Evidence map›Paper›PMID 32898148›Full record

ArticlePloS one2020

Health and kinship matter: Learning about direct-to-consumer genetic testing user experiences via online discussions.

Zhijun Yin, Lijun Song, Ellen W Clayton, Bradley A Malin

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.5field-weighted citation impact, top 10% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

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  13. A bacterial genome assembly and annotation laboratory using a virtual machine.Biochemistry and molecular biology education : a bimonthly publication of the International Union of Biochemistry and Molecular Biology
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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

4 authors at 2 institutions in 1 country.

Zhijun YinDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.ORCID 0000-0002-3075-1337
Lijun SongCenter for Genetic Privacy & Identity in Community Settings, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Ellen W ClaytonCenter for Genetic Privacy & Identity in Community Settings, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.ORCID 0000-0002-0308-4110
Bradley A MalinDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States of America.
Vanderbilt University · USVanderbilt University Medical Center · US

Funding

Genetic Privacy and Identity in Community Settings - GetPreCiSeRM1HG009034 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CLAYTON, ELLEN WRIGHT, MALIN, BRADLEY A. · 2016 to 2024
$8.3M
A Risk Management Framework for Identifiability in Genomics ResearchR01HG006844 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI MALIN, BRADLEY A. · 2012 to 2019
$2.4M
Genetic Privacy and Identity in Sexual and Gender Minorities: GetPrISMR21HG010652 · NHGRI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CLAYTON, ELLEN WRIGHT · 2019 to 2020
$468k
NHGRI NIH HHS R01 HG006844NHGRI NIH HHS R21 HG010652NHGRI NIH HHS RM1 HG009034
6 · The paper itself

Abstract

backgroundMillions of people have undergone direct-to-consumer genetic testing (DTC-GT), but little is known about individuals' motivations and experiences (e.g., discussion topics and emotions after obtaining the test results) in engaging with DTC-GT services. Previous studies either involved only a small number of DTC-GT consumers or were based on hypothetical scenarios.

objectiveOur study aimed to fill this gap by investigating online discussions about DTC-GT that developed naturally among tens of thousands of social media users.

methodsWe focused on the posts that were published in the r/23andme and r/AncestryDNA subreddits, which correspond to the two companies with the largest number of consumers in the DTC-GT market. We applied computational methods to infer and examine the topics discussed, temporal trends in posting rates and themes (e.g., aggregation of related topics), and emotions expressed in these online forums.

resultsWe collected 157,000 posts published by 16,500 Reddit users between 2013 and 2019. We found that the posting rates increased sharply after popular promotional events (e.g., each Amazon Prime Day and Black Friday) and most posts were inquiries into, or status updates about, testing progress. The inferred themes of Ancestral Origin and Kinship/Feelings were the two most frequently discussed, while discussions about the Health Risks theme focused primarily on submitting DTC-GT raw data to third parties for interpretation. The Kinship/Feelings theme exhibited the largest range of emotional response. A qualitative review of the posts with extreme emotions showed that some people became excited because they found their biological parents or other kin, while others became upset because they unexpectedly found that their parents or other kin were not biologically related to them.

conclusionThis research demonstrates that online social media platforms can serve as a rich resource for characterizing actual DTC-GT experiences. The findings suggest that DTC-GT consumers' purchasing behaviors are associated with societal events and that future investigations should consider how DTC-GT challenges our understanding of kinship structure and function, genomic privacy, and the interpretation of health risks.

Indexed as

Direct-To-Consumer Screening and TestingGenetic TestingHealthInternetInterpersonal RelationsHumansProbabilitySocial Media

Identifiers

PMID32898148
PMCPMC7478842
OpenAlexW3084188602

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.