Evidence map›Paper›PMID 33407467›Full record

ArticleBMC medical genomics2021

ShareDNA: a smartphone app to facilitate family communication of genetic results.

Chethan Jujjavarapu, Jeevan Anandasakaran, Laura M Amendola, Cameron Haas, Elizabeth Zampino, Nora B Henrikson, Gail P Jarvik, Sean D Mooney

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

5 citing papers in PubMed, 8 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 3 institutions in 1 country.

Chethan JujjavarapuDepartment of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, WA, USA.
Jeevan AnandasakaranInstitute of Translational Health Sciences, University of Washington, Seattle, WA, USA.
Laura M AmendolaDepartment of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA.
Cameron HaasKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Elizabeth ZampinoInstitute of Translational Health Sciences, University of Washington, Seattle, WA, USA.
Nora B HenriksonKaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
Gail P JarvikDepartment of Medicine (Medical Genetics), University of Washington, Seattle, WA, USA.
Sean D MooneyDepartment of Biomedical Informatics and Medical Education, School of Medicine, University of Washington, Seattle, WA, USA. sdmooney@uw.edu.ORCID 0000-0003-2654-0833
University of Washington · USKaiser Permanente Washington Health Research Institute · USUniversity of Washington Medical Center · US

Funding

Transform Dissemination and Implementation Science in CTSA ProgramsUL1TR002319 · NCATS · UNIVERSITY OF WASHINGTON · PI John K. Amory · 2017 to 2026
$100.0M
Variation, Function, and Disease Supplement ProgramU01HG008657 · NHGRI · UNIVERSITY OF WASHINGTON · PI David Russell Crosslin, Gail Pairitz Jarvik · 2015 to 2026
$13.4M
NCATS NIH HHS UL1 TR002319NHGRI NIH HHS U01 HG008657NIH HHS 5U01HG008657-05
6 · The paper itself

Abstract

backgroundGenetic testing allows patients and clinicians to understand the risk of hereditary diseases. By testing early, individuals can make informed medical decisions about management which may minimize the risk of developing certain diseases. Importantly, genetic test results may also be applicable to patients' biological relatives; thus, these results could also lead to minimizing their risk of disease. However, sharing genetic test results between patients and their relatives is scarce. The most frequently reported problems are that patients cannot clearly explain this information and relatives misinterpret the results. Smartphone apps in the healthcare field are a possible solution as they allow patients to accurately share sensitive information to others, while providing educational material to support understanding the information. However, these apps may not provide security to protect patients' identifiable information. We developed ShareDNA, a smartphone app that (1) allows patients to securely share their genetic test results with others, (2) provides information on how to interpret these results, and (3) minimizes the amount of patient information needed to use the service.

resultsWe recruited thirteen participants to test the usability of our app and provide feedback. We found overall that participants were comfortable with using this app and could easily learn each app function when filling out our questionnaire. Additionally, based on vocalized impressions of the usefulness of the app, participants indicated that the user-interface could be more intuitive and that we needed to add more text within the app to explain why ShareDNA is a secure service.

conclusionsShareDNA is a free smartphone app that allows patients to share their genetic test results with others, including their biological relatives. Sharing these results along with educational material will enable relatives to share accurate information and discuss their possible risk for disease with their clinical providers. As a result, appropriate testing in relatives could be improved.

Indexed as

Genetic TestingMobile ApplicationsSmartphoneAdultCommunicationFamilyFemaleHumansMaleMiddle AgedSurveys and QuestionnairesAppApplicationCascade testingFamily communicationGeneticsGenetic testingSmartphone

Identifiers

PMID33407467
PMCPMC7788871
OpenAlexW3118981323

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.