Journal of General Internal Medicine

, Volume 25, Issue 12, pp 1315–1322 | Cite as

Outcomes of Minimal and Moderate Support Versions of an Internet-Based Diabetes Self-Management Support Program

  • Russell E. Glasgow
  • Deanna Kurz
  • Diane King
  • Jennifer M. Dickman
  • Andrew J. Faber
  • Eve Halterman
  • Tim Wooley
  • Deborah J. Toobert
  • Lisa A. Strycker
  • Paul A. Estabrooks
  • Diego Osuna
  • Debra Ritzwoller
Original Research

Abstract

OBJECTIVE

Internet and other interactive technology-based programs offer great potential for practical, effective, and cost-efficient diabetes self-management (DSM) programs capable of reaching large numbers of patients. This study evaluated minimal and moderate support versions of an Internet-based diabetes self-management program, compared to an enhanced usual care condition.

RESEARCH DESIGN AND METHODS

A three-arm practical randomized trial was conducted to evaluate minimal contact and moderate contact versions of an Internet-based diabetes self-management program, offered in English and Spanish, compared to enhanced usual care. A heterogeneous sample of 463 type 2 patients was randomized and 82.5% completed a 4-month follow-up. Primary outcomes were behavior changes in healthy eating, physical activity, and medication taking. Secondary outcomes included hemoglobin A1c, body mass index, lipids, and blood pressure.

RESULTS

The Internet-based intervention produced significantly greater improvements than the enhanced usual care condition on three of four behavioral outcomes (effect sizes [d] for healthy eating = 0.32; fat intake = 0.28; physical activity= 0.19) in both intent-to-treat and complete-cases analyses. These changes did not translate into differential improvements in biological outcomes during the 4-month study period. Added contact did not further enhance outcomes beyond the minimal contact intervention.

CONCLUSIONS

The Internet intervention meets several of the RE-AIM criteria for potential public health impact, including reaching a large number of persons, and being practical, feasible, and engaging for participants, but with mixed effectiveness in improving outcomes, and consistent results across different subgroups. Additional research is needed to evaluate longer-term outcomes, enhance effectiveness and cost-effectiveness, and understand the linkages between intervention processes and outcomes.

KEY WORDS

internet diabetes self-management RCT health disparities behavior change practical trial 

Supplementary material

11606_2010_1480_MOESM1_ESM.doc (143 kb)
Table A1Track My Progress (DOC 143 kb)
11606_2010_1480_MOESM2_ESM.doc (158 kb)
Table A2Your Food Choices Action Plan (DOC 158 kb)

References

  1. 1.
    Fisher EB, Brownson CA, O'Toole ML, et al. Ecological approaches to self-management: The case of diabetes. Am J Public Health. 2005;95:1523–35.CrossRefPubMedGoogle Scholar
  2. 2.
    Sallis JF, Owen N, Fisher EB. Ecological models of health behavior. In: Glanz K, Rimer BK, Viswanath K, eds. Health behavior and health education. San Francisco: Jossey-Bass; 2008:465–86.Google Scholar
  3. 3.
    Department of Health and Human Services, Centers for Disease Control and Prevention. National Diabetes Fact Sheet. Available at: http://www.cdc.gov/diabetes/pubs/factsheet07.htm. Accessed 07-22-10.
  4. 4.
    Deakin T, McShane CE, Cade JE et al. Group based training for self-management strategies in people with type 2 diabetes mellitus. Cochrane Database Syst Rev. 2005;April 18:CD003417.Google Scholar
  5. 5.
    Lavizzo-Mourey R, Jung M. Fighting unequal treatment: The Robert Wood Johnson Foundation and a quality-improvement approach to disparities. Circulation. 2005;111:1208–9.CrossRefPubMedGoogle Scholar
  6. 6.
    Glasgow RE, Bull SS, Piette JD, et al. Interactive behavior change technology: A partial solution to the competing demands of primary care. Am J Prev Med. 2004;27(25):80–7.CrossRefPubMedGoogle Scholar
  7. 7.
    Piette J. Enhancing support via interactive technologies. Curr Diab Rep. 2002;2:160–5.CrossRefPubMedGoogle Scholar
  8. 8.
    Bull SS, McKay HG, Gaglio B, et al. Harnessing the potential of the Internet to promote diabetes self-management: How well are we doing? Chronic Illn. 2005;1(2):143–55.PubMedGoogle Scholar
  9. 9.
    Tate DF, Jackvony EH, Wing RR. Effects of Internet behavioral counseling on weight loss in adults at risk for type 2 diabetes: A randomized trial. JAMA. 2003;289(14):1833-1836; PMID 12684363.Google Scholar
  10. 10.
    Strecher V. Internet methods for delivering behavioral and health-related interventions (eHealth). Annu Rev Clin Psychol. 2007;3:53–76.CrossRefPubMedGoogle Scholar
  11. 11.
    Goldstein MG, Whitlock EP, DePue J. Multiple health risk behavior interventions in primary care: Summary of research evidence. Am J Prev Med. 2004;27(2 Suppl):61-79; PMID 15275675.Google Scholar
  12. 12.
    Prochaska JJ, Spring B, Nigg CR. Multiple health behavior change research: An introduction and overview. Prev Med. 2008;46:181–8.CrossRefPubMedGoogle Scholar
  13. 13.
    Peña-Purcell N. Hispanics' use of Internet health information: An exploratory study. J Med Libr Assoc. 2008;96:101–7.CrossRefPubMedGoogle Scholar
  14. 14.
    Latino Issues Forum. Latinos, computers and the Internet: How congress and the current administration's framing of the Digital Divide has negatively impacted policy initiatives established to lose the significant technology gap the remains. 2004. Berkeley, Ca.Google Scholar
  15. 15.
    Leeman-Castillo B, Beaty B, Raghunath S, et al. LUCHAR: using computer technology to battle heart disease among Latinos. Am J Public Health. 2010;100(2):272–5.CrossRefPubMedGoogle Scholar
  16. 16.
    Norris SL, Engelgau MM, Narayan KM. Effectiveness of self-management training in type 2 diabetes: Systematic review of randomized controlled trials. Diabetes Care. 2001;24(3):561–87.CrossRefPubMedGoogle Scholar
  17. 17.
    Glasgow RE, Edwards LL, Whitesides H et al. Reach and effectiveness of DVD and in-person diabetes self-management education. Chronic Illness. 2009;5:243-249; PMID 19933245.Google Scholar
  18. 18.
    Thoolen B, de Ridder D, Bensing J et al. Who participates in diabetes self-management interventions? Issues of recruitment and retention. Diabetes Educ. 2007;May/Jun;33:465-474; PMID 17570877.Google Scholar
  19. 19.
    Glasgow RE, Linnan LA. Evaluation of theory-based interventions. In: Glanz K, Rimer BK, Viswanath K, eds. Health Behavior and Health Education: Theory, Research, and Practice. San Francisco, CA: Jossey-Bass; 2008:487–508.Google Scholar
  20. 20.
    Welch G, Shayne R. Interactive behavioral technologies and diabetes self-management support: Recent research findings from clinical trials. Curr Diab Rep. 2006;6:130-136; PMID 16542624.Google Scholar
  21. 21.
    Boren SA, Gunlock TL, Krishna S. et al. Computer-aided diabetes education: A synthesis of randomized controlled trials. AMIA Symposium Proceedings; 2006.Google Scholar
  22. 22.
    Eysenbach G. The law of attrition. J Med Internet Res. 2005;7(1):e11; PMID 15829473.Google Scholar
  23. 23.
    Tunis SR, Stryer DB, Clancey CM. Practical clinical trials: Increasing the value of clinical research for decision making in clinical and health policy. JAMA. 2003;290:1624-1632; PMID 14506122.Google Scholar
  24. 24.
    Thorpe KE, Zwarenstein M, Oxman AD, et al. A pragmatic-explanatory continuum indicator summary (PRECIS): a tool to help trial designers. CMAJ. 2009;180(10):E47–57.PubMedGoogle Scholar
  25. 25.
    Glasgow RE, Strycker LA, Kurz D et al. Recruitment for an Internet-based diabetes self-management program: Scientific and ethical implications. Ann Behav Med. 2010;Apr 22 (epub ahead of print). PMID: 20411443.Google Scholar
  26. 26.
    Glasgow RE, Nutting PA, King DK et al. A practical randomized trial to improve diabetes care. J Gen Intern Med. 2004;19(12):1167-1174; PMID 15610326.Google Scholar
  27. 27.
    Glasgow RE, Christiansen S, Kurz D, et al. Engagement in a diabetes self-management website: Usage patterns and generalizability of program use. J Internet Med Res . 2010. In PressGoogle Scholar
  28. 28.
    Nezu AM. Problem-solving and behavior therapy revisited. Behav Ther. 2004;35:1–33.CrossRefGoogle Scholar
  29. 29.
    Lorig K, Holman H, Sobel Det al. Living a healthy life with chronic conditions. Palo Alto, CA: Bull Publishing; 2000.Google Scholar
  30. 30.
    Bandura A. Self-efficacy: The exercise of control. New York: W.H. Freeman; 1997.Google Scholar
  31. 31.
    Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health literacy. Fam Med. 2004;36(8):588–94.PubMedGoogle Scholar
  32. 32.
    Ammerman A. Starting the conversation-diet. Instrument developed by University of North Carolina in conjunction with NC Prevention Partners, and Heart Disease and Stroke Prevention Branch, NC DHHS. 2004. Personal CommunicationGoogle Scholar
  33. 33.
    Fernald DH, Froshang DB, Dickinson LM et al. Common measures, better outcomes (COMBO): A field test of brief health behavior measures in primary care. Amer J Prev Med. 2008;35(5S):S414-422.Google Scholar
  34. 34.
    Thompson FE, Kipnis V, Subar AF, et al. Performance of a short instrument to estimate usual dietary intake of percent calories from fat. Euro J Clin Nutr. 1998;52:S63.Google Scholar
  35. 35.
    Stewart AL, Mills KM, King AC et al. CHAMPS physical activity questionnaire for older adults: Outcomes for interventions. Med Sci Sports Exerc. 2001;33(7):1126-1141; PMID 11445760.Google Scholar
  36. 36.
    Krousel-Wood M, Munter P, Jannu A et al. Reliability of a medication adherence measure in an outpatient setting. Am J Med Sci. 2005;330:182-133; PMID 16174996.Google Scholar
  37. 37.
    Schafer JL. Multivariate normal multiple imputation algorithms. Pennsylvania State University, Department of Statistics University Park. 1994.Google Scholar
  38. 38.
    Abrams DB, Orleans CT, Niaura RS, et al. Integrating individual and public health perspectives for treatment of tobacco dependence under managed health care: A combined stepped care and matching model. Ann Behav Med. 1996;18(14):290–304.CrossRefPubMedGoogle Scholar
  39. 39.
    Glasgow RE, Nelson CC, Strycker LA et al. Using RE-AIM metrics to evaluate diabetes self-management support interventions. Am J Prev Med. 2006;30(1):67-73; PMID 16414426.Google Scholar
  40. 40.
    Weingarten SR, Henning JM, Badamgarav E, et al. Interventions used in disease management programmes for patients with chronic illness-which ones work? Meta-analysis of published reports. BMJ. 2002;325(7370):925.CrossRefPubMedGoogle Scholar
  41. 41.
    Bond GE, Burr R, Wolf FM, et al. The effects of a web-based intervention on the physical outcomes associated with diabetes among adults age 60 and older: a randomized trial. Diabetes Technol Ther. 2007;9(1):52–9.CrossRefPubMedGoogle Scholar
  42. 42.
    Kim CJ, Kang DH. Utility of a Web-based intervention for individuals with type 2 diabetes: the impact on physical activity levels and glycemic control. Comput Inform Nurs. 2006;24(6):337–45.CrossRefPubMedGoogle Scholar
  43. 43.
  44. 44.
    Internet World Statistics. Available at: http://www.internetworldstats.com/stats14.htm. Accessed July 22, 2010.

Copyright information

© Society of General Internal Medicine 2010

Authors and Affiliations

  • Russell E. Glasgow
    • 1
  • Deanna Kurz
    • 1
  • Diane King
    • 1
  • Jennifer M. Dickman
    • 1
  • Andrew J. Faber
    • 1
  • Eve Halterman
    • 1
  • Tim Wooley
    • 3
  • Deborah J. Toobert
    • 2
  • Lisa A. Strycker
    • 2
  • Paul A. Estabrooks
    • 4
  • Diego Osuna
    • 1
  • Debra Ritzwoller
    • 1
  1. 1.Institute for Health Research, Kaiser Permanente ColoradoDenverUSA
  2. 2.Oregon Research InstituteEugeneUSA
  3. 3.InterVision MediaEugeneUSA
  4. 4.Virginia Polytechnic Institute, State UniversityRoanokeUSA

Personalised recommendations