Evidence map›Paper›PMID 31395102›Full record

ArticleBMC medical informatics and decision making2019

Patients' willingness to share digital health and non-health data for research: a cross-sectional study.

Emily Seltzer, Jesse Goldshear, Sharath Chandra Guntuku, Dave Grande, David A Asch, Elissa V Klinger, Raina M Merchant

Registry-linked trialAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05880147 (App-based Consent for Participation in Pediatric Clinical Research), which is not on this map. Cited by 41 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 3 pooled it
–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.

NCT05880147 nacompletednot on this mapstarted 2023, after this paper: background citation

App-based Consent for Participation in Pediatric Clinical Research: a Feasibility Study

TypeinterventionalSponsorUniversity of British ColumbiaRan2023 to 2024Enrolled120ConditionsConsentArmsConsent App, Traditional paper-based consent
3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  18. The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary.Clinical research in cardiology : official journal of the German Cardiac Society · 2024
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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

7 authors.

Emily SeltzerPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA.
Jesse GoldshearPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA.
Sharath Chandra GuntukuPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA. sharathg@sas.upenn.edu.ORCID 0000-0002-2929-0035
Dave GrandeDivision of General Internal Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, USA.
David A AschPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA.
Elissa V KlingerPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA.
Raina M MerchantPenn Medicine Center for Digital Health, University of Pennsylvania, 3400 Civic Blvd, Philadelphia, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients generate large amounts of digital data through devices, social media applications, and other online activities. Little is known about patients' perception of the data they generate online and its relatedness to health, their willingness to share data for research, and their preferences regarding data use.

methodsPatients at an academic urban emergency department were asked if they would donate any of 19 different types of data to health researchers and were asked about their views on data types' health relatedness. Factor analysis was used to identify the structure in patients' perceptions of willingness to share different digital data, and their health relatedness.

resultsOf 595 patients approached 206 agreed to participate, of whom 104 agreed to share at least one types of digital data immediately, and 78% agreed to donate at least one data type after death. EMR, wearable, and Google search histories (80%) had the highest percentage of reported health relatedness. 72% participants wanted to know the results of any analysis of their shared data, and half wanted their healthcare provider to know.

conclusionPatients in this study were willing to share a considerable amount of personal digital data with health researchers. They also recognize that digital data from many sources reveal information about their health. This study opens up a discussion around reconsidering US privacy protections for health information to reflect current opinions and to include their relatedness to health.

Indexed as

AttitudeHealth Services ResearchPrivacyVolitionAdolescentAdultCross-Sectional StudiesEmergency Service, HospitalFemaleHumansMaleMiddle AgedSocial MediaYoung AdultData donationData privacyDigital healthmHealthSocial media

Identifiers

PMID31395102
PMCPMC6686530

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.