Personal Information Research Articles

Depression in the schistosomiasis japonica population based on the PHQ-9 scale: a cross-sectional survey from Jiangxi Province, China

Depression is the second leading-cause of disability in China. Although studies have shown that more than 80% of patients with advanced schistosomiasis (AS) suffer from anxiety and depression, these study groups are all hospitalized patients with AS and do not represent the extent of the disease in the whole group. To our knowledge, there are no studies assessing the severity of depression in patients with other forms of schistosomiasis japonicum. Therefore, it is necessary to evaluate the occurrence and potential risk factors of depression in the schistosomiasis endemic population. This cross-sectional study was conducted in Jiangxi Province, where schistosomiasis is relatively common in China, as the investigation site. The Patient Health Questionnaire-9 (PHQ-9) scale was selected to assess the depressive symptoms in the study population. At the same time, basic personal information of the research subjects and relevant socio-economics and schistosomiasis endemic area indicators were collected. The survey results show that AS has the highest incidence of depression (34.35%), while non-advanced schistosomiasis (N-AS) and control group (CG) have 22.35% and 22.24% respectively; the incidence of depression in AS is significantly higher than in N-AS and CG, while there is no statistical significance in the comparison between N-AS and CG; the incidence of mild depressive symptoms accounts for 61.08%-75.54% of the total incidence of depression in different groups; multivariate analysis shows that the occurrence of moderate/severe depressive symptoms in the AS group was significantly related to above 60 years old, male, the combination of other serious diseases, personal financial difficulties, and marshland and lake endemic areas. In the N-AS group, the occurrence of moderate/severe depressive symptoms was significantly related to the combination of other serious diseases, personal financial difficulties, significant correlation between marshland and lake endemic areas and the level of control of schistosomiasis epidemics. In conclusion, depression is still relatively common among patients with schistosomiasis patients, especially those with AS. It is recommended that the government and relevant departments consider mental health care when developing prevention and control work in schistosomiasis-endemic areas, in order to effectively protect the physical and mental health of schistosomiasis patients and residents in endemic areas.

Testing the effects of personalized recommendation service, filter bubble and big data attitude on continued use of TikTok

PurposeThis study attempts to identify the determinant factors for Chinese users’ intention of continuous use of TikTok.Design/methodology/approachDrawing on the theoretical background and previous literature, this study proposes the research model followed by research hypotheses. For the purpose of empirical analysis of this study, we conducted a questionnaire survey on current Chinese TikTok platform users. Factor analysis was conducted to verify the reliability and validity of the measurement variables; Confirmatory factor analysis was conducted to ensure that the structural dimensions of the measurement are effective; the analysis results of the structural equation model for hypothesis test.FindingsThe result of the study indicates that the core service traits (entertainment, informativeness and convenience of use) of TikTok all have a positive effect on user engagement and perceived usefulness. In addition, the study found that both personalized recommendation services and filter bubble, which are features of TikTok's service recommendation system, have a positive effect on user engagement and perceived usefulness of TikTok. In addition, it was found that both user engagement and perceived usefulness have a significant positive effect on continuous use intention. Finally, users’ attitude toward big data indicating privacy concern only had a positive moderating effect on the personalized recommendation service but not on filter bubble.Originality/valueAs consumers’ demand for services tailored to their needs and preferences fast increased, it calls for growing concern over the safety of personal data being used by the platforms. Although this paradox over increased user convenience versus privacy protection issue has been persistently recognized, no previous research empirically addressed this issue in the context of social media platforms.

Make data flow: Understanding the (re)usability of research data

Opening data and making datasets reusable is an extremely important and urgent need, especially as we move towards more data-driven studies worldwide. Various stakeholders are involved in the life cycle of data (re)use, including data providers/sharers, data (re)users, data managers/curators, and funding agencies. In response to the divergent demands of these stakeholders, data repositories have been established to bridge their needs and facilitate the cycle of data sharing and (re)use. However, recent studies have shown that data is being shared and (re)used through open data repositories at much lower levels than expected. This underscores a fundamental and often overlooked challenge in research data management, inviting a deeper and more comparative examination of the perspectives of various stakeholders on data (re)use. Using a mixed-method approach that includes metadata analysis, interview-based qualitative studies, and quantitative bibliometric analysis, this project first delves into the facilitating and inhibiting factors affecting a dataset's potential for (re)use, considering the perspectives of both data (re)users and data curators. It will then identify and elucidate the disparities between data (re)users and data curators, proposing suggestions for future data curation efforts. The findings will prompt data curators and data repositories to re-examine their current metadata frameworks and data curation practices, aligning them more closely with the actual needs of data (re)users. Moreover, this effort will make the flow of research data moves more smoothly within our academic communities, and contribute to the building of a more inclusive, equitable, open, and user-friendly research infrastructure.

Sharing for Caring? A Patients' and Clinicians' View on Handling Personal Medical Data in the Context of Digitization: An Exploratory Study.

The healthcare sector is currently undergoing a significant transformation, driven by an increased utilization of data. In this evolving landscape, surveys are of pivotal importance to the comprehension of patient needs and preferences. Moreover, the digital affinity of patients and physicians within the healthcare system is reforming the manner in which healthcare services are accessed and delivered. The utilization and donation of data are influencing the future of medical research and treatment, while artificial intelligence (AI) is empowering patients and physicians with knowledge and improving healthcare delivery. In order to evaluate the opinions of patients and physicians regarding the management of personal health data and the functionality of upcoming data management devices in the context of healthcare digitization, we conducted an exploratory study and designed a survey. The survey focused on a number of key areas, including demographics, experience with digitization, data handling, the identification of needs for upcoming digitization, and AI in healthcare. A total of 40 patients and 15 physicians participated in the survey. The results indicate that data security, timesaving/administrative support, and digital communication are aspects that patients associate with patient-friendly digitization. Based on the responses provided by physicians, it might be concluded that future digital platforms should prioritize usability, time efficacy, data security, and interoperability. In terms of expectations for future digital platforms, there is a notable overlap between the needs expressed by patients and those identified by physicians, particularly in relation to usability, time management, data security, and digital communication. This suggests that the requirements of different stakeholders can be combined in a future system, although individual issues may still require attention.

Editor’s Note: In Defense of Freedoms: Decentralized Networks as a Shield Against AI-Powered State Surveillance in Smart Cities

Associate Editor Ahmed Alrawi discusses the advancement of AI-powered state surveillance in smart cities and how they have sparked concerns. Decentralized systems may present a solution. Dispersed dat and systems make it more difficult for government security agencies and urban administrators to conduct widespread surveillance but also empower individuals with greater control over their personal data.

How Data is Documented: An Analysis of Metadata Schemas for Research Data

The importance of metadata has long been understood by those in the fields of librarianship and research data management. Currently, there are many research data service providers that allow deposit of research data or gather metadata for research data housed elsewhere, following various metadata schemas to describe their collections. These schemas were designed to make their datasets organized, discoverable, and reusable. As data curators initially recognize the need for and begin working on metadata schemas for research data, most previous studies in this field were conducted from their perspectives. However, few of these studies discuss a schema from the perspective of data (re)users. This study aims to take a small step towards filling this gap by evaluating four influential metadata schemas in light of researchers' information-seeking behaviors for research data. This study explores the factors that affect researchers’ efforts in seeking, understanding, and evaluating (re)usable data, and examines how these factors are represented across various fields in the current metadata schemas for research data. The methodology for this study consists of three parts: a meta-analysis of relevant research on researcher’s seeking behaviors for (re)usable data, a crosswalk of the metadata schemas, and a comparison of findings from the previous stages. The findings from this study will offer insights into the development of research data metadata schema in the future, which will enhance the infrastructure for data sharing, ultimately facilitating more effective (re)use of existing data.

DIGITAL TRANSFORMATION AND DATA PROTECTION

In today’s interconnected world, t he incorporation of digital technology across all areas of an organization is the key focus of digital transformation, a strategic business initiative. It involves the assessment and modernization of an organization's processes, products, operations, and technology stack to facilitate ongoing, rapid, customer-driven innovation. Digital transformation goes beyond traditional functions such as sales, marketing, and customer service, centering instead on rethinking and engaging with customers. Moving from paper to spreadsheets to intelligent applications for business management presents an opportunity to rethink how we conduct business and interact with our customers, leveraging digital technology in the process. similarly cybersecurity and data privacy have become critical concerns for businesses of all sizes. This paper explores the role of Digital transformation and the evolving landscapes of cyber threats and the importance of robust cybersecurity measures in safeguarding sensitive business information. It examines the various types of cyberattacks, including malware, phishing, and ransomware, that can compromise business operations and erode consumer trust. Additionally, the paper highlights the significance of data privacy in maintaining compliance with regulations such as GDPR and CCPA, and in protecting the personal information of customers and employees.

Cyber attacks on radiological systems

The base of today’s radiological devices are computers and networks. The radiology department has a specific way of working and there are standards such as DICOM for medical image records, PACS for archiving and communication, and HL7 for information exchange in the medical system. As radiology becomes an economically interesting branch, it becomes a target for cyber-attacks. At the same time, radiological systems contain a lot of personal data that are valuable. The reasons for the attacks are often financial gain, political, ideological or personal. The start of an attack can be physical access to radiological devices or network access. DICOM files can be the trigger of an attack. We divide attacks into those that directly affect patients, those that have an indirect impact, and those that affect the infrastructure. Well known types are Denial-Of-Service, malware, cryptographic attacks and making changes of device settings. When defending against cyber-attacks, it is important to secure communication by e-mail and to keep software updated. The IT department of the radiology department should observe accounts of all users and check the authorizations. Networks must have access restrictions according to workplaces and purposes to prevent unwanted access. Web proxy protection restricts access to Internet sites that are potentially dangerous. The basics of the department’s network, such as servers, must be physically secured from access. DICOM files should be encrypted with the most secure algorithms available. In response to cyber-attacks, it is necessary to have standard procedures and such a system must always be on standby. Known attacks on radiological systems are Kwampiris, Petja/NotPetya, Ryuk, Wannacry, Conti group and BianLian.

Digital Profiling and the Legal Regime of Derived Personal Data

Digital Profiling and the Legal Regime of Derived Personal Data

A study on user willingness to participate in an adverse drug event information sharing system

BackgroundTo prevent the recurrence of Adverse Drug Events (ADEs), particularly drug allergies, it is essential to avoid re-exposure to causative drugs. Awareness of previous ADEs is crucial for patients because they can share accurate information with healthcare providers (HCPs). This study aims to assess users’ willingness to share ADE information and evaluate the factors related to this willingness by utilizing a prospective ADE information-sharing system currently under consideration in South Korea.MethodsIn September 2023, a self-administered questionnaire was collected from a sex-, age-, and regionally stratified nationwide convenience sample of adults recruited through a commercial panel in South Korea. Factors contributing to the willingness to share ADE information and create electronic ADE cards (e-ADE cards) were investigated using multivariate logistic regression analysis.ResultsAmong the 1,000 respondents, 458 (45.8%) were willing to share ADE information, and 521 (52.1%) were willing to create e-ADE cards. The willingness to share personal ADE information and create e-ADE cards was positively associated with the perceived benefits of sharing ADE, trust in HCPs and positive experiences. Notably, older adult patients demonstrated a higher willingness to share information and use e-ADE cards, with rates of 56% and 62%, respectively.ConclusionsOur findings indicate that the approach to sharing personal ADE information should be distinct from that of sharing comprehensive health information. Notably, users are likely to willingly disclose their personal information even if they are not anonymized, owing to the significant perceived benefits of sharing. The findings of this study can enhance awareness about sharing personal ADE information and contribute to the successful establishment of an ADE information-sharing system, thereby improving the patient safety environment.

Data protection legislation in Africa and pathways for enhancing compliance in big data health research

BackgroundThe increasing availability of large volumes of personal data from diverse sources such as electronic health records, research programmes, commercial genetic testing, national health surveys and wearable devices presents significant opportunities for advancing public health, disease surveillance, personalized medicine and scientific research and innovation. However, this potential is hampered by a lack of clarity related to the processing and sharing of personal health data, particularly across varying national regulatory frameworks. This often leaves researcher stakeholders uncertain about how to navigate issues around secondary data use, repurposing data for different research objectives and cross-border data sharing.MethodWe analysed 37 data protection legislation across Africa to identify key principles and requirements for processing and sharing of personal health and genetic data in scientific research. On the basis of this analysis, we propose strategies that data science research initiatives in Africa can implement to ensure compliance with data protection laws while effectively reusing and sharing personal data for health research and scientific innovation.ResultsIn many African countries, health and genetic data are categorized as sensitive and subject to stricter protection. Key principles guiding the processing of personal data include confidentiality, non-discrimination, transparency, storage limitation, legitimacy, purpose specification, integrity, fairness, non-excessiveness, accountability and data minimality. The rights of data subjects include the right to be informed, the right of access, the right to rectification, the right to erasure/deletion of data, the right to restrict processing, the right to data portability and the right to seek compensation. Consent and adequacy assessments were the most common legal grounds for cross-border data transfers. However, considerable variation exists in legal requirements for data transfer across countries, potentially creating barriers to collaborative health research across Africa.ConclusionsWe propose several strategies that data science research initiatives can adopt to align with data protection laws. These include developing a standardized module for safe data flows, using trusted data environments to minimize cross-border transfers, implementing dynamic consent mechanisms to comply with consent specificity and data subject rights and establishing codes of conduct to govern the secondary use of personal data for health research and innovation.

Explaining Privacy Paradox on WeChat

With the development of the information age, people need to disclose personal information in exchange for socializing and related services. At the same time, people's privacy concerns are gradually increasing. Privacy paradox has become a normal phenomenon in social network sites (SNS). The loss of control of privacy might lead to privacy fatigue. Previous work has studied the mechanism of privacy paradox and explored the influence of specific factors on privacy paradox. However, the effect of privacy fatigue on privacy paradox among SNS users has not been studied. In this study, we use structural equation modeling (SEM) to explore the effect of privacy fatigue on personal information disclosure intentions and actual behaviors among WeChat users. Our results of 710 participants showed that privacy fatigue has a mediating role between privacy concern and privacy disclosure intention, and has a positive influence on privacy disclosure intention and disclosure behavior. Based on these results, we provide implications to reduce privacy fatigue and privacy paradox.

ANEL: a novel efficient and lightweight authentication scheme for enhancing security in Vehicular Ad Hoc Networks (VANETs) using elliptic curve cryptography

Vehicular Ad-hoc Networks (VANETs) offer immense potential for revolutionizing modern transportation systems through real-time communication and interaction between vehicles and roadside infrastructure. These networks can significantly enhance traffic management, improve safety, and support various vehicular services. However, ensuring secure communication in VANETs remains a critical challenge due to the highly sensitive nature of the data exchanged, such as location and personal information. Current authentication schemes, including the ANEL scheme, exhibit vulnerabilities like data interception and tracking risks. In this paper, we propose a novel, efficient, and lightweight authentication scheme that leverages elliptic curve cryptography (ECC) and message mapping techniques to address these security issues. The proposed solution strengthens encryption, enhances privacy protection, and mitigates risks such as unauthorized access and man-in-the-middle attacks. Furthermore, the scheme offers scalability and distinguishes between regular and priority users, making it adaptable to various VANET applications. This approach significantly improves the overall security and privacy framework of VANET systems while ensuring the efficient use of computational resources in vehicular environments.

Privacy-Preserving Visualization of Brain Functional Connectivity.

Privacy protection is important in visualization due to the risk of leaking personal sensitive information. In this paper, we study the problem of privacy-preserving visualizations using differential privacy, employing biomedical data from neuroimaging as a use case. We investigate several approaches based on perturbing correlation values and characterize their privacy cost and the impact of pre- and post-processing. To obtain a better privacy/visual utility tradeoff, we propose workflows for connectogram and seed-based connectivity visualizations, respectively. These workflows successfully generate visualizations similar to their non-private counterparts. Experiments show that qualitative assessments can be preserved while guaranteeing privacy. These results show that differential privacy is a promising method for protecting sensitive information in data visualization.

Speaking in Private: Privacy Expectations Depend on Communication Modality

Consumers disclose personal information when they interact with connected technologies. The advent of voice technology has enabled consumers to interact with connected technologies not only through typing but also through speaking. The present research investigates whether consumers expect different levels of privacy for information they disclose via different communication modalities. The results of three studies suggest that consumers have more restrictive privacy expectations for information disclosed via speech as compared with text. The studies probe the viability of several mechanisms that may drive this effect and test practically relevant moderators. The results suggest that the effect is driven, at least in part, by increased feelings of ownership over content disclosed via speech as compared with text. Of relevance to multiple stakeholders, the article discusses implications for privacy regulation, privacy-preserving application design, targeted advertising, and the “privacy paradox.” This paper has been This paper was accepted by Catherine Tucker for the Special Issue on the Human-Algorithm Connection. Funding: This work was supported by Marketing Science Institute [4001309], NYU Stern Center for Global Economy and Business. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03954 .

Decentralized collaborative machine learning for protecting electricity data

In recent years, there has been a noticeable surge in electric power load due to economic development and improved living standards. The growing need for smart power solutions, such as leveraging user electricity data to forecast power peaks and utilizing power data statistics to enhance end-user services, has been on the rise. However, the misuse and unauthorized access of data have prompted stringent regulations to safeguard data integrity. This paper presents a novel decentralized collaborative machine learning framework aimed at predicting peak power loads while protecting the privacy of users’ power data. In this scheme, multiple users engage in collaborative machine learning training within a peer-to-peer network free from a centralized server, with the objective of predicting peak power loads without compromising users’ local data privacy. The proposed approach leverages blockchain technology and advanced cryptographic techniques, including multi-key homomorphic encryption and consistent hashing. Key contributions of this framework include the development of a secure dual-aggregate node aggregation algorithm and the establishment of a verifiable process within a decentralized architecture. Experimental validation has been conducted to assess the feasibility and effectiveness of the proposed scheme, demonstrating its potential to address the challenges associated with predicting peak power loads securely and preserving user data privacy.

A study on media and information and traffic convergence in the digital age on consumption

The digital age is the age of productivity innovation. It is the era of industrial transformation and market development to satisfy the public's eyeball economy. Under traditional productivity, new products are often produced and introduced to the market and the public accepts and adapts to the new products, and those products that are not accepted by the public will be eliminated by the market. Now, in the emerging digital era, through data and its analysis, the product and market have begun to analyse the user and market pain points, according to user data to design and develop products for the needs of the user to enjoy at the same time for the data and traffic payment. This is "information consumption" and "data consumption". Poor information is the tool to make money in the current era. How to grasp the information and data of the user group and consumer demand becomes the key. Emerging media is the key to unlocking users' needs. The purpose of this study is to find the role of this key in the integration of information and traffic into consumption. The significance of this study is to deduce the relationship between media and the convergence of information and traffic to consumption in the digital age by analysing the case of the company. The result of this study is that the digital era has created advanced productivity, and the development of productivity has led to innovations in the means and tools of the media industry, which have contributed to the development of user needs. The media is the key to creating and capturing the needs of user groups. It is also the cornerstone for creating "information consumption" and "traffic consumption".

Toward Context-Aware Privacy Enhancing Technologies for Online Self-Disclosure

Voluntary sharing of personal information is at the heart of user engagement on social media and central to platforms' business models. From the users' perspective, so-called self-disclosure is closely connected with both privacy risks and social rewards. Prior work has studied contextual influences on self-disclosure, from platform affordances and interface design to user demographics and perceived social capital. Our work takes a mixed-methods approach to understand the contextual information which might be integrated in the development of privacy-enhancing technologies. Through observational study of several Reddit communities, we explore the ways in which topic of discussion, group norms, peer effects, and audience size are correlated with personal information sharing. We then build and test a prototype privacy-enhancing tool that exposes these contextual factors. Our work culminates in a browser extension that automatically detects instances of self-disclosure in Reddit posts at the time of posting and provides additional context to users before they post to support enhanced privacy decision-making. We share this prototype with social media users, solicit their feedback, and outline a path forward for privacy-enhancing technologies in this space.

Type of delivery lacks the association with dietary patterns followed by pregnant women in their third trimester.

Background: Maternal nutrition plays a crucial role in fetal development, women's health, and reproductive capacity. Dietary pattern (DP) is a measure of overall diet and has become widespread in nutrition research as an alternative method to studying individual components of the diet. Aim: this study aims to determine the adopted DPs by Jordanian pregnant women and evaluate their potential associations with the mode of delivery. Methods: A cross-sectional study included 249 healthy Jordanian pregnant women in their third trimester of pregnancy who attended antenatal clinics at Jordan University. Personal information was gathered using a pre-tested structured questionnaire. To investigate dietary patterns, a valid and reliable food frequency questionnaire was employed, and a pregnant physical activity questionnaire was used to estimate physical activity levels. The mode of delivery data was collected from the medical records after delivery. Results: The majority of pregnant women (82.3%) fell within the age range of 20 to 35 years. Notably, 34.5% of the mothers were classified as overweight or obese. Additionally, around one in five deliveries involved emergency cesarean sections. Four distinct DPs were identified and labelled as "fruit and vegetables", "healthy", "traditional", and 'fat and sugar" dietary patterns. However, no significant association was found between these identified dietary patterns and the occurrence of Caesarean section (CS) across all tertiles. Conclusion: The analysis revealed no substantial protective effect of the DPs against the occurrence of CS across all tertiles of dietary patterns. However, further studies are needed to either confirm or challenge our findings.

Prevalence of dry eye disease symptoms, associated factors and impact on quality of life among medical students during the pandemic

This cross-sectional study aimed to evaluate the prevalence of dry eye disease (DED) symptoms, their associated factors, and the impact on quality of life (QOL) and mental health among medical students during the COVID-19 pandemic using online surveys. Participants completed questionnaires covering demography, medical history, and personal data. The Thai version of the Dry Eye-related Quality-of-Life Score (DEQS-Th) was used for DED screening. The QOL and mental health challenges (support, coping, stress, and depression) were evaluated by the EuroQoL-5 dimensions-5 levels (EQ-5D-5L) and Thymometer questionnaires. A total of 449 participants were analyzed, with a mean age of 21.8 years and 61.5% female. The prevalence of DED symptoms was 60.4% (95%CI 55.7–64.8). The DEQS-Th score, the EQ-5D-5L score, and all aspects of mental health challenges were significantly worse in DED participants compared to non-DED participants. Associated factors for DED symptoms included preexisting DED (p = 0.001), refractive errors (p = 0.007), allergic conjunctivitis (p = 0.001), artificial tears use (p < 0.001), and decreased EQ-5D-5L score (p < 0.001). This study highlighted the high prevalence of DED symptoms among medical students during the pandemic and its negative impact on QoL and mental health. Notably, female gender, contact lens wear, screen time, and mask-wearing duration were not associated with DED symptoms.