Evidence map›Paper›PMID 39657212›Full record

Observational studyJMIR medical informatics2024

Information Source Characteristics of Personal Data Leakage During the COVID-19 Pandemic in China: Observational Study.

Zhong Wang, Fangru Hu, Jie Su, Yuyao Lin

Abstract readObservational Study
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Zhong WangSchool of Economics, Guangdong University of Technology, Guangzhou, China.ORCID 0000-0003-0801-6173
Fangru HuKey Laboratory of Digital Economy and Data Governance, Guangdong University of Technology, 161 Yinglong Road, Tianhe district, Guangdong province, Guangzhou, 510520, China, 86 18845127665.ORCID 0009-0009-2383-6007
Jie SuSchool of Marxism, Peking University, Beijing, China.ORCID 0000-0001-6090-5264
Yuyao LinKey Laboratory of Digital Economy and Data Governance, Guangdong University of Technology, 161 Yinglong Road, Tianhe district, Guangdong province, Guangzhou, 510520, China, 86 18845127665.ORCID 0000-0002-5973-5680

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19ChinaComputer SecurityConfidentialityHumansInformation SourcesPandemicsPrivacySocial Mediacharacteristics of information sourcesChinaCOVID-19data privacyinformation sourceleakageprivacy leakagepublic healthpublic health emergency

Identifiers

PMID39657212
PMCPMC11651669

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.