Annals of Behavioral Medicine

, Volume 35, Issue 1, pp 19–25 | Cite as

What Types of Evidence are Most Needed to Advance Behavioral Medicine?

Editorial

Abstract

Background

This editorial presents a perspective on the types of evidence most needed to advance behavioral medicine given the current status of the field.

Purpose

The paper argues that the types of evidence most needed at present are evidence that is contextual, practical, and robust.

Methods

Each of the above issues is discussed with attention to characteristics of interventions; representativeness at the multiple levels of setting, clinical staff, and participants; and research design and measures. Arguments are made from philosophy of science, status of the literature, and future directions perspectives.

Results

The current dominant paradigm of reductionistic studies focused predominantly on internal validity using highly homogenous patients and academic settings is not and will not produce the desired translation to real-world practice and policy. Instead, broader “practical” clinical and behavioral trials are needed that address the influence of the context in which programs are conducted, that include outcomes important to decision makers and communities, and that focus on moderating, mediating, and economic issues.

Conclusions

To create programs that will be disseminable, a greater focus is needed on external validity and transparency of reporting. We need to realize that the world is complex and embrace and study this complexity to produce further progress. Such an approach can produce evidence that is both rigorous and relevant.

Keywords

Research methods Design Dissemination Translation Effectiveness RCT 

References

  1. 1.
    Kuhn TS. The Structure of Scientific Revolutions. 2nd ed. Chicago: University of Chicago Press; 1962.Google Scholar
  2. 2.
    Biglan A. Changing Cultural Practices: A Contextualist Framework for Intervention Research. Reno, NV: Context Press; 1995.Google Scholar
  3. 3.
    Thomas P. Integrating Primary Health Care. Oxford, England: Radcliffe Publishing; 2006.Google Scholar
  4. 4.
    Gharajedaghi J. Systems Thinking: Managing Chaos and Complexity. 2nd ed. Boston: Elsevier; 2006.Google Scholar
  5. 5.
    McNulty T, Ferlie E. Reengineering Health Care: The Complexities of Organizational Transformation. Oxford, UK: Oxford University Press; 2002.Google Scholar
  6. 6.
    Shadish WR, Cook TD, Campbell DT. Experimental and Quasi-experimental Design for Generalized Causal Inference. Boston: Houghton Mifflin; 2002.Google Scholar
  7. 7.
    Glasgow RE, Magid DJ, Beck A, Ritzwoller D, Estabrooks PA. Practical clinical trials for translating research to practice Design and measurement recommendations. Med Care. 2005; 43(6): 551–557.PubMedCrossRefGoogle Scholar
  8. 8.
    Tunis SR, Stryer DB, Clancey CM. Practical clinical trials. Increasing the value of clinical research for decision making in clinical and health policy. J Am Med Assoc. 2003; 290: 1624–1632.CrossRefGoogle Scholar
  9. 9.
    Glasgow RE, Davidson KW, Dobkin PL, Ockene J, Spring B. Practical behavioral trials to advance evidence-based behavioral medicine. Ann Behav Med. 2006; 31(1): 5–13.PubMedCrossRefGoogle Scholar
  10. 10.
    Glasgow RE, Emmons KM. How can we increase translation of research into practice? Ann Rev Pub Health. 2007; 28(1): 413–433.CrossRefGoogle Scholar
  11. 11.
    Pawson R, Greenhalgh T, Harvey G, Walshe K. Realist review: A new method of systematic review designed for complex policy interventions. J Health Serv Res Pol. 2005; 10(S1): S21–S39.CrossRefGoogle Scholar
  12. 12.
    Paul GL. Behavior modification research: Design and tactics. In Franks CM, ed. Behavior Therapy: Appraisal and Status. New York: McGraw-Hill; 1969: 29–62.Google Scholar
  13. 13.
    Glass TA, McAtee MJ. Behavioral science at the crossroads in public health: Extending horizons, envisioning the future. Soc Sci Med. 2006; 62(7): 1650–1671.PubMedCrossRefGoogle Scholar
  14. 14.
    Stokols D. Social ecology and behavioral medicine: Implications for training, practice, and policy. Behav Med. 2000; 26: 129–138.PubMedCrossRefGoogle Scholar
  15. 15.
    Cohen J, Cohen P, West SG, Aiken LS. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. 3rd ed. London: Erlbaum; 2003.Google Scholar
  16. 16.
    Murray DM. Statistical models appropriate for designs often used in group-randomized trials. Stat Med. 2001;20(9–10): 1373–1385.PubMedCrossRefGoogle Scholar
  17. 17.
    Campbell M, Fitzpatrick R, Haines A, Kinmonth AL, Sandercock P, Spiegelhalter D, Tyrer P. Framework for design and evaluation of complex interventions to improve health. B Med J.. 2000; 321: 694–696.CrossRefGoogle Scholar
  18. 18.
    Goodman A. Storytelling as best practice: How stories strengthen your organization, engage your audience, and advance your mission. Andy Goodman; 2003.Google Scholar
  19. 19.
    Klesges LM, Dzewaltowski DA, Glasgow RE. Childhood obesity prevention: Reviewing the translation potential of intervention evidence. Am J Prev Med. 2008; in press.Google Scholar
  20. 20.
    Oldenburg B, Ffrench BF, Sallis JF. Health behavior research: The quality of the evidence base. Am J Health Promot. 2000; 14(4): 253–257.PubMedGoogle Scholar
  21. 21.
    Glasgow RE, Klesges LM, Dzewaltowski DA, Bull SS, Estabrooks P. The future of health behavior change research: What is needed to improve translation of research into health promotion practice? Ann Behav Med. 2004; 27(1): 3–12.PubMedCrossRefGoogle Scholar
  22. 22.
    Green LW, Glasgow RE. Evaluating the relevance, generalization, and applicability of research: Issues in external validity and translation methodology. Eval Health Prof. 2006; 29(1): 126–153.PubMedCrossRefGoogle Scholar
  23. 23.
    Glasgow RE, Green LW, Klesges LM, et al. External validity: We need to do more. Ann Behav Med. 2006; 31(2): 105–108.PubMedCrossRefGoogle Scholar
  24. 24.
    Holmes D, Murray S, Perron A, Rail G. Deconstructing the evidence-based discourse in health sciences: Truth, power and fascism. International Journal of Evidence-Based Healthcare. 2006; 4: 180–186.CrossRefGoogle Scholar
  25. 25.
    Mohrer D, Schulz KF, Altman DG, Lepage L. The CONSORT statement: Revised recommendations for improving the quality of reports. JAMA. 2001; 285: 1987–1991.CrossRefGoogle Scholar
  26. 26.
    Rothwell PM. External validity of randomised controlled trials: To whom do the results of this trial apply? Lancet. 2005; 365: 82–93.PubMedCrossRefGoogle Scholar
  27. 27.
    Glasgow RE, Green LW, Ammerman A. A focus on external validity. Eval Health Prof. 2007; 30(2): 115–117.CrossRefGoogle Scholar
  28. 28.
    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.PubMedCrossRefGoogle Scholar
  29. 29.
    Rotheram-Borus MJ, Flannery D, Duan N. Interventions that are CURRES: Cost-effective, useful, realistic, robust, evolving, and sustainable. In Rehmschmidt H, et al, eds., Facilitating Pathways: Care, Treatment, and Prevention in Child and Adolescent Health. New York: Springer; 2004; 235–244.Google Scholar
  30. 30.
    Goodman RM, McLeroy KR, Steckler A, Hoyle R. Development of level of institutionalization scales for health promotion programs. Health Ed Q. 1993; 20: 161–178.Google Scholar
  31. 31.
    Kaplan RM. The significance of quality of life in health care. Q Life Res. 2003; 12(Suppl 1): 3–16.CrossRefGoogle Scholar
  32. 32.
    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(8): 1261–1267.CrossRefGoogle Scholar
  33. 33.
    Berwick DM. A user’s manual for the IOM’s “Quality Chasm” report: Patients’ experience should be the fundamental source of the definition of “quality”. Health Aff. 2002; 21: 80–90.CrossRefGoogle Scholar
  34. 34.
    Institute of Medicine, Committee on Quality Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2003.Google Scholar
  35. 35.
    McGlynn EA. An evidence-based national quality measurement and reporting system. Med Care. 2003; 41(1 Supp): I8–I15.PubMedGoogle Scholar
  36. 36.
    Bandura A. Self-efficacy: The Exercise of Control. New York: W.H. Freeman; 1997.Google Scholar
  37. 37.
    Green LW, Ottosen JM. From efficacy to effectiveness to community and back: Evidence-based practice vs. practice-based evidence. Proceedings from conference: From Clinical Trials to Community: The Science of Translating Diabetes and Obesity Research. National Institutes of Diabetes, Digestive and Kidney Diseases; 2004.Google Scholar
  38. 38.
    Greenwald P, Cullen JW. The new emphasis in cancer control. J Natl Cancer Inst. 1985; 74(3): 543–551.PubMedGoogle Scholar
  39. 39.
    Flay BR. Efficacy and effectiveness trials (and other phases of research) in the development of health promotion programs. Prev Med. 1986; 15: 451–474.PubMedCrossRefGoogle Scholar
  40. 40.
    Stevens VJ, Glasgow RE, Hollis JF, Lichtenstein E, Vogt TM. A smoking cessation intervention for hospitalized patients. Med Care. 1993; 31: 65–72.PubMedCrossRefGoogle Scholar
  41. 41.
    Stevens VJ, Glasgow RE, Toobert DJ, Karanja N, Smith KS. One-year results from a brief, computer-assisted intervention to decrease consumption of fat and increase consumption of fruits and vegetables. Prev Med. 2003; 36(5): 594–600.PubMedCrossRefGoogle Scholar
  42. 42.
    Hallfors D, Cho H, Sanchez V, Khatapoush D, Kim HM, Bauer D. Efficacy vs. effectiveness trial results of an indicated “model” substance abuse program: Implications for public health. Am J Publ Health. 2006; 96(12): 2254–2259.CrossRefGoogle Scholar
  43. 43.
    Estabrooks PA, Glasgow RE. Dissemination, knowledge exchange, or knowledge integration: Explaining the gap between medical office-based physical activity intervention research and practice. Am J Pub Health. 2005; 31(4 Suppl): S45–S56.Google Scholar
  44. 44.
    Stange KC. One size doesn’t fit all. Multimethod research yields new insights into interventions to increase prevention in family practice. J Fam Pract. 1996; 43(4): 358–360.PubMedGoogle Scholar
  45. 45.
    Curry L, Shield R, Wetle T, eds. Improving Aging and Public Health Research: Qualitative and Mixed Methods. Washington, DC: Public Health Association; 2006.Google Scholar
  46. 46.
    Sterman J. All models are wrong: Reflections on becoming a systems scientist. Syst Dyn. 2002; 18: 501–531.CrossRefGoogle Scholar

Copyright information

© The Society of Behavioral Medicine 2008

Authors and Affiliations

  1. 1.Center for Dissemination and Implementation ResearchInstitute For Health Research, Kaiser Permanente ColoradoAuroraUSA
  2. 2.PenroseUSA

Personalised recommendations