Evidence map›Paper›PMID 39873672›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2025

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

Ashwini Nagappan, Xi Zhu

Abstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
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1 · What the graph read from 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.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Ashwini NagappanDepartment of Health Policy and Management, Fielding School of Public Health, UCLA, Los Angeles, CA 90095, United States.
Xi ZhuDepartment of Health Policy and Management, Fielding School of Public Health, UCLA, Los Angeles, CA 90095, United States.

Funding

NRSA Training CoreTL1TR001883 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ALEX BUI, Nina Thawata Harawa · 2016 to 2026
$8.6M
National Center for Advancing Translational ScienceNational Center for Advancing Translational Science TL1TR001883NCATSNCATS NIH HHS TL1 TR001883NIHUCLA CTSI TL1TR001883
6 · The paper itself

Abstract

objectiveTo identify distinct patterns in consumer willingness to share health data with various stakeholders and analyze characteristics across consumer groups. MATERIALS AND

methodsData 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.

resultsWe 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.

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

Indexed as

Consumer BehaviorInformation DisseminationStakeholder ParticipationAdolescentAdultAgedFemaleHumansLatent Class AnalysisMaleMiddle AgedSurveys and QuestionnairesUnited StatesYoung Adultconfidentialitydatalatent class analysispatient-generated health dataprivacy

Identifiers

PMID39873672
PMCPMC12005618

What OpenQuestion holds

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Registered trials

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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.