Patterns of willingness to share health data with key stakeholders in US consumers: a latent class analysis.

IF 4.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Ashwini Nagappan, Xi Zhu
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引用次数: 0

Abstract

Objective: To identify distinct patterns in consumer willingness to share health data with various stakeholders and analyze characteristics across consumer groups.

Materials and methods: Data from the Rock Health Digital Health Consumer Adoption Survey from 2018, 2019, 2020, and 2022 were analyzed. This study comprised a Census-matched representative sample of U.S. adults. Latent class analysis (LCA) identified groups of respondents with similar data-sharing attitudes. Groups were compared by sociodemographics, health status, and digital health utilization.

Results: We identified three distinct LCA groups: (1) Wary (36.8%), (2) Discerning (47.9%), and (3) Permissive (15.3%). The Wary subgroup exhibited reluctance to share health data with any stakeholder, with predicted probabilities of willingness to share ranging from 0.07 for pharmaceutical companies to 0.34 for doctors/clinicians. The Permissive group showed a high willingness, with predicted probabilities greater than 0.75 for most stakeholders except technology companies and government organizations. The Discerning group was selective, willing to share with healthcare-related entities and family (predicted probabilities >0.62), but reluctant to share with other stakeholders (predicted probabilities <0.29). Individual characteristics were associated with LCA group membership.

Discussion: Findings highlight a persistent trust in traditional healthcare providers. However, the varying willingness to share with non-traditional stakeholders suggests that while some consumers are open to sharing, others remain hesitant and selective. Data privacy policies and practices need to recognize and respond to multifaceted and stakeholder-specific attitudes.

Conclusion: LCA reveals significant heterogeneity in health data-sharing attitudes among U.S. consumers, providing insights to inform the development of data privacy policies.

目的确定消费者与不同利益相关者共享健康数据的意愿的不同模式,并分析不同消费者群体的特征:对 Rock Health 数字健康消费者采用情况调查 2018 年、2019 年、2020 年和 2022 年的数据进行了分析。这项研究由人口普查匹配的美国成年人代表性样本组成。潜类分析(LCA)确定了具有相似数据共享态度的受访者群体。根据社会人口统计学、健康状况和数字健康使用情况对这些群体进行了比较:我们确定了三个不同的 LCA 群体:(1) 谨慎型(36.8%)、(2) 明察秋毫型(47.9%)和 (3) 宽容型(15.3%)。警惕亚组表现出不愿意与任何利益相关者共享健康数据,愿意共享的预测概率从制药公司的 0.07 到医生/临床医生的 0.34 不等。许可组显示出较高的意愿,除技术公司和政府组织外,大多数利益相关者的预测概率都大于 0.75。明辨组则有所选择,愿意与医疗保健相关实体和家人分享信息(预测概率大于 0.62),但不愿意与其他利益相关者分享信息(预测概率为讨论):研究结果凸显了人们对传统医疗保健提供者的持续信任。然而,与非传统利益相关者分享信息的意愿却各不相同,这表明尽管一些消费者对分享信息持开放态度,但另一些消费者仍然犹豫不决并有所选择。数据隐私政策和实践需要认识到利益相关者多方面的特定态度,并做出回应:LCA 揭示了美国消费者在健康数据共享态度上的显著异质性,为数据隐私政策的制定提供了启示。
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来源期刊
Journal of the American Medical Informatics Association
Journal of the American Medical Informatics Association 医学-计算机:跨学科应用
CiteScore
14.50
自引率
7.80%
发文量
230
审稿时长
3-8 weeks
期刊介绍: JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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