Author(s):

• Aikaterini Kassavou
• Michael Wang  
• Venus Mirzaei  
• Sonia Shpendi  
• Rana Hasan

Abstract:

Background: Self-monitoring of behavior can support lifestyle modifications; however, we do not know whether such interventions are effective in supporting positive changes in hypertension-related health behaviors and thus in reducing blood pressure in patients treated for hypertension.

Objective: This systematic literature review evaluates the extent to which smartphone app–based self-monitoring of health behavior supports reductions in blood pressure and changes in hypertension-related behaviors. It also explores the behavioral components that might explain intervention effectiveness.

Methods: A systematic search of 7 databases was conducted in August 2021. Article screening, study and intervention coding, and data extraction were completed independently by reviewers. The search strategy was developed using keywords from previous reviews and relevant literature. Trials involving adults, published after the year 2000, and in the English language were considered for inclusion. The random-effects meta-analysis method was used to account for the distribution of the effect across the studies.

Results: We identified 4638 articles, of which 227 were included for full-text screening. A total of 15 randomized controlled trials were included in the review. In total, 7415 patients with hypertension were included in the meta-analysis. The results indicate that app-based behavioral self-monitoring interventions had a small but significant effect in reducing systolic blood pressure (SBP), on average, by 1.64 mmHg (95% CI 2.73-0.55, n=7301; odds ratio [OR] 1.60, 95% CI 0.74-3.42, n=114) and in improving changes in medication adherence behavior (standardized mean difference [SMD] 0.78, 95% CI 0.22-1.34) compared to usual care or minimal intervention. The review found the intervention had a small effect on supporting improvements in healthy diet by changing habits related to high sodium food (SMD –0.44, 95% CI –0.79 to –0.08) and a trend, although insignificant, toward supporting smoking cessation, low alcohol consumption, and better physical activity behaviors. A subgroup analysis found that behavioral self-monitoring interventions combined with tailored advice resulted in higher and significant changes in both SBP and diastolic blood pressure (DBP) in comparison to those not providing tailored advice (SBP: –2.92 mmHg, 95% CI –3.94 to –1.90, n=3102 vs –0.72 mmHg, 95% CI –1.67 to 0.23, n=4199, χ²=9.65, P=.002; DBP: –2.05 mmHg, 95% CI –3.10 to –1.01, n=968 vs 1.54 mmHg, 95% CI –0.53 to 3.61, n=400, χ²=9.19, P=.002).

Conclusions: Self-monitoring of hypertension-related behaviors via smartphone apps combined with tailored advice has a modest but potentially clinically significant effect on blood pressure reduction. Future studies could use rigorous methods to explore its effects on supporting changes in both blood pressure and hypertension-related health behaviors to inform recommendations for policy making and service provision.

Documentation:

https://doi.org/10.2196/34767

References:

1. Zhou B, Carrillo-Larco RM, Danaei G, Riley LM, Paciorek CJ, Stevens GA, et al. . [CrossRef]
2. Hypertension. World Health Organization. 2021.   URL: https://www.who.int/health-topics/hypertension#tab=tab_1 [accessed 2021-08-23]
3. Mazzaglia G, Ambrosioni E, Alacqua M, Filippi A, Sessa E, Immordino V, et al. Adherence to antihypertensive medications and cardiovascular morbidity among newly diagnosed hypertensive patients. Circulation 2009 Oct 20;120(16):1598-1605. [CrossRef] [Medline]
4. York Health Economics Consortium, School of Pharmacy, University of London. Evaluation of the Scale, Causes and Costs of Waste Medicines: Final Report. 2010 Nov.   URL: https:/​/discovery.​ucl.ac.uk/​id/​eprint/​1350234/​1/​Evaluation_of_NHS_Medicines_Waste__web_publication_version.​pdf [accessed 2022-06-07]
5. Schroeder K, Fahey T, Ebrahim S. Interventions for improving adherence to treatment in patients with high blood pressure in ambulatory settings. Cochrane Database Syst Rev 2004(3). [CrossRef]
6. Diaz KM, Shimbo D. Physical activity and the prevention of hypertension. Curr Hypertens Rep 2013 Dec 20;15(6):659-668 [FREE Full text] [CrossRef] [Medline]
7. Huai P, Xun H, Reilly KH, Wang Y, Ma W, Xi B. Physical Activity and Risk of Hypertension. Hypertension 2013 Dec;62(6):1021-1026. [CrossRef]
8. He FJ, Li J, Macgregor GA. Effect of longer term modest salt reduction on blood pressure: Cochrane systematic review and meta-analysis of randomised trials. BMJ 2013 Apr 03;346:f1325-f1325 [FREE Full text] [CrossRef] [Medline]
9. Strazzullo P, D’Elia L, Kandala N, Cappuccio FP. Salt intake, stroke, and cardiovascular disease: meta-analysis of prospective studies. BMJ 2009 Nov 24;339(nov24 1):b4567-b4567 [FREE Full text] [CrossRef] [Medline]
10. John J, Ziebland S, Yudkin P, Roe L, Neil H. Effects of fruit and vegetable consumption on plasma antioxidant concentrations and blood pressure: a randomised controlled trial. The Lancet 2002 Jun;359(9322):1969-1974. [CrossRef]
11. Roerecke M, Kaczorowski J, Tobe SW, Gmel G, Hasan OSM, Rehm J. The effect of a reduction in alcohol consumption on blood pressure: a systematic review and meta-analysis. The Lancet Public Health 2017 Feb;2(2):e108-e120. [CrossRef]
12. Huxley RR, Woodward M. Cigarette smoking as a risk factor for coronary heart disease in women compared with men: a systematic review and meta-analysis of prospective cohort studies. The Lancet 2011 Oct;378(9799):1297-1305. [CrossRef]
13. Quality and Outcomes Framework, 2020-21. NHS Digital. 2021 Sep 30.   URL: https:/​/digital.​nhs.uk/​data-and-information/​publications/​statistical/​quality-and-outcomes-framework-achievement-prevalence-and-exceptions-data/​2020-21 [accessed 2022-06-07]
14. Nieuwlaat R, Wilczynski N, Navarro T, Hobson N, Jeffery R, Keepanasseril A, et al. Interventions for enhancing medication adherence. Cochrane Database Syst Rev 2014 Nov 20(11):CD000011 [FREE Full text] [CrossRef] [Medline]
15. Acin M, Rueda J, Saiz L, Parent MV, Alzueta N, Solà I, et al. Alcohol intake reduction for controlling hypertension. Cochrane Database Syst Rev 2020(9). [CrossRef]
16. Lee L, Mulvaney C, Wong Y, Chan E, Watson M, Lin H. Walking for hypertension. Cochrane Database Syst Rev 2021(2). [CrossRef]
17. Kassavou A, Sutton S. Automated telecommunication interventions to promote adherence to cardio-metabolic medications: meta-analysis of effectiveness and meta-regression of behaviour change techniques. Health Psychol Rev 2018 Mar 12;12(1):25-42. [CrossRef] [Medline]
18. Armitage LC, Kassavou A, Sutton S. Do mobile device apps designed to support medication adherence demonstrate efficacy? A systematic review of randomised controlled trials, with meta-analysis. BMJ Open 2020 Jan 30;10(1):e032045 [FREE Full text] [CrossRef] [Medline]
19. Berry R, Kassavou A, Sutton S. Does self-monitoring diet and physical activity behaviors using digital technology support adults with obesity or overweight to lose weight? A systematic literature review with meta-analysis. Obes Rev 2021 Oct 30;22(10):e13306. [CrossRef] [Medline]
20. The text message is 20 years old today. Ofcom. 2012 Dec 03.   URL: https:/​/www.​ofcom.org.uk/​about-ofcom/​latest/​media/​media-releases/​2012/​the-text-message-is-20-years-old-today [accessed 2021-08-22]
21. Medicines adherence: involving patients in decisions about prescribed medicines and supporting adherence. National Institute for Health and Care Excellence. 2009 Jan 28.   URL: https://www.nice.org.uk/guidance/cg76 [accessed 2022-06-06]
22. Global strategy on digital health 2020-2025. World Health Organization. 2021.   URL: https://apps.who.int/iris/bitstream/handle/10665/344249/9789240020924-eng.pdf [accessed 2021-08-23]
23. Spaulding EM, Marvel FA, Piasecki RJ, Martin SS, Allen JK. User Engagement With Smartphone Apps and Cardiovascular Disease Risk Factor Outcomes: Systematic Review. JMIR Cardio 2021 Feb 03;5(1):e18834 [FREE Full text] [CrossRef] [Medline]
24. French D, Sutton S. Reactivity of measurement in health psychology: how much of a problem is it? What can be done about it? Br J Health Psy. 2010 2010 Dec 24:15-468. [CrossRef]
25. McCambridge J, Kypri K. Can simply answering research questions change behaviour? Systematic review and meta analyses of brief alcohol intervention trials. PLoS One 2011 Oct 5;6(10):e23748 [FREE Full text] [CrossRef] [Medline]
26. McCambridge J, Witton J, Elbourne DR. Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. J Clin Epidemiol 2014 Mar;67(3):267-277 [FREE Full text] [CrossRef] [Medline]
27. Haase J, Farris KB, Dorsch MP. Mobile Applications to Improve Medication Adherence. Telemed J E Health 2017 Feb;23(2):75-79. [CrossRef] [Medline]
28. Park JYE, Li J, Howren A, Tsao NW, De Vera M. Mobile Phone Apps Targeting Medication Adherence: Quality Assessment and Content Analysis of User Reviews. JMIR Mhealth Uhealth 2019 Jan 31;7(1):e11919 [FREE Full text] [CrossRef] [Medline]
29. 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 May 28;7(5):e13645 [FREE Full text] [CrossRef] [Medline]
30. Xu H, Long H. The Effect of Smartphone App-Based Interventions for Patients With Hypertension: Systematic Review and Meta-Analysis. JMIR Mhealth Uhealth 2020 Oct 19;8(10):e21759 [FREE Full text] [CrossRef] [Medline]
31. JMIR Publications.   URL: http://www.jmir.org/search [accessed 2022-06-07]
32. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W, et al. The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: building an international consensus for the reporting of behavior change interventions. Ann Behav Med 2013 Aug;46(1):81-95. [CrossRef] [Medline]
33. Higgins J, Savović J, Page M, Elbers R, Sterne J. Chapter 8: Assessing risk of bias in a randomized trial. Cochrane Handbook for Systematic Reviews of Interventions, version 6.3 (updated February 2022). 2022.   URL: https://training.cochrane.org/handbook/current/chapter-08 [accessed 2020-06-22]
34. RoB 2: A revised Cochrane risk-of-bias tool for randomized trials. Cochrane Methods Bias.   URL: https://methods.cochrane.org/bias/resources/rob-2-revised-cochrane-risk-bias-tool-randomized-trials [accessed 2020-06-16]
35. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003 Sep 06;327(7414):557-560 [FREE Full text] [CrossRef] [Medline]
36. Higgins J, Li T, Deeks J. Chapter 6: Choosing effect measures and computing estimates of effect. Cochrane Handbook for Systematic Reviews of Interventions, version 6.3 (updated February 2022). 2022.   URL: https://training.cochrane.org/handbook/current/chapter-06 [accessed 2020-06-14]
37. Deeks J, Higgins J, Douglas A. Chapter 10: Analysing data and undertaking meta-analyses. Cochrane Handbook for Systematic Reviews of Interventions, version 6.3 (updated February 2022). 2022.   URL: https://training.cochrane.org/handbook/current/chapter-10 [accessed 2022-06-07]
38. Michie S, Prestwich A, de Bruin M. Importance of the nature of comparison conditions for testing theory-based interventions: reply. Health Psychol 2010 Sep;29(5):468-470. [CrossRef] [Medline]
39. Cochrane RevMan. Cochrane Training.   URL: https://training.cochrane.org/online-learning/core-software-cochrane-reviews/revman [accessed 2021-11-14]
40. Chandler J, Sox L, Kellam K, Feder L, Nemeth L, Treiber F. Impact of a Culturally Tailored mHealth Medication Regimen Self-Management Program upon Blood Pressure among Hypertensive Hispanic Adults. Int J Environ Res Public Health 2019 Apr 06;16(7) [FREE Full text] [CrossRef] [Medline]
41. 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 Apr 23;7(4):e10755 [FREE Full text] [CrossRef] [Medline]
42. 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 Aug 10;8(8):e16696 [FREE Full text] [CrossRef] [Medline]
43. 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 Jun 01;178(6):802-809 [FREE Full text] [CrossRef] [Medline]
44. Persell SD, Peprah YA, Lipiszko D, Lee JY, Li JJ, Ciolino JD, et al. Effect of Home Blood Pressure Monitoring via a Smartphone Hypertension Coaching Application or Tracking Application on Adults With Uncontrolled Hypertension: A Randomized Clinical Trial. JAMA Netw Open 2020 Mar 02;3(3):e200255 [FREE Full text] [CrossRef] [Medline]
45. Widmer RJ, Allison TG, Lennon R, Lopez-Jimenez F, Lerman LO, Lerman A. Digital health intervention during cardiac rehabilitation: A randomized controlled trial. Am Heart J 2017 Jun;188:65-72. [CrossRef] [Medline]
46. Del Rosario MB, 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 Inform 2018 Nov;22(6):1938-1948. [CrossRef]
47. 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 Feb 27;105(4):323-329. [CrossRef] [Medline]
48. Petrella RJ, Stuckey MI, Shapiro S, Gill DP. Mobile health, exercise and metabolic risk: a randomized controlled trial. BMC Public Health 2014 Oct 18;14:1082 [FREE Full text] [CrossRef] [Medline]
49. Gong K, Yan Y, 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 (Baltimore) 2020 Apr;99(16):e19715 [FREE Full text] [CrossRef] [Medline]
50. 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 Sep;24(13):1435-1444. [CrossRef] [Medline]
51. Sarfo FS, Treiber F, Gebregziabher M, Adamu S, Nichols M, Singh A, PINGS Team. Phone-based intervention for blood pressure control among Ghanaian stroke survivors: A pilot randomized controlled trial. Int J Stroke 2019 Aug 22;14(6):630-638. [CrossRef] [Medline]
52. Prabhakaran D, Jha D, Prieto-Merino D, Roy A, Singh K, Ajay VS, Members of the Research Steering Committee‚ Investigators‚ Members of the Data SafetyMonitoring Board. 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 Jan 15;139(3):380-391 [FREE Full text] [CrossRef] [Medline]
53. Tian M, Ajay VS, Dunzhu D, Hameed SS, Li X, Liu Z, et al. A Cluster-Randomized, Controlled Trial of a Simplified Multifaceted Management Program for Individuals at High Cardiovascular Risk (SimCard Trial) in Rural Tibet, China, and Haryana, India. Circulation 2015 Sep 01;132(9):815-824 [FREE Full text] [CrossRef] [Medline]
54. 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 Nov 28;27(16):1782-1792 [FREE Full text] [CrossRef] [Medline]
55. Lawes CM, Hoorn SV, Rodgers A. Global burden of blood-pressure-related disease, 2001. The Lancet 2008 May;371(9623):1513-1518. [CrossRef]
56. Prospective Studies Collaboration. Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. The Lancet 2002 Dec;360(9349):1903-1913. [CrossRef]
57. Kassavou A, Court CA, Mirzaei V, Brimicombe J, Edwards S, Sutton S. Process Evaluation of MAPS: A Highly Tailored Digital Intervention to Support Medication Adherence in Primary Care Setting. Front Public Health 2021 Dec 20;9:806168 [FREE Full text] [CrossRef] [Medline]