Evidence map›Paper›PMID 40233172›Full record

ArticleJMIR human factors2025

The Impact of Trust and the Role of the Opt-Out Mechanism in Willingness to Share Health Data via Electronic Health Records in Germany: Telephone Survey Study.

Felix Wilke

Abstract read
In one paragraph

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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 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.

Felix WilkeDepartment of Social Work, University of Applied Sciences Jena, Carl-Zeiss-Promenade 2, Jena, 07745, Germany, 49 3641205815.ORCID 0000-0002-1257-3522

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electronic health records (EHRs) offer a valuable resource for research and health care improvement. However, public acceptance of sharing personal health data is critical to the success of such initiatives. In Germany, automatic data sharing via EHRs will be implemented unless people opt out. Objective: This study aims to assess the willingness of the German population to share health data via EHRs and to explore the role of trust in influencing these attitudes. Methods: A computer-assisted telephone interview study was conducted in December 2023, with 1004 respondents aged 18 years and older, representative of the German population. Descriptive statistics and multivariate linear regression models were used to analyze the data. Results: The survey shows that 43.4% (n=432) of respondents would be willing to share their health data via EHR, and a significant 34% (n=338) remain undecided. While the population is open to adoption of the EHR for personal health issues (n=483, 53% show interest in using it), the opt-out model for data sharing is viewed critically, with 44.7% (n=438) of respondents rejecting it. Socioeconomic status significantly influences the willingness to share data, with higher income, education, and digital literacy being associated with greater openness to data sharing. However, trust emerged as the most significant factor. Additionally, experiences with digital technologies increase the willingness to share personal health data. Conclusions: The German population shows general openness toward EHRs and data sharing. Trust plays a critical role in promoting willingness to share health data. The findings highlight challenges in Germany's transition to an opt-out system.

Indexed as

Electronic Health RecordsInformation DisseminationTrustAdolescentAdultAgedFemaleGermanyHumansMaleMiddle AgedSurveys and QuestionnairesYoung Adultcitizensdata sharingdigitalizationelectronic health recordhealthopt-outtrust

Identifiers

PMID40233172
PMCPMC12013774

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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.