Published on in Vol 22, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19028, first published .
Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey

Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey

Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey

Journals

  1. Bonner C, Trevena L, Gaissmaier W, Han P, Okan Y, Ozanne E, Peters E, Timmermans D, Zikmund-Fisher B. Current Best Practice for Presenting Probabilities in Patient Decision Aids: Fundamental Principles. Medical Decision Making 2021;41(7):821 View
  2. Jang Y, Sim J, Yang J, Kwon N. Improving heart rate variability information consistency in Doppler cardiogram using signal reconstruction system with deep learning for Contact-free heartbeat monitoring. Biomedical Signal Processing and Control 2022;76:103691 View
  3. Bonner C, Batcup C, Fajardo M, Trevena L. Biological age calculators to motivate lifestyle change: Environmental scan of online tools and evaluation of behaviour change techniques. Health Promotion Journal of Australia 2023;34(1):202 View
  4. Bonner C, Batcup C, Ayre J, Cvejic E, Trevena L, McCaffery K, Doust J. The Impact of Health Literacy–Sensitive Design and Heart Age in a Cardiovascular Disease Prevention Decision Aid: Randomized Controlled Trial and End-User Testing. JMIR Cardio 2022;6(1):e34142 View
  5. Riley V, Gidlow C, Fedorowicz S, Lagord C, Thompson K, Woolner J, Taylor R, Clark J, Lloyd-Harris A. The Impact and Perception of England’s Web-Based Heart Age Test of Cardiovascular Disease Risk: Mixed Methods Study. JMIR Cardio 2023;7:e39097 View
  6. Bonner C, Batcup C, Cornell S, Fajardo M, Hawkes A, Trevena L, Doust J. Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects. JMIR Cardio 2021;5(2):e31056 View
  7. Abdel-Qadir H, Austin P, Sivaswamy A, Chu A, Wijeysundera H, Lee D. Comorbidity-stratified estimates of 30-day mortality risk by age for unvaccinated men and women with COVID-19: a population-based cohort study. BMC Public Health 2023;23(1) View
  8. Heron N, O’Connor S, Kee F, Thompson D, Cupples M, Donnelly M. Refining a primary care shared decision-making aid for lifestyle change: a mixed-methods study. BJGP Open 2022;6(1):BJGPO.2021.0100 View
  9. Starnecker F, Reimer L, Nissen L, Jovanović M, Kapsecker M, Rospleszcz S, von Scheidt M, Krefting J, Krüger N, Perl B, Wiehler J, Sun R, Jonas S, Schunkert H. Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study. JMIR Cardio 2023;7:e50813 View
  10. Desiderio A, Pastorino M, Campitelli M, Longo M, Miele C, Napoli R, Beguinot F, Raciti G. DNA methylation in cardiovascular disease and heart failure: novel prediction models?. Clinical Epigenetics 2024;16(1) View
  11. Svenšek A, Lorber M, Gosak L, Verbert K, Klemenc-Ketis Z, Stiglic G. The Role of Visualization in Estimating Cardiovascular Disease Risk: Scoping Review. JMIR Public Health and Surveillance 2024;10:e60128 View
  12. Raussi V, Kujala S, Hörhammer I, Savolainen K, Autio R, Koskela T. Comparing a Digital Health Check With Traditional Nurse-Led Health Examinations Among Long-Term Unemployed Individuals: Comparison Study. Journal of Medical Internet Research 2024;26:e49802 View
  13. Sastre-Alzamora T, Tárraga López P, López-González Á, Vallejos D, Paublini H, Ramírez Manent J. Usefulness of Atherogenic Indices for Predicting High Values of Avoidable Lost Life Years Heart Age in 139,634 Spanish Workers. Diagnostics 2024;14(21):2388 View