Annals of Behavioral Medicine

, Volume 40, Issue 1, pp 40–48 | Cite as

Recruitment for an Internet-Based Diabetes Self-Management Program: Scientific and Ethical Implications

  • Russell E. Glasgow
  • Lisa A. Strycker
  • Deanna Kurz
  • Andrew Faber
  • Hillary Bell
  • Jennifer M. Dickman
  • Eve Halterman
  • Paul A. Estabrooks
  • Diego Osuna
Original Article



Little is known about the reach of Internet self-management interventions.


The aim of this study was to evaluate different definitions of participation rate and compare characteristics among subcategories of participants and nonparticipants on demographic and clinical factors using de-identified electronic medical record data.


Data are presented on recruitment results and characteristics of 2,603 health maintenance organization members having type 2 diabetes invited to participate in an Internet self-management program.


There was a 37% participation rate among all members attempted to contact and presumed eligible. There were several significant differences between participants and nonparticipants and among subgroups of participants (e.g., proactive volunteers vs. telephone respondents) on factors including age, income, ethnicity, smoking rate, education, blood pressure, and hemoglobin A1c.


These results have important implications for the impact of different recruitment methods on health disparities and generalization of results. We provide recommendations for reporting of eligibility rate, participation rate, and representativeness analyses.


Recruitment Participation Clinical trials Representativeness Research methods 


  1. 1.
    Thoolen B, de Ridder D, Bensing J, Gorter K, Rutten G. Who participates in diabetes self-management interventions? Issues of recruitment and retention. Diab Educ. 2007; 33: 465–474.CrossRefGoogle Scholar
  2. 2.
    Glasgow RE. What types of evidence are most needed to advance behavioral medicine? Ann Behav Med. 2007; 35: 19–25.Google Scholar
  3. 3.
    Van Spall HGC, Toren A, Kiss A, Fowler RA. Eligibility criteria of randomized controlled trials published in high-impact general medical journals. J Am Med Assoc. 2007; 297: 1233–1240.CrossRefGoogle Scholar
  4. 4.
    Shavers-Hornaday VL, Lynch CF, Burmeister LF, Torner JC. Why are African-Americans underrepresented in medical research studies? Ethn Health. 1997; 2: 31–45.CrossRefPubMedGoogle Scholar
  5. 5.
    Murthy VH, Krumholz HM, Gross CP. Participation in cancer clinical trials: Race-, sex-, age-based disparities. J Am Med Assoc. 2004; 291: 2726.CrossRefGoogle Scholar
  6. 6.
    Wendler D, Kington R, Madans J, et al. Are racial and ethnic minorities less willing to participate in health research? PLoS Med. 2005; 3: e19.CrossRefPubMedGoogle Scholar
  7. 7.
    Strecher V. Internet methods for delivering behavioral and health-related interventions (eHealth). Annu Rev Clin Psychol. 2007; 3: 53–76.CrossRefPubMedGoogle Scholar
  8. 8.
    Tate D. Introduction to special series on the Science of Internet Intervention Research. Annals Behav Med. 2010. In Press.Google Scholar
  9. 9.
    Pena-Purcell N. Hispanic use of Internet health information: An exploratory study. J Med Libr Assoc. 2008; 96: 101–107.CrossRefPubMedGoogle Scholar
  10. 10.
    Wilson JJ, Mick R, Wei J, Rustgi AK. Clinical trial resources on the Internet must be designed to reach underrepresented minorities. Cancer J. 2006; 12: 475–481.CrossRefPubMedGoogle Scholar
  11. 11.
    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: 3–12. PMID 14979358.CrossRefPubMedGoogle Scholar
  12. 12.
    Stopponi MA, Alexander GL, McClure JB, et al. Recruitment to a randomized web-based nutritional intervention trial: Characteristics of participants compared to non-participants. J Med Internet Res. 2009; 11: e38.CrossRefPubMedGoogle Scholar
  13. 13.
    Toobert DJ, Glasgow RE, Strycker LA, Barrera M Jr, Ritzwoller DP, Weidner G. Long-term effects of the Mediterranean lifestyle program: A randomized clinical trial for postmenopausal women with type 2 diabetes. Int J Behav Nutri Phys Act. 2007; 17: 1. PMID 17229325.CrossRefGoogle Scholar
  14. 14.
    Danaher BG, Seeley JR. Methodological issues in research on web-based behavioral interventions. Annals Behav Med. 2010. In Press.Google Scholar
  15. 15.
    Glasgow RE, Strycker LA, King D, et al. Robustness of a computer-assisted diabetes self-management intervention across patient characteristics, healthcare settings, and intervention staff. Am J Manage Care. 2006; 12: 137–145. PMID 16524346.Google Scholar
  16. 16.
    Centers for Disease Control and Prevention. Age adjusted percentage of population with diagnosed diabetes by race and sex, 1980-2006. Accessed September 21, 2009.
  17. 17.
    Nielson J. Digital divide: The three stages. Retrieved August 22, 2009.
  18. 18.
    Moore M, Bias RG, Prentice K, Fletcher R, Vaughn T. Web usability testing with a Hispanic medically underserved population. J Med Libr Assoc. 2009; 97: 114–121.CrossRefPubMedGoogle Scholar
  19. 19.
    Fogel J, Albert SM, Schnabel F, Ditkoff BA, Neugut AI. Racial/ethnic differences and potential psychological benefits in use of the Internet by women with breast cancer. Psychooncology. 2003; 12: 107–117.CrossRefPubMedGoogle Scholar
  20. 20.
    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
  21. 21.
    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: 551–557. PMID 15908849.CrossRefPubMedGoogle Scholar
  22. 22.
    Whitlock EP, Orleans CT, Pender N, Allan J. Evaluating primary care behavioral counseling interventions: An evidence-based approach. Am J Prev Med. 2002; 22: 267–284.CrossRefPubMedGoogle Scholar
  23. 23.
    Glasgow RE, Goldstein MG, Ockene J, Pronk NP. Translating what we have learned into practice: Principles and hypotheses for addressing multiple behaviors in primary care. Am J Prev Med. 2004; 27: 88–101. PMID 15275677.CrossRefPubMedGoogle Scholar
  24. 24.
    Glasgow RE, Christiansen S, Kurz D, King D, Woolley T, Faber A, et al. Engagement in a diabetes self-management website: Usage patterns and correlates. Submitted for publication, 2009.Google Scholar
  25. 25.
    Quinn E. PAR-Q: The physical activity readiness questionnaire, take the PAR-Q before you start and exercise program. Accessed September 21, 2009.
  26. 26.
    Chew LD, Bradley KA, Boyko EJ. Brief questions to identify patients with inadequate health literacy. Fam Med. 2004; 36: 588–594.PubMedGoogle Scholar
  27. 27.
    Glasgow RE. Outcomes of and for diabetes education research. Diab Educ. 1999; 25: 74–88.CrossRefGoogle Scholar
  28. 28.
    Parra-Medina D, D'Antonio A, Smith SM, Levin S, Kirkner G, Mayer-Davis E. Successful recruitment and retention strategies for a randomized weight management trial for people with diabetes living in rural, medially underserved counties of South Carolina: The POWER study. J Am Diet Assoc. 2004; 104: 70–75.CrossRefPubMedGoogle Scholar
  29. 29.
    Des Jarlais DC, Lyles C, Crepaz N, TREND Group. Improving the reporting quality of nonrandomized evaluations of behavioral and public health interventions: The TREND statement. Am J Public Health. 2004; 94: 361–366.CrossRefPubMedGoogle Scholar
  30. 30.
    Scott JC, Conner DA, Venohor I, et al. Effectiveness of a group outpatient visit model for chronically ill older health maintenance organization members: A 2-year randomized trial of the Cooperative Health Care Clinic. J Am Geriatr Soc. 2004; 52: 1463–1470.CrossRefPubMedGoogle Scholar
  31. 31.
    Chong N. The Latino Patient: A Cultural Guideline for Health Care Providers. Boston: International Press; 2002.Google Scholar

Copyright information

© The Society of Behavioral Medicine 2010

Authors and Affiliations

  • Russell E. Glasgow
    • 1
  • Lisa A. Strycker
    • 2
  • Deanna Kurz
    • 1
  • Andrew Faber
    • 1
  • Hillary Bell
    • 1
  • Jennifer M. Dickman
    • 1
  • Eve Halterman
    • 1
  • Paul A. Estabrooks
    • 3
  • Diego Osuna
    • 1
  1. 1.Institute for Health ResearchKaiser Permanente ColoradoDenverUSA
  2. 2.Oregon Research InstituteEugeneUSA
  3. 3.Virginia Tech RiversideRoanokeUSA

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