee, L., Taylor, R. M., & Accurso, E. C. (2010). Methodological challenges of characterizing usual care psychotherapeutic practice. Administration and Policy in Mental Health and Mental Health Services Research, 37, 208–220. doi: 10.1007/s10488-009-0237-8.CrossRefPubMedGoogle Scholar
  24. Garland, A. F., Haine-Schlagel, R., Brookman-Frazee, L., Baker-Ericzen, M., Trask, E., & Fawley-King, K. (2013). Improving community-based mental health care for children: Translating knowledge into action. Administration and Policy in Mental Health and Mental Health Services Research, 40, 6–22. doi: 10.1007/s10488-012-0450-8.CrossRefPubMedPubMedCentralGoogle Scholar
  25. Gioia, G. A., Isquith, P. K., Guy, S. C., & Kenworthy, L. (2000). Test review: Behavior rating inventory of executive function. Child Neuropsychology, 6, 235–238. doi: 10.1076/chin. Scholar
  26. Gioia, G. A., Isquith, P. K., Retzlaff, P. D., & Espy, K. A. (2002). Confirmatory factor analysis of the Behavior Rating Inventory of Executive Function (BRIEF) in a clinical sample. Child Neuropsychology, 8, 249–257.CrossRefPubMedGoogle Scholar
  27. Gmel, G., Venzin, V., Marmet, K., Danko, G., & Labhart, F. (2012). A quasi-randomized group trial of a brief alcohol intervention on risky single occasion drinking among secondary school students. International Journal of Public Health, 57, 935–944. doi: 10.1007/s00038-012-0419-0.CrossRefPubMedGoogle Scholar
  28. Greenbaum, P. E., & Dedrick, R. F. (2007). Changes in use of alcohol, marijuana, and services by adolescents with serious emotional disturbance: A parallel-process growth mixture model. Journal of Emotional and Behavioral Disorders, 15, 21–32. doi: 10.1177/10634266070150010301.CrossRefGoogle Scholar
  29. Henderson, C. E., Dakof, G., Greenbaum, P. E., & Liddle, H. A. (2010). Effectiveness of multidimensional family therapy with higher severity substance-abusing adolescents: Report from two randomized controlled trials. Journal of Consulting and Clinical Psychology, 78, 885–897. doi: 10.1037/a0020620.CrossRefPubMedPubMedCentralGoogle Scholar
  30. Henggeler, S. W., & Sheidow, A. J. (2012). Empirically supported family-based treatments for conduct disorder and delinquency in adolescents. Journal of Marital and Family Therapy, 38, 30–58. doi: 10.1111/j.1752-0606.2011.00244.x.CrossRefPubMedGoogle Scholar
  31. Hogue, A., Dauber, S., Samuolis, J., & Liddle, H. A. (2006). Treatment techniques and outcomes in multidimensional family therapy for adolescent behavior problems. Journal of Family Psychology, 20, 535–543. doi: 10.1037/0893-3200.20.4.535.CrossRefPubMedPubMedCentralGoogle Scholar
  32. Hogue, A., Dauber, S., & Henderson, C. E. (2014a). Therapist self-report of evidence-based practices in usual care for adolescent behavior problems: Factor and construct validity. Administration and Policy in Mental Health and Mental Health Services Research, 41, 126–139.CrossRefPubMedGoogle Scholar
  33. Hogue, A., Dauber, S., Henderson, C. E., Bobek, M., Johnson, C., Lichvar, E., & Morgenstern, J. (2014b). Randomized trial of family therapy versus non-family treatment for adolescent behavior problems in usual care. Journal of Clinical Child and Adolescent Psychology,. doi: 10.1080/15374416.2014.963857.PubMedCentralGoogle Scholar
  34. Hogue, A., Henderson, C. E., Ozechowski, T. J., & Robbins, M. S. (2014c). Evidence base on outpatient behavioral treatments for adolescent substance use: Updates and recommendations 2007-2013. Journal of Clinical Child and Adolescent Psychology, 43, 697–720. doi: 10.1080/15374416.2014.915550.CrossRefGoogle Scholar
  35. Huey, S. J., & Polo, A. J. (2008). Evidence-based psychosocial treatments for ethnic minority youth. Journal of Clinical Child and Adolescent Psychology, 37, 262–301. doi: 10.1080/15374410701820174.CrossRefPubMedPubMedCentralGoogle Scholar
  36. Huey, S. J., Henggeler, S. W., Brondino, M. J., & Pickrel, S. G. (2000). Mechanisms of change in multisystemic therapy: Reducing delinquent behavior through therapist adherence and improved family and peer functioning. Journal of Consulting and Clinical Psychology, 68, 451–467. doi: 10.1037//0022-006X.68.3.451.CrossRefPubMedGoogle Scholar
  37. Institute of Medicine. (2006). Improving the quality of healthcare for mental and substance-use conditions. Washington, D.C.: National Academy Press.Google Scholar
  38. James, C., Stams, G. J. J., Asscher, J. J., De Roo, A. K., & van der Laan, P. H. (2013). Aftercare programs for reducing recidivism among juvenile and young adult offenders: A meta-analytic review. Clinical Psychology Review, 33, 263–274.CrossRefPubMedGoogle Scholar
  39. Judd, C. M., McClelland, G. H., & Ryan, C. S. (2008). Data analysis: A model comparison approach (2nd ed.). New York: Routledge.Google Scholar
  40. Kataoka, S. H., Zhang, L., & Wells, K. B. (2002). Unmet need for mental health care among U.S children: Variation by ethnicity and insurance status. American Journal of Psychiatry, 159, 1548–1555. doi: 10.1176/appi.ajp.159.9.1548.CrossRefPubMedGoogle Scholar
  41. Kazdin, A. E. (1994). Methodology, design, and evaluation in psychotherapy research. In A. Bergin & S. Garfield (Eds.), Handbook of psychotherapy and behavior change (4th ed., pp. 19–71). New York: Wiley.Google Scholar
  42. Kolko, D. J., & Pardini, D. A. (2010). ODD dimensions, ADHD, and callous–unemotional traits as predictors of treatment response in children with disruptive behavior disorders. Journal of Abnormal Psychology, 119, 713. doi: 10.1037/a0020910.CrossRefPubMedGoogle Scholar
  43. Kraemer, H. C., Wilson, G. T., Fairburn, C. G., & Agras, W. S. (2002). Mediators and moderators of treatment effects in randomized clinical trials. Archives of General Psychiatry, 59, 877–883. doi: 10.1001/archpsyc.59.10.877.CrossRefPubMedGoogle Scholar
  44. Le Grange, D., Crosby, R. D., & Lock, J. (2008). New research: Predictors and moderators of outcome in family-based treatment for adolescent Bulimia Nervosa. Journal of the American Academy of Child and Adolescent Psychiatry, 47, 464–470. doi: 10.1097/CHI.0b013e3181640816.CrossRefPubMedGoogle Scholar
  45. Lecrubier, Y., Sheehan, D. V., Weiller, E., Amorim, P., Bonora, I., Sheehan, K. H., et al. (1997). The Mini International Neuropsychiatric Interview (MINI): A short diagnostic structured interview: Reliability and validity according to the CIDI. European Psychiatry, 12, 224–231. doi: 10.1016/S0924-9338(97)83296-8.CrossRefGoogle Scholar
  46. Lindhiem, O., Higa, J., Trentacosta, C. J., Herschell, A. D., & Kolko, D. J. (2014). Skill acquisition and utilization during evidence-based psychosocial treatments for childhood disruptive behavior problems: A review and meta-analysis. Clinical Child and Family Psychology Review, 17, 41–66. doi: 10.1007/s10567-013-0136-0.CrossRefPubMedPubMedCentralGoogle Scholar
  47. Little, R. J. A., & Rubin, D. B. (1987). Statistical analysis with missing data. New York: John Wiley.Google Scholar
  48. Mares, D., McLuckie, A., Schwartz, M., & Saini, M. (2007). Executive function impairments in children with attention-deficit hyperactivity disorder: Do they differ between school and home environments? Canadian Journal of Psychiatry, 52, 527–534.CrossRefPubMedGoogle Scholar
  49. Masi, G., Manfredi, A., Milone, A., Muratori, P., Polidori, L., Ruglioni, L., & Muratori, F. (2011). Predictors of nonresponse to psychosocial treatment in children and adolescents with disruptive behavior disorders. Journal of Child and Adolescent Psychopharmacology, 21, 51–55. doi: 10.1089/cap.2010.0039.CrossRefPubMedGoogle Scholar
  50. McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7, 64–82.CrossRefPubMedGoogle Scholar
  51. McKay, M. M., & Bannon, W. M. (2004). Engaging families in child mental health services. Child and adolescent psychiatric clinics of North America, 13, 905–921. doi: 10.1016/j.chc.2004.04.001.CrossRefPubMedGoogle Scholar
  52. Minuchin, S., & Fishman, H. C. (1981). Family therapy techniques. Cambridge: Harvard University Press.Google Scholar
  53. Monahan, K. C., Rhew, I. C., Hawkins, J. D., & Brown, E. C. (2014). Adolescent pathways to co-occurring problem behavior: The effects of peer delinquency and peer substance use. Journal of Research on Adolescence, 24, 630–645. doi: 10.1111/jora.12053.CrossRefPubMedGoogle Scholar
  54. Moos, R. H., & Moos, B. S. (1986). Family environment scale manual (2nd ed.). Palo Alto: Consulting Psychologists Press Inc.Google Scholar
  55. Muthén, L. K., & Muthén, B. O. (1998–2015). Mplus user’s guide (7th ed.). Los Angeles: Muthén & Muthén.Google Scholar
  56. O’Neil, K. A., Podell, J. L., Benjamin, C. L., & Kendall, P. C. (2010). Comorbid depressive disorders in anxiety-disordered youth: Demographic, clinical, and family characteristics. Child Psychiatry and Human Development, 41, 330–341. doi: 10.1007/s10578-009-0170-9.CrossRefPubMedGoogle Scholar
  57. Ozechowski, T. J., & Waldron, H. B. (2010). Assertive outreach strategies for narrowing the adolescent substance abuse treatment gap: Implications for research, practice, and policy. Journal of Behavioral Health Services and Research, 37, 40–63. doi: 10.1007/s11414-008-9136-0.CrossRefPubMedGoogle Scholar
  58. Radloff, L. S. (1977). The CES-D scale a self-report depression scale for research in the general population. Applied Psychological Measurement, 1, 385–401.CrossRefGoogle Scholar
  59. Riosa, P. B., McArthur, B. A., & Preyde, M. (2011). Effectiveness of psychosocial intervention for children and adolescents with comorbid problems: A systematic review. Child and Adolescent Mental Health, 16, 177–185. doi: 10.1111/j.1475-3588.2011.00609.x.CrossRefGoogle Scholar
  60. Robbins, M. S., Szapocznik, J., Dillon, F. R., Turner, C. W., Mitrani, V. B., & Feaster, D. J. (2008). The efficacy of structural ecosystems therapy with drug-abusing/dependent African American and Hispanic American adolescents. Journal of Family Psychology, 22, 51–61. doi: 10.1037/0893-3200.22.1.51.CrossRefPubMedGoogle Scholar
  61. Sheehan, K. H., Janavs, J., Weiller, E., Keskiner, A., et al. (1997). The validity of the Mini International Neuropsychiatric Interview (MINI) according to the SCID-P and its reliability. European Psychiatry, 12, 232–241.CrossRefGoogle Scholar
  62. Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., et al. (1998). The Mini International Neuropsychiatric Interview (MINI): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59, 22–33.PubMedGoogle Scholar
  63. Sibley, M. H., Pelham, W. E., Molina, B. S., Gnagy, E. M., Waschbusch, D. A., Biswas, A., et al. (2011). The delinquency outcomes of boys with ADHD with and without comorbidity. Journal of Abnormal Child Psychology, 39, 21–32. doi: 10.1007/s10802-010-9443-9.CrossRefPubMedPubMedCentralGoogle Scholar
  64. Sobell, L. C., & Sobell, M. B. (1996). Timeline Followback user’s guide: A calendar method for assessing alcohol & drug use. Toronto: Addiction Research Foundation.Google Scholar
  65. Sotsky, S. M., Glass, D. R., Shea, M. T., Pilkonis, P. A., Collins, J. F., Elkin, I., & Oliveri, M. E. (1991). Patient predictors of response to psychotherapy and pharmacotherapy: Findings in the NIMH Treatment of Depression Collaborative Research Program. American Journal of Psychiatry, 148, 997–1008.CrossRefPubMedGoogle Scholar
  66. Sroufe, L. A., & Rutter, M. (1984). The domain of developmental psychopathology. Child Development, 55, 17–29.CrossRefPubMedGoogle Scholar
  67. Steinberg, L. (2010). A behavioral scientist looks at the science of adolescent brain development. Brain and Cognition, 72, 160–164. doi: 10.1016/j.bandc.2009.11.003.CrossRefPubMedGoogle Scholar
  68. Tamm, L., Trello-Rishel, K., Riggs, P., Nakonezny, P. A., Acosta, M., Bailey, G., & Winhusen, T. (2013). Predictors of treatment response in adolescents with comorbid substance use disorder and attention-deficit/hyperactivity disorder. Journal of Substance Abuse Treatment, 44, 224–230. doi: 10.1016/j.jsat.2012.07.001.CrossRefPubMedGoogle Scholar
  69. Valo, S., & Tannock, R. (2010). Diagnostic instability of DSM-IV ADHD subtypes: Effects of informant source, instrumentation, and methods for combining symptom reports. Journal of Clinical Child and Adolescent Psychology, 39, 749–760. doi: 10.1080/15374416.2010.517172.CrossRefPubMedGoogle Scholar
  70. Van Ryzin, M., & Leve, L. D. (2012). Affiliation with delinquent peers as a mediator of the effects of Multidimensional Treatment Foster Care for delinquent girls. Journal of Consulting and Clinical Psychology, 80, 588–596. doi: 10.1037/a0027336.CrossRefPubMedPubMedCentralGoogle Scholar
  71. Weissman, M. M., Orvaschel, H., & Padian, N. (1980). Children’s symptom and social functioning self-report scales comparison of mothers’ and children’s reports. The Journal of Nervous and Mental Disease, 168, 736–740. doi: 10.1097/00005053-198012000-00005.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Aaron Hogue
    • 1
    Email author
  • Craig E. Henderson
    • 2
  • Adam T. Schmidt
    • 2
  1. 1.The National Center on Addiction and Substance AbuseNew YorkUSA
  2. 2.Department of PsychologySam Houston State UniversityHuntsvilleUSA

Personalised recommendations