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Public Trust, Private Data: Four Considerations for the Future of Health.

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Title: Public Trust, Private Data: Four Considerations for the Future of Health.
Authors: Dasgupta, Nabarun (AUTHOR), Schoendorf, Jennifer D. (AUTHOR), Lau, Denys T. (AUTHOR), Thorpe, Lorna (AUTHOR)
Source: American Journal of Public Health. Jan2026, Vol. 116 Issue 1, p57-61. 5p.
Subjects: Data security, Diffusion of innovations, Data management, Terms & phrases, Communities of practice, Interprofessional relations, Public sector, Health, Food security, Population health, Government agencies, Private sector, Information resources, Research bias, Trust, Medical research, Content mining, Data quality, Honesty, Corporations, Public health, Public administration, Report writing, Mergers & acquisitions, Interpersonal relations, Reliability (Personality trait), Cognition, Algorithms
Abstract: The article focuses on the implications of the current political movement toward deregulation in the American health sector, particularly regarding the roles of privately and publicly held data. It argues that while private data sources can provide detailed insights into health issues, publicly held data are essential for broader public health questions and maintaining trust. The authors highlight concerns about data quality, transparency, and selection bias in privately held data, emphasizing the need for independent validation and methods transparency to foster public trust. They conclude that both data types are crucial for effective public health decision-making, but the shift towards privatization may undermine trust if not managed carefully. [Extracted from the article]
Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Public Trust, Private Data: Four Considerations for the Future of Health.
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  Data: <searchLink fieldCode="AR" term="%22Dasgupta%2C+Nabarun%22">Dasgupta, Nabarun</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Schoendorf%2C+Jennifer+D%2E%22">Schoendorf, Jennifer D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lau%2C+Denys+T%2E%22">Lau, Denys T.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Thorpe%2C+Lorna%22">Thorpe, Lorna</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22American+Journal+of+Public+Health%22">American Journal of Public Health</searchLink>. Jan2026, Vol. 116 Issue 1, p57-61. 5p.
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  Data: <searchLink fieldCode="DE" term="%22Data+security%22">Data security</searchLink><br /><searchLink fieldCode="DE" term="%22Diffusion+of+innovations%22">Diffusion of innovations</searchLink><br /><searchLink fieldCode="DE" term="%22Data+management%22">Data management</searchLink><br /><searchLink fieldCode="DE" term="%22Terms+%26+phrases%22">Terms & phrases</searchLink><br /><searchLink fieldCode="DE" term="%22Communities+of+practice%22">Communities of practice</searchLink><br /><searchLink fieldCode="DE" term="%22Interprofessional+relations%22">Interprofessional relations</searchLink><br /><searchLink fieldCode="DE" term="%22Public+sector%22">Public sector</searchLink><br /><searchLink fieldCode="DE" term="%22Health%22">Health</searchLink><br /><searchLink fieldCode="DE" term="%22Food+security%22">Food security</searchLink><br /><searchLink fieldCode="DE" term="%22Population+health%22">Population health</searchLink><br /><searchLink fieldCode="DE" term="%22Government+agencies%22">Government agencies</searchLink><br /><searchLink fieldCode="DE" term="%22Private+sector%22">Private sector</searchLink><br /><searchLink fieldCode="DE" term="%22Information+resources%22">Information resources</searchLink><br /><searchLink fieldCode="DE" term="%22Research+bias%22">Research bias</searchLink><br /><searchLink fieldCode="DE" term="%22Trust%22">Trust</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+research%22">Medical research</searchLink><br /><searchLink fieldCode="DE" term="%22Content+mining%22">Content mining</searchLink><br /><searchLink fieldCode="DE" term="%22Data+quality%22">Data quality</searchLink><br /><searchLink fieldCode="DE" term="%22Honesty%22">Honesty</searchLink><br /><searchLink fieldCode="DE" term="%22Corporations%22">Corporations</searchLink><br /><searchLink fieldCode="DE" term="%22Public+health%22">Public health</searchLink><br /><searchLink fieldCode="DE" term="%22Public+administration%22">Public administration</searchLink><br /><searchLink fieldCode="DE" term="%22Report+writing%22">Report writing</searchLink><br /><searchLink fieldCode="DE" term="%22Mergers+%26+acquisitions%22">Mergers & acquisitions</searchLink><br /><searchLink fieldCode="DE" term="%22Interpersonal+relations%22">Interpersonal relations</searchLink><br /><searchLink fieldCode="DE" term="%22Reliability+%28Personality+trait%29%22">Reliability (Personality trait)</searchLink><br /><searchLink fieldCode="DE" term="%22Cognition%22">Cognition</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: The article focuses on the implications of the current political movement toward deregulation in the American health sector, particularly regarding the roles of privately and publicly held data. It argues that while private data sources can provide detailed insights into health issues, publicly held data are essential for broader public health questions and maintaining trust. The authors highlight concerns about data quality, transparency, and selection bias in privately held data, emphasizing the need for independent validation and methods transparency to foster public trust. They conclude that both data types are crucial for effective public health decision-making, but the shift towards privatization may undermine trust if not managed carefully. [Extracted from the article]
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  Data: <i>Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=pbh&AN=189940342
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.2105/AJPH.2025.308328
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 57
    Subjects:
      – SubjectFull: Data security
        Type: general
      – SubjectFull: Diffusion of innovations
        Type: general
      – SubjectFull: Data management
        Type: general
      – SubjectFull: Terms & phrases
        Type: general
      – SubjectFull: Communities of practice
        Type: general
      – SubjectFull: Interprofessional relations
        Type: general
      – SubjectFull: Public sector
        Type: general
      – SubjectFull: Health
        Type: general
      – SubjectFull: Food security
        Type: general
      – SubjectFull: Population health
        Type: general
      – SubjectFull: Government agencies
        Type: general
      – SubjectFull: Private sector
        Type: general
      – SubjectFull: Information resources
        Type: general
      – SubjectFull: Research bias
        Type: general
      – SubjectFull: Trust
        Type: general
      – SubjectFull: Medical research
        Type: general
      – SubjectFull: Content mining
        Type: general
      – SubjectFull: Data quality
        Type: general
      – SubjectFull: Honesty
        Type: general
      – SubjectFull: Corporations
        Type: general
      – SubjectFull: Public health
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      – SubjectFull: Reliability (Personality trait)
        Type: general
      – SubjectFull: Cognition
        Type: general
      – SubjectFull: Algorithms
        Type: general
    Titles:
      – TitleFull: Public Trust, Private Data: Four Considerations for the Future of Health.
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              Text: Jan2026
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              Y: 2026
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