Evidence mapPaperPMID 40063296Full record

ArticleJournal of racial and ethnic health disparities2026

Sharing Patient-Generated Health Data: The Role of Healthcare Quality, Mistrust, and Discrimination Across Race-Gender Identities.

Fatima G Fairfax

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In one paragraph

Article in Journal of racial and ethnic health disparities, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Fatima G FairfaxDepartment of Sociology, Duke University, Durham, NC, USA. Fatima.fairfax@duke.edu.ORCID 0009-0001-7232-3832

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The widespread adoption of personal health devices has introduced a new source of health data for patients and providers to use in healthcare settings. Using patient-generated health data (PGHD) in healthcare settings has been found to improve patient-provider interactions and care outcomes. However, rates of PGHD sharing vary across the population. The decision to share one's PGHD with providers is influenced by past healthcare encounters including quality of care, medical mistrust, and healthcare discrimination. Furthermore, those experiences and patients' responses to them should be examined with an intersectional lens to acknowledge how gendered racism impacts health and healthcare. Using the 2022 Health Information National Trends Survey (HINTS) and logistic regression, this study shows how racial discrimination, healthcare quality, and medical mistrust are associated with patients' willingness and decision to share PGHD with providers among different race-gender identities. Factors associated with patients' perceived willingness to share data are not the same factors that are associated with actually sharing PGHD with providers. Perceived racial discrimination in healthcare settings was only significantly associated with willingness to share PGHD among Black men and white men. Meanwhile, poor overall healthcare quality was significantly associated with incidences of sharing data among Black and Hispanic women. These varied patterns across intent to share and choice to share, as well as across race-gender identity, reveal important insights into barriers to effective integration of PGHD in clinical spaces and the use of this technology to address healthcare inequities.

Indexed as

Gender IdentityQuality of Health CareRacial GroupsRacismTrustAdolescentAdultAgedBlack or African AmericanFemaleHealthcare DisparitiesHumansMaleMiddle AgedUnited StatesWhiteHealthcare disparitiesHealth technologyIntersectionalityMedical racismMedical sexismPatient-generated health data

Identifiers

PMID40063296

What Socratic 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 Socratic graph.