Political views and organizational distrust affect rural residents’ willingness to share personal data for COVID-19 contact tracing: A cross-sectional survey study Article Swipe
YOU?
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· 2023
· Open Access
·
· DOI: https://doi.org/10.1017/cts.2023.33
Background: We aimed to examine the attitudes of Pennsylvania rural residents toward data sharing in the setting of the COVID-19 pandemic. Specifically, we were interested in better understanding their willingness to provide personal information for contact tracing to public health staff investigating COVID-19 cases, as well as their concerns. We used a validated scale to describe the influence of distrust of healthcare organizations on their attitudes. Methods: We mailed 4000 surveys to rural residents identified from the electronic medical record of a healthcare system in central Pennsylvania. Data were entered into a REDCap database and analyzed using descriptive summaries, and both binomial and multivariable logistic regression. Results: Binomial logistic regression showed that both distrust in healthcare organizations and political values influence respondents’ willingness to share information with contact tracers as well as their concerns about sharing personal data. When our multivariable model was applied, political values remained and were consistently associated with willingness to share and concerns about sharing their data. Conclusion: This study is a first step in eliciting rural residents’ willingness to share personal data for contact tracing by public health officials. Understanding and addressing rural residents’ willingness to share personal data and their concerns about sharing those data will help public health officials identify effective strategies for managing COVID-19 and future pandemics in rural communities. By involving community members at the ground level, public health staff can ensure residents’ buy-in for the need to collect their personal data, thereby helping to mitigate the public health crises.
Related Topics
- Type
- article
- Language
- en
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- https://doi.org/10.1017/cts.2023.33
- https://www.cambridge.org/core/services/aop-cambridge-core/content/view/99580D8186763E34D5A0A572BCC02C66/S205986612300033Xa.pdf/div-class-title-political-views-and-organizational-distrust-affect-rural-residents-willingness-to-share-personal-data-for-covid-19-contact-tracing-a-cross-sectional-survey-study-div.pdf
- OA Status
- gold
- Cited By
- 4
- References
- 44
- Related Works
- 10
- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4360985222Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1017/cts.2023.33Digital Object Identifier
- Title
-
Political views and organizational distrust affect rural residents’ willingness to share personal data for COVID-19 contact tracing: A cross-sectional survey studyWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-01-01Full publication date if available
- Authors
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Jennifer B. McCormick, Margaret Hopkins, Erik Lehman, Michael J. GreenList of authors in order
- Landing page
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https://doi.org/10.1017/cts.2023.33Publisher landing page
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/99580D8186763E34D5A0A572BCC02C66/S205986612300033Xa.pdf/div-class-title-political-views-and-organizational-distrust-affect-rural-residents-willingness-to-share-personal-data-for-covid-19-contact-tracing-a-cross-sectional-survey-study-div.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://www.cambridge.org/core/services/aop-cambridge-core/content/view/99580D8186763E34D5A0A572BCC02C66/S205986612300033Xa.pdf/div-class-title-political-views-and-organizational-distrust-affect-rural-residents-willingness-to-share-personal-data-for-covid-19-contact-tracing-a-cross-sectional-survey-study-div.pdfDirect OA link when available
- Concepts
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Distrust, Public health, Health care, Survey data collection, Public relations, Contact tracing, Respondent, Psychology, Business, Medicine, Nursing, Political science, Coronavirus disease 2019 (COVID-19), Disease, Statistics, Law, Infectious disease (medical specialty), Psychotherapist, Pathology, MathematicsTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
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2025: 3, 2023: 1Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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