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Exploring Refinements in Targeted Behavioral Medicine Intervention to Advance Public Health

  • Original Article
  • Published:
Annals of Behavioral Medicine

Abstract

Background

Similar to other fields, a targeted behavioral medicine perspective can aid decision-making related to participant–intervention matching.

Purpose

To present one potentially useful definition of intervention targeting activity; describe potential targeting domains of particular relevance to behavioral medicine; discuss different statistical approaches to aid the targeted intervention development process; and discuss the challenges and opportunities accompanying the incorporation of targeted intervention development methods into behavioral randomized clinical trial (RCT) research.

Methods

Drawing from recent conceptual work by the MacArthur group and other scientists in the field, methods and approaches to undertaking moderator analysis are discussed.

Results

Examples of moderator analyses are provided which reflect the different statistical methods and variable domains that may serve as moderators of intervention success.

Conclusions

The recommended exploratory work can help to make the most efficient use of RCTs to identify the best paths for subsequent RCT development in a resource-constrained era.

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References

  1. Office of Behavioral and Social Sciences Research. Healthier Lives through Behavioral and Social Sciences Research. Bethesda, MD: OBSSR, National Institutes of Health; 2006.

    Google Scholar 

  2. Ockene JK, Emmons KM, Mermelstein RJ, et al. Relapse and maintenance issues for smoking cessation. Health Psychol. 2000; 19: 17–31.

    Article  PubMed  Google Scholar 

  3. Haskell WL, Alderman EL, Fair JM, et al. Effects of intensive multiple risk factor reduction on coronary atherosclerosis and clinical cardiac events in men and women with coronary artery disease: The Stanford Coronary Risk Intervention Project (SCRIP). Circulation. 1994; 89: 975–990.

    PubMed  Google Scholar 

  4. Lorig KR, Mazonson PD, Holman HR. Evidence suggesting that health education for self-management in patients with chronic arthritis has sustained health benefits while reducing health costs. Arthritis Rheum. 1993; 36: 439–446.

    Article  PubMed  Google Scholar 

  5. Diabetes Prevention Program Research Group. Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin. New Engl J Med. 2002; 346: 393–403.

    Article  Google Scholar 

  6. Tuomilehto J, Lindstrom J, Eriksson JG, et al. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N Engl J Med. 2001; 344: 1343–1350.

    Article  PubMed  Google Scholar 

  7. Pan XR, Li GW, Hu YH, et al. Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study. Diabetes Care. 1997; 20: 537–544.

    Article  PubMed  Google Scholar 

  8. Durantini MR, Albarracin D, Mitchell AL, Earl AN, Gillette JC. Conceptualizing the influence of social agents of behavior change: A meta-analysis of the effectiveness of HIV-prevention interventionists for different groups. Psychol Bull. 2006; 132: 212–248.

    Article  PubMed  Google Scholar 

  9. Christensen AJ. Patient-by-treatment context interaction in chronic disease: A conceptual framework for the study of patient adherence. Psychosom Med. 2000; 62: 435–443.

    PubMed  Google Scholar 

  10. Evans WE, Relling MV. Moving towards individualized medicine with pharmacogenomics. Nature. 2004; 429: 464–468.

    Article  PubMed  Google Scholar 

  11. Owens EB, Hinshaw SP, Kraemer HC, Arnold LE, Abikoff HB, Cantwell DP, et al. Which treatment for whom for ADHD? Moderators of treatment response in the MTA. J Consult Clin Psychol. 2003; 71: 540–552.

    Article  PubMed  Google Scholar 

  12. Orleans TC, Gruman J, Ulmer C, Emont SL, Hollendonner JK. Rating our progress in population health promotion: Report card on six behaviors. Am J Health Promot. 1999; 14: 75–82.

    PubMed  Google Scholar 

  13. Campbell MK, Tessar O, DeVellis B, et al. Effects of a tailored health promotion program for female blue-collar workers: Health works for women. Prev Med. 2002; 34: 313–323.

    Article  PubMed  Google Scholar 

  14. King AC, Bauman A, Calfas K. Innovative approaches to understanding and influencing physical activity. Am J Prev Med. 2002; 232 Suppl: 56–63.

    Google Scholar 

  15. Mattson ME, Allen JP. Research on matching alcoholic patients to treatments: Findings, issues, and implications. J Addict Dis. 1991; 11: 33–49.

    Article  PubMed  Google Scholar 

  16. Kent D, Hayward R. When averages hide individual differences in clinical trials. Am Sci. 2007; 95: 60–68.

    Google Scholar 

  17. Kraemer HC, Wilson GT, Fairburn CG, Agras WS. Mediators and moderators of treatment effects in randomized clinical trials. Arch Gen Psychiatry. 2002; 59: 887–883.

    Article  Google Scholar 

  18. Zerhouni EA. NIH in the postdoubling era: Realities and strategies for the future. In: NIMH Council Meeting; September; Bethesda, MD; 2006.

  19. Murphy GM Jr., Hollander SB, Rodrigues C, Krema C, Schatzberg AF. Effects of the serotonic transporter gene promoter polymorphism on mirtazapine and paroxetine efficacy and adverse events in geriatric major depression. Arch Gen Psychiatry. 2004; 61: 1163–1169.

    Article  PubMed  Google Scholar 

  20. Rothwell PM. Treating individuals 1: External validity of randomised controlled trials: “To whom do the results of this trial apply?”. The Lancet. 2005; 365: 82–93.

    Article  Google Scholar 

  21. Kraemer HC, Frank E, Kupfer DJ. Moderators of treatment outcomes: Clinical, research, and policy importance. JAMA. 2006; 296: 1286–1289.

    Article  PubMed  Google Scholar 

  22. Napolitano MA, Marcus BH. Targeting and tailoring physical activity information using print and information technologies. Exerc Sport Sci Rev. 2002; 30: 122–128.

    Article  PubMed  Google Scholar 

  23. Moyer A, Finney JW, Elworth JT, Kraemer HC. Can methodological features account for patient–treatment matching findings in the alcohol field? J Stud Alcohol. 2001; 62: 62–73.

    PubMed  Google Scholar 

  24. Skinner HA. Different strokes for different folks: Differential treatment for alcohol abuse. In: Meyer RE, Babor TF, Glueck BC, Jaffe JH, O’Brien JE, Stabenau JR, eds. Evaluation of the Alcoholic: Implications for Research, Theory, and Treatment. Washington, DC: Government Printing Office; 1981: 349–367.

    Google Scholar 

  25. Marcus BH, Bock BC, Pinto BM, Forsyth LH, Roberts MB, Traficante RM. Efficacy of an individualized, motivationally-tailored physical activity intervention. Ann Behav Med. 1998; 20: 174–180.

    Article  PubMed  Google Scholar 

  26. Strecher VJ, Marcus A, Bishop K, et al. A randomized controlled trial of multiple tailored messages for smoking cessation among callers to the Cancer Information Service. J Health Commun. 2005; 10: 105–118.

    Article  PubMed  Google Scholar 

  27. Killen JD, Fortmann SP, Kraemer HC, Varady A, Newman B. Who will relapse? Symptoms of nicotine dependence predict long-term relapse after smoking cessation. J Consult Clin Psychol. 1992; 60: 797–801.

    Article  PubMed  Google Scholar 

  28. Winkleby MA, Flora JA, Kraemer HC. A community-based heart disease intervention: Predictors of change. Am J Publ Health. 1994; 84: 767–772.

    Google Scholar 

  29. King AC, Satariano W, Marti J, Zhu W. Multi-level modeling of walking behavior: Advances in understanding the interactions of people, place, and time. Med Sci Sports Exerc, 2008;in press.

  30. Wilcox S, Dowda M, Griffin SF, et al. Results of the first year of Active for Life: Translation of two evidence-based physical activity programs for older adults into community settings. Am J Publ Health. 2006; 96: 1201–1209.

    Article  Google Scholar 

  31. King AC, Castro C, Wilcox S. From science to practice and back again: Predictors of successful physical activity participation in a telephone-based dissemination research program. Int J Behav Nutr Phys Act. 2008;5(abstract).

  32. Castro FG, Barrera M Jr, Martinez CR Jr. The cultural adaptation of prevention interventions: Resolving tensions between fidelity and fit. Prev Sci. 2004; 5: 41–45.

    Article  PubMed  Google Scholar 

  33. Munoz RF, Mendelson T. Toward evidence-base interventions for diverse populations: The San Francisco General Hospital Prevention and Treatment Manuals. J Consult Clin Psychol. 2005; 73: 790–799.

    Article  PubMed  Google Scholar 

  34. Behrens JT. Principles and procedures of exploratory data analysis. Psychol Methods. 1997; 2: 131–160.

    Article  Google Scholar 

  35. Greenhouse JB, Greenhouse JBW. Exploratory statistical methods, with applications to psychiatric research. Psychoneuroendocrinology. 1992; 17: 423–441.

    Article  PubMed  Google Scholar 

  36. Tukey J. Exploratory Data Analysis. Reading, MA: Addison-Wesley; 1977.

    Google Scholar 

  37. Wilkinson L, The Task Force on Statistical Inference of the APA Board of Scientific Affairs. Statistical methods in psychology journals: Guidelines and explanations. Am Psychol. 1999; 54: 594–604.

    Article  Google Scholar 

  38. Wang R, Lagakos SW, Ware JH, Hunter DJ, Drazen JM. Statistics in medicine—Reporting of subgroup analyses in clinical trials. N Engl J Med. 2007; 357: 2189–2194.

    Article  PubMed  Google Scholar 

  39. King AC, Kiernan M, Oman RF, Kraemer HC, Hull M, Ahn D. Can we identify who will adhere to long-term physical activity? Application of signal detection methodology as a potential aid to clinical decision-making. Health Psychol. 1997; 16: 380–389.

    Article  PubMed  Google Scholar 

  40. Schneiderman N, Saab PG, Catellier DJ, et al. Psychosocial treatment within sex by ethnicity subgroups in the Enhancing Recovery in Coronary Heart Disease clinical trial. Psychosom Med. 2004; 66: 475–483.

    Article  PubMed  Google Scholar 

  41. King AC, Stokols D, Talen E, Brassington GS, Killingsworth R. Theoretical approaches to the promotion of physical activity: Forging a transdisciplinary paradigm. Am J Prev Med. 2002; 232S: 15–25.

    Article  PubMed  Google Scholar 

  42. Kraemer HC, Stice E, Kazdin A, Offord D, Kupfer D. How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. Am J Psychiatr. 2001; 158: 848–856.

    PubMed  Google Scholar 

  43. King AC, Marcus BH, Dunn AL, et al. Identifying subgroups who succeed or fail with three physical activity interventions: The Activity Counseling Trial. Health Psychol. 2006; 25: 336–347.

    Article  PubMed  Google Scholar 

  44. Kiernan M, King AC, Stefanick M, Kraemer HC. Characteristics of successful and unsuccessful dieters: An application of signal detection methodology. Ann Behav Med. 1998; 20: 1–6.

    Article  PubMed  Google Scholar 

  45. Berry DA, Cirrincione C, Henderson IC, et al. Estrogen-receptor status and outcomes of modern chemotherapy for patients with node-positive breast cancer. JAMA. 2006; 295: 1658–1667.

    Article  PubMed  Google Scholar 

  46. Killen JD, Fortmann SP, Davis L, Strausberg L, Varady A. Do heavy smokers benefit from higher dose nicotine patch therapy? Exp Clin Psychopharmacol. 1999; 7: 226–233.

    Article  PubMed  Google Scholar 

  47. Pittas AG, Das SK, Hajduk CL, et al. A low-glycemic load diet facilitates greater weight loss in overweight adults with high insulin secretion but not in overweight adults with low insulin secretion in the CALERIE Trial. Diabetes Care. 2005; 28: 2939–2941.

    Article  PubMed  Google Scholar 

  48. Ebbeling CB, Leidig MM, Feldman HA, Lovesky MM, Ludwig DS. Effects of a low-glycemic load vs low-fat diet in obese young adults: A randomized trial. JAMA. 2007; 297: 2092–2102.

    Article  PubMed  Google Scholar 

  49. Cornier MA, Donahoo WT, Pereira R, et al. Insulin sensitivity determines the effectiveness of dietary macronutrient composition on weight loss in obese women. Obes Res. 2005; 13: 703–709.

    Article  PubMed  Google Scholar 

  50. Sallis JF, Owen N. In: Glanz K, Rimer BK, Lewis FM, eds. Health Behavior and Health Education: Theory, Research, and Practice. Ecological models of health behavior. 3rd ed. San Francisco: Jossey-Bass; 2002: 462–484.

    Google Scholar 

  51. Murphy SA. An experimental design for the development of adaptive treatment strategies. Stat Med. 2005; 24: 1455–1481.

    Article  PubMed  Google Scholar 

  52. Collins LM, Murphy SA, Nair VN, Strecher VJ. A strategy for optimizing and evaluating behavioral interventions. Ann Behav Med. 2005; 30: 65–73.

    Article  PubMed  Google Scholar 

  53. Insel TR. Beyond efficacy: The STAR*D trial. Am J Psychiatry. 2006; 163: 5–7.

    Article  PubMed  Google Scholar 

  54. Rush AJ, Trivedi M, Fava M. Depression, IV: STAR*D treatment trial for depression. Am J Psychiatry. 2003; 160: 237–245.

    Article  PubMed  Google Scholar 

  55. Trivedi MH, Fava M, Wisniewski SR, et al. Medication augmentation after the failure of SSRIs for depression. N Engl J Med. 2006; 354: 1243–1252.

    Article  PubMed  Google Scholar 

  56. Killen JD, Fortmann SP, Kraemer HC, Varady AN, Davis L, Newman B. Interactive effects of depression symptoms, nicotine dependence, and weight change on late smoking relapse. J Consult Clin Psychol. 1996; 64: 1060–1067.

    Article  PubMed  Google Scholar 

  57. Biddle SJH, Nigg CR. Theories of exercise behavior. Int J Sport Psychol. 2000; 31: 290–304.

    Google Scholar 

  58. King AC, Friedman R, Marcus B, et al. Harnessing motivational forces in the promotion of physical activity: The Community Health Advice by Telephone (CHAT) Project. Health Educ Res. 2002; 17: 627–636.

    Article  PubMed  Google Scholar 

  59. Williams GG, Gagne M, Ryan RM, Deci EL. Facilitating autonomous motivation for smoking cessation. Health Psychol. 2002; 21: 40–50.

    Article  PubMed  Google Scholar 

  60. Efron B. The efficiency of logistic regression compared to normal discriminant. J Am Stat Assoc. 1975; 70: 892–898.

    Article  Google Scholar 

  61. Kiernan M, Kraemer HC, Winkleby MA, King AC, Taylor CB. Do logistic regression and signal detection identify different subgroups at risk? Implications for the design of tailored interventions. Psychol Methods. 2001; 6: 35–48.

    Article  PubMed  Google Scholar 

  62. Kraemer HC. Evaluating Medical Tests: Objective and Quantitative Guidelines. Newbury Park, CA: Sage; 1992.

    Google Scholar 

  63. King AC, Toobert D, Ahn D, et al. Perceived environments as physical activity correlates and moderators of interventions in five studies. Am J Health Promot. 2006; 21: 24–35.

    PubMed  Google Scholar 

  64. Kraemer HC. Toward non-parametric and clinically meaningful moderators and mediators. Stat Med. 2007; 27(10): 1679–1692.

    Google Scholar 

  65. Cook RJ, Sackett DL. The number needed to treat: A clinically useful measure of treatment effect. Br Med J. 1995; 310: 452–454.

    Google Scholar 

  66. Grissom RJ, Kim JJ. Effect Sizes for Research. Mahwah, NJ: Erlbaum; 2005.

    Google Scholar 

  67. King AC, Haskell WL, Taylor CB, Kraemer HC, DeBusk RF. Group- versus home-based exercise training in healthy older men and women: A community-based clinical trial. JAMA. 1991; 266: 1535–1542.

    Article  PubMed  Google Scholar 

  68. Gaudard M, Ramsey P, Stephens M. Interactive data mining and design of experiments: The JMP partition and custom design platforms. In: JMP version 5.1.2 (SAS). Cary, NC: SAS; 2006.

  69. Lemon SC, Roy J, Clark MA, Friedmann PD, Rakowski W. Classification and regression tree analysis in public health: Methodological review and comparison with logistic regression. Ann Behav Med. 2003; 26: 172–181.

    Article  PubMed  Google Scholar 

  70. Kraemer HC. Assessment of 2 X 2 association: Generalization of signal detection methods. Am Stat. 1988; 42: 37–49.

    Article  Google Scholar 

  71. Glasgow RE, Lichtenstein E, Marcus AC. Why don’t we see more translation of health promotion research to practice? Rethinking the efficacy-to-effectiveness transition. Am J Publ Health. 2003; 93: 1261–1267.

    Google Scholar 

  72. Davidson KW, Goldstein M, Kaplan RM, et al. Evidence-based behavioral medicine: What is it and how do we achieve it? Ann Behav Med. 2003; 26: 161–171.

    Article  PubMed  Google Scholar 

  73. Rosen L, Manor O, Engelhard D, Zucker D. In defense of the randomized controlled trial for health promotion research. Am J Publ Health. 2006; 96: 1181–1186.

    Article  Google Scholar 

  74. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: The RE-AIM framework. Am J Publ Health. 1999; 89: 1322–1327.

    Article  Google Scholar 

  75. Atienza AA, Yaroch AL, Masse LC, Moser RP, Hesse BW, King AC. Identifying sedentary subgroups: The National Cancer Institute’s Health Information National Trends Survey. Am J Prev Med. 2006; 31: 383–390.

    Article  PubMed  Google Scholar 

  76. Pickering TG, Shimbo D, Haas D. Ambulatory blood pressure monitoring. New Engl J Med. 2006; 354: 2368–2374.

    Article  PubMed  Google Scholar 

  77. Pence C, McErlane K. Anticoagulation self-monitoring. Am J Nurs. 2005; 105: 62–65.

    PubMed  Google Scholar 

  78. Harris ND, Baykouchev SB, Marques JL, et al. A portable system for monitoring physiological responses to hypoglycaemia. J Med Eng Technol. 1996; 20: 196–202.

    Article  PubMed  Google Scholar 

  79. Patrick K, Intille SS, Zabinsky MF. An ecological framework for cancer communication: Implications for research. J Med Internet Res. 2005; 7: 1–7.

    Article  Google Scholar 

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Acknowledgments

This work was funded in part by Public Health Service Grant #R01AG021010 from the National Institute on Aging awarded to Dr. King. The views expressed in this paper represent those of the authors and not of the National Cancer Institute.

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Correspondence to Abby C. King Ph.D..

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King, A.C., Ahn, D.F., Atienza, A.A. et al. Exploring Refinements in Targeted Behavioral Medicine Intervention to Advance Public Health. ann. behav. med. 35, 251–260 (2008). https://doi.org/10.1007/s12160-008-9032-0

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  • DOI: https://doi.org/10.1007/s12160-008-9032-0

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