Choosing the Appropriate Design to Optimize Behavioral and Social Interventions

1. Choosing the Appropriate Design to Optimize Behavioral and Social Interventions C Hendricks Brown University of Miami Miller School of Medicine Director Prevention Science & Methodology Group (PSMG) Director, Center for Prevention Implementation Methodology (NIDA, OBSSR) Director, Social Systems Informatics at the Center for Computational Science

2. Center for Prevention Implementation Methodology (Ce-PIM) on Drug Abuse and Sexual Risk Behavior NIDA, OBSSR

3. Prevention Science and Methodology Group (PSMG)Collaborative Data Synthesis for Adolescent Depression Trials NIMH R01-MH040859- 23 NIH Summer Institute on Social and Behavioral Intervention Research

4. What do we mean by • Design • Optimize • Behavioral and Social Interventions NIH Summer Institute on Social and Behavioral Intervention Research

5. What do we mean by • Choosing -- who? • Design -- randomized or not? • Optimize – ways to have greater impact? • Behavioral and Social Interventions – what type of interventions? NIH Summer Institute on Social and Behavioral Intervention Research

6. DESIGN and design • Starting Place for a Design • Community, Research, and Funder Stakeholders NIH Summer Institute on Social and Behavioral Intervention Research

7. Schematic of an Intervention Research Design Institutional & Community Partnerships Determine Research Question(s) Research Team Expertise Population Intervention Conditions Sampling, Sample Size and Enrolling Measures and Follow-up/ Assessment Procedures Assignment to Intervention Condition Ethics/Human Subjects/Values Financial/Logistics NIH Summer Institute on Social and Behavioral Intervention Research

8. Design comes through an Integration of Research, Community, and Methodology Develop Programs Tech Assistance Conduct Evaluation Community Research Mandate Community Resources, Deliver Programs Quality Improvement Measuring Modeling Testing Methodology NIH Summer Institute on Social and Behavioral Intervention Research

9. Where are we going in Research? NIH Summer Institute on Social and Behavioral Intervention Research

10. Just like windshield wipers, Good Designs help us see….. NIH Summer Institute on Social and Behavioral Intervention Research

11. What do we mean by Optimal Intervention? • Find the most efficacious intervention based on overall impact AdaptiveTrial Designs Comparative Effectiveness Trial 2. Deliver intervention that addresses the specific needs of a target population Designs to Test Moderation • Deliver an optimal intervention for each person – Personalized intervention trials Preference Trials 4. Implement intervention to have broadest impact at a population level Enrollment Trials Implementation Trials Roll-Out Dynamic Wait-Listed Trials NIH Summer Institute on Social and Behavioral Intervention Research

12. Find the most efficacious intervention based on overall impact Adaptive Trial Designs Comparative Effectiveness Trial • Adaptive Some of these adaptations affect • specific elements of the study design of an ongoing trial, Adaptive Design (2) some relate to the next trialor stages within a trial: Adaptive Sequencing of Trials (3) relate to the intervention or to its delivery. Adaptive Intervention NIH Summer Institute on Social and Behavioral Intervention Research

13. Adaptive Design, Sequencing, and Intervention Brown, Ten Have, Jo et al., 2009 Ann Rev P H • Adaptive Design: planned modification of characteristics of the trial itself based on information from the data already accumulated. Optimal Dose Trial (Draglin & Fedrov 2004) First Trial 1: 0 10* 20 Second Trial 2: 5 10 15 Internet, m-health based trials NIH Summer Institute on Social and Behavioral Intervention Research

14. Optimal Dose Presentation to Center for Personalized Prevention Research

15. Presentation to Center for Personalized Prevention Research

16. Presentation to Center for Personalized Prevention Research

17. When to use Optimal Dosage Trials • Potential for enrolling many people (Munoz Internet Interventions for Smoking Cessation) • Quick response (intermediate outcome) to interventions • Easily manipulate dosage Mobile and Internet behavioral interventions fit these well. NIH Summer Institute on Social and Behavioral Intervention Research

18. Comparative Effectiveness Trials • Test Two or More Treatments Head to Head • Potential advantage in treatment (vs. prevention trials) where requirement is to do something Example: Earlise Ward (U Wisc Madison) Behavioral Intervention for Depressed African American Adults Testing Standard Coping with Depression Course vs Oh Happy Day Culturally Adapted Version NIH Summer Institute on Social and Behavioral Intervention Research

19. Issues with delivery in group settings • Attempt to recruit 10 women per group • Unethical (and inefficient) to delay treatment too long • Formed a group of 4 women, 2 couldn’t work with that schedule • Need a design protocol that is sufficiently flexible to deal with anticipated problems without destroying the trial NIH Summer Institute on Social and Behavioral Intervention Research

20. Comparative EffectivenessIt is possible to compare two interventions that are never directly tested against one another • Trial 1 A vs Control A – C • Trial 2 B vs Control B – C Difference estimates A – B Network Meta-Analysis Hoaglin & Hawkins 2011 Report of the ISPOR Task Force on Indirect Comparisons: Good Research Practices Part II, Value in Health 14, 429-437. NIH Summer Institute on Social and Behavioral Intervention Research

21. Example: Indirect Comparison of Good Behavior Game (G) and Mastery Learning (M) through Controls (C) School 6 School 1 School 7 School 12 Ctl G M Kellam, Brown et al.; Brown, Wang et al., Drug & AlcDep 2008 NIH Summer Institute on Social and Behavioral Intervention Research

22. Findings NIH Summer Institute on Social and Behavioral Intervention Research

23. 2. Optimal Designs: Deliver intervention that addresses the specific needs of a target population How does benefit vary by baseline level of risk; should there be different interventions by level of risk? Do impulsive youth respond differently to interventions to prevent drug abuse than do non-impulsive youth? Do minority, depressed women do better on CBT or antidepressants? Should antidepressants be given for those with more moderate levels of baseline depression? NIH Summer Institute on Social and Behavioral Intervention Research

24. Example: Moderation of Intervention Effect on Proximal Target by Baseline Extended Teen Intn Brief Teen Intn Impulsive Impulsive Decision Making Randomize Drug Use Presentation to Center for Personalized Prevention Research

25. Statistical Power to Detect Moderation Effects for Subgroups • Essentially need at least 4 times the size you need for examining main effects • Need either a very large study or combine different studies together in an integrative data analysis (Brown et al., PrevSci, 2011) NIH Summer Institute on Social and Behavioral Intervention Research

26. Growth Mixture Models: WECare Miranda et al, JAMA 2003, Siddique et al., under review Med CBT NIH Summer Institute on Social and Behavioral Intervention Research

27. Statistical Power can be calculated for • Longer term studies: growth models • Variation in impact: growth mixture models • Muthen , Brown et al., 2002 Biostatistics NIH Summer Institute on Social and Behavioral Intervention Research

28. How Does Baseline Level of Depression Affect Improvement in the Slope of Depressive Symptoms for Antidepressants? Helen Denne Schulte School of Nursing Visiting Lecture

29. 3. Deliver an optimal intervention for each person • Personalized intention: Collins, Murphy, et al. AJPM 2007 • What are generally better intervention components? Multiphase Optimization Strategy Trial (MOST) A, a , B ,b C, c D, d, E, e, F, f -- 64 different combinations reduce # of combinations tested by assuming higher order interactions are small Fractional factorial design: ABCD, abcd, aBcD, … 16 combinations NIH Summer Institute on Social and Behavioral Intervention Research

30. Nonresponders to a first intervention get a follow-up intervention Sequential Multiple Assignment Randomized Trial (SMART), Collins et al., 2007 NIH Summer Institute on Social and Behavioral Intervention Research

31. SMART Trial for Conduct Problem Prevention Monitor Parent Focused Responder CPP Youth Focused Youth Focused Non Responder Randomize CPP Parent/Youth Focused Randomize CPP Parent/Youth Focused Non Responder Randomize CPP Parent Focused Responder Monitor Presentation to Center for Personalized Prevention Research

32. Example 1: Proposed SMART Trial for Conduct Problem Prevention Monitor Parent Focused Responder CPP Youth Focused Youth Focused Non Responder Randomize CPP Parent/Youth Focused Randomize CPP Parent/Youth Focused Non Responder Randomize CPP Parent Focused Responder Monitor Presentation to Center for Personalized Prevention Research

33. Another Personalized Intervention: Preference • Preference Trial NIH Summer Institute on Social and Behavioral Intervention Research

34. Would allowing subjects to choose their preferred treatment . . . • Increase the uptake of evidence-based interventions? • Increase the adherence to one of these interventions? • Improve outcomes? NIH Summer Institute on Social and Behavioral Intervention Research

35. Equipoise: Another approach related to Preference or Choice • Equipoise – ideally there should be no preference in a trial for one intervention over another • Clinician equipoise • Subject equipoise • One interesting Equipoise design: Offer a range of different intervention options for a subject, but randomize only to one that the subject states she is willing to take. • Nothing, Watchful waiting, SSRI, TCA, CBT • X x NIH Summer Institute on Social and Behavioral Intervention Research

36. Preference Trial Standard Assignment Usual Service Assign by Preference Home PMTO Choice Randomize Randomize Clinic PMTO In-Person Group PMTO On-Line Group PMTO Presentation to Center for Personalized Prevention Research

37. Example 3: Preference Trial Standard Assignment Usual Service Assign by Preference Home PMTO Choice Randomize Randomize Clinic PMTO In-Person Group PMTO On-Line Group PMTO Presentation to Center for Personalized Prevention Research

38. Traditional Randomized Trial: Randomization AFTER Consent Consent to be Randomized to RCT? Randomized No Info CBT Antidepressant NIH Summer Institute on Social and Behavioral Intervention Research

39. Doubly Randomized Trial: Randomization BEFORE and AFTER Consent Randomized to Invitation Consent to Preference Arm of Trial Consent to be Randomized To RCT? No Info Yes No Yes No No Randomized to RCT No Info CBT AD Both CBT Antidepressant NIH Summer Institute on Social and Behavioral Intervention Research

40. Adaptive Enrollment Designs: Who gets into a trial • Testing Motivational Interviewing Strategies Presentation to Center for Personalized Prevention Research

41. Example 3: Encouragement/Preference Trial MI - 2 MI - 1 Home PMTO Choice Randomize Clinic PMTO In-Person Group PMTO On-Line Group PMTO Presentation to Center for Personalized Prevention Research

42. Complier (Participant) Average Causal Effect (CACE) Modeling for Encouragement Designs High Low Non- Participant Non- Participant Participant Participant Presentation to Center for Personalized Prevention Research

43. Designs to Screen a Large Number of Baseline Characteristics Interacting with Intervention (e.g., G x E) • So far, reports are limited to single locus alleles (Brody) • How to begin searching for multiple gene interactions NIH Summer Institute on Social and Behavioral Intervention Research

44. Propose 2-Phase Trials to Screen and Confirm Interactions • Phase I • Phase II Presentation to Center for Personalized Prevention Research

45. Propose 2-Phase Trials To Look at Interaction • Phase I: Test for interactions among a finite subset of K covariates (genotypes), say with Power of 0.9, but Type I error of say 0.2. From analysis, Select the L top covariates • Phase II: Compute a new sample size Rerun New Study but Limit Interactions to those who have passed through first phase Presentation to Center for Personalized Prevention Research

46. An Example • Looking at 20 G x E Interactions • Phase I: set α = 0.20 β = 0.90 z = 1.28 Screen in for 2nd stage all significant interactions, drop all non-significant ones Start up new study: set α = 0.05 β = 0.90 z = 1.96 Select all that are significant, drop others 20 Interactions: 5 are Non-Null, 15 Null How well does this procedure Find ANY Non-Null interaction? Find ALL Non-Null interactions? Find at least HALF the Non-Null interactions? Presentation to Center for Personalized Prevention Research

47. Good at picking up at least half Presentation to Center for Personalized Prevention Research

48. 4. Optimum Intervention: Deliver intervention to have broadest impact at a population level The best intervention won’t produce population impact if people won’t take it, isn’t delivered with fidelity, or sustained. Dissemination and Implementation Research Enrollment Trials Encouragement Trials Implementation Trials Roll-Out Dynamic Wait-Listed Trials NIH Summer Institute on Social and Behavioral Intervention Research

49. Glasgow, AJPM 2007 Example: Dissemination of eHealth Interventions To what extent did participants • log onto the website each week? • decrease their fast food consumption? Assessment • Automated measures of website engagement • participant self-monitoring. NIH Summer Institute on Social and Behavioral Intervention Research

50. Designs for Dissemination Who gets invited and who comes? — What percent of those invited participate? — What are the characteristics of participants? — What are barriers to patient participation in this context? NIH Summer Institute on Social and Behavioral Intervention Research