Observational studyJMIR medical informatics2024
Information Source Characteristics of Personal Data Leakage During the COVID-19 Pandemic in China: Observational Study.
Observational study in JMIR medical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
The trial behind it
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Who cites it
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: During the COVID-19 pandemic, in the period of preventing and controlling the spread of the virus, a large amount of personal data was collected in China, and privacy leakage incidents occurred. Objective: We aimed to examine the information source characteristics of personal data leakage during the COVID-19 pandemic in China. Methods: We extracted information source characteristics of 40 personal data leakage cases using open coding and analyzed the data with 1D and 2D matrices. Results: In terms of organizational characteristics, data leakage cases mainly occurred in government agencies below the prefecture level, while few occurred in the medical system or in high-level government organizations. The majority of leakers were regular employees or junior staff members rather than temporary workers or senior managers. Family WeChat groups were the primary route for disclosure; the forwarding of documents was the main method of divulgence, while taking screenshots and pictures made up a comparatively smaller portion. Conclusions: We propose the following suggestions: restricting the authority of nonmedical institutions and low-level government agencies to collect data, strengthening training for low-level employees on privacy protection, and restricting the flow of data on social media through technical measures.
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