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      <ref-type name="Journal Article">17</ref-type>
      <work-type>ACL : Articles dans des revues avec comité de lecture répertoriées par l'AERES</work-type>
      <contributors>
        <authors>
          <author>
            <style face="normal" font="default" size="100%">Touzani, R.</style>
          </author>
          <author>
            <style face="bold" font="default" size="100%">Schultz, Emilien</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Holmes, S. M.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Vandentorren, S.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Arwidson, P.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Guillemin, F.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Rey, D.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Rouquette, A.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Bouhnik, A. D.</style>
          </author>
          <author>
            <style face="normal" font="default" size="100%">Mancini, J.</style>
          </author>
        </authors>
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      <titles>
        <title>Early acceptability of a mobile app for contact tracing during the COVID-19 pandemic in France : national web-based survey</title>
        <secondary-title>JMIR mHealth and uHealth</secondary-title>
      </titles>
      <pages>e27768 [13 ]</pages>
      <keywords>
        <keyword>COVID-19</keyword>
        <keyword>mobile app</keyword>
        <keyword>contact tracing</keyword>
        <keyword>HLS19</keyword>
        <keyword>health care disparities</keyword>
        <keyword>public health</keyword>
        <keyword>FRANCE</keyword>
      </keywords>
      <dates>
        <year>2021</year>
      </dates>
      <call-num>fdi:010082770</call-num>
      <language>ENG</language>
      <periodical>
        <full-title>JMIR mHealth and uHealth</full-title>
      </periodical>
      <isbn>2291-5222</isbn>
      <accession-num>ISI:000692249000002</accession-num>
      <number>7</number>
      <electronic-resource-num>10.2196/27768</electronic-resource-num>
      <urls>
        <related-urls>
          <url>https://www.documentation.ird.fr/hor/fdi:010082770</url>
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        <pdf-urls>
          <url>https://horizon.documentation.ird.fr/exl-doc/pleins_textes/2021-10/010082770.pdf</url>
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      </urls>
      <volume>9</volume>
      <remote-database-provider>Horizon (IRD)</remote-database-provider>
      <abstract>Background: Several countries have implemented mobile apps in an attempt to trace close contacts of patients with COVID-19 and, in turn, reduce the spread of SARS-CoV-2. However, the effectiveness of this approach depends on the adherence of a large segment of the population. Objective: The aims of this study were to evaluate the acceptability of a COVID-19 contact tracing mobile app among the French population and to investigate the barriers to its use. Methods: The Health Literacy Survey 2019 questioned 1003 people in France during the COVID-19 pandemic on the basis of quota sampling. The survey collected sociodemographic characteristics and health literacy data, as well as information on participants' communication with caregivers, trust in institutions, and COVID-19 knowledge and preventive behaviors. The acceptability of a mobile app for contact tracing was measured by a single question, the responses to which were grouped into three modalities: app-supporting, app-willing, and app-reluctant. Multinomial logistic regression analysis was performed to identify the factors associated with the acceptability of a mobile app during the COVID-19 pandemic. Results: Only 19.2% (193/1003) of all participants were app-supporting, whereas half of them (504/1003, 50.3%) were reluctant. The factors associated with willingness or support toward the contact tracing app included lower financial deprivation (app-willing: adjusted odds ratio [aOR] 0.8, 95% CI 0.69-0.93; app-supporting: aOR 0.7, 95% CI 0.58-0.84) and higher perceived usefulness of using a mobile app to send completed health questionnaires to doctors (app-willing: aOR 2.3, 95% CI 1.70-3.26; app-supporting: aOR 3.1, 95% CI 2.04-4.82). Furthermore, the likelihood of supporting the mobile app increased with age over 60 years (aOR 1.9, 95% CI 1.13-3.22), trust in political representatives (aOR 2.7, 95% CI 1.72-4.23), feeling concerned about the pandemic situation (aOR 2.2, 95% CI 1.47-3.32), and knowledge about the transmission of COVID-19 (aOR 2.0, 95% CI 1.39-2.96). Conclusions: The most socioeconomically precarious people, who are at a higher risk of SARS-CoV-2 infection, are also the most reluctant to using a contact tracing mobile app. Therefore, optimal adherence can only be effective with a targeted discourse on public health benefits to adopt such an app, which should be combined with a reduction in inequalities by acting on structural determinants.</abstract>
      <custom6>052 ; 056 ; 122</custom6>
      <custom1>UR259 / UR196</custom1>
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