CovidStanfordV1, Main, Exploration, bibRecord, 000810

Americans' perceptions of privacy and surveillance in the COVID-19 pandemic.

Identifieur interne : 000810 ( Main/Exploration ); précédent : 000809; suivant : 000811

Americans' perceptions of privacy and surveillance in the COVID-19 pandemic.

Auteurs : Baobao Zhang [États-Unis] ; Sarah Kreps [États-Unis] ; Nina Mcmurry [Allemagne] ; R Miles Mccain [États-Unis]

Source :

PloS one [ 1932-6203 ] ; 2020.

RBID : pubmed:33362218

Descripteurs français

KwdFr :
- Adulte (MeSH), Adulte d'âge moyen (MeSH), Applications mobiles (MeSH), Enquêtes et questionnaires (MeSH), Femelle (MeSH), Humains (MeSH), Mâle (MeSH), Ordiphone (MeSH), Pandémies (MeSH), Perception (MeSH), Quarantaine (psychologie), Surveillance de la santé publique (MeSH), Traçage des contacts (éthique), Vie privée (MeSH), États-Unis (MeSH).
MESH :
- psychologie : Quarantaine.
- éthique : Traçage des contacts.
- Adulte, Adulte d'âge moyen, Applications mobiles, Enquêtes et questionnaires, Femelle, Humains, Mâle, Ordiphone, Pandémies, Perception, Surveillance de la santé publique, Vie privée, États-Unis.
Wicri :
- geographic : États-Unis.

English descriptors

KwdEn :
- Adult (MeSH), COVID-19 (epidemiology), COVID-19 (psychology), COVID-19 (virology), Contact Tracing (ethics), Female (MeSH), Humans (MeSH), Male (MeSH), Middle Aged (MeSH), Mobile Applications (MeSH), Pandemics (MeSH), Perception (MeSH), Privacy (MeSH), Public Health Surveillance (MeSH), Quarantine (psychology), SARS-CoV-2 (pathogenicity), Smartphone (MeSH), Surveys and Questionnaires (MeSH), United States (MeSH).
MESH :
- geographic : United States.
- epidemiology : COVID-19.
- ethics : Contact Tracing.
- pathogenicity : SARS-CoV-2.
- psychology : COVID-19, Quarantine.
- virology : COVID-19.
- Adult, Female, Humans, Male, Middle Aged, Mobile Applications, Pandemics, Perception, Privacy, Public Health Surveillance, Smartphone, Surveys and Questionnaires.

Abstract

OBJECTIVE

To study the U.S. public's attitudes toward surveillance measures aimed at curbing the spread of COVID-19, particularly smartphone applications (apps) that supplement traditional contact tracing.

METHOD

We deployed a survey of approximately 2,000 American adults to measure support for nine COVID-19 surveillance measures. We assessed attitudes toward contact tracing apps by manipulating six different attributes of a hypothetical app through a conjoint analysis experiment.

RESULTS

A smaller percentage of respondents support the government encouraging everyone to download and use contact tracing apps (42%) compared with other surveillance measures such as enforcing temperature checks (62%), expanding traditional contact tracing (57%), carrying out centralized quarantine (49%), deploying electronic device monitoring (44%), or implementing immunity passes (44%). Despite partisan differences on a range of surveillance measures, support for the government encouraging digital contact tracing is indistinguishable between Democrats (47%) and Republicans (46%), although more Republicans oppose the policy (39%) compared to Democrats (27%). Of the app features we tested in our conjoint analysis experiment, only one had statistically significant effects on the self-reported likelihood of downloading the app: decentralized data architecture increased the likelihood by 5.4 percentage points.

CONCLUSION

Support for public health surveillance policies to curb the spread of COVID-19 is relatively low in the U.S. Contact tracing apps that use decentralized data storage, compared with those that use centralized data storage, are more accepted by the public. While respondents' support for expanding traditional contact tracing is greater than their support for the government encouraging the public to download and use contact tracing apps, there are smaller partisan differences in support for the latter policy.

DOI: 10.1371/journal.pone.0242652
PubMed: 33362218
PubMed Central: PMC7757814

Affiliations:

Links toward previous steps (curation, corpus...)

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Le document en format XML

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<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term>
<term>COVID-19 (epidemiology)</term>
<term>COVID-19 (psychology)</term>
<term>COVID-19 (virology)</term>
<term>Contact Tracing (ethics)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Mobile Applications (MeSH)</term>
<term>Pandemics (MeSH)</term>
<term>Perception (MeSH)</term>
<term>Privacy (MeSH)</term>
<term>Public Health Surveillance (MeSH)</term>
<term>Quarantine (psychology)</term>
<term>SARS-CoV-2 (pathogenicity)</term>
<term>Smartphone (MeSH)</term>
<term>Surveys and Questionnaires (MeSH)</term>
<term>United States (MeSH)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Applications mobiles (MeSH)</term>
<term>Enquêtes et questionnaires (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Ordiphone (MeSH)</term>
<term>Pandémies (MeSH)</term>
<term>Perception (MeSH)</term>
<term>Quarantaine (psychologie)</term>
<term>Surveillance de la santé publique (MeSH)</term>
<term>Traçage des contacts (éthique)</term>
<term>Vie privée (MeSH)</term>
<term>États-Unis (MeSH)</term>
</keywords>
<keywords scheme="MESH" type="geographic" xml:lang="en"><term>United States</term>
</keywords>
<keywords scheme="MESH" qualifier="epidemiology" xml:lang="en"><term>COVID-19</term>
</keywords>
<keywords scheme="MESH" qualifier="ethics" xml:lang="en"><term>Contact Tracing</term>
</keywords>
<keywords scheme="MESH" qualifier="pathogenicity" xml:lang="en"><term>SARS-CoV-2</term>
</keywords>
<keywords scheme="MESH" qualifier="psychologie" xml:lang="fr"><term>Quarantaine</term>
</keywords>
<keywords scheme="MESH" qualifier="psychology" xml:lang="en"><term>COVID-19</term>
<term>Quarantine</term>
</keywords>
<keywords scheme="MESH" qualifier="virology" xml:lang="en"><term>COVID-19</term>
</keywords>
<keywords scheme="MESH" qualifier="éthique" xml:lang="fr"><term>Traçage des contacts</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Female</term>
<term>Humans</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Mobile Applications</term>
<term>Pandemics</term>
<term>Perception</term>
<term>Privacy</term>
<term>Public Health Surveillance</term>
<term>Smartphone</term>
<term>Surveys and Questionnaires</term>
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<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Applications mobiles</term>
<term>Enquêtes et questionnaires</term>
<term>Femelle</term>
<term>Humains</term>
<term>Mâle</term>
<term>Ordiphone</term>
<term>Pandémies</term>
<term>Perception</term>
<term>Surveillance de la santé publique</term>
<term>Vie privée</term>
<term>États-Unis</term>
</keywords>
<keywords scheme="Wicri" type="geographic" xml:lang="fr"><term>États-Unis</term>
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<front><div type="abstract" xml:lang="en"><p><b>OBJECTIVE</b>
</p>
<p>To study the U.S. public's attitudes toward surveillance measures aimed at curbing the spread of COVID-19, particularly smartphone applications (apps) that supplement traditional contact tracing.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHOD</b>
</p>
<p>We deployed a survey of approximately 2,000 American adults to measure support for nine COVID-19 surveillance measures. We assessed attitudes toward contact tracing apps by manipulating six different attributes of a hypothetical app through a conjoint analysis experiment.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>A smaller percentage of respondents support the government encouraging everyone to download and use contact tracing apps (42%) compared with other surveillance measures such as enforcing temperature checks (62%), expanding traditional contact tracing (57%), carrying out centralized quarantine (49%), deploying electronic device monitoring (44%), or implementing immunity passes (44%). Despite partisan differences on a range of surveillance measures, support for the government encouraging digital contact tracing is indistinguishable between Democrats (47%) and Republicans (46%), although more Republicans oppose the policy (39%) compared to Democrats (27%). Of the app features we tested in our conjoint analysis experiment, only one had statistically significant effects on the self-reported likelihood of downloading the app: decentralized data architecture increased the likelihood by 5.4 percentage points.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSION</b>
</p>
<p>Support for public health surveillance policies to curb the spread of COVID-19 is relatively low in the U.S. Contact tracing apps that use decentralized data storage, compared with those that use centralized data storage, are more accepted by the public. While respondents' support for expanding traditional contact tracing is greater than their support for the government encouraging the public to download and use contact tracing apps, there are smaller partisan differences in support for the latter policy.</p>
</div>
</front>
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<Abstract><AbstractText Label="OBJECTIVE">To study the U.S. public's attitudes toward surveillance measures aimed at curbing the spread of COVID-19, particularly smartphone applications (apps) that supplement traditional contact tracing.</AbstractText>
<AbstractText Label="METHOD">We deployed a survey of approximately 2,000 American adults to measure support for nine COVID-19 surveillance measures. We assessed attitudes toward contact tracing apps by manipulating six different attributes of a hypothetical app through a conjoint analysis experiment.</AbstractText>
<AbstractText Label="RESULTS">A smaller percentage of respondents support the government encouraging everyone to download and use contact tracing apps (42%) compared with other surveillance measures such as enforcing temperature checks (62%), expanding traditional contact tracing (57%), carrying out centralized quarantine (49%), deploying electronic device monitoring (44%), or implementing immunity passes (44%). Despite partisan differences on a range of surveillance measures, support for the government encouraging digital contact tracing is indistinguishable between Democrats (47%) and Republicans (46%), although more Republicans oppose the policy (39%) compared to Democrats (27%). Of the app features we tested in our conjoint analysis experiment, only one had statistically significant effects on the self-reported likelihood of downloading the app: decentralized data architecture increased the likelihood by 5.4 percentage points.</AbstractText>
<AbstractText Label="CONCLUSION">Support for public health surveillance policies to curb the spread of COVID-19 is relatively low in the U.S. Contact tracing apps that use decentralized data storage, compared with those that use centralized data storage, are more accepted by the public. While respondents' support for expanding traditional contact tracing is greater than their support for the government encouraging the public to download and use contact tracing apps, there are smaller partisan differences in support for the latter policy.</AbstractText>
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<ForeName>Baobao</ForeName>
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<AffiliationInfo><Affiliation>Department of Government, Cornell University, Ithaca, NY, United States of America.</Affiliation>
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<ForeName>Sarah</ForeName>
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<AffiliationInfo><Affiliation>Institutions and Political Inequality Unit, WZB Berlin Social Science Center, Berlin, Germany.</Affiliation>
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<ForeName>R Miles</ForeName>
<Initials>RM</Initials>
<Identifier Source="ORCID">0000-0001-5326-9212</Identifier>
<AffiliationInfo><Affiliation>Stanford University, Palo Alto, CA, United States of America.</Affiliation>
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<MeshHeading><DescriptorName UI="D018907" MajorTopicYN="N">Privacy</DescriptorName>
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<MeshHeading><DescriptorName UI="D062486" MajorTopicYN="N">Public Health Surveillance</DescriptorName>
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<Reference><Citation>Health Educ Q. 1988 Summer;15(2):175-83</Citation>
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<tree><country name="États-Unis"><region name="État de New York"><name sortKey="Zhang, Baobao" sort="Zhang, Baobao" uniqKey="Zhang B" first="Baobao" last="Zhang">Baobao Zhang</name>
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<country name="Allemagne"><region name="Berlin"><name sortKey="Mcmurry, Nina" sort="Mcmurry, Nina" uniqKey="Mcmurry N" first="Nina" last="Mcmurry">Nina Mcmurry</name>
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   |étape=   Exploration
   |type=    RBID
   |clé=     pubmed:33362218
   |texte=   Americans' perceptions of privacy and surveillance in the COVID-19 pandemic.
}}

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HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i   -Sk "pubmed:33362218" \
       | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd   \
       | NlmPubMed2Wicri -a CovidStanfordV1

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	Serveur d'exploration sur le Covid à Stanford
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Serveur d'exploration sur le Covid à Stanford

Americans' perceptions of privacy and surveillance in the COVID-19 pandemic.

Americans' perceptions of privacy and surveillance in the COVID-19 pandemic.

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