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.edujlochman@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. BenchBedside Type 1 Translational Research

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. Inconsistent Discipline Mediates Maternal Depression Effect on Child Aggression (Barry, Dunlap, Lochman & Wells, 2008, Child and Family Behavior Therapy) Low SES High Maternal Parenting Stress High Maternal Distress Inconsistent Parenting Practices 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 Child Disruptive Behavior Variables Maternal Depression Maternal Depression (controlling for Inconsistent Discipline) Inconsistent Discipline (controlling for Maternal Depression) Aggression.12 *.09.22 **

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. Marital Conflict and Parenting Predicting Child Aggression 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 (S a and S b ) were used in the Sobel test, Z = 2.170, p = 0.030. 0.438 a (0.134S a ) 0.493 b (0.162S b ) Time 1 Aggress marital conflict (IV) Time 3 Children’s aggression (DV) 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) Neighborhood Effects (Fite. Lochman, & Wells, 2009, Journal of Community Psychology)

16. Neighborhood Context: Predicting Children’s Aggression in 6 th Grade (Beta) Neighborhood disadvantage predicts proactive but not reactive aggression Proactive Aggression Reactive Aggression Gender.46*.19 Race-.18-.04 5 th grade Proactive Aggression.08.11 5 th grade Reactive Aggression.16.14 Neighborhood Disadvantage.25*.19

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) – 8 th – 9 th grades -Reactive and Proactive Aggression (Teacher rated; Dodge & Coie, 1987) – 5 th grade -Perceived Peer Delinquency - 8 th grade -Peer Rejection – classroom sociometrics – 5 th grade

20. Proactive and Reactive Aggression and Substance Use – Structural Equation Model Chi Square (5)=3.64, p=.60, CFI=1.00, RMSEA=.00 (Fite, Colder, Lochman & Wells, 2007, Psychology of Addictive Behaviors) 5 th Gr Proactive Aggression  8 th Gr Peer Delinquency  9 th Gr Alcohol Use 5 th Gr Reactive Aggression  5 th Gr Low Peer Acceptance  8 th Gr Peer Delinquency  9 th 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) 1. Cue encoding difficulties, by excessively recalling hostile social cues 2. Hostile attributional biases, and distorted perceptions of self and other in peer conflict situations 3. Dominance and revenge oriented social goals 4. Generate less competent problem solutions, with fewer verbal assertion, compromise and bargaining solutions 5. Expect that aggressive solutions will work, and value aggressive solutions more 6. 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 4 th 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 Skin Conductance Cortisol Reactive Aggression (T) ns 2.1* Reactive Aggression (P) 3.1** ns Aggressive Game Response 4.1** ns State Angerns 2.2*

26. Social Cognitive Processes in Aggressive Children (Crick & Dodge, 1994; Lochman, Whidby & FitzGerald, 2000) 1. Cue encoding difficulties, by excessively recalling hostile social cues 2. Hostile attributional biases, and distorted perceptions of self and other in peer conflict situations 3. Non-affiliative social goals 4. Generate less competent problem solutions, with fewer verbal assertion, compromise and bargaining solutions 5. Expect that aggressive solutions will work, and value aggressive solutions more 6. Poor enactment of solutions, due to weak social skills

27. Reactive and Proactive Aggression (Dodge & Coie, 1987; Dodge, Lochman, Harnish, Bates & Pettit, 1997; Lochman & Wells, 1999) 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

28. Contextual Social-Cognitive Model Background Context Mediational Processes Outcomes Contextual Social-Cognitive Model Background Context Mediational Processes Outcomes

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 Component Lochman & 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 Child Component Only vs Control Child + Parent Component vs Control Intervention Cells in Normative Range Delinquency -.37 * * Substance Use (Parent-rated) -.66 * * School Behavioral Improvement.42 *.34 * *

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

37. One-Year Follow-up Outcomes for the CSAP-funded Study Lochman & 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 Children Lochman, 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 Clinics van 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 Psychiatry van 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. BedsidePractice Type 2 Translational Research

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

51. Training Effects on Dissemination of Interventions The nature of the training provided for an intervention can affect outcomes Training that is intense, ongoing and carefully specified has led to greater adherence to the principles of the intervention protocol and to the strongest effects for MST (Henggeler et al, 1998)

52. Training Study: Field Trial Lochman, Boxmeyer, Powell, Qu, Wells, & Windle (2009). Journal of Consulting and Clinical Psychology. School selection: 57 schools from 5 public school systems Range of urban and suburban schools in Alabama Random assignment by counselor to: – Basic Training (CP-BT; 19 schools) – Intensive Training (CP-IT; 19 schools) – Care-as-usual comparison (C; 19 schools)

53. Field Trial Methods Participant selection: Teacher screening for “at-risk” youth – Rated proactive and reactive aggressive behavior of all 3 rd grade students (Hill et al., 2004; Lochman & CPPRG, 1995) – 3,774 3 rd graders screened – 30% most aggressive eligible for participation – 531 participating students (79% of 670 contacted): 183 CP-BT schools; 168 in CP-IT; 180 in C 84% Af Am; 14% Cauc; 2% Other 95% retention at post-intervention (2 yrs after baseline)

54. Field Trial Methods Counselor characteristics: 49 counselors – 17 in CP-BT, 15 in CP-IT, 17 in C – 8 counselors served 2 of the participating schools 96% Female, 4% Male 51% Af Am, 49% Caucasian 18% Doctoral level, 80% Master level, 2% BA Years experience: – 9.9 in CP-BT, 11.9 in CP-IT, 8.8 in C

55. Field Trial Methods Counselor characteristics (cont.): 80% indicated prior experience leading child groups – Group counseling time was a requirement for guidance counselors 28% reported using some type of manualized group intervention – No specific program in widespread use

56. Field Trial Methods Timeline: 3 rd Grade4 th Grade5 th Grade Child screening Baseline Assessment Counselors Trained Intervention underway Midpoint Assessment Intervention Continues Post- Assessment

57. Field Trial Methods Training process: (1) 3 days of workshop training (2) Monthly meetings (2 hours) while intervention underway For CP-IT counselors only: (3) Individualized feedback on audiotaped sessions (4) Technical assistance from trainers via telephone and email contacts

58. Results: Program Implementation - Delivery Not at all Partially Completely

59. Results: Program Implementation Implementation Quality – Counselor engagement (audio coder ratings, with children and with parents; 5-point ratings on 14 items on warm tone, tone not irritable, makes teaching moments, provides consequences for group rules, stops to clarify material; elaborates beyond manualized material, stimulates discussion, etc) – alpha:.86 (w/ children),.82 (w/ parents)

60. Results: Implementation Quality p<.02

61. Results: Training Outcomes Outcomes: HLM used to evaluate if intervention condition/training intensity influenced: -Children’s externalizing behavior problems -Child and parent mediating processes Two-level model with: -Level 1 Students (within-unit model) -Level 2 Counselors (between-unit model)

62. Results: Training Outcomes Two-level HLM model: -Level 1 within-unit model in equation form as:  TRT1 and TRT2 are the two orthogonal contrasts, and X is baseline score.  Contrast TRT1 compares CP-IT vs Control.  Contrast TRT2 compares CP-BT vs Control. -Level 2 between-unit model in equation form as: The Wald test compares CP-IT vs CP-BT.

63. Results: Training Outcomes CP-Intensive vs Control Estimate (SE) Behavior Problems BASC Externalizing (teacher-report) -.41* (.11) BASC Externalizing (parent-report) -.23*(.12) NYS Minor Assault (child-report) -.25** (.12) **p<.01, *p<.05,

64. CP-Intensive vs Control Estimate (SE) Behavior Problems BASC Externalizing (teacher-report) -.41* (.11) BASC Externalizing (parent-report) -.23*(.12) NYS Minor Assault (child-report) -.25** (.12) Targeted Processes BASC Social/Academic (teacher).35* (.13) BASC Social (parent) Outcome Expectations (child) -.24* (.08) APQ Inconsistent Discipline (parent) **p<.01, *p<.05,

65. CP-Intensive vs Control Estimate (SE) CP-Basic vs Control: Estimate (SE) Behavior Problems BASC Externalizing (teacher-report) -.41* (.11) BASC Externalizing (parent-report) -.23*(.12) NYS Minor Assault (child- report) -.25** (.12) Targeted Processes BASC Social/Academic (teacher).35* (.13).24+ (.13) BASC Social (parent) Outcome Expectations (child) -.24* (.08) APQ Inconsistent Discipline (parent) **p<.01, *p<.05, +p=.06

66. CP-Intensive vs Control Estimate (SE) CP-Basic vs Control: Estimate (SE) CP Intensive vs CP-Basic Chi Square (DF) Behavior Problems BASC Externalizing (teacher-report) -.41* (.11) 3.87 (1)* BASC Externalizing (parent-report) -.23*(.12) NYS Minor Assault (child- report) -.25** (.12) 6.23 (1)* Targeted Processes BASC Social/Academic (teacher).35* (.13).24+ (.13) BASC Social (parent) Outcome Expectations (child) -.24* (.08) 5.64 (1)* APQ Inconsistent Discipline (parent) **p<.01, *p<.05, +p=.06

67. Conclusions/Implications for Training Evidence-based prevention programs such as Coping Power can be disseminated effectively to counselors in real-world settings, although:  The intensity of training makes a difference in whether improvements in children’s outcomes and mediating processes occur  Ongoing supervisory feedback about program implementation (particularly to foster client engagement) may be critical to promoting positive outcomes  The intensity of training required will likely vary according to the experience and prior training of the providers, to the type of psychopathology being addressed, and to the complexity of the program being used

68. The Effect of School and Counselor Characteristics on Implementation of a Preventive Intervention Lochman, Powell, Boxmeyer, Qu, Wells, & Windle. (in press). Professional Psychology: Research and Practice

69. Systems Effects on Dissemination of Interventions New interventions may need organizational support to be adequately implemented

70. Field Trial: Sample and Design The two training conditions, with 32 counselors, were pooled for these analyses

71. Field Trial: Implementation Analyses The predictors of implementation: 1. school environment (Moos’ Work Environment Scale; Moos, 1981) – completed by all 4 th and 5 th grade teachers - staff relationships (staff cohesion and support) - staff autonomy - degree of managerial control

72. Field Trial: Implementation Analyses 2. counselor characteristics - neuroticism (NEO Five Factor Inventory; Costa & McCrae, 1992) - extraversion (NEO) - openness (NEO) - agreeableness (NEO) - conscientiousness (NEO) - cynicism (Cynicism about Organizational Change; Reichers et al, 1997)

73. Field Trial: Post Analyses Implementation dependent variables are: 1. Program Delivery – Objectives completed – Sessions scheduled 2. Implementation Quality – Counselor engagement (audio coder ratings, with children and with parents)

74. Hierarchical Regression Analyses Beta Coefficients (Standard Errors): Program Delivery *p<.05, +p<.10 Objectives Completed Sessions Scheduled Agreeableness.086* (.042).185+ (.103) Managerial Control -.286+ (.149)

75. Hierarchical Regression Analyses Beta Coefficients (Standard Errors): Counselor Engagement **p<.01, *p<.05 With Children With Parents Conscientiousness.068* (.032) Agreeableness.112** (.039) Managerial Control X Cynicism -.734** (.200) Autonomy X Cynicism.674** (.173)

76. Autonomy X Cynicism

77. Conclusions About Counselor and School Characteristics The GOOD NEWS: It is ok to be neurotic, not particularly open-minded, not particularly extraverted, and cynical if you are in the right work environment Degree and quality of implementation can be influenced by agreeableness and conscientiousness of counselors and by characteristics of the school setting which interact with counselor characteristics (counselor cynicism in interaction with school autonomy and rigid managerial control)