Zhou B, Perel P, Mensah GA, Ezzati M. Global epidemiology, health burden and effective interventions for elevated blood pressure and hypertension. Nat Rev Cardiol. 2021;18:785–802.
Google Scholar
Xu X, Shi Z, Zhou L, Lin J, Atlantis E, Chen X, et al. Impact of COVID−19 on risks and deaths of non-communicable diseases in the Western Pacific region. Lancet Reg Health West Pac. 2024;43:100795.
Google Scholar
Alessa T, Hawley MS, Hock ES, de Witte L. Smartphone apps to support self-management of hypertension: review and content analysis. JMIR Mhealth Uhealth. 2019;7:e13645.
Google Scholar
Kitt J, Fox R, Tucker KL, McManus RJ. New approaches in hypertension management: a review of current and developing technologies and their potential impact on hypertension care. Curr Hypertens Rep. 2019;21:44.
Google Scholar
Statista. Smartphone penetration rate in Japan from 2018 to 2022 with a forecast until 2027. https://www.statista.com/statistics/275102/share-of-the-population-to-own-a-smartphone-japan/. Accessed Sep 29th, 2023.
Burke LE, Ma J, Azar KM, Bennett GG, Peterson ED, Zheng Y, et al. Current science on consumer use of mobile health for cardiovascular disease prevention: a scientific statement from the american heart association. Circulation. 2015;132:1157–213.
Google Scholar
Jamaladin H, van de Belt TH, Luijpers LC, de Graaff FR, Bredie SJ, Roeleveld N, et al. Mobile apps for blood pressure monitoring: systematic search in app stores and content analysis. JMIR Mhealth Uhealth. 2018;6:e187.
Google Scholar
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Bmj. 2021;372:n71.
Google Scholar
Grønli TM, Hansen J, Ghinea G, Younas M. Mobile Application Platform Heterogeneity: Android vs Windows Phone vs iOS vs. Firefox OS. 2014 IEEE 28th International Conference on Advanced Information Networking and Applications (AINA); 2014.
Japan Council for Quality Health Care. Minds Manual Developing Committee ed. Minds Manual for Guideline Development 2020 ver. 3.0. https://minds.jcqhc.or.jp/methods/cpg-development/minds-manual/. Accessed Dec 3, 2023.
National Institute for Health and Care Excellence (NICE). Developing NICE guidelines: the manual. 2014. https://www.nice.org.uk/media/default/about/what-we-do/our-programmes/developing-nice-guidelines-the-manual.pdf. Accessed Mar 28th, 2024.
Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.
Google Scholar
Egger M, Smith Davey, Schneider G, Minder M. C. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997;315:629–34.
Google Scholar
Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56:455–63.
Google Scholar
Higgins JPT, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. (editors). Cochrane Handbook for Systematic Reviews of Interventions version 6.4 (updated August 2023). Cochrane, 2023. Available from www.training.cochrane.org/handbook.
Auton A, Zaman S, Padayachee Y, Samways JW, Quaife NM, Sweeney M, et al. Smartphone-based remote monitoring for chronic heart failure: mixed methods analysis of user experience from patient and nurse perspectives. JMIR Nurs. 2023;6:e44630.
Google Scholar
Beger C, Rüegger D, Lenz A, Wagner S, Haller H, Schmidt-Ott KM, et al. Blood pressure dynamics during home blood pressure monitoring with a digital blood pressure coach-a prospective analysis of individual user data. Front Cardiovasc Med. 2023;10:1115987.
Google Scholar
Brewer LC, Jones C, Slusser JP, Pasha M, Lalika M, Chacon M, et al. mHealth intervention for promoting hypertension self-management among African American patients receiving care at a community health center: formative evaluation of the Faith! hypertension app. JMIR Form Res. 2023;7:e45061.
Google Scholar
Falah F, Sajadi SA, Pishgooie AH. Effect of a mobile-based educational app on blood pressure of patients with hypertension. BMJ Mil Health. 2023;169:e001577.
Leupold F, Karimzadeh A, Breitkreuz T, Draht F, Klidis K, Grobe T, et al. Digital redesign of hypertension management with practice and patient apps for blood pressure control (PIA study): A cluster-randomised controlled trial in general practices. EClinicalMedicine. 2023;55:101712.
Google Scholar
Oclaman JM, Murray ML, Grandis DJ, Beatty AL. The association between mobile app use and change in functional capacity among cardiac rehabilitation participants: cohort study. JMIR Cardio. 2023;7:e44433.
Google Scholar
Wang S, Leung M, Leung SY, Han J, Leung W, Hui E, et al. Safety, feasibility, and acceptability of telemedicine for hypertension in primary care: a proof-of-concept and pilot randomized controlled trial (SATE-HT). J Med Syst. 2023;47:34.
Google Scholar
Wong EML, Leung DYP, Wang Q, Leung AYM, Cheung ASP. The effect of a lifestyle intervention program using a mobile application versus the effect of a program using a booklet for adults with metabolic syndrome: a three-arm randomized controlled trial. J Nurs Scholarsh. 2023;55:936–48.
Google Scholar
Zhang N, Zhou M, Li M, Ma G. Effects of smartphone-based remote interventions on dietary intake, physical activity, weight control, and related health benefits among the older population with overweight and obesity in China: randomized controlled trial. J Med Internet Res. 2023;25:e41926.
Google Scholar
Alsaqer K, Bebis H. Self-care of hypertension of older adults during COVID−19 lockdown period: a randomized controlled trial. Clin Hypertens. 2022;28:21.
Google Scholar
Branch OH, Rikhy M, Auster-Gussman LA, Lockwood KG, Graham SA. Relationships between blood pressure reduction, weight loss, and engagement in a digital app-based hypertension care program: observational study. JMIR Form Res. 2022;6:e38215.
Google Scholar
Indraratna P, Biswas U, McVeigh J, Mamo A, Magdy J, Vickers D, et al. A smartphone-based model of care to support patients with cardiac disease transitioning from hospital to the community (TeleClinical Care): pilot randomized controlled trial. JMIR Mhealth Uhealth. 2022;10:e32554.
Google Scholar
Kanai M, Toda T, Yamamoto K, Akimoto M, Hagiwara Y. A mobile health-based disease management program improves blood pressure in people with multiple lifestyle-related diseases at risk of developing vascular disease - a retrospective observational study. Circ Rep. 2022;4:322–9.
Google Scholar
Kawai Y, Waki K, Yamaguchi S, Shibuta T, Miyake K, Kimura S, et al. The use of information and communication technology-based self-management system dialbeticslite in treating abdominal obesity in Japanese office workers: prospective single-arm pilot intervention study. JMIR Diabetes. 2022;7:e40366.
Google Scholar
Li Y, Gong Y, Zheng B, Fan F, Yi T, Zheng Y, et al. Effects on adherence to a mobile app-based self-management digital therapeutics among patients with coronary heart disease: pilot randomized controlled trial. JMIR Mhealth Uhealth. 2022;10:e32251.
Google Scholar
Ma Y, Cheng HY, Sit JWH, Chien WT. The effects of a smartphone-enhanced nurse-facilitated self-care intervention for Chinese hypertensive patients: a randomised controlled trial. Int J Nurs Stud. 2022;134:104313.
Google Scholar
Ögmundsdóttir Michelsen H, Sjölin I, Bäck M, Gonzalez Garcia M, Olsson A, Sandberg C, et al. Effect of a lifestyle-focused web-based application on risk factor management in patients who have had a myocardial infarction: randomized controlled trial. J Med Internet Res. 2022;24:e25224.
Google Scholar
Mitrani LR, Goldenthal I, Leskowitz J, Wan EY, Dizon J, Saluja D, et al. Risk factor management of atrial fibrillation using mHealth: the atrial fibrillation – helping address care with remote technology (AF-HEART) pilot study. Cardiovasc Digit Health J. 2022;3:14–20.
Google Scholar
Parker SM, Barr M, Stocks N, Denney-Wilson E, Zwar N, Karnon J, et al. Preventing chronic disease in overweight and obese patients with low health literacy using eHealth and teamwork in primary healthcare (HeLP-GP): a cluster randomised controlled trial. BMJ Open. 2022;12:e060393.
Google Scholar
Pletcher MJ, Fontil V, Modrow MF, Carton T, Chamberlain AM, Todd J, et al. Effectiveness of standard vs enhanced self-measurement of blood pressure paired with a connected smartphone application: a randomized clinical trial. JAMA Intern Med. 2022;182:1025–34.
Google Scholar
Sakboonyarat B, Mungthin M, Hatthachote P, Srichan Y, Rangsin R. Model development to improve primary care services using an innovative network of homecare providers (WinCare) to promote blood pressure control among elderly patients with noncommunicable diseases in Thailand: a prospective cohort study. BMC Prim Care. 2022;23:40.
Google Scholar
Wong AKC, Wong FKY, Chow KKS, Wong SM, Bayuo J, Ho AKY. Effect of a mobile health application with nurse support on quality of life among community-dwelling older adults in Hong Kong: a randomized clinical trial. JAMA Netw Open. 2022;5:e2241137.
Google Scholar
Wong EML, Leung DYP, Tam HL, Ko SY, Leung AYM, Lam SC, et al. Effectiveness of a nurse-led support programme using a mobile application versus phone advice on patients at risk of coronary heart disease – a pilot randomized controlled trial. Risk Manag Health Policy. 2022;15:597–610.
Google Scholar
Xia SF, Maitiniyazi G, Chen Y, Wu XY, Zhang Y, Zhang XY, et al. Web-based tangplan and wechat combination to support self-management for patients with type 2 diabetes: randomized controlled trial. JMIR Mhealth Uhealth. 2022;10:e30571.
Google Scholar
Yang L, Xu J, Kang C, Bai Q, Wang X, Du S, et al. Effects of mobile phone-based telemedicine management in patients with type 2 diabetes mellitus: a randomized clinical trial. Am J Med Sci. 2022;363:224–31.
Google Scholar
Yilmaz E, Uzuner A, Bajgora M, Dogan B, Altikardes ZA, Kavakli Geris B, et al. Effect of eTansiyon smartphone application on hypertension control. Prim Health Care Res Dev. 2022;23:e64.
Google Scholar
Zhang Y, Tao Y, Zhong Y, Thompson J, Rahmani J, Bhagavathula AS, et al. Feedback based on health advice via tracing bracelet and smartphone in the management of blood pressure among hypertensive patients: a community-based RCT trial in Chongqing, China. Medicine. 2022;101:e29346.
Google Scholar
Zhong J, Zhang H, Li Z, Qian D, Zhang Y, Li C, et al. Effect of social app-assisted education and support on glucose control in patients with coronary heart disease and diabetes mellitus. Front Cardiovasc Med. 2022;9:947130.
Google Scholar
Kario K, Nomura A, Harada N, Okura A, Nakagawa K, Tanigawa T, et al. Efficacy of a digital therapeutics system in the management of essential hypertension: the HERB-DH1 pivotal trial. Eur Heart J. 2021;42:4111–22.
Google Scholar
Kario K, Nomura A, Kato A, Harada N, Tanigawa T, So R, et al. Digital therapeutics for essential hypertension using a smartphone application: a randomized, open-label, multicenter pilot study. J Clin Hypertens. 2021;23:923–34.
Google Scholar
Lim SL, Ong KW, Johal J, Han CY, Yap QV, Chan YH, et al. Effect of a smartphone app on weight change and metabolic outcomes in Asian adults with type 2 diabetes: a randomized clinical trial. JAMA Netw Open. 2021;4:e2112417.
Google Scholar
Lim SL, Ong KW, Johal J, Han CY, Yap QV, Chan YH, et al. A smartphone app-based lifestyle change program for prediabetes (D’LITE Study) in a multiethnic Asian population: a randomized controlled trial. Front Nutr. 2021;8:780567.
Google Scholar
Frith G, Carver K, Curry S, Darby A, Sydes A, Symonds S, et al. Changes in patient activation following cardiac rehabilitation using the Active(+)me digital healthcare platform during the COVID−19 pandemic: a cohort evaluation. BMC Health Serv Res. 2021;21:1363.
Google Scholar
Fruhwirth V, Berger L, Gattringer T, Fandler-Höfler S, Kneihsl M, Schwerdtfeger A, et al. Evaluation of a newly developed smartphone app for risk factor management in young patients with ischemic stroke: a pilot study. Front Neurol. 2021;12:791545.
Google Scholar
Gazit T, Gutman M, Beatty AL. Assessment of hypertension control among adults participating in a mobile technology blood pressure self-management program. JAMA Netw Open. 2021;4:e2127008.
Google Scholar
Jia W, Zhang P, Zhu D, Duolikun N, Li H, Bao Y, et al. Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): a cluster randomized trial. PLoS Med. 2021;18:e1003754.
Google Scholar
Li A, Del Olmo MG, Fong M, Sim K, Lymer SJ, Cunich M, et al. Effect of a smartphone application (Perx) on medication adherence and clinical outcomes: a 12-month randomised controlled trial. BMJ Open. 2021;11:e047041.
Google Scholar
Payne Riches S, Piernas C, Aveyard P, Sheppard JP, Rayner M, Albury C, et al. A mobile health salt reduction intervention for people with hypertension: results of a feasibility randomized controlled trial. JMIR Mhealth Uhealth. 2021;9:e26233.
Google Scholar
Tekkeşin A, Hayıroğlu M, Çinier G, Özdemir YS, İnan D, Yüksel G, et al. Lifestyle intervention using mobile technology and smart devices in patients with high cardiovascular risk: a pragmatic randomised clinical trial. Atherosclerosis. 2021;319:21–7.
Google Scholar
Wang CH, Yang HW, Huang HL, Hsiao CY, Jiu BK, Lin C, et al. Long-term effect of device-guided slow breathing on blood pressure regulation and chronic inflammation in patients with essential hypertension using a wearable ECG device. Acta Cardiol Sin. 2021;37:195–203.
Google Scholar
Yan LL, Gong E, Gu W, Turner EL, Gallis JA, Zhou Y, et al. Effectiveness of a primary care-based integrated mobile health intervention for stroke management in rural China (SINEMA): a cluster-randomized controlled trial. PLoS Med. 2021;18:e1003582.
Google Scholar
Yin BD, Tu DH, Yang N, Wang J. The application effect of internet technology on managing patients with hypertension in a medical center: A prospective case-control study. Medicine. 2021;100:e28027.
Google Scholar
Cho SMJ, Lee JH, Shim JS, Yeom H, Lee SJ, Jeon YW, et al. Effect of smartphone-based lifestyle coaching app on community-dwelling population with moderate metabolic abnormalities: randomized controlled trial. J Med Internet Res. 2020;22:e17435.
Google Scholar
Dorsch MP, Cornellier ML, Poggi AD, Bilgen F, Chen P, Wu C, et al. Effects of a Novel Contextual Just-In-Time Mobile App Intervention (LowSalt4Life) on Sodium intake in Adults with hypertension: pilot randomized controlled trial. JMIR Mhealth Uhealth. 2020;8:e16696.
Google Scholar
Freene N, van Berlo S, McManus M, Mair T, Davey R. A Behavioral Change Smartphone App and Program (ToDo-CR) to decrease sedentary behavior in cardiac rehabilitation participants: prospective feasibility cohort study. JMIR Form Res. 2020;4:e17359.
Google Scholar
Gong K, Yan YL, Li Y, Du J, Wang J, Han Y, et al. Mobile health applications for the management of primary hypertension: A multicenter, randomized, controlled trial. Medicine. 2020;99:e19715.
Google Scholar
Kim DY, Kwon H, Nam KW, Lee Y, Kwon HM, Chung YS. Remote management of poststroke patients with a smartphone-based management system integrated in clinical care: prospective, nonrandomized, interventional study. J Med Internet Res. 2020;22:e15377.
Google Scholar
Lee DY, Yoo SH, Min KP, Park CY. Effect of voluntary participation on mobile health care in diabetes management: randomized controlled open-label trial. JMIR Mhealth Uhealth. 2020;8:e19153.
Google Scholar
Lim SL, Johal J, Ong KW, Han CY, Chan YH, Lee YM, et al. Lifestyle intervention enabled by mobile technology on weight loss in patients with nonalcoholic fatty liver disease: randomized controlled trial. JMIR Mhealth Uhealth. 2020;8:e14802.
Google Scholar
Lunde P, Bye A, Bergland A, Grimsmo J, Jarstad E, Nilsson BB. Long-term follow-up with a smartphone application improves exercise capacity post cardiac rehabilitation: a randomized controlled trial. Eur J Prev Cardiol. 2020;27:1782–92.
Google Scholar
Poonprapai P, Lerkiatbundit S, Saengcharoen W. Family support-based intervention using a mobile application provided by pharmacists for older adults with diabetes to improve glycaemic control: a randomised controlled trial. Int J Clin Pharm. 2022;44:680–8.
Google Scholar
Takeyama N, Moriyama M, Kazawa K, Steenkamp M, Rahman MM. A health guidance app to improve motivation, adherence to lifestyle changes and indicators of metabolic disturbances among Japanese civil servants. Int J Environ Res Public Health. 2020;17:8147.
Wang S, Li Y, Tian J, Peng X, Yi L, Du C, et al. A randomized controlled trial of brain and heart health manager-led mHealth secondary stroke prevention. Cardiovasc Diagn Ther. 2020;10:1192–9.
Google Scholar
Wingo BC, Rinker JR, Goss AM, Green K, Wicks V, Cutter GR, et al. Feasibility of improving dietary quality using a telehealth lifestyle intervention for adults with multiple sclerosis. Mult Scler Relat Disord. 2020;46:102504.
Google Scholar
Yang Y, Lee EY, Kim HS, Lee SH, Yoon KH, Cho JH. Effect of a mobile phone-based glucose-monitoring and feedback system for type 2 diabetes management in multiple primary care clinic settings: cluster randomized controlled trial. JMIR Mhealth Uhealth. 2020;8:e16266.
Google Scholar
Yu C, Liu C, Du J, Liu H, Zhang H, Zhao Y, et al. Smartphone-based application to improve medication adherence in patients after surgical coronary revascularization. Am Heart J. 2020;228:17–26.
Google Scholar
Yudi MB, Clark DJ, Tsang D, Jelinek M, Kalten K, Joshi SB, et al. SMARTphone-based, early cardiac REHABilitation in patients with acute coronary syndromes: a randomized controlled trial. Coron Artery Dis. 2021;32:432–40.
Google Scholar
Or CK, Liu K, So MKP, Cheung B, Yam LYC, Tiwari A, et al. Improving self-care in patients with coexisting type 2 diabetes and hypertension by technological surrogate nursing: randomized controlled trial. J Med Internet Res. 2020;22:e16769.
Google Scholar
Sun YQ, Jia YP, Lv JY, Ma GJ. The clinical effects of a new management mode for hypertensive patients: a randomized controlled trial. Cardiovasc Diagn Ther. 2020;10:1805–15.
Google Scholar
Alonso-Domínguez R, García-Ortiz L, Patino-Alonso MC, Sánchez-Aguadero N, Gómez-Marcos MA, Recio-Rodríguez JI. Effectiveness of a multifactorial intervention in increasing adherence to the mediterranean diet among patients with diabetes mellitus type 2: a controlled and randomized study (EMID Study). Nutrients. 2019;11:162.
Apiñaniz A, Cobos-Campos R, Sáez de Lafuente-Moríñigo A, Parraza N, Aizpuru F, Pérez I, et al. Effectiveness of randomized controlled trial of a mobile app to promote healthy lifestyle in obese and overweight patients. Fam Pr. 2019;36:699–705.
Google Scholar
Baron KG, Duffecy J, Richardson D, Avery E, Rothschild S, Lane J. Technology assisted behavior intervention to extend sleep among adults with short sleep duration and prehypertension/stage 1 hypertension: a randomized pilot feasibility study. J Clin Sleep Med. 2019;15:1587–97.
Google Scholar
Choi BG, Dhawan T, Metzger K, Marshall L, Akbar A, Jain T, et al. Image-based mobile system for dietary management in an american cardiology population: pilot randomized controlled trial to assess the efficacy of dietary coaching delivered via a smartphone app versus traditional counseling. JMIR Mhealth Uhealth. 2019;7:e10755.
Google Scholar
Gonzalez-Sanchez J, Recio-Rodriguez JI, Fernandez-delRio A, Sanchez-Perez A, Magdalena-Belio JF, Gomez-Marcos MA, et al. Using a smartphone app in changing cardiovascular risk factors: a randomized controlled trial (EVIDENT II study). Int J Med Inf. 2019;125:13–21.
Google Scholar
Guthrie NL, Berman MA, Edwards KL, Appelbaum KJ, Dey S, Carpenter J, et al. Achieving rapid blood pressure control with digital therapeutics: retrospective cohort and machine learning study. JMIR Cardio. 2019;3:e13030.
Google Scholar
Márquez Contreras E, Márquez Rivero S, Rodríguez García E, López-García-Ramos L, Carlos Pastoriza Vilas J, Baldonedo Suárez A, et al. Specific hypertension smartphone application to improve medication adherence in hypertension: a cluster-randomized trial. Curr Med Res Opin. 2019;35:167–73.
Google Scholar
Patel A, Praveen D, Maharani A, Oceandy D, Pilard Q, Kohli MPS, et al. Association of multifaceted mobile technology-enabled primary care intervention with cardiovascular disease risk management in rural Indonesia. JAMA Cardiol. 2019;4:978–86.
Google Scholar
Prabhakaran D, Jha D, Prieto-Merino D, Roy A, Singh K, Ajay VS, et al. Effectiveness of an mHealth-based electronic decision support system for integrated management of chronic conditions in primary care: the mwellcare cluster-randomized controlled trial. Circulation. 2019;139:380–91.
Google Scholar
Santo K, Singleton A, Rogers K, Thiagalingam A, Chalmers J, Chow CK, et al. Medication reminder applications to improve adherence in coronary heart disease: a randomised clinical trial. Heart. 2019;105:323–9.
Google Scholar
Zha P, Qureshi R, Porter S, Chao YY, Pacquiao D, Chase S, et al. Utilizing a mobile health intervention to manage hypertension in an underserved community. West J Nurs Res. 2020;42:201–9.
Google Scholar
Maddison R, Rawstorn JC, Stewart RAH, Benatar J, Whittaker R, Rolleston A, et al. Effects and costs of real-time cardiac telerehabilitation: randomised controlled non-inferiority trial. Heart. 2019;105:122–9.
Google Scholar
Yamaguchi S, Waki K, Nannya Y, Nangaku M, Kadowaki T, Ohe K. Usage patterns of gluconote, a self-management smartphone app, based on researchkit for patients with type 2 diabetes and prediabetes. JMIR Mhealth Uhealth. 2019;7:e13204.
Google Scholar
Li X, Li T, Chen J, Xie Y, An X, Lv Y, et al. A WeChat-based self-management intervention for community middle-aged and elderly adults with hypertension in guangzhou, china: a cluster-randomized controlled Trial. Int J Environ Res Public Health. 2019;16:4058.
Fukuoka Y, Vittinghoff E, Hooper J. A weight loss intervention using a commercial mobile application in Latino Americans-Adelgaza Trial. Transl Behav Med. 2018;8:714–23.
Google Scholar
Morawski K, Ghazinouri R, Krumme A, Lauffenburger JC, Lu Z, Durfee E, et al. Association of a smartphone application with medication adherence and blood pressure control: the MedISAFE-BP randomized clinical trial. JAMA Intern Med. 2018;178:802–9.
Google Scholar
Pan F, Wu H, Liu C, Zhang X, Peng W, Wei X, et al. Effects of home telemonitoring on the control of high blood pressure: a randomised control trial in the Fangzhuang Community Health Center, Beijing. Aust J Prim Health. 2018;24:398–403.
Google Scholar
Rosario MBD, Lovell NH, Fildes J, Holgate K, Yu J, Ferry C, et al. Evaluation of an mHealth-based adjunct to outpatient cardiac rehabilitation. IEEE J Biomed Health Inf. 2018;22:1938–48.
Google Scholar
Senecal C, Widmer RJ, Johnson MP, Lerman LO, Lerman A. Digital health intervention as an adjunct to a workplace health program in hypertension. J Am Soc Hypertens. 2018;12:695–702.
Google Scholar
Tanaka K, Sasai H, Wakaba K, Murakami S, Ueda M, Yamagata F, et al. Professional dietary coaching within a group chat using a smartphone application for weight loss: a randomized controlled trial. J Multidiscip Health. 2018;11:339–47.
Google Scholar
Balk-Møller NC, Poulsen SK, Larsen TM. Effect of a nine-month web- and app-based workplace intervention to promote healthy lifestyle and weight loss for employees in the social welfare and health care sector: a randomized controlled trial. J Med Internet Res. 2017;19:e108.
Google Scholar
Eyles H, McLean R, Neal B, Jiang Y, Doughty RN, McLean R, et al. A salt-reduction smartphone app supports lower-salt food purchases for people with cardiovascular disease: findings from the SaltSwitch randomised controlled trial. Eur J Prev Cardiol. 2017;24:1435–44.
Google Scholar
Frias J, Virdi N, Raja P, Kim Y, Savage G, Osterberg L. Effectiveness of digital medicines to improve clinical outcomes in patients with uncontrolled hypertension and type 2 diabetes: prospective, open-label, cluster-randomized pilot clinical trial. J Med Internet Res. 2017;19:e246.
Google Scholar
Munster-Segev M, Fuerst O, Kaplan SA, Cahn A. Incorporation of a stress reducing mobile app in the care of patients with type 2 diabetes: a prospective study. JMIR Mhealth Uhealth. 2017;5:e75.
Google Scholar
Muntaner-Mas A, Vidal-Conti J, Borràs PA, Ortega FB, Palou P. Effects of a Whatsapp-delivered physical activity intervention to enhance health-related physical fitness components and cardiovascular disease risk factors in older adults. J Sports Med Phys Fit. 2017;57:90–102.
Plotnikoff RC, Wilczynska M, Cohen KE, Smith JJ, Lubans DR. Integrating smartphone technology, social support and the outdoor physical environment to improve fitness among adults at risk of, or diagnosed with, Type 2 Diabetes: Findings from the ‘eCoFit’ randomized controlled trial. Prev Med. 2017;105:404–11.
Google Scholar
Kim JY, Wineinger NE, Steinhubl SR. The influence of wireless self-monitoring program on the relationship between patient activation and health behaviors, medication adherence, and blood pressure levels in hypertensive patients: a substudy of a randomized controlled trial. J Med Internet Res. 2016;18:e116.
Google Scholar
Ong SW, Jassal SV, Miller JA, Porter EC, Cafazzo JA, Seto E, et al. Integrating a smartphone-based self-management system into usual care of advanced CKD. Clin J Am Soc Nephrol. 2016;11:1054–62.
Google Scholar
Paul L, Wyke S, Brewster S, Sattar N, Gill JM, Alexander G, et al. Increasing physical activity in stroke survivors using STARFISH, an interactive mobile phone application: a pilot study. Top Stroke Rehabil. 2016;23:170–7.
Google Scholar
Willey S, Walsh JK. Outcomes of a mobile health coaching platform: 12-week results of a single-arm longitudinal study. JMIR Mhealth Uhealth. 2016;4:e3.
Google Scholar
Zhou W, Chen M, Yuan J, Sun Y. Welltang – A smart phone-based diabetes management application – Improves blood glucose control in Chinese people with diabetes. Diabetes Res Clin Pr. 2016;116:105–10.
Google Scholar
Seo WK, Kang J, Jeon M, Lee K, Lee S, Kim JH, et al. Feasibility of using a mobile application for the monitoring and management of stroke-associated risk factors. J Clin Neurol. 2015;11:142–8.
Google Scholar
Petrella RJ, Stuckey MI, Shapiro S, Gill DP. Mobile health, exercise and metabolic risk: a randomized controlled trial. BMC Public Health. 2014;14:1082.
Google Scholar
Mira JJ, Navarro I, Botella F, Borrás F, Nuño-Solinís R, Orozco D, et al. A Spanish pillbox app for elderly patients taking multiple medications: randomized controlled trial. J Med Internet Res. 2014;16:e99.
Google Scholar
Waki K, Fujita H, Uchimura Y, Omae K, Aramaki E, Kato S, et al. DialBetics: a novel smartphone-based self-management support system for type 2 diabetes patients. J Diabetes Sci Technol. 2014;8:209–15.
Google Scholar
Widmer RJ, Allison TG, Keane B, Dallas A, Lerman LO, Lerman A. Using an online, personalized program reduces cardiovascular risk factor profiles in a motivated, adherent population of participants. Am Heart J. 2014;167:93–100.
Google Scholar
Moore JO, Marshall M, Judge D, Moss F, SJ Gilroy, Crocker J, et al. Technology-supported apprenticeship in the management of hypertension: a randomized controlled trial. J Clin Outcomes Manag. 2014;21:110–2.
Logan AG, Irvine MJ, McIsaac WJ, Tisler A, Rossos PG, Easty A, et al. Effect of home blood pressure telemonitoring with self-care support on uncontrolled systolic hypertension in diabetics. Hypertension. 2012;60:51–7.
Google Scholar
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;34:1934–42.
Google Scholar
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: an open-label, international, multicenter, randomized study. Diabetes Care. 2010;33:109–15.
Google Scholar
Kalagara R, Chennareddy S, Scaggiante J, Matsoukas S, Bhimani A, Smith C, et al. Blood pressure management through application-based telehealth platforms: a systematic review and meta-analysis. J Hypertens. 2022;40:1249–56.
Google Scholar
Kassavou A, Wang M, Mirzaei V, Shpendi S, Hasan R. The association between smartphone app-based self-monitoring of hypertension-related behaviors and reductions in high blood pressure: systematic review and meta-analysis. JMIR Mhealth Uhealth. 2022;10:e34767.
Google Scholar
Jakob R, Harperink S, Rudolf AM, Fleisch E, Haug S, Mair JL, et al. Factors influencing adherence to mhealth apps for prevention or management of noncommunicable diseases: systematic review. J Med Internet Res. 2022;24:e35371.
Google Scholar
Yao Y, Guo Y, Lip GYH. The effects of implementing a mobile health-technology supported pathway on atrial fibrillation-related adverse events among patients with multimorbidity: the mAFA-II randomized clinical trial. JAMA Netw Open. 2021;4:e2140071.
Google Scholar
The American Heart Association. Download the HF Helper App. https://www.heart.org/en/health-topics/heart-failure/heart-failure-tools-resources/hf-helper-app. Accessed May 21, 2024.
Siafi E, Konstantinidis D, Andrikou I, Polyzos D, Drogkaris S, Manta E, et al. Blood pressure management with the esh care App – Preliminary results. J Hypertens. 2022;40:e278.
Google Scholar
Kotecha D, Chua WWL, Fabritz L, Hendriks J, Casadei B, Schotten U, et al. European Society of Cardiology smartphone and tablet applications for patients with atrial fibrillation and their health care providers. Europace. 2018;20:225–33.
Google Scholar
Zhang W, Zhang S, Deng Y, Wu S, Ren J, Sun G, et al. Trial of intensive blood-pressure control in older patients with hypertension. N. Engl J Med. 2021;385:1268–79.
Google Scholar
Fujiwara T, Hoshide S, Kanegae H, Kario K. Cardiovascular event risks associated with masked nocturnal hypertension defined by home blood pressure monitoring in the J-HOP nocturnal blood pressure study. Hypertension. 2020;76:259–66.
Google Scholar
Fujiwara T, Yano Y, Hoshide S, Kanegae H, Kario K. Association of cardiovascular outcomes with masked hypertension defined by home blood pressure monitoring in a japanese general practice population. JAMA Cardiol. 2018;3:583–90.
Google Scholar
Staplin N, de la Sierra A, Ruilope LM, Emberson JR, Vinyoles E, Gorostidi M, et al. Relationship between clinic and ambulatory blood pressure and mortality: an observational cohort study in 59,124 patients. Lancet. 2023;401:2041–50.
Google Scholar
McLean G, Band R, Saunderson K, Hanlon P, Murray E, Little P, et al. Digital interventions to promote self-management in adults with hypertension systematic review and meta-analysis. J Hypertens. 2016;34:600–12.
Google Scholar
Tucker KL, Sheppard JP, Stevens R, Bosworth HB, Bove A, Bray EP, et al. Self-monitoring of blood pressure in hypertension: A systematic review and individual patient data meta-analysis. PLoS Med. 2017;14:e1002389.
Google Scholar
Shan R, Ding J, Plante TB, Martin SS. Mobile health access and use among individuals with or at risk for cardiovascular disease: 2018 Health Information National Trends Survey (HINTS). J Am Heart Assoc. 2019;8:e014390.
Google Scholar
U.S. Food and Drug Administration. Policy for Device Software Functions and Mobile Medical Applications. Guidance for Industry and Food and Drug Administration Staff. 2022. https://www.fda.gov/regulatory-information/search-fda-guidance-documents/policy-device-software-functions-and-mobile-medical-applications).
NS MEDICAL DEVICES. Biospectal gets CE Mark for OptiBP blood pressure monitoring app. https://www.nsmedicaldevices.com/company-news/biospectal-gets-ce-mark-for-optibp-blood-pressure-monitoring-app/. Accessed May 21, 2024.
Degott J, Ghajarzadeh-Wurzner A, Hofmann G, Proença M, Bonnier G, Lemkaddem A, et al. Smartphone based blood pressure measurement: accuracy of the OptiBP mobile application according to the AAMI/ESH/ISO universal validation protocol. Blood Press Monit. 2021;26:441–8.
Google Scholar
Hofmann G, Proença M, Degott J, Bonnier G, Lemkaddem A, Lemay M, et al. A novel smartphone app for blood pressure measurement: a proof-of-concept study against an arterial catheter. J Clin Monit Comput. 2023;37:249–59.
Google Scholar
Omboni S, Ferrari R. The role of telemedicine in hypertension management: focus on blood pressure telemonitoring. Curr Hypertens Rep. 2015;17:535.
Google Scholar
Nomura A, Tanigawa T, Kario K, Igarashi A. Cost-effectiveness of digital therapeutics for essential hypertension. Hypertens Res. 2022;45:1538–48.
Google Scholar
Murphy AR, Low CA. Another step (count) towards leveraging mobile health data for clinical prediction. Lancet Digit Health. 2021;3:e687–e688.
Google Scholar
Nishizawa M, Hoshide S, Okawara Y, Matsuo T, Kario K. Strict blood pressure control achieved using an ICT-based home blood pressure monitoring system in a catastrophically damaged area after a disaster. J Clin Hypertens (Greenwich). 2017;19:26–9.
Google Scholar
Frandsen TF, Nielsen MFB, Eriksen MB. Avoiding searching for outcomes called for additional search strategies: a study of Cochrane review searches. J Clin Epidemiol. 2022;149:83–8.
Google Scholar
