ArticleHealth services research2018
Public Trust in Health Information Sharing: A Measure of System Trust.
Article in Health services research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
63 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Why do people trust (or mistrust) health organizations? A systematic review.International journal for equity in health · 2026Pooled it
- Patient and Public Willingness to Share Personal Health Data for Third-Party or Secondary Uses: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Transforming Health Data to Actionable Information: Recent Progress and Future Opportunities in Health Information Exchange.Yearbook of medical informatics · 2022Pooled it
- Operationalizing transparency regarding the use of health data for research: a cross-sectional survey of citizens' perspectives.BMC public health · 2026Article
- Patient Perceptions and Acceptance of Blockchain-Based Health Data Sharing in Oncology: Cross-Sectional Survey.JMIR formative research · 2026Article
- "Just be honest with us": A qualitative analysis of Canadians' public trust during the COVID-19 pandemic.Canadian journal of public health = Revue canadienne de sante publique · 2026Article
- Public Expectations for Food and Drug Administration Approval of AI-Based Clinical Decision Support Tools: Quantitative Study.JMIR AI · 2026Article
- Privacy concerns regarding personal health information in Myanmar: A cross-sectional survey in a least developed country.PLOS digital health · 2026Article
- Physician versus patient use of AI for diabetes prevention: public perceptions and comfort levels.Frontiers in digital health · 2026Article
- Empowering AI assisted clinical drug development: tactics to address data bias, the digital divide and missing patient populations through AI and digital solutions.Frontiers in digital health · 2026Review
- Community perspectives on health AI: hopes, concerns and implications for health systems and trustworthy AI.AI and ethics · 2026Article
- Trust Dynamics and Equity in Public Health in Canada: Protocol for a Mixed Methods Project in the Postpandemic Era.JMIR research protocols · 2025Article
- Trust transfer from medical AI to doctors and hospitals: Integrating digital, AI, and scientific literacy in a cross-sectional framework.BMC medical ethics · 2025Article
- Public satisfaction and trust towards the health system in China and associated factors: a mixed-methods study.BMC public health · 2025Article
- Comfort With Sharing Food Insecurity Risk for Clinical Care Among Individuals With and Without a Cancer History: Findings From a National Survey.AJPM focus · 2025Article
- The Ethics of Informed Consent for Data Registries: Moving Beyond Moral Minimalism to the High Ground.Bioethics · 2025Article
- Evolutionary game analysis of healthcare data governance in China's experimental data trading pilots.NPJ digital medicine · 2025Article
- The Longitudinal Analysis of Patient Perspectives on Data Use in Healthcare: Desire for Notification and Concern About Data Sharing.Journal of general internal medicine · 2025Article
- Expectations of healthcare AI and the role of trust: understanding patient views on how AI will impact cost, access, and patient-provider relationships.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Patients' Trust in Health Systems to Use Artificial Intelligence.JAMA network open · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
objectiveTo measure public trust in a health information sharing in a broadly defined health system (system trust), inclusive of health care, public health, and research; to identify individual characteristics that predict system trust; and to consider these findings in the context of national health initiatives (e.g., learning health systems and precision medicine) that will expand the scope of data sharing. DATA SOURCES: Survey data (n = 1,011) were collected in February 2014. STUDY
designWe constructed a composite index of four dimensions of system trust-competency, fidelity, integrity, and trustworthiness. The index was used in linear regression evaluating demographic and psychosocial predictors of system trust. DATA COLLECTION: Data were collected by GfK Custom using a nationally representative sample and analyzed in Stata 13.0. PRINCIPAL
findingsOur findings suggest the public's trust may not meet the needs of health systems as they enter an era of expanded data sharing. We found that a majority of the U.S. public does not trust the organizations that have health information and share it (i.e., the health system) in one or more dimensions. Together, demographic and psychosocial factors accounted for ~18 percent of the observed variability in system trust. Future research should consider additional predictors of system trust such as knowledge, attitudes, and beliefs to inform policies and practices for health data sharing.
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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.