MyDigiTwin

2020

Cardiovascular disease (CVD) is the leading global cause of mortality and morbidity, with ischemic heart disease (IHD) representing approximately half of all CVD-related deaths. Precise, personalized risk assessment and treatment recommendations are crucial for addressing the diverse population at risk of CVD. Current standard approaches rely on algorithms that incorporate a limited set of traditional risk factors to estimate CVD and IHD risk. However, significant cardiovascular events often occur in individuals categorized as low risk, underscoring the need for ongoing research to enhance preventive strategies.

The Focus
The MyDigiTwin initiative aims to provide individuals with personalized insights into their cardiac health, enabling proactive monitoring and management of cardiovascular conditions. This integrated digital health platform empowers individuals to take control of their cardiac health by offering accessible, data-driven insights and tools.

The Research
MyDigiTwin is a pioneering research initiative focused on revolutionizing cardiac health management by integrating advanced AI technologies with extensive patient data. The development of MyDigiTwin involves harnessing large-scale longitudinal datasets from over 500,000 patients, combined with sophisticated AI algorithms. This approach enables the platform to analyze diverse health parameters and generate tailored recommendations for users based on their unique health profiles. By leveraging AI and comprehensive patient data, MyDigiTwin represents an innovative approach to preventive and personalized healthcare, facilitating early detection and intervention for cardiovascular conditions.

Origin
This project was funded within the Big Data & Health Program. The focus of this public-private research program is the use of big data for the early detection and prevention of cardiovascular diseases. The program has been developed by NWO, ZonMw, the Dutch Heart Foundation, the Top Sectors Life Sciences & Health (LSH), ICT and Creative Industry, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center. Within this research program, the ambitions of the Dutch Heart Foundation, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center were aligned with the ambitions of Commit2Data for the Top Sectors ICT, LSH, and Creative Industry, as described in the 2018-2019 Kennis- en Innovatiecontracts between NWO and the Top Sectors.

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PERFECT-FIT

2020
Smoking tobacco and physical inactivity are key preventable risk factors of cardiovascular disease (CVD). Perfect Fit aims to prevent CVD, promote well-being, and reduce healthcare costs, particularly targeting disadvantaged populations where smoking and physical inactivity are prevalent. The Research The project develops tailored, evidence-based, near real-time computer coaching for quitting smoking and enhancing PA. For every individual, a personal model is designed which generates personalized recommendations based on high-quality existing and newly collected data, and adapts to changing circumstances/progress (similar to a TomTom navigation system), using machine learning techniques and incorporating domain-specific expert knowledge (e.g. health behaviour change strategies). Virtual coaches (VCs) communicate advice in a motivating way that fits individuals’ persuasive communication styles. Perfect Fit integrates big-data science, sensor technology, and personalized real-time feedback to support smoking cessation and promote adequate physical activity (in both gym settings and daily life). The key questions of this study are: Which adaptivity is needed to create a robust, safe, and effective interaction between individuals and machines? How can we develop advanced data science methods and embed this in current smoking cessation and PA coaching practice? How do measurement modalities, feedback and communication affect individuals’ smoking status and PA? Origin This project was funded within the Big Data & Health Program. The focus of this public-private research program is the use of big data for the early detection and prevention of cardiovascular diseases. The program has been developed by NWO, ZonMw, the Dutch Heart Foundation, the Top Sectors Life Sciences & Health (LSH), ICT and Creative Industry, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center. Within this research program, the ambitions of the Dutch Heart Foundation, the Ministry of Health, Welfare and Sport, and the Netherlands eScience Center were aligned with the ambitions of Commit2Data for the Top Sectors ICT, LSH, and Creative Industry, as described in the 2018-2019 Kennis- en Innovatiecontracts between NWO and the Top Sectors.
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Supreme Nudge

2017
A healthy lifestyle - a healthy diet and adequate exercise - contribute significantly to chronic disease prevention. People with a lower socioeconomic position (SEP) often have an unhealthier lifestyle than people with a higher SEP. However, interventions aimed at promoting a healthy lifestyle reach precisely this lower SEP target group poorly and may increase social inequality. A possible explanation is that interventions traditionally tend to focus on individual determinants of behavior such as knowledge, attitudes and intentions. Moreover, these interventions are often not effective, partly because they do not take into account the - social, physical and political - context in which lifestyle choices are made: unhealthy behavior can be seen as an automatic reaction to the 'obesogenic' environment. Changes in and of the environment in which people live can go a long way in promoting healthy lifestyles and reaching all target groups. Changes in the environment should ensure that the healthy choice becomes the easy choice, the obvious choice or even the only choice, especially also for the hard to reach and change target groups such as people with lower education. However, whether environmental interventions are also effective in improving cardiovascular disease risk factors in the longer term is not known and needs to be investigated. The Research Supermarkets form one of the most important point-of-choice settings with the potential to directly influence purchasing behaviors. ‘Nudges’ (small environmental encouragements) target the quick, automatic choices and do not require conscious decision making, and pricing strategies can seduce consumers to buy healthier alternatives. Such environmental cues can make it easier to initiate and maintain a healthy lifestyle, and as such, to improve cardiometabolic health. In addition, the use of theory-based mobile applications is an effective way to provide tailored and context-specific feedback on physical activity behaviors through the stimulation of ‘goal setting’ and ‘self-management’. Being incorporated in structures and systems, environmental interventions can make the healthy choice an easy choice for everyone. As such, these types of interventions are especially effective in reaching otherwise difficult-to-reach groups such as people with a lower socioeconomic position (SEP). In particular, a combination of ‘nudging’ (targeting automatic behaviors), ‘pricing’ (responding to the price-sensitivity of low income consumers) and tailored physical activity feedback and support (which works better than general education), seems promising for lowering cardiometabolic risk in individuals with low SEP. Yet, the existing evidence is mostly restricted to short-term effects on (proxies of) health behaviors, and little is known about long-term impact of such integrated interventions on cardiometabolic risk factors. With SUPREME NUDGE we expand a previous successful Dutch supermarket pricing strategy intervention, and incorporate promising elements such as nudging and ICT applications to provide real-time and context-specific physical activity feedback. We will investigate the effects of this approach on dietary behaviors, physical activity and established cardiometabolic risk factors in adults with a lower SEP. Using principles from Participatory Action Research and systems thinking, we will consult with the relevant stakeholders to explore options for upscaling and further implementation in society. Outcomes will provide policy- and practice relevant evidence with clear, stepwise and realistic leverage points for helping individuals to maintain healthy behaviors and improve their cardiometabolic health by making the healthy choice the easy choice. SUPREME NUDGE is coordinated by the Amsterdam UMC, location VU University, and includes partners from the VU University, University of Amsterdam, Utrecht University Medical Center, Utrecht University, the Dutch Nutrition Center, Te Velde Research, Nynke van der Laan (ICT developer), Duwtje (creative designers) and supermarket chain Coop. The origin The Heart Foundation aims for more people to make healthy choices, so that they feel vital and run less risk of developing (again) cardiovascular diseases, which was one of the themes of the reserach agenda. With its prevention programs, ZonMw contributes to the improvement of prevention practice, to health gains and to reducing socioeconomic health disparities. Results from research show that healthy behavior cannot be taken for granted, and is strongly influenced by people's social and physical environment and socioeconomic status. Proven effective, innovative and accessible methods to enable people to maintain a healthy lifestyle for a long time are lacking. Therefore, the Dutch Heart Foundation and ZonMw have collaborated to form the program "Gezond leven: goed voor het Hart!". SUPREME NUDGE is one of the projects funded from this program.
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