{"title":"中国 COVID-19 大流行期间个人数据泄露的信息源特征:观察研究。","authors":"Zhong Wang, Fangru Hu, Jie Su, Yuyao Lin","doi":"10.2196/51219","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>We aimed to examine the information source characteristics of personal data leakage during the COVID-19 pandemic in China.</p><p><strong>Methods: </strong>We extracted information source characteristics of 40 personal data leakage cases using open coding and analyzed the data with 1D and 2D matrices.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":56334,"journal":{"name":"JMIR Medical Informatics","volume":"12 ","pages":"e51219"},"PeriodicalIF":3.1000,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651669/pdf/","citationCount":"0","resultStr":"{\"title\":\"Information Source Characteristics of Personal Data Leakage During the COVID-19 Pandemic in China: Observational Study.\",\"authors\":\"Zhong Wang, Fangru Hu, Jie Su, Yuyao Lin\",\"doi\":\"10.2196/51219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>We aimed to examine the information source characteristics of personal data leakage during the COVID-19 pandemic in China.</p><p><strong>Methods: </strong>We extracted information source characteristics of 40 personal data leakage cases using open coding and analyzed the data with 1D and 2D matrices.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":56334,\"journal\":{\"name\":\"JMIR Medical Informatics\",\"volume\":\"12 \",\"pages\":\"e51219\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-12-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11651669/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"JMIR Medical Informatics\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.2196/51219\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MEDICAL INFORMATICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"JMIR Medical Informatics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/51219","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICAL INFORMATICS","Score":null,"Total":0}
Information Source Characteristics of Personal Data Leakage During the COVID-19 Pandemic in China: Observational Study.
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.
期刊介绍:
JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals.
Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.