From leadership research to district action: Public Perceptions of Personal Data Spaces for Citizen-Centered Health Data Governance in Belgium: Cross-Sectional Survey

AI-assisted editorial implementation guide. Proposed district actions are separate from the original authors’ findings and recommendations. Independent peer review of this guide is not asserted.

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Evidence and transfer

Education-related source: verify which participants, institutions and outcomes were actually studied before district adoption. Source publication type: research-article. License and identity checks do not establish study quality or causality.

Original authors’ abstract, reproduced under the source license:

Abstract Highlights What are the main findings? • Support for Personal Data Spaces (PDSs) was conditional and significantly associated with understanding of PDSs, trust in technology, and privacy attitudes. • Citizens valued control over their data more strongly than transparency and preferred storing medical over lifestyle data. Willingness to share varied by purpose and recipient type, with substantially larger differences associated with recipient type. What are the implications of the main findings? • PDSs can contribute to meaningful citizen participation particularly when technological features are embedded in governance arrangements that provide real agency, credible safeguards, and demonstrable public value. Abstract Background/Objectives: Personal Data Spaces (PDSs) are promoted as infrastructures that strengthen citizen participation in health data governance through transparency and individual control. However, empirical evidence on citizens’ views of PDSs remains limited. This study examined how citizens evaluate We Are, a proposed citizen-centered PDS model in Flanders, Belgium, including overall support, preferences for control and transparency, acceptance of different data types and uses, and factors associated with support. Methods: An online survey was conducted among 1041 adults aged 18–79 years in Flanders using quotas for gender, age, education, province, and urbanization. Participants evaluated the We Are model and completed measures concerning reasons for support, control and transparency, storage of medical and lifestyle data, and data sharing across purposes and recipient types. Data were analyzed using t-tests, linear regression, and mixed models with repeated measures. Results: We Are evaluations were ambivalent but slightly positive (M = 2.51 on a 1–4 scale) and did not differ significantly from the scale midpoint. Sociodemographic characteristics explained little variance in support (R2 = 0.033), whereas adding understanding and psychographic factors increased variance to R2 = 0.238. Respondents valued control more than transparency and were more willing to store medical than lifestyle data (Δ = 0.380, p < 0.001). Willingness to share data was higher for both personal and public non-commercial uses than for public commercial uses, whereas personal commercial uses were rated lower. Private recipients were associated with lower willingness to share than public recipients. Conclusions: Support for PDSs was conditional and related more strongly to understanding and psychographic factors than to sociodemographic characteristics. These findings indicate that PDSs should be embedded in governance arrangements that provide real agency, credible safeguards, and demonstrable public value. Keywords: personal data spaces, health data, governance, citizen participation, patient empowerment, shared decision-making, data sharing, public perceptions, survey study, digital health

Study methods

We used data from an internet-based survey of an opt-in sample of adults aged 18 to 79 in Flanders, Belgium, matched to demographic quotas. A quota-based sampling strategy was applied to approximate the distribution of the Flemish population with respect to gender, age, education, province, and urbanization level. The final sample (N = 1041) reflects these characteristics. The survey was administered online by an external research organization, Indiville, via its Bpact panel, an existing opt-in online panel of participants in Belgium used for survey research on societal topics [22,23]. Data collection took place in January 2024. Participants were invited by email, without disclosure of the survey topic. The number of panel members invited to participate was not available to the researchers, and a response rate could therefore not be calculated. No statistical weighting was applied. Participants were rewarded through the panel’s points-based incentive system redeemable for monetary rewards or charitable donations. As participation relied on an opt-in panel, self-selection bias remains possible and should be considered when interpreting results.

Limitations

This study makes several contributions to the understanding of citizen participation in health data governance through PDSs. A first strength is the use of a large survey sample of 1041 respondents matched to the Flemish population across key sociodemographic characteristics, including age, gender, educational level, province, and urbanization level. This provides broad demographic coverage within the Flemish context. Second, the survey was carefully developed and tested for clarity, usability, and completeness, minimizing missing data and ensuring robust measurement. Third, the use of the We Are model, co-developed with patient experience experts, allowed the survey to present a concrete and coherent governance scenario rather than a purely technical or abstract description of data-linking technology, thereby increasing ecological validity.

A 90-day district inquiry

Days 1–15 · Appraise. Read the source methods, recruitment, comparator, outcomes and limitations. Record how the study setting differs from your district and which claim the design can support.
Days 16–30 · Design. Select one recurring district decision. Publish the decision owner, evidence requirements, consultation process and appeal route; test the process on a bounded low-risk decision. Agree participation, privacy protections, baseline and stopping rules before starting.
Days 31–60 · Observe. Collect the pre-agreed measures, keep a log of implementation changes and invite confidential voluntary feedback. Preserve existing support for staff and learners.
Days 61–90 · Decide. Track decision time, unresolved objections, documented reasons, appeals and access differences. Review whether the process changes who can participate and who carries the burden. Make a dated decision to stop, revise or extend the inquiry.

Board decision brief

Present the local problem, source setting, evidence limits, intervention, responsible owner, total cost, measured changes and uncertainty. Separate staff perceptions, implementation measures and student learning outcomes.

Attribution and reuse

Cato van Schyndel; Jochem van Noord; Erik Laes; Karin Hannes; Nathalie Lambrechts. Public Perceptions of Personal Data Spaces for Citizen-Centered Health Data Governance in Belgium: Cross-Sectional Survey. Healthcare (2026-10-15). https://doi.org/10.3390/healthcare14203461

Prepared 2026-11-07. Source authorship and DOI are preserved. The abstract and source passages are attributed extracts; this editorial guide is offered under the same CC BY 4.0 license.