Skip to main content
Log in

Prioritizing multiple health behavior change research topics: expert opinions in behavior change science

  • Original Research
  • Published:
Translational Behavioral Medicine

Abstract

Multiple health behavior change (MHBC) approaches are understudied. The purpose of this study is to provide strategic MHBC research direction. This cross-sectional study contacted participants through the Society of Behavioral Medicine email listservs and rated the importance of 24 MHBC research topics (1 = not at all important, 5 = extremely important) separately for general and underserved populations. Participants (n = 76) were 79 % female; 76 % White, 10 % Asian, 8 % African American, 5 % Hispanic, and 1 % Native Hawaiian/Pacific Islander. Top MHBC research priorities were predictors of behavior change and the sustainability, long-term effects, and dissemination/translation of interventions for both populations. Recruitment and retention of participants (t(68) = 2.17, p = 0.000), multi-behavioral indices (t(68) = 3.54, p = 0.001), and measurement burden (t(67) = 5.04, p = 0.001) were important for the underserved. Results identified the same top research priorities across populations. For the underserved, research should emphasize recruitment, retention, and measurement burden.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. US Department of Health and Human Services. Healthy People 2010: Conference Edition. Washington: DCUS Government Printing Office; 2000.

  2. Public Health Agency of Canada. Preventing disease: a vital Investment: WHO global report. Geneva, Switzerland: World Health Organization, 2005. Available at http://www.who.int/chp/chronic_disease_report/en/. Accessibility verified June, 24 2013.

  3. Centers for Disease Control and Prevention. Prevalence of self-reported physically active adults--United States, 2007. MMWR Morb Mortal Wkly Rep. 2008; 57:1297–1300.

  4. Centers for Disease Control and Prevention. BRFSS prevalence and trends data. Available at http://apps.nccd.cdc.gov/brfss/page.asp?cat=AC&yr=2007&state=US-AC. Accessibility verified June, 24 2013.

  5. National Center for Health Statistics. Health, United States, 2007: With chartbook on trends in the health of Americans. Hyattsville, MD: National Center for Health Statistics, 2007. Available at http://www.cdc.gov/nchs/data/hus/hus07.pdf. Accessibility verified June, 24 2013.

  6. Naimi TS, Brewer RD, Miller JW, Okoro C, Mehrotra C. What do binge drinkers drink? Implications for alcohol control policy. Am J Prev Med. 2007; 33: 188-193.

    Article  PubMed  Google Scholar 

  7. Ottevaere C, Huybrechts I, Benser J, et al. Clustering patterns of physical activity, sedentary and dietary behavior among European adolescents: The HELENA study. BMC Public Health. 2011; 11: 328.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kremers SPJ, De Bruijn GJ, Schaalma H, Brug J. Clustering of energy balance-related behaviours and their intrapersonal determinants. Psychol Health. 2004; 19: 595-606.

    Article  Google Scholar 

  9. de Vries H, van ’t Riet J, Spigt M, et al. Clusters of lifestyle behaviors: results from the Dutch SMILE study. Prev Med. 2008; 46: 203-208.

    Article  PubMed  Google Scholar 

  10. Cameron AJ, Crawford DA, Salmon J, et al. Clustering of obesity-related risk behaviors in children and their mothers. Ann Epidemiol. 2011; 21: 95-102.

    Article  PubMed  Google Scholar 

  11. Bao W, Srinivasan SR, Wattigney WA, Berenson GS. Persistence of multiple cardiovascular risk clustering related to syndrome X from childhood to young adulthood. The Bogalusa Heart Study. Arch Intern Med. 1994; 154: 1842-1847.

    Article  CAS  PubMed  Google Scholar 

  12. Pronk NP, Anderson LH, Crain AL, et al. Meeting recommendations for multiple healthy lifestyle factors—prevalence, clustering, and predictors among adolescent, adult, and senior health plan members. Am J Prev Med. 2004; 27: 25-33.

    Article  PubMed  Google Scholar 

  13. Abegunde D, Mathers C, Adam T, Ortegon M, Strong K. The burden and costs of chronic diseases in low-income and middle-income countries. Lancet. 2007; 370: 1929-1938.

    Article  PubMed  Google Scholar 

  14. Edington DW, Yen LT, Witting P. The financial impact of changes in personal health practices. J Occup Environ Med. 1997; 39: 1037-1046.

    Article  CAS  PubMed  Google Scholar 

  15. Prochaska JJ, Nigg CR, Spring B, Velicer WF, Prochaska JO. The benefits and challenges of multiple health behavior change in research and in practice. Prev Med. 2010; 50: 26-29.

    Article  PubMed  Google Scholar 

  16. Trust for America’s Health. Prevention for a healthier America: investments in disease prevention yield significant savings, stronger communities. 2008. Washington, D.C. Available at http://healthyamericans.org/reports/prevention08/Prevention08.pdf. Accessibility verified June, 24 2013.

  17. Danaei G, Ding EL, Mozaffarian D, et al. The preventable causes of death in the United States: comparative risk assessment of dietary, lifestyle, and metabolic risk factors. PLoS Med. 2009; 6: e1000058.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Tsai J, Ford ES, Li C, et al. Multiple healthy behaviors and optimal self-rated health: findings from the Behavioral Risk Factor Surveillance System Survey. Prev Med. 2007; 2010(51): 268-274.

    Google Scholar 

  19. Harrington J, Perry IJ, Lutomski J, et al. Living longer and feeling better: healthy lifestyle, self-rated health, obesity and depression in Ireland. Eur J Pub Health. 2010; 20: 91-95.

    Article  Google Scholar 

  20. Spencer CA, Jamrozik K, Norman PE, Lawrence-Brown M. A simple lifestyle score predicts survival in healthy elderly men. Prev Med. 2005; 40: 712-717.

    Article  PubMed  Google Scholar 

  21. Willcox BJ, He Q, Chen R, et al. Midlife risk factors and healthy survival in men. JAMA. 2006; 296: 2343-2350.

    Article  CAS  PubMed  Google Scholar 

  22. Sarkeala T, Heinavaara S, Anttila A. Breast cancer mortality with varying invitational policies in organised mammography. Br J Cancer. 2008; 98: 641-645.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Lobelo F, Pate R, Parra D, Duperly J, Pratt M. Burden of mortality associated to physical inactivity in Bogota, Colombia. Rev Salud Publica (Bogota). 2006; 8(Suppl 2): 28-41.

    Article  Google Scholar 

  24. Williams AE, Vogt TM, Stevens VJ, et al. Work, weight, and wellness: the 3W Program: a worksite obesity prevention and intervention trial. Obesity. 2007; 15(Suppl 1): 16S-26S.

    Article  PubMed  Google Scholar 

  25. Toobert DJ, Glasgow RE, Strycker LA, et al. Long-term effects of the Mediterranean lifestyle program: a randomized clinical trial for postmenopausal women with type 2 diabetes. Int J Behav Nutr Phys Act. 2007; 4: 1.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Prochaska JO, Velicer WF, Redding C, et al. Stage-based expert systems to guide a population of primary care patients to quit smoking, eat healthier, prevent skin cancer, and receive regular mammograms. Prev Med. 2005; 41: 406-416.

    Article  PubMed  Google Scholar 

  27. Emmons KM, Marcus BH, Linnan L, Rossi JS, Abrams DB. Mechanisms in multiple risk factor interventions: smoking, physical activity, and dietary fat intake among manufacturing workers. Working Well Research Group. Prev Med. 1994; 23: 481-489.

    Article  CAS  PubMed  Google Scholar 

  28. Emmons KM, McBride CM, Puleo E, et al. Project PREVENT: a randomized trial to reduce multiple behavioral risk factors for colon cancer. Cancer Epidemiol Biomarkers Prev. 2005; 14: 1453-1459.

    Article  PubMed  Google Scholar 

  29. Prochaska JJ, Spring B, Nigg CR. Multiple health behavior change research: an introduction and overview. Prev Med. 2008; 46: 181-188.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Noar SM, Mehrotra P. Toward a new methodological paradigm for testing theories of health behavior and health behavior change. Patient Educ Couns. 2011; 82: 468-474.

    Article  PubMed  Google Scholar 

  31. Nigg CR, Allegrante JP, Ory M. Theory-comparison and multiple-behavior research: common themes advancing health behavior research. Health Educ Res. 2002; 17: 670-679.

    Article  PubMed  Google Scholar 

  32. Prochaska JJ, Velicer WF, Nigg CR, Prochaska JO. Methods of quantifying change in multiple risk factor interventions. Prev Med. 2008; 46: 260-265.

    Article  PubMed  Google Scholar 

  33. Prochaska JJ, Sallis JF. A randomized controlled trial of single versus multiple health behavior change: promoting physical activity and nutrition among adolescents. Health Psychol. 2004; 23: 314-318.

    Article  PubMed  Google Scholar 

  34. Prochaska JJ, Prochaska JO. A review of multiple health behavior change interventions for primary prevention. Am J Lifestyle Med. 2011; 5: 208-221.

    Article  Google Scholar 

  35. Prochaska JO. Multiple health behavior research represents the future of preventive medicine. Prev Med. 2008; 46: 281-285.

    Article  PubMed  Google Scholar 

  36. Evers KE, Quintiliani LM. Advances in multiple health behavior change research. Transl Behav Med. 2013; 3: 59-61.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. 1999; 89(9): 1322-1327.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Gaglio B, Shoup JA, Glasgow RE. The RE-AIM framework: a systematic review of use over time. Am J Public Health. 2013; 103: e38-e46.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Noar SM, Chabot M, Zimmerman RS. Applying health behavior theory to multiple behavior change: considerations and approaches. Prev Med. 2008; 46: 275-280.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

The authors would like to thank the participants for their contributions, Dr. Angela Sy for her guidance, and the Health Behavior Change Research Workgroup for their contribution.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Claudio R. Nigg.

Ethics declarations

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Implications

Practice: Specifically for underserved populations, MHBC practitioners need to creatively address and improve recruitment and retention of participants, consider and minimize measurement burden, and relatedly implement MHBC indices to track progress.

Policy: Policy makers should use these results toward devoting resources and developing policies that address participant recruitment and retention, measurement burden, and creation and standardization of multi-behavioral indices.

Research: MHBC research should focus on measuring predictors of behavior change, improving sustainability, dissemination/translation of MHBC interventions and addressing the long-term effects.

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Amato, K., Park, E. & Nigg, C.R. Prioritizing multiple health behavior change research topics: expert opinions in behavior change science. Behav. Med. Pract. Policy Res. 6, 220–227 (2016). https://doi.org/10.1007/s13142-015-0381-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13142-015-0381-5

Keywords

Navigation