Evidence map›Paper›PMID 34106074›Full record

ArticleJournal of medical Internet research2021

Consumer Views on Health Applications of Consumer Digital Data and Health Privacy Among US Adults: Qualitative Interview Study.

David Grande, Xochitl Luna Marti, Raina M Merchant, David A Asch, Abby Dolan, Meghana Sharma, Carolyn C Cannuscio

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.8field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 16 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Digital phenotyping and ASCVD risk: An exploratory cross-sectional analysis using online behavioral data.American heart journal plus : cardiology research and practice · 2026
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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 at 2 institutions in 1 country.

David GrandeDivision of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-6717-6735
Xochitl Luna MartiDivision of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-7102-6940
Raina M MerchantDepartment of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-9801-6881
David A AschDivision of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-7970-286X
Abby DolanDepartment of Emergency Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-5994-0617
Meghana SharmaDivision of General Internal Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-9601-4460
Carolyn C CannuscioDepartment of Family Medicine and Community Health, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0001-9082-6313
University of Pennsylvania · USUniversity of Pennsylvania Health System · US

Funding

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
NHGRI NIH HHS R01 HG009655
6 · The paper itself

Abstract

backgroundIn 2020, the number of internet users surpassed 4.6 billion. Individuals who create and share digital data can leave a trail of information about their habits and preferences that collectively generate a digital footprint. Studies have shown that digital footprints can reveal important information regarding an individual's health status, ranging from diet and exercise to depression. Uses of digital applications have accelerated during the COVID-19 pandemic where public health organizations have utilized technology to reduce the burden of transmission, ultimately leading to policy discussions about digital health privacy. Though US consumers report feeling concerned about the way their personal data is used, they continue to use digital technologies.

objectiveThis study aimed to understand the extent to which consumers recognize possible health applications of their digital data and identify their most salient concerns around digital health privacy.

methodsWe conducted semistructured interviews with a diverse national sample of US adults from November 2018 to January 2019. Participants were recruited from the Ipsos KnowledgePanel, a nationally representative panel. Participants were asked to reflect on their own use of digital technology, rate various sources of digital information, and consider several hypothetical scenarios with varying sources and health-related applications of personal digital information.

resultsThe final cohort included a diverse national sample of 45 US consumers. Participants were generally unaware what consumer digital data might reveal about their health. They also revealed limited knowledge of current data collection and aggregation practices. When responding to specific scenarios with health-related applications of data, they had difficulty weighing the benefits and harms but expressed a desire for privacy protection. They saw benefits in using digital data to improve health, but wanted limits to health programs' use of consumer digital data.

conclusionsCurrent privacy restrictions on health-related data are premised on the notion that these data are derived only from medical encounters. Given that an increasing amount of health-related data is derived from digital footprints in consumer settings, our findings suggest the need for greater transparency of data collection and uses, and broader health privacy protections.

Indexed as

Interviews as TopicQualitative ResearchAdolescentAdultCohort StudiesConsumer BehaviorConsumer Health InformationData CollectionDatasets as TopicFemaleHumansMaleMiddle AgedPrivacyUnited StatesYoung Adultdigital epidemiologydigital health privacyhealth lawhealth privacyprivacy law

Identifiers

PMID34106074
PMCPMC8262668
OpenAlexW3172242389

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.