ArticleJournal of medical Internet research2014
Web-based self-assessment health tools: who are the users and what is the impact of missing input information?
Article in Journal of medical Internet research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 33 citations in OpenAlex.
- Clinical Validity, Understandability, and Actionability of Online Cardiovascular Disease Risk Calculators: Systematic Review.Journal of medical Internet research · 2018Pooled it
- Health and eHealth Literacy of Patients With Diabetes in Low-Income Countries: Perspective From Guinea and Burkina Faso.JMIR diabetes · 2024Article
- Guideline-Based Cardiovascular Risk Assessment Delivered by an mHealth App: Development Study.JMIR cardio · 2023Article
- The Impact and Perception of England's Web-Based Heart Age Test of Cardiovascular Disease Risk: Mixed Methods Study.JMIR cardio · 2023Article
- Biological age calculators to motivate lifestyle change: Environmental scan of online tools and evaluation of behaviour change techniques.Health promotion journal of Australia : official journal of Australian Association of Health Promotion Professionals · 2023Article
- The Development and Evaluation of "Life Age"-a Primary Prevention and Population-Focused Risk Communication Tool: Feasibility Study With a Single-Arm Repeated Measures Design.JMIR formative research · 2022Article
- Predicted heart age profile across 41 countries: A cross-sectional study of nationally representative surveys in six world regions.EClinicalMedicine · 2022Article
- Association of physical activity with vascular aging in a population with intermediate cardiovascular risk, analysis by sex: MARK study.Biology of sex differences · 2022Article
- Article
- Interventions Using Heart Age for Cardiovascular Disease Risk Communication: Systematic Review of Psychological, Behavioral, and Clinical Effects.JMIR cardio · 2021Review
- Self-Assessment of Health among the Citizens of Serbia in the Transition Period.Iranian journal of public health · 2021Article
- Experiences of a National Web-Based Heart Age Calculator for Cardiovascular Disease Prevention: User Characteristics, Heart Age Results, and Behavior Change Survey.Journal of medical Internet research · 2020Article
- Dentists' willingness to screen for cardiovascular disease in the dental care setting: Findings from a nationally representative survey.Community dentistry and oral epidemiology · 2019Article
- Should heart age calculators be used alongside absolute cardiovascular disease risk assessment?BMC cardiovascular disorders · 2018Article
- Validity of a method for the self-screening of cardiovascular risk.Clinical epidemiology · 2018Article
- Cardiovascular Disease Risk Assessment in the United States and Low- and Middle-Income Countries Using Predicted Heart/Vascular Age.Scientific reports · 2017Article
- Online self-assessment of cardiovascular risk using the Joint British Societies (JBS3)-derived heart age tool: a descriptive study.BMJ open · 2016Article
- eHealth Literacy: In the Quest of the Contributing Factors.Interactive journal of medical research · 2016Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundWeb-based health applications, such as self-assessment tools, can aid in the early detection and prevention of diseases. However, there are concerns as to whether such tools actually reach users with elevated disease risk (where prevention efforts are still viable), and whether inaccurate or missing information on risk factors may lead to incorrect evaluations.
objectiveThis study aimed to evaluate (1) evaluate whether a Web-based cardiovascular disease (CVD) risk communication tool (Heart Age tool) was reaching users at risk of developing CVD, (2) the impact of awareness of total cholesterol (TC), HDL-cholesterol (HDL-C), and systolic blood pressure (SBP) values on the risk estimates, and (3) the key predictors of awareness and reporting of physiological risk factors.
methodsHeart Age is a tool available via a free open access website. Data from 2,744,091 first-time users aged 21-80 years with no prior heart disease were collected from 13 countries in 2009-2011. Users self-reported demographic and CVD risk factor information. Based on these data, an individual's 10-year CVD risk was calculated according to Framingham CVD risk models and translated into a Heart Age. This is the age for which the individual's reported CVD risk would be considered "normal". Depending on the availability of known TC, HDL-C, and SBP values, different algorithms were applied. The impact of awareness of TC, HDL-C, and SBP values on Heart Age was determined using a subsample that had complete risk factor information.
resultsHeart Age users (N=2,744,091) were mostly in their 20s (22.76%) and 40s (23.99%), female (56.03%), had multiple (mean 2.9, SD 1.4) risk factors, and a Heart Age exceeding their chronological age (mean 4.00, SD 6.43 years). The proportion of users unaware of their TC, HDL-C, or SBP values was high (77.47%, 93.03%, and 46.55% respectively). Lacking awareness of physiological risk factor values led to overestimation of Heart Age by an average 2.1-4.5 years depending on the (combination of) unknown risk factors (P<.001). Overestimation was greater in women than in men, increased with age, and decreased with increasing CVD risk. Awareness of physiological risk factor values was higher among diabetics (OR 1.47, 95% CI 1.46-1.50 and OR 1.74, 95% CI 1.71-1.77), those with family history of CVD (OR 1.22, 95% CI 1.22-1.23 and OR 1.43, 95% CI 1.42-1.44), and increased with age (OR 1.05, 95% CI 1.05-1.05 and OR 1.07, 95% CI 1.07-1.07). It was lower in smokers (OR 0.52, 95% CI 0.52-0.53 and OR 0.71, 95% CI 0.71-0.72) and decreased with increasing Heart Age (OR 0.92, 95% CI 0.92-0.92 and OR 0.97, 95% CI 0.96-0.97) (all P<.001).
conclusionsThe Heart Age tool reached users with low-moderate CVD risk, but with multiple elevated CVD risk factors, and a heart age higher than their real age. This highlights that Web-based self-assessment health tools can be a useful means to interact with people who are at risk of developing disease, but where interventions are still viable. Missing information in the self-assessment health tools was shown to result in inaccurate self-health assessments. Subgroups at risk of not knowing their risk factors are identifiable and should be specifically targeted in health awareness programs.
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