ArticleJMIR human factors2025
Public Attitudes and Predictors of Public Awareness of Personal Digital Health Data Sharing for Research: Cross-Sectional Study in Japan.
Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Strengthening public health data governance: A Co-regulatory framework for integrating wearable health data into health systems.Journal of public health research · 2026Article
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Abstract
Background: As digital technology advances, health-related data can be scientifically analyzed to predict illnesses. The analysis of international data collected during health examinations and health status monitoring, along with data collected during medical care delivery, can contribute to precision medicine and the public good. Understanding citizens' attitudes and predictors of digital health data sharing is critical in promoting data-driven research. Objective: This study aims to determine the public acceptability of data sharing and the attitudes and influencing factors toward data sharing. Methods: A cross-sectional web-based survey was conducted in Japan from November 11-18, 2023. We analyzed 1000 valid responses. Five factors were investigated as predictors of participants' attitudes toward sharing digital health data for social benefit: (1) individual sociodemographic characteristics, (2) types of health data shared, (3) motivation for sharing data, (4) data sharing concerns, and (5) reasonable access and control over the data. The association of these factors with the respondents' willingness to share was analyzed. We summarized demographic characteristics based on gender, age group, affiliated educational institution, and education history and degree. Continuous variables are expressed as mean (SE). Logistic regression was used to analyze the association between attitudes and acceptability of sharing digital health data and the predicting factors, such as participants' preferences regarding data access and control, underlying concerns, motivations for data sharing, demographic characteristics, and eHealth literacy. Results: The mean age of the participants and the SD was 52.8 (19.8) years. We identified the factors influencing respondents' willingness to share a wide range of personal digital health data in Japan, including data in medical records, biobank samples, and digitized social communication. Approximately 70% of the participants were willing to share their digital health data. The motives associated with positive willingness to share digital health data were helping future patients (odds ratio [OR] 2.5860, 95% CI 1.8849-3.5481; P<.001), receiving their own results (OR 2.2261, 95% CI 1.6243-3.0509; P<.001), and receiving financial benefits (OR 1.8059, 95% CI 1.2630-2.5822; P=.001). Concerns associated with negative willingness to share data were data being used for unethical projects (OR 0.5104, 95% CI 0.5104-0.722; P<.001) and agreeing to contract terms that they did not fully understand (OR 0.7114, 95% CI 0.5228-0.9681; P=.04). Compared with men, women were less willing to share data (OR 0.722, 95% CI 0.539-0.967; P=.03). Furthermore, the higher one's eHealth literacy, the more positive their willingness to share digital health data (OR 1.0680, 95% CI 1.0450-1.0920; P<.001). Conclusions: This study found differences in the types of data people are willing to share. Therefore, the significance of sharing data should be fully communicated to people to motivate them to share their data and contribute to their overall health.
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