Cardiovascular disease (CVD) is the leading cause of death in the Netherlands and worldwide. While prevention strategies have improved, many population groups, including women, individuals with a migration background, and people with lower socioeconomic status, remain underrepresented in cardiovascular research and prevention programs. As a result, current risk prediction models and lifestyle recommendations are based largely on homogeneous datasets that do not reflect real-world diversity. This structural imbalance limits the generalisability of evidence and contributes to persistent health disparities. The Data Donation Model (DDM) aims to address this gap by introducing a citizen-led, transparent, and participatory approach to data sharing for cardiovascular prevention and health research. In this model, individuals voluntarily contribute their lifestyle, behavioural, and wearable/app data for research while maintaining full control over consent and use. The DDM incorporates dynamic electronic consent, granular sharing options, and transparency dashboards that allow participants to view how their data contribute to ongoing research projects. This participatory design strengthens trust, autonomy, and inclusiveness in data governance. This study evaluates the feasibility, inclusiveness, and acceptability of implementing the DDM at scale within the general population. It forms the pilot phase of a broader national data donation infrastructure coordinated by Amsterdam UMC in collaboration with the TRAIN Health Awareness Platform (technical partner) and community organisations. Approximately 450 participants will take part in this first phase, with future expansion planned up to 10,000 citizens. Participants can connect any wearable device or health app (such as a smart ring, smartwatch, or fitness tracker) to the TRAIN platform and complete short digital questionnaires on lifestyle, sleep, stress, and wellbeing. All participants can donate data for up to 5 years, with the freedom to stop or modify consent at any time. An optional 12-week TRAIN Heart Journey provides guided feedback on physical activity, stress, and recovery patterns, but participation in this module is not required for data donation. The main outcomes are (1) feasibility and acceptability of the DDM (recruitment, retention, adherence, and user satisfaction), (2) inclusiveness of participation across demographic groups, and (3) trust and engagement with science and data governance. Secondary outcomes include behavioural and physiological changes (activity, sleep, stress) and self-efficacy. Exploratory analyses will evaluate long-term engagement and, for consenting participants, linkage with official mortality data from Statistics Netherlands (CBS). The findings will inform future national strategies for equitable, citizen-driven cardiovascular prevention and contribute to developing inclusive guidelines based on real-world data from diverse populations.
Background and Rationale Cardiovascular disease (CVD) remains the leading global cause of mortality. Although preventive strategies have advanced, many population groups continue to be structurally underrepresented in research, including people with a migration background, lower socioeconomic status, lower health literacy, and women. As a result, current datasets and risk prediction models do not accurately reflect population diversity, which limits generalisability and contributes to persistent health inequities. The Data Donation Model (DDM) aims to address these gaps by offering a citizen-driven, transparent approach to sharing lifestyle, behavioural, and wearable/app-derived health data for preventive cardiovascular research. The DDM allows participants to maintain full control over data use through dynamic electronic consent, granular sharing settings, and real-time insight into how their data contribute to research. This approach operationalises ethical principles of autonomy, transparency, and reciprocity, and aligns with modern frameworks for Responsible Data Stewardship and FAIR/Open Science. Study Purpose This pilot study evaluates whether the DDM can be implemented at scale within the general population. The focus is on operational feasibility, user experience, inclusiveness of participation, and engagement with dynamic consent tools. Results will guide the development of a long-term, citizen-governed data infrastructure for cardiovascular prevention research. Study Design This is a prospective, observational cohort study with digital enrolment and follow-up. Participation is open to adults from the general population without recruitment through clinical centres. The study infrastructure is hosted on the TRAIN Health Awareness Platform, which facilitates data donation and device/app integration. Approximately 450 participants will be enrolled during this pilot phase. Participants voluntarily connect one or more wearable devices or health applications of their choice. They also complete periodic questionnaires via the platform. An optional 12-week digital lifestyle module ("TRAIN Heart Journey") is available but not assigned as part of the research design. Data donation may continue for up to five years, depending on individual consent preferences. Procedures and Data Streams After electronic informed consent, participants gain access to a personal dashboard where they can: connect their chosen wearable(s) or health app(s); manage consent settings; complete lifestyle and wellbeing questionnaires; monitor their own engagement and data-sharing status. Collected data include device-generated behaviour and wellbeing indicators (e.g., activity metrics, sleep patterns, physiological parameters depending on device type), as well as digital questionnaire responses. No biospecimens are collected, and no identifiable data are used for analysis; all data are pseudonymised at source. Analytical Framework Feasibility will be evaluated using technical performance indicators (data transmission stability, completeness), recruitment and retention characteristics, and participant engagement metrics. Inclusiveness will be assessed using demographic distributions and literacy indicators. Exploratory analyses will focus on long-term participation patterns and-where separately consented-linkage to national mortality records via secure legal frameworks. Quantitative analyses may include longitudinal modelling of device-based behavioural and physiological signals and descriptive analysis of user-platform interactions. Qualitative and mixed-methods analyses may be used to explore trust, transparency, and participant experience with the DDM. Data Management and Protection All data handling complies with the General Data Protection Regulation (GDPR). Data are stored in a secure, Health-RI-aligned cloud environment using encryption, pseudonymisation, and role-based access controls. Participants may modify or withdraw consent at any time through the dynamic consent interface. Optional linkage to external datasets (e.g., mortality data) requires additional explicit consent. Ethical Considerations The Medical Ethics Review Committee determined that the study does not fall under the Dutch Medical Research Involving Human Subjects Act (non-WMO). The study does not involve investigational products or assigned interventions and poses minimal risk. Participation is voluntary and withdrawal has no consequences. Dissemination Results will be disseminated through peer-reviewed publications, scientific conferences, and citizen-focused communication channels facilitated by the TRAIN Health Awareness Platform and partner community organisations. Insights from this pilot will inform the subsequent scale-up of a national, citizen-driven data donation infrastructure designed to support equitable, population-representative cardiovascular prevention.
Study Type
OBSERVATIONAL
Enrollment
450
An optional 12-week digital feedback module offered within the TRAIN platform to participants who choose to engage with guided lifestyle support. This is not an assigned intervention but part of the broader participatory data-donation framework.
Recruitment Rate
Number of participants enrolled per month during the active recruitment period. Recruitment rate reflects the feasibility of enrolling adults from the general population into the Data Donation Model (DDM) via the TRAIN Health Awareness Platform. Unit of Measure: Participants per month
Time frame: From study start until end of recruitment (anticipated 12 months).
Retention Rate at 12 Weeks
Proportion of enrolled participants who complete the 12-week follow-up period with at least one questionnaire assessment. This measure reflects the feasibility of retaining participants in a fully digital observational study. Unit of Measure: Percentage of participants (%)
Time frame: From enrolment to 12 weeks after enrolment.
Adherence to Wearable and App Use
Proportion of follow-up days with any recorded wearable or app data (e.g., activity, sleep, or heart-rate-derived signals), calculated per participant and summarised at group level. This measure reflects adherence to using the connected device(s) and the TRAIN platform in daily life. Unit of Measure: Percentage of follow-up days with data (%)
Time frame: From enrolment to 12 weeks after enrolment.
Wearable Data Completeness
Proportion of expected data points that are successfully captured and stored for each participant over the 12-week period, based on predefined minimum criteria for valid days (e.g., ≥1 full day of activity and sleep data). This reflects the technical feasibility of continuous data capture within the Data Donation Model. Unit of Measure: Percentage of expected data points (%)
Time frame: From enrolment to 12 weeks after enrolment.
Participant Satisfaction Score
Overall satisfaction with the Data Donation Model and the TRAIN platform, measured using a brief user experience questionnaire with items rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). The primary outcome is the mean total score; higher scores indicate greater satisfaction and acceptability. Unit of Measure: Mean score on a 1-5 Likert scale (points)
Time frame: At 12 weeks after enrolment.
Change in Daily Step Count
Description: Change in total number of steps per day recorded by connected wearable devices. Unit of Measure: Steps per day
Time frame: Baseline to 12 weeks.
Change in Active Minutes per Day
Description: Change in daily minutes classified as "active" or moderate-to-vigorous activity by the wearable device. Unit of Measure: Minutes per day
Time frame: Baseline to 12 weeks.
Change in Heart Rate Variability
Description: Change in daily HRV as measured by the wearable device, reflecting autonomic balance and recovery. Unit of Measure: Milliseconds (ms)
Time frame: Baseline to 12 weeks.
Change in Resting Heart Rate
Description: Change in resting heart rate based on valid daily RHR recordings from the wearable device. Unit of Measure: Beats per minute (bpm)
Time frame: Baseline to 12 weeks.
Change in Sleep Efficiency
Change in sleep efficiency (total sleep time ÷ time in bed), derived from wearable algorithms. Unit of Measure: Percentage (%)
Time frame: Baseline to 12 weeks.
Change in Health-Related Quality of Life (EQ-5D-5L)
Change in health-related quality of life measured using the EuroQoL EQ-5D-5L instrument (range: 5-25; higher scores indicate worse health). Unit of Measure: Score (points)
Time frame: Baseline to 12 weeks after enrolment.
Change in Self-Efficacy (GSES)
Description: Change in perceived self-efficacy measured with the General Self-Efficacy Scale (10-40; higher scores indicate better self-efficacy). Unit of Measure: Score (points)
Time frame: Baseline to 12 weeks.
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Inclusiveness of Participation
Representation and adherence will be analysed across demographic and literacy strata (sex, migration background, socioeconomic status, and health literacy). The Health Literacy Questionnaire (HLQ) and demographic data will characterise diversity and identify barriers to engagement. Unit of Measure: Proportion of participants (%)
Time frame: During and after completion of 12-week period.
Change in Trust in Medical Research
Description: Change in trust using adapted items from the Trust in Medical Researchers scale (range: typically 5-25; higher scores indicate more trust). Unit of Measure: Score (points)
Time frame: Baseline and 12 weeks.
Change in Perceived Transparency
Description: Change in perceived transparency using items adapted from validated public attitudes toward data-sharing instruments (range varies by item; higher scores indicate greater perceived transparency). Unit of Measure: Score (points)
Time frame: Baseline to 12 weeks.
Long-Term Data Donation and Engagement
Sustained participation and data donation patterns among participants who continue sharing data beyond the 12-week period, including frequency of updates and completeness of long-term wearable data. Unit of Measure: Percentage of expected data points (%)
Time frame: Up to 5 years after enrolment.
Mortality Linkage (Optional, CBS Data)
For participants who provide additional consent, linkage of pseudonymised data with official mortality records from Statistics Netherlands (CBS) to evaluate long-term outcomes and population health trends. Unit of Measure: Mortality status (yes/no)
Time frame: Up to 5 years after enrolment.