Web-Based Interventions Targeting Cardiovascular Risk Factors in Middle-Aged and Older People: A Systematic Review and Meta-Analysis
Open accessAbstract
BACKGROUND: Web-based interventions can improve single cardiovascular risk factors in adult populations. In view of global aging and the associated increasing burden of cardiovascular disease, older people form an important target population as well. OBJECTIVE: In this systematic review and meta-analysis, we evaluated whether Web-based interventions for cardiovascular risk factor management reduce the risk of cardiovascular disease in older people. METHODS: Embase, Medline, Cochrane and CINAHL were systematically searched from January 1995 to November 2014. Search terms included cardiovascular risk factors and diseases (specified), Web-based interventions (and synonyms) and randomized controlled trial. Two authors independently performed study selection, data-extraction and risk of bias assessment. In a meta-analysis, outcomes regarding treatment effects on cardiovascular risk factors (blood pressure, glycated hemoglobin A1c (HbA1C), low-density lipoprotein (LDL) cholesterol, smoking status, weight and physical inactivity) and incident cardiovascular disease were pooled with random effects models. RESULTS: A total of 57 studies (N=19,862) fulfilled eligibility criteria and 47 studies contributed to the meta-analysis. A significant reduction in systolic blood pressure (mean difference -2.66 mmHg, 95% CI -3.81 to -1.52), diastolic blood pressure (mean difference -1.26 mmHg, 95% CI -1.92 to -0.60), HbA1c level (mean difference -0.13%, 95% CI -0.22 to -0.05), LDL cholesterol level (mean difference -2.18 mg/dL, 95% CI -3.96 to -0.41), weight (mean difference -1.34 kg, 95% CI -1.91 to -0.77), and an increase of physical activity (standardized mean difference 0.25, 95% CI 0.10-0.39) in the Web-based intervention group was found. The observed effects were more pronounced in studies with short (<12 months) follow-up and studies that combined the Internet application with human support (blended care). No difference in incident cardiovascular disease was found between groups (6 studies). CONCLUSIONS: Web-based interventions have the potential to improve the cardiovascular risk profile of older people, but the effects are modest and decline with time. Currently, there is insufficient evidence for an effect on incident cardiovascular disease. A focus on long-term effects, clinical endpoints, and strategies to increase sustainability of treatment effects is recommended for future studies.
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Digital health tools that enable two-way human interactions are better accepted, while replacing human communications with automatic responses is less favored.
“Digital health tools that enable two-way human interactions are better accepted while replacing human communications with automatic responses is less favored.”
From Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries (2023) · cites this paper as [26]
Lack of guidance for patients is subject to low acceptance and waning interests in using digital health over time.
“Lack of guidance for patients is subject to low acceptance and waning interests in using digital health over time.”
From Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries (2023) · cites this paper as [26]
The development in technologies and infrastructures provides solid ground for digital health advancement, including penetration of cell phones and the internet.
“The development in technologies and infrastructures provide solid ground for digital health advancement, including penetration of cell phones and the internet.”
From Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries (2023) · cites this paper as [26]
In the included studies, digital health interventions for individuals' behavioral outcomes showed positively inclined results, although mixed, especially when substantiated by behavioral science theories.
“For individuals’ behavioral outcomes, although still mixed, we consistently observed positively inclined results, especially when substantiated by behavioral science theories26,82.”
From Digital health interventions for non-communicable disease management in primary health care in low-and middle-income countries (2023) · cites this paper as [26]
There is some evidence that theory-based interventions are more effective.
“We considered these subgroup analyses because there is some evidence that theory-based interventions are more effective [60-62]”
From Fitbit-based interventions for healthy lifestyle outcomes: systematic review and meta-analysis (2020) · cites this paper as [60]
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“We considered these subgroup analyses because there is some evidence that theory-based interventions are more effective [60-62] and that the effects of wearable activity trackers may not be sustainable over time, favoring short interventions.”
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Avrupa İnme için Eylem Planı 2018-2030
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e-Coaching for Intensive Cardiac Rehabilitation
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LSTM Step Prediction and Ontology-Based Recommendation Generation in Activity eCoaching
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Tecnologías móviles e inalámbricas para cuidar nuestra salud
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- Authors
- Beishuizen, C. R., Stephan, B. C., van Gool, W. A., Brayne, C., Peters, R. J., Andrieu, S., Kivipelto, M., Soininen, H., Busschers, W. B., Moll van Charante, E. P., & Richard, E.
- Affiliations
- Amsterdam UMC Location University of Amsterdam (NL)
- Newcastle University (GB)
- University of Cambridge (GB)
- Inserm (FR)
- Karolinska Institutet (SE)
- University of Eastern Finland (FI)
- Corresponding author
- Richard, Edo
- ORCID
- Venue
- Journal of Medical Internet Research
- Publisher
- JMIR Publications Inc.
- Published
- 2016-03-11
- Volume
- 18
- Issue
- 3
- Pages
- e55
- ISSN
- 1438-8871 (ISSN-L)
- PMC
- PMC4808240
- OpenAlex
- W2294364812
- Cited by
- 128
- References
- 89
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 11 · 2023: 14 · 2022: 25 · 2021: 17 · 2020: 11 · 2019: 8 · 2018: 21 · 2017: 8 · 2016: 2
- FWCI
- 2.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of Medical Internet Research (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (acceptedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- UEF eRepo (University of Eastern Finland) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Funders
- National Institute for Health and Care Research (NF-SI-0611-10084)
- Newcastle University
- European Commission (2007–2013, FP7 2007-2013, FP7/2007, 305654)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- online intervention, cardiovascular risk factors, older adults, middle-aged adults, cardiovascular disease prevention, blood pressure, HbA1c, LDL cholesterol, weight loss, physical activity, smoking, blended care, internet-based health interventions, population aging, cardiovascular risk management, treatment effects over time, physical inactivity, obesity, diabetes risk, hypertension, dyslipidemia
- MeSH terms
- Aged, Blood Pressure, Body Weight, Cardiovascular Diseases, Glycated Hemoglobin, Humans, Cholesterol, LDL, Middle Aged, Motor Activity, Risk Factors, Smoking, Therapy, Computer-Assisted, Weight Loss, Randomized Controlled Trials as Topic, Smoking Cessation, Internet, Risk Reduction Behavior, Sedentary Behavior
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