Skip to main content
SpringerLink
Log in

Self-monitoring to increase physical activity in patients with cardiovascular disease: a systematic review and meta-analysis

  • Review
  • Published:
Aging Clinical and Experimental Research Aims and scope Submit manuscript

Abstract

Background and aims

It is important to encourage physical activity in patients with cardiovascular disease (CVD), and self-monitoring is considered to contribute to increased physical activity. However, the effects of self-monitoring on CVD patients remain to be established. In this study, we examined the influence of self-monitoring on physical activity of patients with CVD via a systematic review and meta-analysis.

Methods

Screening of randomized controlled trials only was undertaken twice on PubMed (date of appraisal: August 29, 2017). The inclusion criteria included outpatients with CVD, interventions for them, daily step counts as physical activity included in the outcome, and self-monitoring included in the intervention. Assessments of the risk of bias and meta-analysis in relation to the mean change of daily step counts were conducted to verify the effects of self-monitoring.

Results

From 205 studies retrieved on PubMed, six studies were included, with the oldest study published in 2005. Participants included 693 patients of whom 541 patients completed each study program. Their mean age was 60.8 years, and the ratio of men was 79.6%. From these 6 studies, a meta-analysis was conducted with 269 patients of 4 studies including only RCTs with step counts in the intervention group and the control group, and self-monitoring significantly increased physical activity (95% confidence interval, 1916–3090 steps per day, p < 0.05). The average intervention period was about 5 months. Moreover, four studies involved intervention via the internet, and five studies confirmed the use of self-monitoring combined with other behavior change techniques.

Conclusion

The results suggest that self-monitoring of physical activity by patients with CVD has a significantly positive effect on their improvement. Moreover, the trend toward self-monitoring combined with setting counseling and activity goals, and increased intervention via the internet, may lead to the future development and spread of self-monitoring for CVD patients.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

BCTs:

Behavior change techniques

BMI:

Body mass index

CI:

Confidence interval

CVD:

Cardiovascular disease

MD:

Mean difference

RCT:

Randomized controlled trial

SMD:

Standardized mean difference

References

  1. Roger VL (2013) Epidemiology of heart failure. Circ Res 113:646–656

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. WHO (2017 ) The top 10 causes of death. WHO. http://www.who.int/mediacentre/factsheets/fs310/en/. Accessed 30 Oct 2017

  3. Kalogeropoulos VV, Georgiopoulou SB, Kritchevsky BM, Psaty NL, Smith AB, Newman et al (2009) Epidemiology of incident heart failure in a contemporary elderly population: the health, aging, and body composition study. Arch Intern Med 169:708–715

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. DH Cardiovascular Disease Team (2013) Cardiovascular disease outcomes strategy: improving outcomes for people with or at risk of cardiovascular disease. Department of Health, London,

    Google Scholar 

  5. Leon AS, Franklin BA, Costa F, Balady GJ, Berra KA, Stewart KJ et al (2005) Cardiac rehabilitation and secondary prevention of coronary heart disease. Circulation 111:369–376

    Article  PubMed  Google Scholar 

  6. WHO (2010) The atlas of heart disease and stroke. http://www.who.int/cardiovascular_diseases/resources/atlas/en/. Accessed 30 Nov 2017

  7. WHO (2013) The World Health Report 2002—reducing risks, promoting healthy life. http://www.who.int/whr/2002/en/. Accessed 30 Nov 2017

  8. Ayabe M, Brubaker PH, Dobrosielski D, Miller HS, Kiyonaga A, Shindo M et al (2008) Target step count for the secondary prevention of cardiovascular disease. Circ J 72:299–303

    Article  PubMed  Google Scholar 

  9. Garber CE, Blissmer B, Deschenes MR, Franklin BA, Lamonte MJ, Lee IM et al (2011) Quantity and quality of exercise for developing and maintain cardiorespiratory, musculoskeletal, and neuromotor fitness in apparently healthy adults. Med Sci Sports Exerc 43:1134–1359

    Google Scholar 

  10. Tudor-Locke C, Craig CL, Aoyagi Y, Bell RC, Croteau KA, De Bourdeaudhuij I et al (2011) How many steps/day are enough? For older adults and special populations. Int J Behav Nutr Phys Act 8:80

    Article  PubMed  PubMed Central  Google Scholar 

  11. Bravata DM, Smith-Spangler C, Sundaram V, Gienger AL, Lin N, Lewis R et al (2007) Using pedometers to increase physical activity and improve health: a systematic review. JAMA 298:2296–2304

    Article  CAS  PubMed  Google Scholar 

  12. US Department of Health and Human Services (1996) Physical activity and health: a report of the surgeon general, US Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Atlanta

  13. Franco OH (2005) Cardiovascular disease prevention: from meta-analyses to life expectancies. PrintPartners Ipskamp, Enschede

    Google Scholar 

  14. Anderson L, Thompson DR, Oldridge N, Zwisler AD, Rees K, Martin N et al. (2016) Exercise-based cardiac rehabilitation for coronary heart disease. Cochrane Database Syst Rev (1):CD001800. https://doi.org/10.1002/14651858.CD001800.pub3

  15. Bäck M (2012) Exercise and physical activity in relation to kinesiophobia and cardiac risk markers in coronary artery disease. Aidla Trading AB/Kompendiet, Gothenburg

    Google Scholar 

  16. Kesaniemi YK, Danforth E Jr, Jensen MD, Kopelman PG, Lefebvre P, Reeder BA (2001) Dose-response issues concerning physical activity and health: an evidence-based symposium. Med Sci Sports Exerc 33:S351–S358

    Article  CAS  PubMed  Google Scholar 

  17. Nelson ME, Layne JE, Bernstein MJ, Nuernberger A, Castaneda C, Kaliton D et al (2004) The effects of multidimensional home-based exercise on functional performance in elderly people. J Gerontol A Biol Sci Med Sci 59:154–160

    Article  PubMed  Google Scholar 

  18. Stewart RAH, Held C, Hadziosmanovic N, Armstrong PW, Cannon CP, Granger CB et al (2017) Physical activity and mortality in patients with stable coronary heart disease. J Am Coll Cardiol 70:1689–1700

    Article  PubMed  Google Scholar 

  19. Fitzgerald JD, Johnson L, Hire DG, Ambrosius WT, Anton SD, Dodson JA et al (2015) Association of objectively measured physical activity with cardiovascular risk in mobility-limited older adults. J Am Heart Assoc 4:e001288

    Article  PubMed  PubMed Central  Google Scholar 

  20. Abraham C, Michie S (2008) A taxonomy of behavior change techniques used in interventions. Health Psychol 27:379–387

    Article  PubMed  Google Scholar 

  21. Michie S, Richardson M, Johnston M, Abraham C, Francis J, Hardeman W et al (2013) 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 46:81–95

    Article  PubMed  Google Scholar 

  22. Khaled R, James N, Biddle R (2005) An analysis of persuasive technology tool strategies. https://www.researchgate.net/publication/221253988_An_Analysis_of_Persuasive_Technology_Tool_Strategies. Accessed 16 Nov 2017

  23. Bird EL, Baker G, Mutrie N, Ogilvie D, Sahlqvist S, Powell J (2013) Behavior change techniques used to promote walking and cycling: a systematic review. Health Psychol 32:829–838

    Article  PubMed  PubMed Central  Google Scholar 

  24. Kang M, Marshall SJ, Barreira TV, Lee JO (2009) Effect of pedometer-based physical activity interventions: a meta-analysis. Res Q Exerc Sport 80:648–655

    PubMed  Google Scholar 

  25. Tudor-Locke C (2010) Steps to better cardiovascular health: how many steps does it take to achieve good health and how confident are we in this number? Curr Cardiovasc Risk Rep 4:271–276

    Article  PubMed  PubMed Central  Google Scholar 

  26. Izawa KP, Watanabe S, Oka K, Hiraki K, Morio Y, Kasahara Y et al (2013) Usefulness of step counts to predict mortality in Japanese patients with heart failure. Am J Cardiol 111:1767–1771

    Article  PubMed  Google Scholar 

  27. Harris TJ, Owen CG, Victor CR, Adams R, Ekelund U, Cook DG (2009) A comparison of questionnaire, accelerometer, and pedometer: measures in older people. Med Sci Sports Exerc 41:1392–1402

    Article  PubMed  Google Scholar 

  28. Williams SL, French DP (2011) What are the most effective intervention techniques for changing physical activity self-efficacy and physical activity behaviour-and are they the same? Health Educ Res 26:308–322

    Article  CAS  PubMed  Google Scholar 

  29. Ferrier S, Blanchard CM, Vallis M, Giacomantonio N (2011) Behavioural interventions to increase the physical activity of cardiac patients: a review. Eur J Cardiovasc Prev Rehabil 18:15–32

    Article  PubMed  Google Scholar 

  30. ter Hove N, Huisstede BM, Stam HJ, van Domburg RT, Sunamura M, van den Berg-Emons R et al (2015) Does cardiac rehabilitation after an acute cardiac syndrome lead to changes in physical activity habits? Systematic review. Phys Ther 95:167–179

    Article  Google Scholar 

  31. Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD et al (2011) The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ 343:d5928

    Article  PubMed  PubMed Central  Google Scholar 

  32. Devi R, Powell J, Singh S (2014) A web-based program improves physical activity outcomes in a primary care angina population: randomized controlled trial. J Med Internet Res 16:e186

    Article  PubMed  PubMed Central  Google Scholar 

  33. Izawa KP, Watanabe S, Omiya K, Hirano Y, Oka K, Osada N et al (2005) Effect of the self-monitoring approach on exercise maintenance during cardiac rehabilitation: a randomized, controlled trial. Am J Phys Med Rehabil 84:313–321

    Article  PubMed  Google Scholar 

  34. Izawa KP, Watanabe S, Hiraki K, Morio Y, Kasahara Y, Takeichi N et al (2012) Determination of the effectiveness of accelerometer use in the promotion of physical activity in cardiac patients: a randomized controlled trial. Arch Phys Med Rehabil 93:1896–1902

    Article  PubMed  Google Scholar 

  35. Martin SS, Feldman DI, Blumenthal RS, Jones SR, Post WS, McKibben RA et al (2015) mActive: a randomized clinical trial of an automated mhealth intervention for physical activity promotion. J Am Heart Assoc 4:e002239

    Article  PubMed  PubMed Central  Google Scholar 

  36. Reid RD, Morrin LI, Beaton LJ, Papadakis S, Kocourek J, McDonnell L et al (2012) Randomized trial of an internet-based computer-tailored expert system for physical activity in patients with heart disease. Eur J Prev Cardiol 19:1357–1364

    Article  PubMed  Google Scholar 

  37. Thorup C, Hansen J, Gronkjaer M, Andreasen JJ, Nielsen G, Sorensen EE et al (2016) Cardiac patients’ walking activity determined by a step counter in cardiac telerehabilitation: data from the intervention arm of a randomized controlled trial. J Med Internet Res 18:e69

    Article  PubMed  PubMed Central  Google Scholar 

  38. Harris TJ, Owen CG, Victor CR, Adams R, Cook DG (2009) What factors are associated with physical activity in older people, assessed objectively by accelerometry? Br J Sports Med 43:442–450

    Article  CAS  PubMed  Google Scholar 

  39. Klompstra L, Jaarsma T, Strömberg A (2015) Physical activity in patients with heart failure: barriers and motivations with special focus on sex differences. Patient Preference Adherence 9:1603–1610

    Article  PubMed  PubMed Central  Google Scholar 

  40. Slovinec D’Angelo ME, Pelletier LG, Reid RD, Huta V (2014) The roles of self-efficacy and motivation in the prediction of short- and long-term adherence to exercise among patients with coronary heart disease. Health Psychol 33:1344–1353

    Article  PubMed  Google Scholar 

  41. Zutz A, Ignaszewski A, Bates J, Lear SA (2007) Utilization of the internet to deliver cardiac rehabilitation at a distance: a pilot study. Telemed J E Health 13:323–330

    Article  PubMed  Google Scholar 

  42. Kanai M, Nozoe M, Izawa KP, Takeuchi Y, Kubo H, Mase K et al (2017) Promoting physical activity in hospitalized patients with mild ischemic stroke: a pilot study. Top Stroke Rehabil 24:256–261

    Article  PubMed  Google Scholar 

  43. Gleeson-Kreig JM (2006) Self-monitoring of physical activity: effects on self-efficacy and behavior in people with type 2 diabetes. Diabetes Educ 32:69–77

    Article  PubMed  Google Scholar 

  44. Vooijs M, Alpay LL, Snoeck-Stroband JB, Beerthuizen T, Siemonsma PC, Abbink JJ et al (2014) Validity and usability of low-cost accelerometers for internet-based self-monitoring of physical activity in patients with chronic obstructive pulmonary disease. Interact J Med Res 3:e14

    Article  PubMed  PubMed Central  Google Scholar 

  45. Uman LS (2011) Systematic reviews and meta-analyses. J Can Acad Child Adolesc Psychiatry 20:57–59

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was benefitted by the support and encouragement of Taku Shinoda (Kobe University Graduate School of Health Sciences, Kobe University), Masashi Kanai (Kobe University Graduate School of Health Sciences), and Masato Ogawa (Kobe University Graduate School of Health Sciences). We also thank Dr. Minato Nakazawa, Department of International Health, Graduate School of Health Sciences, Kobe University, for statistical support in the present study.

Funding

This work was supported by a Grant from JSPS KAKENHI (No. JP17K01500). Neither the authors nor their associated institutions report any financial relationships with industry relevant to this study.

Author information

Authors and Affiliations

  1. Department of Health Science, Faculty of Medicine, Kobe University, Kobe, Japan

    Yuji Kanejima

  2. Department of Physical Therapy, Kokura Rehabilitation College, Kitakyushu, Japan

    Masahiro Kitamura

  3. Department of Public Health, Graduate School of Health Science, Kobe University, 7-10-2 Tomogaoka, Suma-ku, Kobe, 654-0142, Japan

    Masahiro Kitamura & Kazuhiro P. Izawa

  4. Cardiovascular stroke Renal Project (CRP), Kobe, Japan

    Yuji Kanejima, Masahiro Kitamura & Kazuhiro P. Izawa

Authors
  1. Yuji Kanejima
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masahiro Kitamura
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kazuhiro P. Izawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kazuhiro P. Izawa.

Ethics declarations

Conflict of interest

All authors declare no conflicts of interest in relation to the work reported in this manuscript.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

For this type of study, formal consent form is not required.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kanejima, Y., Kitamura, M. & Izawa, K.P. Self-monitoring to increase physical activity in patients with cardiovascular disease: a systematic review and meta-analysis. Aging Clin Exp Res 31, 163–173 (2019). https://doi.org/10.1007/s40520-018-0960-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40520-018-0960-7

Keywords

Search

Navigation