Trial reportJournal of medical Internet research2022
Effect of a Lifestyle-Focused Web-Based Application on Risk Factor Management in Patients Who Have Had a Myocardial Infarction: Randomized Controlled Trial.
Trial report in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03260582 (Implementation and Assessment of a Life-style Focused Patient Support Application), which is not on this map. Cited by 18 papers, 9 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Implementation and Assessment of a Life-style Focused Patient Support Application (App) and Activity Trackers for Improving Risk Factor Management, Physical Activity, Quality of Life and Prognosis in Post-myocardial Infarction Patients
Who cites it
18 citing papers in PubMed, 9 syntheses or guidelines pooled it, 28 citations in OpenAlex.
- Pooled it
- Smartphone application-based interventions for cardiometabolic risk factor management: A systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2026Pooled it
- A systematic review and meta-analysis testing the effect of lifestyle modification and medication optimization programs on cholesterol and blood pressure in patients with cardiovascular disease.Systematic reviews · 2025Pooled it
- Smartphone application-based intervention to lower blood pressure: a systematic review and meta-analysis.Hypertension research : official journal of the Japanese Society of Hypertension · 2025Pooled it
- Health-promotion interventions targeting multiple behaviors: A meta-analytic review of general and behavior-specific processes of change.Psychological bulletin · 2024Pooled it
- Effectiveness and Feasibility of Telehealth-Based Dietary Interventions Targeting Cardiovascular Disease Risk Factors: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2024Pooled it
- Digital health intervention in patients undergoing cardiac rehabilitation: systematic review and meta-analysis.F1000Research · 2024Pooled it
- Benefits and Harms of Digital Health Interventions Promoting Physical Activity in People With Chronic Conditions: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2023Pooled it
- The effect of telemedicine on secondary prevention of atherosclerotic cardiovascular disease: A systematic review and meta-analysis.Frontiers in cardiovascular medicine · 2022Pooled it
- Artificial Intelligence-Enhanced Telerehabilitation in Post-Acute Coronary Syndrome: A Narrative Review of Opportunities, Evidence, and Future Directions.Life (Basel, Switzerland) · 2026Review
- Article
- A study on the intervention effect of a case management model that breaks through spatiotemporal characteristics in home-based phase II exercise rehabilitation post PCI.Frontiers in cardiovascular medicine · 2024Article
- A prospective, randomized, controlled, multicentre trial for secondary prevention in patients with chronic coronary syndrome using a smartphone application for digital therapy: the CHANGE study protocol.European heart journal. Digital health · 2023Article
- Mobile App and Digital System for Patients after Myocardial Infarction (afterAMI): Results from a Randomized Trial.Journal of clinical medicine · 2023Article
- Physical Therapy Programs in Older Adults with Coronary Artery Disease: Preferences to Technology-Based Cardiac Physical Therapy Programs.International journal of environmental research and public health · 2022Article
- The Impact of Smartphone Apps Designed to Reduce Food Waste on Improving Healthy Eating, Financial Expenses and Personal Food Waste: Crossover Pilot Intervention Trial Studying Students' User Experiences.JMIR formative research · 2022Article
- Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiac rehabilitation is central in reducing mortality and morbidity after myocardial infarction. However, the fulfillment of guideline-recommended cardiac rehabilitation targets is unsatisfactory. eHealth offers new possibilities to improve clinical care.
objectiveThis study aims to assess the effect of a web-based application designed to support adherence to lifestyle advice and self-control of risk factors (intervention) in addition to center-based cardiac rehabilitation, compared with cardiac rehabilitation only (usual care).
methodsAll 150 patients participated in cardiac rehabilitation. Patients randomized to the intervention group (n=101) received access to the application for 25 weeks where information about lifestyle (eg, diet and physical activity), risk factors (eg, weight and blood pressure [BP]), and symptoms could be registered. The software provided feedback and lifestyle advice. The primary outcome was a change in submaximal exercise capacity (Watts [W]) between follow-up visits. Secondary outcomes included changes in modifiable risk factors between baseline and follow-up visits and uptake and adherence to the application. Regression analysis was used, adjusting for relevant baseline variables.
resultsThere was a nonsignificant trend toward a larger change in exercise capacity in the intervention group (n=66) compared with the usual care group (n=40; +14.4, SD 19.0 W, vs +10.3, SD 16.1 W; P=.22). Patients in the intervention group achieved significantly larger BP reduction compared with usual care patients at 2 weeks (systolic -27.7 vs -16.4 mm Hg; P=.006) and at 6 to 10 weeks (systolic -25.3 vs -16.4 mm Hg; P=.02, and diastolic -13.4 vs -9.1 mm Hg; P=.05). A healthy diet index score improved significantly more between baseline and the 2-week follow-up in the intervention group (+2.3 vs +1.4 points; P=.05), mostly owing to an increase in the consumption of fish and fruit. At 6 to 10 weeks, 64% (14/22) versus 46% (5/11) of smokers in the intervention versus usual care groups had quit smoking, and at 12 to 14 months, the respective percentages were 55% (12/22) versus 36% (4/11). However, the number of smokers in the study was low (33/149, 21.9%), and the differences were nonsignificant. Attendance in cardiac rehabilitation was high, with 96% (96/100) of patients in the intervention group and 98% (48/49) of patients receiving usual care only attending 12- to 14-month follow-up. Uptake (logging data in the application at least once) was 86.1% (87/101). Adherence (logging data at least twice weekly) was 91% (79/87) in week 1 and 56% (49/87) in week 25.
conclusionsComplementing cardiac rehabilitation with a web-based application improved BP and dietary habits during the first months after myocardial infarction. A nonsignificant tendency toward better exercise capacity and higher smoking cessation rates was observed. Although the study group was small, these positive trends support further development of eHealth in cardiac rehabilitation.
trial registrationClinicalTrials.gov NCT03260582; https://clinicaltrials.gov/ct2/show/NCT03260582. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1186/s13063-018-3118-1.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.