John E. Lochman The University of Alabama & Utrecht University

1. Taking Evidence Based Programmes to the Real World: The American Experience and Lessons for Tallaght West John E. Lochman The University of Alabama & Utrecht University Box 870348, Department of Psychology, The University of Alabama Tuscaloosa, AL 35487 205-348-7678; jlochman@ua.edu Research and Policy Workshop – November 22, 2009

2. This presentation’s translational research topics: • Type 1: Risk factors for children’s antisocial behavior: a contextual social-cognitive model • Coping Power efficacy and effectiveness studies • Type 2: Coping Power dissemination study

3. Type 1 Translational Research Bench Bedside

4. Is aggressive behavior a stable behavior pattern, or not? • Subgroup of chronic aggressive children are at risk of most physical violence during adolescence (Nagin & Tremblay, 1999)

5. Summary of Stability and Predictive Utility of Children’s Aggression • Aggressive behavior during early childhood predicts adolescent delinquency, substance use, and school problems • Thus, preventive interventions can target high risk aggressive children, and, from a prevention science perspective, these interventions should address the malleable risk factors that produce and maintain children’s aggressive behavior

6. Child Factors: biology and temperament • Family Context • Neighborhood Context • Peer Context • Later Emerging Child Factors: social cognitive processes and emotional regulation

7. Family Context links to Childhood Aggression • Parent depression and anxiety • Marital conflict • These family factors can influence child behavior through their effect on parenting processes

8. Low SES High Maternal Parenting Stress Inconsistent Parenting Practices High Maternal Distress Inconsistent Discipline Mediates Maternal Depression Effect on Child Aggression(Barry, Dunlap, Lochman & Wells, 2008, Child and Family Behavior Therapy) Child Disruptive Behavior Problems

9. Maternal Distress Predicting Parenting • Sample: 215 boys, overweighted for aggression; 9-12 years of age; 59% African-American

10. Maternal Distress and Parenting Predicting Child Aggression and Attention Problems

11. Marital Conflict and Parenting Predicting Child Aggression(Baden, Lochman & Wells, under review) • Sample: 74 boys, overweighted for aggression; 9-12 years of age; 46% African-American - in families with marital/cohabiting partner • Constructs (and measures) - Child Aggression (CBCL; TRF) - Marital conflict (Conflict Tactics Scale, verbal and physical aggression; O’Leary Porter Marital Discord) - Harsh parenting (Conflict Tactics Scale, verbal and physical aggression) • Multiple imputation for missing data

12. 0.493b (0.162Sb) 0.438a (0.134Sa) Time 1 Aggress marital conflict (IV) Time 3 Children’s aggression (DV) Mediational model highlighting the significant indirect effect of marital conflict on children, supportive of the mediating role of aggressive parenting. Path coefficients (ab) and standard errors (Saand Sb) were used in the Sobel test, Z = 2.170, p = 0.030. Marital Conflict and Parenting Predicting Child Aggression Time 2 Aggressive parenting (Mediator)

13. Child Factors: biology and temperament • Family Context • Neighborhood Context • Peer Context • Later Emerging Child Factors: social cognitive processes and emotional regulation

14. Neighborhood Context • Neighborhood crime rates and social cohesion can affect disruptive behavior in children (Colder, Mott, Levy & Flay, 2000; Guerra, Huesmann & Spindler, 2003 Majumder, Moss & Murrelle, 1998; Maughan, 2001) , especially starting during middle childhood (Ingoldsby & Shaw, 2002) • Fite et al (2009):Neighborhood Disadvantage (census information: percent below poverty, percent receiving public assistance, percent of adults unemployed, percent of adults with 12 or fewer years of education, etc), from 22 aggregated neighborhoods with126 at-risk aggressive children; 66% male; 79% African-American

15. Neighborhood Effects (Fite. Lochman, & Wells, 2009, Journal of Community Psychology)

16. Neighborhood Context: Predicting Children’s Aggression in 6th Grade (Beta) • Neighborhood disadvantage predicts proactive but not reactive aggression

17. Child Factors: biology and temperament • Family Context • Neighborhood Context • Peer Context • Later Emerging Child Factors: social cognitive processes and emotional regulation

18. Peer Context • Peer Rejection: By elementary school, aggressive behavior can lead to peer rejection, although the relation is bidirectional (Coie, Dodge & Kupersmidt, 1990) - Additive risk for aggression and rejection exists (Coie, Lochman, Terry & Hyman, 1992) • Deviant Peers: Peer rejection from the broad peer group may set the stage for involvement with deviant peers, which is itself a critical peer risk factor by adolescence

19. Proactive and Reactive Aggression and Substance Use (Fite, Colder, Lochman & Wells, 2007, Psychology of Addictive Behaviors) • Sample: 126 at-risk aggressive children; 66% male; 79% African-American • Measures - Substance Use – Center for Substance Abuse Prevention Student Survey (3 items assessing whether ever had alcohol, tobacco or marijuana use) – 8th – 9th grades - Reactive and Proactive Aggression (Teacher rated; Dodge & Coie, 1987) – 5th grade - Perceived Peer Delinquency - 8th grade - Peer Rejection – classroom sociometrics – 5th grade

20. Proactive and Reactive Aggression and Substance Use – Structural Equation ModelChi Square (5)=3.64, p=.60, CFI=1.00, RMSEA=.00(Fite, Colder, Lochman & Wells, 2007, Psychology of Addictive Behaviors) • 5th Gr Proactive Aggression  8th Gr Peer Delinquency  9th Gr Alcohol Use • 5th Gr Reactive Aggression  5th Gr Low Peer Acceptance  8th Gr Peer Delinquency  9th Gr Alcohol Use With 126 at-risk aggressive children

21. Child Factors: biology and temperament • Family Context • Neighborhood Context • Peer Context • Later Emerging Child Factors: social cognitive processes and emotional regulation

22. Social Cognitive Processes in Aggressive Children(Crick & Dodge, 1994; Lochman, Whidby & FitzGerald, 2000) • Cue encoding difficulties, by excessively recalling hostile social cues • Hostile attributional biases, and distorted perceptions of self and other in peer conflict situations • Dominance and revenge oriented social goals • Generate less competent problem solutions, with fewer verbal assertion, compromise and bargaining solutions • Expect that aggressive solutions will work, and value aggressive solutions more • Poor enactment of solutions, due to weak social skills

23. Effects of Anger-Related Processes on Social Information Processing • Attributions, physiological arousal, and reactive aggression

24. Effects of Threat Induction on Boys’ Attributions and Heart Rate (Williams, Lochman, Phillips & Barry, 2003, Journal of Clinical Child and Adolescent Psychology) • In response to experimental threat induction (stranger peer is angry and ready to fight), the most aggressive 4th grade boys have increases in heart rate and in hostile attributions • Correlation of .41 between heart rate increase and increase in hostile attributions

25. Reactive Aggression and Physiological Response Following Provocation(Clanton & Lochman, in preparation) • 20 minute recovery: After a 20 minute recovery period following children’s response to provocation on a computer game, higher levels of reactive aggression and anger were associated with greater difficulty in reducing arousal; no prediction of proactive aggression

26. Social Cognitive Processes in Aggressive Children(Crick & Dodge, 1994; Lochman, Whidby & FitzGerald, 2000) • Cue encoding difficulties, by excessively recalling hostile social cues • Hostile attributional biases, and distorted perceptions of self and other in peer conflict situations • Non-affiliative social goals • Generate less competent problem solutions, with fewer verbal assertion, compromise and bargaining solutions • Expect that aggressive solutions will work, and value aggressive solutions more • Poor enactment of solutions, due to weak social skills

27. Reactive Aggression: Encoding errors Hostile attributions Lower perceived social and general competence More sad and depressed More harsh and non-involved parenting Neighborhood violence Proactive Aggression: Expectations that aggression will work Low fearfulness Cognitive dysregulation – little concern for long-term consequences or goals Involved with peers who are approving of deviant behaviors Reactive and Proactive Aggression (Dodge & Coie, 1987; Dodge, Lochman, Harnish, Bates & Pettit, 1997; Lochman & Wells, 1999)

28. Contextual Social-Cognitive ModelBackground ContextMediational ProcessesOutcomes

29. Empirically Supported Treatment for Externalizing Disorders in School-age Children • Coping Power program

30. School Age Children: Coping Power • Child Component Content • Anger management training, including methods for self-instruction, distraction, and relaxation • Perspective-taking and attribution retraining • Social problem-solving in a variety of situations (peer, teacher, family) • Resistance to peer pressure and focus on involvement with non-deviant peer groups

31. School Age Children: Coping Power • Parent Component Content • Positive attention and rewards for appropriate child behavior. • Clear commands, rules, expectations, and monitoring. • Use of consistent consequences for negative child behavior (response cost, time-out, withdrawal of privileges). • Improvement of family communication and increasing family activities. • Improvement of parents’ own stress management.

32. NIDA-funded Study of Coping Power Child Component Only, and of Child Component Plus Parent ComponentLochman & Wells (2004), Journal of Consulting and Clinical Psychology, 72, 571-578

33. Significant Contrasts (effect sizes) with Control Cell & Normative Comparison: Outcomes at 1 Year Follow-up

34. Contextual Social-Cognitive Mediators and Child Outcome at a One Year Follow-up: Mediation of Coping Power EffectsLochman & Wells (2002), Development and Psychopathology, 14, 945-967

37. One-Year Follow-up Outcomes for the CSAP-funded StudyLochman & Wells (2002) Psychology of Addictive Behaviors, 16, S40-S54 Lochman, J.E. & Wells, K.C. (2003), Behavior Therapy, 34, 493-515

38. Substance Use(youth self report of use of Tobacco, Alcohol, and Marijuana in the past month)Coping Power vs Control: F(1,120)=10.8, p=.001

39. Delinquent Behavior(Youth self report of theft, assault, property destruction, fraud, and drug selling in the past month) Coping Power vs Control: F(1,129)=4.30, p=.04

40. Teacher-rated Peer Aggressive Behavior(fighting and harming others from the TOCA-R) Coping Power vs Control: F(1,80)=4.18, p=.04

41. Longer – Term 3 Year Follow-up:TOCA Aggression: Coping Power vs Control

42. Coping Power Dissemination Study with Aggressive Deaf ChildrenLochman, J.E., FitzGerald, D.P., Gage, S.M., Kanakly, M.K., Whidby, J.M., Barry, T.D., Pardini, D.A., & McElroy, H. (2001), Journal of the American Deafness and Rehabilitation Association, 35, 39-61

43. Sample • 49 aggressive deaf children, based on teacher-rated aggression on a screening measure administered in residential school for the deaf • 33 males, 16 females • 64% African American, 34% Caucasian, 2% Hispanic

44. Competent Problem Solutions (verbal assertion, cooperation, positive action) F(1, 36 ) = 11.04, p < .01

45. Coping Power Cost Effectiveness Study with ODD/CD Dutch Children in Child Psychiatry Clinicsvan de Wiel, N.M.H., Matthys, W., Cohen-Kettenis, P.T., Maassen, G.H., Lochman, J.E., & van Engeland, H. (2007).Behavior Modification.Zonnevylle-Bender, M.J.S., Matthys, W., van de Wiel, N.M.H., & Lochman, J. (2007) Journal of the American Academy of Child and Adolescent Psychiatryvan de Wiel, NMH, Matthys, W, Cohen-Kettenis, P, & van Engeland, H (2003), Behavior Therapy.

46. Results at 4 yr FU Substance Use CAU (N=31) UCPP(N=30) p Tobacco (last month) 42% 17% 0.02 Alcohol (last month) 65% 67% ns Marijuana (ever) 31% 13% 0.04

47. Dissemination of Coping Power to Real-World Settings

48. Type 2 Translational Research Bedside Practice

49. Dissemination of Evidence-Based Interventions • The implementation and outcomes of programs have been found to be highly variable when programs have been disseminated, leading to the apparent failure of many effective interventions once they are in widespread use in education (Battistich, 2001; Kalafat et al., 2007; Kam et al., 2003) and mental health settings (e.g., August, et al., 2006; Henggeler et al., 1997; Schoenwald et al. 2004).

50. Dissemination within real-world settings: training issues and organizational factors