A Novel User Utility Score for Diabetes Management Using Tailored Mobile Coaching: Secondary Analysis of a Randomized Controlled Trial

Min-Kyung Lee, Da Young Lee, Hong-Yup Ahn, Cheol-Young Park, Min-Kyung Lee, Da Young Lee, Hong-Yup Ahn, Cheol-Young Park

Abstract

Background: Mobile health applications have been developed to support diabetes self-management, but their effectiveness could depend on patient engagement. Therefore, patient engagement must be examined through multifactorial tailored behavioral interventions from an individual perspective.

Objective: This study aims to evaluate the usefulness of a novel user utility score (UUS) as a tool to measure patient engagement by using a mobile health application for diabetes management.

Methods: We conducted a subanalysis of results from a 12-month randomized controlled trial of a tailored mobile coaching (TMC) system among insurance policyholders with type 2 diabetes. UUS was calculated as the sum of the scores for 4 major core components (range 0-8): frequency of self-monitoring blood glucose testing, dietary and exercise records, and message reading rate. We explored the association between UUS for the first 3 months and glycemic control over 12 months. In addition, we investigated the relationship of UUS with blood pressure, lipid profile, and self-report scales assessing diabetes self-management.

Results: We divided 72 participants into 2 groups based on UUS for the first 3 months: UUS:0-4 (n=38) and UUS:5-8 (n=34). There was a significant between-group difference in glycated hemoglobin test (HbA1c) levels for the 12-months study period (P=.011). The HbA1c decrement at 12 months in the UUS:5-8 group was greater than that of the UUS:0-4 group [-0.92 (SD 1.24%) vs -0.33 (SD 0.80%); P=.049]. After adjusting for confounding factors, UUS was significantly associated with changes in HbA1c at 3, 6, and 12 months; the regression coefficients were -0.113 (SD 0.040; P=.006), -0.143 (SD 0.045; P=.002), and -0.136 (SD 0.052; P=.011), respectively. Change differences in other health outcomes between the 2 groups were not observed throughout a 12-month follow-up.

Conclusions: UUS as a measure of patient engagement was associated with changes in HbA1c over the study period of the TMC system and could be used to predict improved glycemic control in diabetes self-management through mobile health interventions.

Trial registration: ClinicalTrial.gov NCT03033407; https://ichgcp.net/clinical-trials-registry/NCT03033407.

Keywords: diabetes management; mobile applications; patient engagement; type 2 diabetes.

Conflict of interest statement

Conflicts of Interest: None declared.

©Min-Kyung Lee, Da Young Lee, Hong-Yup Ahn, Cheol-Young Park. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 24.02.2021.

Figures

Figure 1
Figure 1
Glycated hemoglobin (HbA1c) levels for the 12-month study period in the UUS:0-4 group and UUS:5-8 group. Repeated-measures ANOVA revealed significant differences between the groups over 12 months (P=.011). The last observation carried forward (LOCF) imputation method was used. UUS: user utility score.

References

    1. Baik I. Projection of Diabetes Prevalence in Korean Adults for the Year 2030 Using Risk Factors Identified from National Data. Diabetes Metab J. 2019;43(1):90. doi: 10.4093/dmj.2018.0043.
    1. Song SO, Lee Y, Kim DW, Song YD, Nam JY, Park KH, Kim DJ, Park SW, Lee HC, Lee B. Trends in Diabetes Incidence in the Last Decade Based on Korean National Health Insurance Claims Data. Endocrinol Metab. 2016;31(2):292. doi: 10.3803/enm.2016.31.2.292.
    1. American Diabetes Association Abridged for Primary Care Providers. Clin Diabetes. 2018 Dec 17;37(1):11–34. doi: 10.2337/cd18-0105.
    1. Seuring T, Archangelidi O, Suhrcke M. The Economic Costs of Type 2 Diabetes: A Global Systematic Review. Pharmacoeconomics. 2015 Aug 19;33(8):811–31. doi: 10.1007/s40273-015-0268-9.
    1. Powell P, Corathers S, Raymond J, Streisand R. New approaches to providing individualized diabetes care in the 21st century. Curr Diabetes Rev. 2015 Jul 29;11(4):222–30. doi: 10.2174/1573399811666150421110316.
    1. Pal K, Dack C, Ross J, Michie S, May C, Stevenson F, Farmer A, Yardley L, Barnard M, Murray E. Digital Health Interventions for Adults With Type 2 Diabetes: Qualitative Study of Patient Perspectives on Diabetes Self-Management Education and Support. J Med Internet Res. 2018 Jan 29;20(2):e40. doi: 10.2196/jmir.8439.
    1. Powers MA, Bardsley J, Cypress M, Duker P, Funnell MM, Hess Fischl A, Maryniuk MD, Siminerio L, Vivian E. Diabetes Self-management Education and Support in Type 2 Diabetes: A Joint Position Statement of the American Diabetes Association, the American Association of Diabetes Educators, and the Academy of Nutrition and Dietetics. Diabetes Care. 2015 Jul 05;38(7):1372–82. doi: 10.2337/dc15-0730.
    1. Asif M. The prevention and control the type-2 diabetes by changing lifestyle and dietary pattern. J Educ Health Promot. 2014;3(1):1. doi: 10.4103/2277-9531.127541.
    1. Chen L, Pei J, Kuang J, Chen H, Chen Z, Li Z, Yang H. Effect of lifestyle intervention in patients with type 2 diabetes: a meta-analysis. Metabolism. 2015 Feb;64(2):338–47. doi: 10.1016/j.metabol.2014.10.018.
    1. Babazadeh T, Dianatinasab M, Daemi A, Nikbakht HA, Moradi F, Ghaffari-Fam Saber. Association of Self-Care Behaviors and Quality of Life among Patients with Type 2 Diabetes Mellitus: Chaldoran County, Iran. Diabetes Metab J. 2017 Dec;41(6):449–456. doi: 10.4093/dmj.2017.41.6.449.
    1. Iyengar V, Wolf A, Brown A, Close K. Challenges in Diabetes Care: Can Digital Health Help Address Them? Clin Diabetes. 2016 Jul 22;34(3):133–41. doi: 10.2337/diaclin.34.3.133.
    1. Beck J, Greenwood DA, Blanton L, Bollinger ST, Butcher MK, Condon JE, Cypress M, Faulkner P, Fischl AH, Francis T, Kolb LE, Lavin-Tompkins JM, MacLeod J, Maryniuk M, Mensing C, Orzeck EA, Pope DD, Pulizzi JL, Reed AA, Rhinehart AS, Siminerio L, Wang J, 2017 Standards Revision Task Force 2017 National Standards for Diabetes Self-Management Education and Support. Diabetes Educ. 2018 Feb;44(1):35–50. doi: 10.1177/0145721718754797.
    1. Diabetes Association A. 7. Diabetes Technology: Dia Care. 2018 Dec 17;42(Supplement 1):S71–S80. doi: 10.2337/dc19-s007.
    1. Swan M. Health 2050: The Realization of Personalized Medicine through Crowdsourcing, the Quantified Self, and the Participatory Biocitizen. J Pers Med. 2012 Sep 12;2(3):93–118. doi: 10.3390/jpm2030093.
    1. Izahar S, Lean QY, Hameed MA, Murugiah MK, Patel RP, Al-Worafi YM, Wong TW, Ming LC. Content Analysis of Mobile Health Applications on Diabetes Mellitus. Front Endocrinol (Lausanne) 2017;8:318. doi: 10.3389/fendo.2017.00318. doi: 10.3389/fendo.2017.00318.
    1. Kaufman N, Khurana I. Using Digital Health Technology to Prevent and Treat Diabetes. Diabetes Technol Ther. 2016 Feb;18 Suppl 1(S1):S56–68. doi: 10.1089/dia.2016.2506.
    1. Simacek KF, Nelson T, Miller-Baldi M, Bolge SC. Patient engagement in type 2 diabetes mellitus research: what patients want. PPA. 2018 Apr;Volume 12:595–606. doi: 10.2147/ppa.s159707.
    1. Lee DY, Park J, Choi D, Ahn H, Park S, Park C. The effectiveness, reproducibility, and durability of tailored mobile coaching on diabetes management in policyholders: A randomized, controlled, open-label study. Sci Rep. 2018 Feb 26;8(1):3642. doi: 10.1038/s41598-018-22034-0. doi: 10.1038/s41598-018-22034-0.
    1. Polonsky WH, Fisher L. Self-Monitoring of Blood Glucose in Noninsulin-Using Type 2 Diabetic Patients: Right answer, but wrong question: self-monitoring of blood glucose can be clinically valuable for noninsulin users. Diabetes Care. 2012 Dec 20;36(1):179–182. doi: 10.2337/dc12-0731.
    1. Porter J, Huggins CE, Truby H, Collins J. The Effect of Using Mobile Technology-Based Methods That Record Food or Nutrient Intake on Diabetes Control and Nutrition Outcomes: A Systematic Review. Nutrients. 2016 Dec 17;8(12) doi: 10.3390/nu8120815.
    1. Huang X, Pan J, Chen D, Chen J, Chen F, Hu T. Efficacy of lifestyle interventions in patients with type 2 diabetes: A systematic review and meta-analysis. Eur J Intern Med. 2016 Jan;27:37–47. doi: 10.1016/j.ejim.2015.11.016.
    1. Sahin C, Courtney KL, Naylor PJ, E Rhodes R. Tailored mobile text messaging interventions targeting type 2 diabetes self-management: A systematic review and a meta-analysis. Digit Health. 2019;5:2055207619845279. doi: 10.1177/2055207619845279.
    1. Lee D, Yoo S, Min K, Park C. Effect of Voluntary Participation on Mobile Health Care in Diabetes Management: Randomized Controlled Open-Label Trial. JMIR Mhealth Uhealth. 2020 Sep 18;8(9):e19153. doi: 10.2196/19153.
    1. Choi EJ, Nam M, Kim SH, Park CG, Toobert DJ, Yoo JS, Chu SH. Psychometric properties of a Korean version of the summary of diabetes self-care activities measure. Int J Nurs Stud. 2011 Mar;48(3):333–7. doi: 10.1016/j.ijnurstu.2010.08.007.
    1. Lee E, Lee YW, Lee K, Nam M, Kim YS, Han SJ. A Korean version of the Appraisal of Diabetes Scale (ADS-K): psychometric evaluation with a population of Koreans with type 2 diabetes. J Transcult Nurs. 2015 May 29;26(3):270–8. doi: 10.1177/1043659614524793.
    1. Toobert DJ, Hampson SE, Glasgow RE. The summary of diabetes self-care activities measure: results from 7 studies and a revised scale. Diabetes Care. 2000 Jul 01;23(7):943–50. doi: 10.2337/diacare.23.7.943.
    1. Carey MP, Jorgensen RS, Weinstock RS, Sprafkin RP, Lantinga LJ, Carnrike CLM, Baker MT, Meisler AW. Reliability and validity of the Appraisal of Diabetes Scale. J Behav Med. 1991 Feb;14(1):43–50. doi: 10.1007/bf00844767.
    1. Barello S, Graffigna G, Vegni E. Patient engagement as an emerging challenge for healthcare services: mapping the literature. Nurs Res Pract. 2012;2012:905934. doi: 10.1155/2012/905934. doi: 10.1155/2012/905934.
    1. Serrano-Gil M, Jacob S. Engaging and empowering patients to manage their type 2 diabetes, Part I: a knowledge, attitude, and practice gap? Adv Ther. 2010 Jun;27(6):321–33. doi: 10.1007/s12325-010-0034-5.
    1. Lee K, Kwon H, Lee B, Lee G, Lee JH, Park YR, Shin S. Effect of self-monitoring on long-term patient engagement with mobile health applications. PLoS One. 2018 Jul 26;13(7):e0201166. doi: 10.1371/journal.pone.0201166.
    1. Lee M, Lee K, Yoo S, Park C. Impact of initial active engagement in self-monitoring with a telemonitoring device on glycemic control among patients with type 2 diabetes. Sci Rep. 2017 Jun 20;7(1):3866. doi: 10.1038/s41598-017-03842-2. doi: 10.1038/s41598-017-03842-2.
    1. Anton SD, LeBlanc E, Allen HR, Karabetian C, Sacks F, Bray G, Williamson DA. Use of a computerized tracking system to monitor and provide feedback on dietary goals for calorie-restricted diets: the POUNDS LOST study. J Diabetes Sci Technol. 2012 Sep 01;6(5):1216–25. doi: 10.1177/193229681200600527.
    1. Wu X, Guo X, Zhang Z. The Efficacy of Mobile Phone Apps for Lifestyle Modification in Diabetes: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth. 2019 Jan 15;7(1):e12297. doi: 10.2196/12297.
    1. Quinn CC, Shardell MD, Terrin ML, Barr EA, Ballew SH, Gruber-Baldini AL. Cluster-randomized trial of a mobile phone personalized behavioral intervention for blood glucose control. Diabetes Care. 2011 Sep 25;34(9):1934–42. doi: 10.2337/dc11-0366.
    1. Travasso C. Lifestyle advice by text messages helps prevent type 2 diabetes in high risk men. BMJ. 2013 Sep 23;347(sep23 1):f5750–f5750. doi: 10.1136/bmj.f5750.
    1. Yoon K, Kim H. A short message service by cellular phone in type 2 diabetic patients for 12 months. Diabetes Res Clin Pract. 2008 Feb;79(2):256–61. doi: 10.1016/j.diabres.2007.09.007.
    1. Hartz A, Kent S, James P, Xu Y, Kelly M, Daly J. Factors that influence improvement for patients with poorly controlled type 2 diabetes. Diabetes Res Clin Pract. 2006 Dec;74(3):227–32. doi: 10.1016/j.diabres.2006.03.023.
    1. Kodama S, Tanaka Shiro, Saito Kazumi, Shu Miao, Sone Yasuko, Onitake Fumiko, Suzuki Emiko, Shimano Hitoshi, Yamamoto Shigeru, Kondo Kazuo, Ohashi Yasuo, Yamada Nobuhiro, Sone Hirohito. Effect of aerobic exercise training on serum levels of high-density lipoprotein cholesterol: a meta-analysis. Arch Intern Med. 2007 May 28;167(10):999–1008. doi: 10.1001/archinte.167.10.999.
    1. Lee S, Kim Y, Kuk JL. What Is the Role of Resistance Exercise in Improving the Cardiometabolic Health of Adolescents with Obesity? J Obes Metab Syndr. 2019 Jun 30;28(2):76–91. doi: 10.7570/jomes.2019.28.2.76.
    1. Cahn A, Akirov A, Raz I. Digital health technology and diabetes management. J Diabetes. 2018 Jan;10(1):10–17. doi: 10.1111/1753-0407.12606.
    1. Quinn CC, Butler EC, Swasey KK, Shardell MD, Terrin MD, Barr EA, Gruber-Baldini AL. Mobile Diabetes Intervention Study of Patient Engagement and Impact on Blood Glucose: Mixed Methods Analysis. JMIR Mhealth Uhealth. 2018 Feb 02;6(2):e31. doi: 10.2196/mhealth.9265.
    1. Graffigna G, Barello S, Libreri C, Bosio CA. How to engage type-2 diabetic patients in their own health management: implications for clinical practice. BMC Public Health. 2014 Jun 25;14(1):648. doi: 10.1186/1471-2458-14-648.
    1. Remmers C, Hibbard J, Mosen DM, Wagenfield M, Hoye RE, Jones C. Is patient activation associated with future health outcomes and healthcare utilization among patients with diabetes? J Ambul Care Manage. 2009;32(4):320–7. doi: 10.1097/JAC.0b013e3181ba6e77.
    1. Wiederhold BK, Riva G, Graffigna G. Ensuring the best care for our increasing aging population: health engagement and positive technology can help patients achieve a more active role in future healthcare. Cyberpsychol Behav Soc Netw. 2013 Jun;16(6):411–2. doi: 10.1089/cyber.2013.1520.

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