Effect of Smartphone-Based Lifestyle Coaching App on Community-Dwelling Population With Moderate Metabolic Abnormalities: Randomized Controlled Trial

So Mi Jemma Cho, Jung Hyun Lee, Jee-Seon Shim, Hyungseon Yeom, Su Jin Lee, Yong Woo Jeon, Hyeon Chang Kim, So Mi Jemma Cho, Jung Hyun Lee, Jee-Seon Shim, Hyungseon Yeom, Su Jin Lee, Yong Woo Jeon, Hyeon Chang Kim

Abstract

Background: Metabolic disorders are established precursors to cardiovascular diseases, yet they can be readily prevented with sustained lifestyle modifications.

Objective: We assessed the effectiveness of a smartphone-based weight management app on metabolic parameters in adults at high-risk, yet without physician diagnosis nor pharmacological treatment for metabolic syndrome, in a community setting.

Methods: In this 3-arm parallel-group, single-blind, randomized controlled trial, we recruited participants aged 30 to 59 years with at least 2 conditions defined by the Third Report of the National Cholesterol Education Program expert panel (abdominal obesity, high blood pressure, high triglycerides, low high-density lipoprotein cholesterol, and high fasting glucose level). Participants were randomly assigned (1:1:1) by block randomization to either the nonuser group (control), the app-based diet and exercise self-logging group (app only), or the app-based self-logging and personalized coaching from professional dieticians and exercise coordinators group (app with personalized coaching). Assessments were performed at baseline, week 6, week 12, and week 24. The primary outcome was change in systolic blood pressure (between baseline and follow-up assessments). Secondary outcomes were changes in diastolic blood pressure, body weight, body fat mass, waist circumference, homeostatic model of assessment of insulin resistance, triglyceride level, and high-density lipoprotein cholesterol level between baseline and follow-up assessments. Analysis was performed using intention-to-treat.

Results: Between October 28, 2017 and May 28, 2018, 160 participants participated in the baseline screening examination. Participants (129/160, 80.6%) who satisfied the eligibility criteria were assigned to control (n=41), app only (n=45), or app with personalized coaching (n=43) group. In each group, systolic blood pressure showed decreasing trends from baseline (control: mean -10.95, SD 2.09 mmHg; app only: mean -7.29, SD 1.83 mmHg; app with personalized coaching: mean -7.19, SD 1.66 mmHg), yet without significant difference among the groups (app only: P=.19; app with personalized coaching: P=.16). Instead, those in the app with personalized coaching group had greater body weight reductions (control: mean -0.12, SD 0.30 kg; app only: mean -0.35, SD 0.36 kg, P=.67; app with personalized coaching: mean -0.96, SD 0.37 kg; P=.08), specifically by body fat mass reduction (control: mean -0.13, SD 0.34 kg; app only: mean -0.64, SD 0.38 kg, P=.22; app with personalized coaching: mean -0.79, SD 0.38 kg; P=.08).

Conclusions: Simultaneous diet and exercise self-logging and persistent lifestyle modification coaching were ineffective in lowering systolic blood pressure but effective in losing weight and reducing body fat mass. These results warrant future implementation studies of similar models of care on a broader scale in the context of primary prevention.

Trial registration: ClinicalTrials.gov NCT03300271; https://ichgcp.net/clinical-trials-registry/NCT03300271.

Keywords: health behavior; lifestyle modification; metabolic health; mobile health.

Conflict of interest statement

Conflicts of Interest: None declared.

©So Mi Jemma Cho, Jung Hyun Lee, Jee-Seon Shim, Hyungseon Yeom, Su Jin Lee, Yong Woo Jeon, Hyeon Chang Kim. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 09.10.2020.

Figures

Figure 1
Figure 1
Flow diagram of the study participants. CMERC: Cardiovascular and Metabolic Diseases Etiology Research Center.
Figure 2
Figure 2
Example of personalized coaching.
Figure 3
Figure 3
Systolic blood pressure changes from the baseline across the 3 groups at each time point. AO: app-only; APC: app with personalized coaching; CO: control, SBP: systolic blood pressure.
Figure 4
Figure 4
Body weight changes from the baseline across the 3 groups at each time point. AO: app-only; APC: app with personalized coaching; CO: control, SBP: systolic blood pressure.
Figure 5
Figure 5
Body fat mass changes from the baseline across the 3 groups at each time point. AO: app-only; APC: app with personalized coaching; CO: control.

References

    1. Wilson PWF, D'Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation. 2005 Nov 15;112(20):3066–72. doi: 10.1161/CIRCULATIONAHA.105.539528.
    1. Mottillo S, Filion KB, Genest J, Joseph L, Pilote L, Poirier P, Rinfret S, Schiffrin EL, Eisenberg MJ. The Metabolic Syndrome and Cardiovascular Risk. Journal of the American College of Cardiology. 2010 Sep;56(14):1113–1132. doi: 10.1016/j.jacc.2010.05.034.
    1. Kang S, Kim S, Cho JH, Yoon C, Hwang S, Lee H, Youn T, Chae I, Kim C. Prevalence, Awareness, Treatment, and Control of Hypertension in Korea. Sci Rep. 2019 Jul 29;9(1):10970. doi: 10.1038/s41598-019-46965-4. doi: 10.1038/s41598-019-46965-4.
    1. Kim B, Won JC, Lee JH, Kim H, Park JH, Ha KH, Won KC, Kim DJ, Park KS. Diabetes Fact Sheets in Korea, 2018: An Appraisal of Current Status. Diabetes Metab J. 2019;43(4):487. doi: 10.4093/dmj.2019.0067.
    1. Jeong JS, Kwon HS. Prevalence and Clinical Characteristics of Dyslipidemia in Koreans. Endocrinol Metab (Seoul) 2017 Mar;32(1):30–35. doi: 10.3803/EnM.2017.32.1.30.
    1. Garrett P, Brown CA, Hart-Hester S, Hamadain E, Dixon C, Pierce W, Rudman WJ. Identifying barriers to the adoption of new technology in rural hospitals: a case report. Perspect Health Inf Manag. 2006 Oct 25;3:9.
    1. Mosa ASM, Yoo I, Sheets L. A systematic review of healthcare applications for smartphones. BMC Med Inform Decis Mak. 2012;12:67. doi: 10.1186/1472-6947-12-67.
    1. Boulos MNK, Brewer AC, Karimkhani C, Buller DB, Dellavalle RP. Mobile medical and health apps: state of the art, concerns, regulatory control and certification. Online J Public Health Inform. 2014;5(3):229. doi: 10.5210/ojphi.v5i3.4814.
    1. Burke LE, Ma J, Azar KMJ, Bennett GG, Peterson ED, Zheng Y, Riley W, Stephens J, Shah SH, Suffoletto B, Turan TN, Spring B, Steinberger J, Quinn CC, American Current Science on Consumer Use of Mobile Health for Cardiovascular Disease Prevention: A Scientific Statement From the American Heart Association. Circulation. 2015 Sep 22;132(12):1157–213. doi: 10.1161/CIR.0000000000000232.
    1. Pandey A, Krumme A, Patel T, Choudhry N. The Impact of Text Messaging on Medication Adherence and Exercise Among Postmyocardial Infarction Patients: Randomized Controlled Pilot Trial. JMIR Mhealth Uhealth. 2017 Aug 03;5(8):e110. doi: 10.2196/mhealth.7144.
    1. Haapala I, Barengo NC, Biggs S, Surakka L, Manninen P. Weight loss by mobile phone: a 1-year effectiveness study. Public Health Nutr. 2009 Dec;12(12):2382–91. doi: 10.1017/S1368980009005230.
    1. Cottrell E, Chambers R, O'Connell P. Using simple telehealth in primary care to reduce blood pressure: a service evaluation. BMJ Open. 2012;2(6) doi: 10.1136/bmjopen-2012-001391.
    1. Kang S, Kim S, Cho JH, Yoon C, Hwang S, Lee H, Youn T, Chae I, Kim C. Prevalence, Awareness, Treatment, and Control of Hypertension in Korea. Sci Rep. 2019 Jul 29;9(1):10970. doi: 10.1038/s41598-019-46965-4. doi: 10.1038/s41598-019-46965-4.
    1. Logan AG, Irvine MJ, McIsaac WJ, Tisler A, Rossos PG, Easty A, Feig DS, Cafazzo JA. Effect of home blood pressure telemonitoring with self-care support on uncontrolled systolic hypertension in diabetics. Hypertension. 2012 Jul;60(1):51–7. doi: 10.1161/HYPERTENSIONAHA.111.188409.
    1. Whelton PK, Carey RM, Aronow WS, Casey DE, Collins KJ, Dennison HC, DePalma SM, Gidding S, Jamerson KA, Jones DW, MacLaughlin EJ, Muntner P, Ovbiagele B, Smith SC, Spencer CC, Stafford RS, Taler SJ, Thomas RJ, Williams KA, Williamson JD, Wright JT. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA Guideline for the Prevention, Detection, Evaluation, and Management of High Blood Pressure in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. Hypertension. 2017 Nov 13;:e13–e115. doi: 10.1161/HYP.0000000000000065.
    1. Williams B, Mancia G, Spiering W, Agabiti Rosei E, Azizi M, Burnier M, Clement DL, Coca A, de Simone G, Dominiczak A, Kahan T, Mahfoud F, Redon J, Ruilope L, Zanchetti A, Kerins M, Kjeldsen SE, Kreutz R, Laurent S, Lip GYH, McManus R, Narkiewicz K, Ruschitzka F, Schmieder RE, Shlyakhto E, Tsioufis C, Aboyans V, Desormais I, ESC Scientific Document Group 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J. 2018 Sep 01;39(33):3021–3104. doi: 10.1093/eurheartj/ehy339.
    1. Shim J, Song BM, Lee JH, Lee SW, Park JH, Choi DP, Lee MH, Ha KH, Kim DJ, Park S, Lee W, Kim HC. Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) cohort: study protocol and results of the first 3 years of enrollment. Epidemiol Health. 2017;39:e2017016. doi: 10.4178/epih.e2017016. doi: 10.4178/epih.e2017016.
    1. National Cholesterol Education Program Expert Panel Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report. Circulation. 2002 Dec 17;106(25):3143–3143. doi: 10.1161/circ.106.25.3143.
    1. Chun MY. Validity and Reliability of Korean Version of International Physical Activity Questionnaire Short Form in the Elderly. Korean J Fam Med. 2012;33(3):144. doi: 10.4082/kjfm.2012.33.3.144.
    1. Twisk J, Bosman L, Hoekstra T, Rijnhart J, Welten M, Heymans M. Different ways to estimate treatment effects in randomised controlled trials. Contemp Clin Trials Commun. 2018 Jun;10:80–85. doi: 10.1016/j.conctc.2018.03.008.
    1. Schippers M, Adam PCG, Smolenski DJ, Wong HTH, de Wit J B F. A meta-analysis of overall effects of weight loss interventions delivered via mobile phones and effect size differences according to delivery mode, personal contact, and intervention intensity and duration. Obes Rev. 2017 Apr;18(4):450–459. doi: 10.1111/obr.12492.
    1. Madsen LB, Kirkegaard P, Pedersen EB. Blood pressure control during telemonitoring of home blood pressure. A randomized controlled trial during 6 months. Blood Press. 2008;17(2):78–86. doi: 10.1080/08037050801915468.
    1. Nolan RP, Liu S, Shoemaker JK, Hachinski V, Lynn H, Mikulis DJ, Wennberg RA, Moy LM, Zbib A. Therapeutic benefit of internet-based lifestyle counselling for hypertension. Can J Cardiol. 2012 May;28(3):390–6. doi: 10.1016/j.cjca.2012.02.012.
    1. Piette JD, Datwani H, Gaudioso S, Foster SM, Westphal J, Perry W, Rodríguez-Saldaña J, Mendoza-Avelares MO, Marinec N. Hypertension management using mobile technology and home blood pressure monitoring: results of a randomized trial in two low/middle-income countries. Telemed J E Health. 2012 Oct;18(8):613–20. doi: 10.1089/tmj.2011.0271.
    1. Liu S, Dunford SD, Leung YW, Brooks D, Thomas SG, Eysenbach G, Nolan RP. Reducing blood pressure with Internet-based interventions: a meta-analysis. Can J Cardiol. 2013 May;29(5):613–21. doi: 10.1016/j.cjca.2013.02.007.
    1. Patrick K, Raab F, Adams MA, Dillon L, Zabinski M, Rock CL, Griswold WG, Norman GJ. A text message-based intervention for weight loss: randomized controlled trial. J Med Internet Res. 2009;11(1):e1. doi: 10.2196/jmir.1100.
    1. Khaylis A, Yiaslas T, Bergstrom J, Gore-Felton C. A review of efficacious technology-based weight-loss interventions: five key components. Telemed J E Health. 2010 Nov;16(9):931–8. doi: 10.1089/tmj.2010.0065.
    1. Abraham C, Michie S. A taxonomy of behavior change techniques used in interventions. Health Psychol. 2008 May;27(3):379–87. doi: 10.1037/0278-6133.27.3.379.
    1. Liang X, Wang Q, Yang X, Cao J, Chen J, Mo X, Huang J, Wang L, Gu D. Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis. Diabet Med. 2011 Apr;28(4):455–63. doi: 10.1111/j.1464-5491.2010.03180.x.
    1. Park M, Kim H. Evaluation of mobile phone and Internet intervention on waist circumference and blood pressure in post-menopausal women with abdominal obesity. Int J Med Inform. 2012 Jun;81(6):388–94. doi: 10.1016/j.ijmedinf.2011.12.011.

Source: PubMed

Sponsors et collaborateurs

Les conditions médicales

Interventions en matière de drogue

3
S'abonner