Evidence map›Paper›PMID 36862410›Full record

ArticleJAMA network open2023

Consumer Views on Privacy Protections and Sharing of Personal Digital Health Information.

Ravi Gupta, Raghuram Iyengar, Meghana Sharma, Carolyn C Cannuscio, Raina M Merchant, David A Asch, Nandita Mitra, David Grande

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
15.0field-weighted citation impact, top 1% of its field
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

16 citing papers in PubMed, 26 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Ravi GuptaJohns Hopkins University School of Medicine, Baltimore, Maryland.
Raghuram IyengarWharton School, University of Pennsylvania, Philadelphia.
Meghana SharmaPerelman School of Medicine, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania, Philadelphia.
Carolyn C CannuscioPerelman School of Medicine, Department of Family Medicine and Community Health, University of Pennsylvania, Philadelphia.
Raina M MerchantLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.
David A AschWharton School, University of Pennsylvania, Philadelphia.
Nandita MitraLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia.
David GrandePerelman School of Medicine, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania, Philadelphia.
University of Pennsylvania · USJohns Hopkins University · US

Funding

Digital Phenotyping and Cardiovascular HealthR01HL141844 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MERCHANT, RAINA · 2019 to 2022
$3.1M
Patient Preferences for Collecting and Repurposing Genetic, Consumer and Health Care InformationR01HG009655 · NHGRI · UNIVERSITY OF PENNSYLVANIA · PI GRANDE, DAVID T · 2017 to 2020
$1.9M
Mentoring and Patient Oriented Research in Cardiovascular Health and Digital Data ScienceK24HL157621 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MERCHANT, RAINA · 2021 to 2025
$615k
NHGRI NIH HHS R01 HG009655NHLBI NIH HHS K24 HL157621NHLBI NIH HHS R01 HL141844
6 · The paper itself

Abstract

Importance: Digital health information has many potential health applications, but privacy is a growing concern among consumers and policy makers. Consent alone is increasingly seen as inadequate to safeguard privacy. Objective: To determine whether different privacy protections are associated with consumers' willingness to share their digital health information for research, marketing, or clinical uses. Design, Setting, and Participants: This 2020 national survey with an embedded conjoint experiment recruited US adults from a nationally representative sample with oversampling of Black and Hispanic individuals. Willingness to share digital information across 192 different scenarios reflecting the product of 4 possible privacy protections, 3 uses of information, 2 users of information, and 2 sources of digital information was evaluated. Each participant was randomly assigned 9 scenarios. The survey was administrated between July 10 and July 31, 2020, in Spanish and English. Analysis for this study was conducted between May 2021 and July 2022. Main Outcomes and Measures: Participants rated each conjoint profile on a 5-point Likert scale measuring their willingness to share their personal digital information (with 5 indicating the most willingness to share). Results are reported as adjusted mean differences. Results: Of the 6284 potential participants, 3539 (56%) responded to the conjoint scenarios. A total of 1858 participants (53%) were female, 758 (21%) identified as Black, 833 (24%) identified as Hispanic, 1149 (33%) had an annual income less than $50 000, and 1274 (36%) were 60 years or older. Participants were more willing to share health information with the presence of each individual privacy protection, including consent (difference, 0.32; 95% CI, 0.29-0.35; P < .001), followed by data deletion (difference, 0.16; 95% CI, 0.13-0.18; P < .001), oversight (difference, 0.13; 95% CI, 0.10-0.15; P < .001), and transparency of data collected (difference, 0.08; 95% CI, 0.05-0.10; P < .001). The relative importance (importance weight on a 0%-100% scale) was greatest for the purpose of use (29.9%) but when considered collectively, the 4 privacy protections together were the most important (51.5%) factor in the conjoint experiment. When the 4 privacy protections were considered separately, consent was the most important (23.9%). Conclusions and Relevance: In this survey study of a nationally representative sample of US adults, consumers' willingness to share personal digital health information for health purposes was associated with the presence of specific privacy protections beyond consent alone. Additional protections, including data transparency, oversight, and data deletion may strengthen consumer confidence in sharing their personal digital health information.

Indexed as

Electronic Health RecordsPrivacyAdultFemaleHumansIncomeInformation DisseminationMaleUnited States

Identifiers

PMID36862410
PMCPMC9982693
OpenAlexW4322758178

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.