Patient-Centered Risk Prediction, Prevention, and Intervention Platform (TIMELY) to Support the Continuum of Care in Coronary Artery Disease Using eHealth and Artificial Intelligence Protocol for a Randomized Controlled Trial

Open Access
Authors
  • Mirela Habibovic
  • Emma Douma
  • Hendrik Schäfer
  • Manuela Sestayo-Fernandez
  • Tom Roovers
  • Xin Sun
  • Henrik Schmidt
  • Mona Kotewitsch
  • Jos Widdershoven
  • David Cantarero-Prieto
  • Frank Mooren
  • Carlos Pena-Gil
  • José Rámon González Juanatey
  • Martin Schmidt
  • Hagen Malberg
  • Vassilis Tsakanikas
  • Dimitrios Fotiadis
  • Dimitris Gatsios
  • Jos Bosch
  • Willem Johan Kop
  • Boris Schmitz
Publication date August 2025
Journal JMIR Research Protocols
Article number e66283
Volume | Issue number 14
Number of pages 14
Organisations
  • Faculty of Social and Behavioural Sciences (FMG) - Psychology Research Institute (PsyRes)
Abstract
Background: Cardiac rehabilitation (CR) programs have shown promising results in tertiary prevention. However, achieving sustained behavioral changes remains a challenge.
Objective: The TIMELY project aims to develop and evaluate a personalized, artificial intelligence–driven eHealth platform and app to support sustainable behavior change during phase-3 CR, subsequently reducing cardiac risk scores.
Methods: An international, multicenter, randomized controlled trial will be conducted to evaluate the effectiveness of the TIMELY integrated platform and app. A total of 360 patients with cardiac conditions will be approached to participate in the study across Germany, Spain, and the Netherlands. Patients will be randomly assigned (1:1) to either the intervention group or the control group (care as usual). The intervention group will receive fully web-based, behavior change support through the TIMELY app, with personalized exercise prescription, chatbot assistance, and monitoring devices (eg, activity watch). Both groups will continue to receive care as usual, complete validated questionnaires, undergo physical tests, and provide blood samples. Assessments will be conducted at baseline and at 3, 6, and 12 months.
Results: Trial recruitment has been finalized in July 2024. A total of 358 patients have been recruited and randomly assigned to the intervention (n=180, 50.1%) or care-as-usual (n=178, 49.7%) condition. As of January 2025, the 6-month follow-up has been completed for all participants. Follow-up data collection will be completed in May 2025. Results regarding the primary and secondary objectives are expected in September 2025.
Conclusions: This project will test a personalized platform and app, supported by artificial intelligence and designed to support health behavior change during phase-3 CR. It will target multiple health behaviors, with a primary focus on physical activity and fitness levels, using an integrated approach.
Document type Article
Language English
Published at
https://doi.org/10.2196/66283 (Final published version)
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