Current Diabetes Reports

, 11:486 | Cite as

Mobile Intervention Design in Diabetes: Review and Recommendations

  • Shelagh A. Mulvaney
  • Lee M. Ritterband
  • Lindsay Bosslet
Psychosocial Aspects (Korey Hood, Section Editor)

Abstract

Mobile technology enhances the potential to assess, prompt, educate, and engage individuals with diabetes. The near-ubiquitous presence of mobile phones allows real-time contextually relevant support for diabetes self-care. We review the design of mobile interventions included in a recent meta-analysis. Although mobile programs can lead to improvements in glycemic control, many aspects, such as the role of the diabetes clinician, real-time features, and patient engagement have not been documented. Studies with the greatest impact on hemoglobin A1c integrated patient feedback and a role for clinicians. Research is needed regarding feasible and efficacious roles for clinical support in mobile interventions. Recommendations for design and research include the following: consideration of patient and clinician burden; identification of patterns and metrics for patient treatment adherence and engagement; integration of goal setting and problem solving; enhancing patient education; a greater focus on patient-centered motivational strategies; and utilization of study designs that relate intervention design elements to outcomes.

Keywords

Diabetes Mobile phone Intervention design Self-management Review Patient engagement 

Notes

Disclosure

No potential conflicts of interest relevant to this article were reported.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. 1.
    • Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X et al. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet Med. 2011;28(4):455–63. doi:10.1111/j.1464-5491.2010.03180.x. This study provided the most recent and quantitative review of mobile diabetes studies. PubMedCrossRefGoogle Scholar
  2. 2.
    Wei J, Hollin I, Kachnowski S. A review of the use of mobile phone text messaging in clinical and healthy behaviour interventions. J Telemed Telecare. 2011;17(1):41–8. doi:10.1258/jtt.2010.100322.PubMedCrossRefGoogle Scholar
  3. 3.
    Piette JD. Interactive behavior change technology to support diabetes self-management: where do we stand? Diabetes Care. 2007;30(10):2425–32. doi:10.2337/dc07-1046.PubMedCrossRefGoogle Scholar
  4. 4.
    Benhamou PY, Melki V, Boizel R, Perreal F, Quesada JL, Bessieres-Lacombe S, et al. One-year efficacy and safety of Web-based follow-up using cellular phone in type 1 diabetic patients under insulin pump therapy: the PumpNet study. Diabetes Metab. 2007;33(3):220–6. doi:10.1016/j.diabet.2007.01.002.PubMedCrossRefGoogle Scholar
  5. 5.
    Istepanian RS, Zitouni K, Harry D, Moutosammy N, Sungoor A, Tang B, et al. Evaluation of a mobile phone telemonitoring system for glycaemic control in patients with diabetes. J Telemed Telecare. 2009;15(3):125–8. doi:10.1258/jtt.2009.003006.PubMedCrossRefGoogle Scholar
  6. 6.
    Rami B, Popow C, Horn W, Waldhoer T, Schober E. Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus. Eur J Pediatr. 2006;165(10):701–5. doi:10.1007/s00431-006-0156-6.PubMedCrossRefGoogle Scholar
  7. 7.
    Yoo HJ, Park MS, Kim TN, Yang SJ, Cho GJ, Hwang TG, et al. A Ubiquitous chronic disease care system using cellular phones and the internet. Diabet Med. 2009;26(6):628–35. doi:10.1111/j.1464-5491.2009.02732.x.PubMedCrossRefGoogle Scholar
  8. 8.
    Vähätalo MA, Virtamo HE, Viikari JS, Rönnemaa T. Cellular phone transferred self blood glucose monitoring: prerequisites for positive outcome. Practical Diabetes Int. 2004;21(5):192–4. doi:10.1002/pdi.642.CrossRefGoogle Scholar
  9. 9.
    Kwon HS, Cho JH, Kim HS, Lee JH, Song BR, Oh JA, et al. Development of web-based diabetic patient management system using short message service (SMS). Diabetes Res Clin Pract. 2004;66 Suppl 1:S133–7.PubMedCrossRefGoogle Scholar
  10. 10.
    Farmer AJ, Gibson OJ, Dudley C, Bryden K, Hayton PM, Tarassenko L, et al. A randomized controlled trial of the effect of real-time telemedicine support on glycemic control in young adults with type 1 diabetes. Diabetes Care. 2005;28(11):2697–702.PubMedCrossRefGoogle Scholar
  11. 11.
    Cho J-H, Lee H-C, Lim D-J, Kwon H-S, Yoon K-H. Mobile communication using a mobile phone with a glucometer for glucose control in Type 2 patients with diabetes: as effective as an Internet-based glucose monitoring system. J Telemed Telecare. 2009;15(2):77–82. doi:10.1258/jtt.2008.080412.PubMedCrossRefGoogle Scholar
  12. 12.
    Kim HS, Kim NC, Ahn SH. Impact of a nurse short message service intervention for patients with diabetes. J Nurs Care Qual. 2006;21(3):266–71.PubMedCrossRefGoogle Scholar
  13. 13.
    Yoon K-H, Kim H-S. A short message service by cellular phone in type 2 diabetic patients for 12 months. Diabetes Res Clin Pract. 2008;79(2):256–61. doi:10.1016/j.diabres.2007.09.007.PubMedCrossRefGoogle Scholar
  14. 14.
    Kim S-I, Kim H-S. Effectiveness of mobile and internet intervention in patients with obese type 2 diabetes. Int J Med Inform. 2008;77(6):399–404.PubMedCrossRefGoogle Scholar
  15. 15.
    Kollmann A, Riedl M, Kastner P, Schreier G, Ludvik B. Feasibility of a mobile phone-based data service for functional insulin treatment of type 1 diabetes mellitus patients. J Med Internet Res. 2007;9(5):36. doi:10.2196/jmir.9.5.e36.CrossRefGoogle Scholar
  16. 16.
    Kim CS, Park SY, Kang JG, Lee SJ, Ihm SH, Choi MG, et al. Insulin dose titration system in diabetes patients using a short messaging service automatically produced by a knowledge matrix. Diabetes Technol Ther. 2010;12(8):663–9. doi:10.1089/dia.2010.0031.Google Scholar
  17. 17.
    • Quinn CC, Clough SS, Minor JM, Lender D, Okafor MC, Gruber-Baldini A. WellDoc mobile diabetes management randomized controlled trial: change in clinical and behavioral outcomes and patient and physician satisfaction. Diabetes Technol Ther. 2008;10(3):160–8. This study combined many desirable features in the intervention with feasible automated advice and an optional clinician component. PubMedCrossRefGoogle Scholar
  18. 18.
    Hanauer DA, Wentzell K, Laffel N, Laffel LM. Computerized Automated Reminder Diabetes System (CARDS): e-mail and SMS cell phone text messaging reminders to support diabetes management. Diabetes Technol Ther. 2009;11(2):99–106. doi:10.1089/dia.2008.0022.PubMedCrossRefGoogle Scholar
  19. 19.
    Turner JA, Deyo RA, Loeser JD, Von Korff M, Fordyce WE. The importance of placebo effects in pain treatment and research. JAMA. 1994;271(20):1609–14.PubMedCrossRefGoogle Scholar
  20. 20.
    Turner J, Larsen M, Tarassenko L, Neil A, Farmer A. Implementation of telehealth support for patients with type 2 diabetes using insulin treatment: an exploratory study. Inform Prim Care. 2009;17(1):47–53.PubMedGoogle Scholar
  21. 21.
    Franklin VL, Waller A, Pagliari C, Greene SA. A randomized controlled trial of Sweet Talk, a text-messaging system to support young people with diabetes. Diabet Med. 2006;23(12):1332–8.PubMedCrossRefGoogle Scholar
  22. 22.
    Rossi MC, Perozzi C, Consorti C, Almonti T, Foglini P, Giostra N, et al. An interactive diary for diet management (DAI): a new telemedicine system able to promote body weight reduction, nutritional education, and consumption of fresh local produce. Diabetes Technol Ther. 2010;12(8):641–7. doi:10.1089/dia.2010.0025.PubMedCrossRefGoogle Scholar
  23. 23.
    Franklin V, Greene A, Waller A, Greene S, Pagliari C. Patients’ engagement With “Sweet Talk”–a text messaging support system for young people with diabetes. J Med Internet Res. 2008;10(2).Google Scholar
  24. 24.
    Rami B, Popow C, Horn W, Waldhoer T, Schober E. Telemedical support to improve glycemic control in adolescents with type 1 diabetes mellitus. Eur J Pediatr. 2006;165(10):701–5. doi:10.1007/s00431-006-0156-6.PubMedCrossRefGoogle Scholar
  25. 25.
    Faridi Z, Liberti L, Shuval K, Northrup V, Ali A, Katz DL. Evaluating the impact of mobile telephone technology on type 2 diabetic patients’ self-management: the NICHE pilot study. J Eval Clin Pract. 2008;14(3):465–9. doi:10.1111/j.1365-2753.2007.00881.x.PubMedCrossRefGoogle Scholar
  26. 26.
    Liu CT, Yeh YT, Lee TI, Li YC. Observations on online services for diabetes management. Diabetes Care. 2005;28(11):2807–8.PubMedCrossRefGoogle Scholar
  27. 27.
    Liu AH, Zeiger R, Sorkness C, Mahr T, Ostrom N, Burgess S, et al. Development and cross-sectional validation of the Childhood Asthma Control Test. J Allergy Clin Immunol. 2007;119(4):817–25. doi:10.1016/j.jaci.2006.12.662.PubMedCrossRefGoogle Scholar
  28. 28.
    Rossi MCE, Nicolucci A, Pellegrini F, Bruttomesso D, Bartolo PD, Marelli G, et al. Interactive diary for diabetes: a useful and easy-to-use new telemedicine system to support the decision-making process in type 1 diabetes. Diabetes Technol Ther. 2009;11(1):19–24. doi:10.1089/dia.2008.0020.PubMedCrossRefGoogle Scholar
  29. 29.
    • Rossi MCE, Nicolucci A, Di Bartolo P, Bruttomesso D, Girelli A, Ampudia FJ et al. Diabetes interactive diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life. Diabetes Care. 2010;33(1):109–15. doi:10.2337/dc09-1327. This intervention uniquetly attempted to influence nutritional behaviors, and integrated many desirable features in their system. PubMedCrossRefGoogle Scholar
  30. 30.
    Mulvaney SA, Hood KK, Schlundt DG, Osborn CY, Johnson KB, Rothman RL et al. Development and initial validation of the barriers to diabetes adherence measure for adolescents. Diabetes Res Clin Pract. In Press, Corrected Proof. doi:10.1016/j.diabres.2011.06.010.
  31. 31.
    Beyer H, Holtzblatt K. Contextual design: defining customer-centered systems. San Diego: Academic Press; 1998.Google Scholar
  32. 32.
    Farmer A, Gibson O, Hayton P, Bryden K, Dudley C, Neil A, et al. A real-time, mobile phone-based telemedicine system to support young adults with type 1 diabetes. Inform Prim Care. 2005;13(3):171–7.PubMedGoogle Scholar
  33. 33.
    Waller A, Franklin V, Pagliari C, Greene S. Participatory design of a text message scheduling system to support young people with diabetes. Health Informatics J. 2006;12(4):304–18.PubMedCrossRefGoogle Scholar
  34. 34.
    World Health Organization. Reducing risks, promoting healthy life. Geneva: World Health Organization; 2002.Google Scholar
  35. 35.
    Couper MP, Peytchev A, Strecher VJ, Rothert K, Anderson J. Following up nonrespondents to an online weight management intervention: randomized trial comparing mail versus telephone. J Med Internet Res. 2007;9(2):e16. doi:v9i2e1610.2196/jmir.9.2.e16.PubMedCrossRefGoogle Scholar
  36. 36.
    Glasgow RE, Nelson CC, Kearney KA, Reid R, Ritzwoller DP, Strecher VJ, et al. Reach, engagement, and retention in an Internet-based weight loss program in a multi-site randomized controlled trial. J Med Internet Res. 2007;9(2):e11. doi:v9i2e1110.2196/jmir.9.2.e11.PubMedCrossRefGoogle Scholar
  37. 37.
    Glasgow RE, Eakin EG, Toobert DJ. How generalizable are the results of diabetes self-management research? The impact of participation and attrition. Diabetes Educ. 1996;22(6):573–4, 81–2, 84–5.Google Scholar
  38. 38.
    Eysenbach G. The law of attrition. J Med Internet Res. 2005;7(1):e11.PubMedCrossRefGoogle Scholar
  39. 39.
    Heron K, Smyth J. Ecological momentary interventions: incorporating mobile technology into psychosocial and health behaviour treatments. Br J Health Psychol. 2010;15(1):1–39. doi:10.1348/135910709X466063.PubMedCrossRefGoogle Scholar
  40. 40.
    Kluger AN, DeNisi A. The effects of feedback interventions on performance: a historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychol Bull. 1996;119(2):254–84.CrossRefGoogle Scholar
  41. 41.
    Chapin R, Williams D, Adair R. Diabetes control improved when inner-city patients received graphic feedback about glycosylated hemoglobin levels. J Gen Intern Med. 2003;18(2):120–4.PubMedCrossRefGoogle Scholar
  42. 42.
    Kreuter MW, Wray RJ. Tailored and targeted health communication: strategies for enhancing information relevance. Am J Health Behav. 2003;27 Suppl 3:S227–32.PubMedGoogle Scholar
  43. 43.
    Danaher BG, Seeley JR. Methodological issues in research on web-based behavioral interventions. Ann Behav Med. 2009;38(1):28–39. doi:10.1007/s12160-009-9129-0.PubMedCrossRefGoogle Scholar
  44. 44.
    Collins L, Baker T, Mermelstein R, Piper M, Jorenby D, Smith S, et al. The multiphase optimization strategy for engineering effective tobacco use interventions. Ann Behav Med. 2011;41(2):208–26. doi:10.1007/s12160-010-9253-x.PubMedCrossRefGoogle Scholar
  45. 45.
    Funnell MM, Brown TL, Childs BP, Haas LB, Hosey GM, Jensen B, et al. National standards for diabetes self-management education. Diabetes Care. 2009;32 suppl 1:S87–94. doi:10.2337/dc08-S097.PubMedCrossRefGoogle Scholar
  46. 46.
    Welch G, Shayne R. Interactive behavioral technologies and diabetes self-management support: recent research findings from clinical trials. Curr Diab Rep. 2006;6(2):130–6. doi:10.1007/s11892-006-0024-9.PubMedCrossRefGoogle Scholar
  47. 47.
    Thaler RH, Sunstein CR. Nudge: improving decisions about health, wealth, and happiness. New York: Penguin; 2009.Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Shelagh A. Mulvaney
    • 1
  • Lee M. Ritterband
    • 2
  • Lindsay Bosslet
    • 1
  1. 1.School of Nursing, Pediatrics, & Biomedical InformaticsVanderbilt University Medical CenterNashvilleUSA
  2. 2.Department of Psychiatry and Neurobehavioral SciencesUniversity of VirginiaCharlottesvilleUSA

Personalised recommendations