Privacy Issues Research Articles

Looking Back on Digital Medical Education Over the Last 25 Years and Looking to the Future: Narrative Review

Background The last 25 years have seen enormous progression in digital technologies across the whole of the health service, including health education. The rapid evolution and use of web-based and digital techniques have been significantly transforming this field since the beginning of the new millennium. These advancements continue to progress swiftly, even more so after the COVID-19 pandemic. Objective This narrative review aims to outline and discuss the developments that have taken place in digital medical education across the defined time frame. In addition, evidence for potential opportunities and challenges facing digital medical education in the near future was collated for analysis. Methods Literature reviews were conducted using PubMed, Web of Science Core Collection, Scopus, Google Scholar, and Embase. The participants and learners in this study included medical students, physicians in training or continuing professional development, nurses, paramedics, and patients. Results Evidence of the significant steps in the development of digital medical education in the past 25 years was presented and analyzed in terms of application, impact, and implications for the future. The results were grouped into the following themes for discussion: learning management systems; telemedicine (in digital medical education); mobile health; big data analytics; the metaverse, augmented reality, and virtual reality; the COVID-19 pandemic; artificial intelligence; and ethics and cybersecurity. Conclusions Major changes and developments in digital medical education have occurred from around the start of the new millennium. Key steps in this journey include technical developments in teleconferencing and learning management systems, along with a marked increase in mobile device use for accessing learning over this time. While the pace of evolution in digital medical education accelerated during the COVID-19 pandemic, further rapid progress has continued since the resolution of the pandemic. Many of these changes are currently being widely used in health education and other fields, such as augmented reality, virtual reality, and artificial intelligence, providing significant future potential. The opportunities these technologies offer must be balanced against the associated challenges in areas such as cybersecurity, the integrity of web-based assessments, ethics, and issues of digital privacy to ensure that digital medical education continues to thrive in the future.

Development of Internet of Things (IoT) and its Impact on the Healthcare Industry

The Internet of Things (IoT) has the potential to modernize healthcare through remote patient monitoring, disease management, and improved health outcomes. IoT devices, such as wearables and sensors, can collect and transmit data in real time, enabling healthcare providers to make informed and timely decisions. This paper examines the current state of the Internet of Things in healthcare, the opportunities presented by the Internet of Things, and the challenges faced during implementation. This paper first describes the benefits of IoT in healthcare, including improving patient outcomes, reducing healthcare costs, and increasing access to care. We look at a variety of IoT devices used in healthcare, including wearables, smart implants, and medical sensors. This paper also outlines the challenges facing the use of IoT in healthcare, including data security, privacy issues, and regulatory issues. The paper concludes with a discussion of the future of IoT in healthcare and its potential impact on the healthcare industry.

Integrating Citizen Experiences in Cultural Heritage Archives with a Linked Non-Open Data Hub

This article explores and presents innovative methods and technologies for supporting citizen curation of cultural heritage. Relevant outcomes of the Social Participation, Cohesion and Inclusion through Cultural Engagement (SPICE) project are presented, focusing on enhancing the state of content management and delivery strategies in museums and memory institutions. We argue that citizen curation requires a principled way of managing and integrating citizen responses, contributions and dataflows in the domain of cultural heritage, raising challenges and opportunities such as integration of distributed and diverse data sources, authoritativeness, interdependence, privacy, data reuse and rights management. The solution is a Linked Data Hub (LDH), which integrates museum collections and user-generated content and repurposes them to end-user systems tailored to specific use cases for citizens and museum practitioners. Such LDH must be non-open , by offering an approach that gives citizens and organisations, such as museums or engagement agencies, meaningful control over their data by implementing user-tailored policies and negotiated access and terms of use. Additionally, our solution addresses privacy violations in user-contributed content by offering a near-real-time content monitoring framework. We present the LDH discussing pilot applications within the EU-funded project SPICE, including ‘Deep Viewpoints’, which currently supports the Irish Museum of Modern Art (IMMA) in citizen curation activities. Overall, this article serves as a critical milestone in closing functional gaps and advancing the state of technology in managing citizen responses and contributions in the cultural heritage domain.

Studying how AI tools integrated with social media can help teachers manage classrooms by providing insights into student behavior, engagement levels, and areas needing improvement

This study is conducted to determine how AI tools have assimilated into social media and the impacts on student engagement, behavior, and performance. Indeed, with the rapid progress that education technology has witnessed so far, AI stands out in transforming the very approach traditional classroom management utilized toward time. This study is qualitative in nature and seeks to identify teacher practices on class management and improvement of student outcomes while using AI-driven platforms and social media tools. The interviewees comprised 20 teachers, semi-structured interviews, group discussions, and observation. Using the thematic analysis of NVivo software, it has found a major issue that how effective AI tools had been in student monitoring, engagement, usage of social media, and solving the problems like technical issues and the privacy concern. Results: AI tools made the classroom dynamics totally change as now the teachers could use data collected on time for personalized learning and intervention purposes. However, some of the challenges realized include teacher training and data security. The author concludes this research study by making recommendations to the teaching fraternity to use AI and social media tools in the classroom and on proper training, professional development, and ensuring the data privacy. Long-term impacts of AI tools on the academic performance and well-being of students; comparative studies of different school settings, among other directions that explored in future research. This work fits into the thematic development of the transforming potential of AI and social media in new educational environments.

Generative AI in Education: Assessing Usability, Ethical Implications, and Communication Effectiveness

The rapid expansion of generative artificial intelligence tools for textual production, such as ChatGPT, has been accompanied by a proliferation of similar tools used for creating images, audiovisual content, and motion graphics. These tools, valued for their creativity, are increasingly employed in the fields of art, education, and entertainment to enhance content creation, particularly on social media, while also reducing production costs. However, their use is not without controversy, as they raise significant ethical concerns, including the potential for generating fake news and disinformation. This paper presents an analysis of higher education students’ perspectives on the use of generative artificial intelligence tools within the context of a university course. The research was conducted through semi-structured interviews with 10 fourth-year students from the Department of Communication and Digital Media at the University of Western Macedonia. The study aims to provide an initial understanding of the impact of these tools in both education and communication, focusing on students who are future professionals in the communication field. The interviews explored the potential benefits of these technologies, which were valued highly, and the challenges presented such as privacy and credibility issues, which concerned the participants. Misinformation and deception were cited as the most significant risks, while these tools were evaluated positively in terms of communicative purposes, but still maintaining skepticism.

Effects of Cultural Factors at the Individual Level on Online Privacy Among Vietnamese University Students: An Empirical Study Using a PLS-SEM Approach

The research investigates how Hofstede’s cultural dimensions at the individual level influence online privacy among Vietnamese university students. The previous research findings, APCO model, Hofstede’s theory of cultural dimensions and the protection motivation theory were adopted to conduct the study hypotheses. Data from a sample of 386 students at a private university in Hanoi was analysed with the Partial Least Squares-Structural Equation Modeling (PLS-SEM). Findings show that collectivism, long-term orientation and uncertainty avoidance had a positive impact on privacy concern but they did not directly influence privacy behavior. Instead, they could affect privacy behavior through privacy concern. Masculinity had no significant impact on both privacy concern and privacy behavior. Power distance positively influenced privacy behavior, but it did not have any effects on privacy concern. Regarding the relationship between privacy concern and privacy behavior, the findings suggest a potential two-way connection between privacy concern and behavior, requiring longitudinal research to examine it thoroughly.

Visual Content Privacy Protection: A Survey

Vision is the most important sense for people, and it is also one of the main ways of cognition. As a result, people tend to utilize visual content to capture and share their life experiences, which greatly facilitates the transfer of information. Meanwhile, it also increases the risk of privacy violations, e.g., an image or video can reveal different kinds of privacy-sensitive information. Scholars have persistently pursued the advancement of tailored privacy protection measures. Various surveys attempt to consolidate these efforts from specific viewpoints. Nevertheless, these surveys tend to focus on particular issues, scenarios, or technologies, hindering a comprehensive overview of existing solutions on a broader scale. In this survey, a framework that encompasses various concerns and solutions for visual privacy is proposed, which allows for a macro understanding of privacy concerns from a comprehensive level. It is based on the fact that privacy concerns have corresponding adversaries, and divides privacy protection into three categories, based on computer vision (CV) adversary, based on human vision (HV) adversary, and based on CV & HV adversary. For each category, we analyze the characteristics of the main approaches to privacy protection, and then systematically review representative solutions. Open challenges and future directions for visual privacy protection are also discussed.

Privacy paradox stems from overconfidence: a study of users’ privacy disclosure in online knowledge communities

ABSTRACT In OKCs, knowledge sharing is the main activity of users. However, the process of sharing knowledge inevitably discloses privacy. Understanding users’ privacy-disclosure behavior in OKCs is crucial for community development. In order to expose the phenomenon of privacy-disclosure behavior and privacy paradox in OKC, this study employs an explanatory sequential mixed methods design to explore the relationships among users’ privacy literacy (PL), the privacy paradox, and privacy-disclosure intentions in OKCs. We developed a research model based on privacy calculus and protective motivation theory, testing it among 442 long-term OKC users. Additionally, semi-structured interviews with 25 users provide qualitative insights. This paper indicates that many OKC users overestimate their PL, which influences their privacy-disclosure intentions and contributes to the privacy paradox. This implies that overestimating PL may be another reason for the privacy paradox. Furthermore, privacy attitudes and subjective norms emerge as significant factors shaping users’ decisions to disclose personal information, with peer perceptions playing a crucial role in users’ disclosure behaviors. This study contributes to the existing literature on privacy issues in OKCs by shedding light on the complexities surrounding users’ privacy behaviors. It offers practical recommendations for community managers and users to enhance privacy protection.

Blockchain and Machine Learning: A Multidisciplinary Synergistic Approach for Fraud Detection in Finance, Healthcare, and Cybersecurity

The integration of Blockchain and Machine Learning (ML) technologies offers a transformative approach to combating fraud across various sectors, including finance, healthcare, and cybersecurity. Blockchain's decentralized and immutable nature ensures data integrity and transparency, while Machine Learning algorithms enable the detection of intricate fraud patterns through predictive analytics and anomaly detection. This synergistic combination provides a robust mechanism for identifying fraudulent activities in real time, minimizing human error, and optimizing decision-making processes. In the financial sector, Blockchain enhances the security and transparency of transactions, while ML models analyze transaction data to identify unusual patterns that may indicate fraud. In healthcare, Blockchain ensures the secure sharing of medical records, and ML assists in detecting fraudulent claims and potential identity theft. Cybersecurity applications leverage Blockchain for secure communication and data storage, with ML identifying potential threats or vulnerabilities. By combining these two cutting-edge technologies, organizations can strengthen their fraud detection systems, improve trust, and mitigate the risks associated with financial losses, data breaches, and privacy violations. This paper explores the multidisciplinary synergy of Blockchain and ML, illustrating their potential to revolutionize fraud detection mechanisms across multiple domains, providing a comprehensive overview of current advancements, challenges, and future directions for their integration in the fight against fraud.

Artificial intelligence terminology, methodology, and critical appraisal: A primer for headache clinicians and researchers.

The goal is to provide an overview of artificial intelligence (AI) and machine learning (ML) methodology and appraisal tailored to clinicians and researchers in the headache field to facilitate interdisciplinary communications and research. The application of AI to the study of headache and other healthcare challenges is growing rapidly. It is critical that these findings be accurately interpreted by headache specialists, but this can be difficult for non-AI specialists. This paper is a narrative review of the fundamentals required to understand ML/AI headache research. Using guidance from key leaders in the field of headache medicine and AI, important references were reviewed and cited to provide a comprehensive overview of the terminology, methodology, applications, pitfalls, and bias of AI. We review how AI models are created, common model types, methods for evaluation, and examples of their application to headache medicine. We also highlight potential pitfalls relevant when consuming AI research, and discuss ethical issues of bias, privacy and abuse generated by AI. Additionally, we highlight recent related research from across headache-related applications. Many promising current and future applications of ML and AI exist in the field of headache medicine. Understanding the fundamentals of AI will allow readers to understand and critically appraise AI-related research findings in their proper context. This paper will increase the reader's comfort in consuming AI/ML-based research and will prepare them to think critically about related research developments.

Advertising Breaks the Privacy of WeChat Circle of Friends Analysis

With the rapid development of Internet technology and the popularity of smart phones, social media has become an indispensable part of People's Daily life. WeChat, one of the largest social media platforms in China, has gained popularity for its moments function due to its high degree of privacy and user viscosity. However, with the rise of the social media advertising market, the frequent appearance of advertising messages in WeChat moments not only disrupts the social experience of users, but also may cause users to worry about privacy leakage. This study aims to deeply analyze how advertisement delivery breaks the privacy of WeChat circle of friends, and explore the possibility of optimizing advertisement delivery strategy, including delivery quantity, delivery characteristics, target audience positioning and so on. Through the optimization strategy, the purpose is to reduce the intrusion of user privacy, improve user experience, and achieve a win-win situation between business interests and user privacy protection. Using questionnaire survey and hot list comparison, the study analyzed the impact of advertising on users' privacy perception, attitude and behavior. Suppose the results show that AD delivery breaks the privacy of WeChat moments to some extent, and users are put off by frequent and non-personalized ads. The study also found that gender, age, occupation and other factors have an impact on the perception of privacy in WeChat circle of friends. Based on the research results, marketing strategies and content suggestions for different user groups are proposed, in order to better safeguard users' privacy rights and social experience while ensuring the effect of advertising delivery and promote the sustainable development of social media platforms and advertising industry.

A Research on the Protection of Personal Information in the Context of Face Recognition Technology

The rapid development of science and technology, coupled with the extensive use of the Internet, has led to the emergence of face recognition technology as a prominent high-tech power, which has become an integrated part of people’s daily life. While facilitating convenience in life, face recognition technology also presents a multitude of legal risks and challenges. The diversity and opacity of the Internet provide an optimal environment for those engaged in illicit activities to exploit its shortcomings for a range of illegal and criminal pursuits. As restrictions on the use of face recognition technology are lifted and its scope of application expands, the risk of data leakage and violations of individual privacy, as well as its potential use as a tool for crimes, continues to rise. China still has deficiencies and vulnerability in the implementation of face recognition technology. For instance, the pertinent legislation and regulatory frameworks governing the face recognition industry and the collection and utilization of personal data remain somewhat ambiguous and incomplete, which may result in the infringement of privacy rights. It would be prudent for China to draw upon the experiences and solutions that have been developed domestically and abroad to improve and tailor the existing legal system and regulations to the country's specific circumstances. This approach would serve to reinforce the protection of personal information, facilitate the more effective utilization of the technology for the benefit of the nation and society, enhance convenience for citizens, and reinforce their sense of security and well-being.

Digital Twins for Smarter Iranian Cities: A Future Studies Perspective

This study explores the future of Urban Digital Twin (UDT) in urban planning systems of developing countries, with a focus on Iran. Despite UDT's growing popularity, its implementation in developing countries is limited. The research identifies critical factors influencing UDT development, including organisational acceptance, urban infrastructure, policy and legislation, and technology and innovation. Using a futures studies approach, the study employs the Delphi method, MICMAC (Matrix Impact Cross-Reference Multiplication Applied to a Classification) technique, and SISMW (Strategic Uncertainties and Strengths Weaknesses Opportunities and Threats Matrix) methodologies to analyse these factors. The study reveals that international sanctions, organisational factors, technological factors, and infrastructure limitations hinder UDT development in Iran. However, UDT technology has the potential to transform urban planning in developing countries. The study provides a roadmap for collaboration between public and private sectors and research institutes to facilitate UDT implementation, highlighting the importance of legislative frameworks, digital infrastructure, innovation, and stakeholder engagement. Policy implications suggest that governments should prioritise supportive policies, investments in digital infrastructure, and collaborative efforts to address data privacy, security, and ownership issues. By addressing these challenges, developing countries can leverage UDT technology to improve urban planning, resource management, and quality of life.

Exploring barriers and facilitators to blood donation in secondary schools in Malawi.

Despite the Malawi Blood Transfusion Service (MBTS) increasing the amount of blood collected since its inception in 2004, Malawi remains with a 27% deficit in required blood supplies nationally. We sought to understand the facilitators and barriers to blood donation among secondary school students in Malawi. We utilised a qualitative exploratory design, with a sample of 135 participants purposefully selected from 16 secondary schools across Malawi. Data collection methods included in-depth interviews with 20 participants (inclusive of first-time and repeat donors, lapsed and non-donors), 20 key informant interviews (including community leaders, policy-level stakeholders and MBTS staff), and 16 focus group discussions involving 95 participants (community stakeholders and all donor categories). We used the consolidated framework for implementation research (CFIR) to assess barriers and facilitators of blood donation, focusing only on four CFIR domains: internal and external factors; the implementation process and individual characteristics influencing blood donation. Blood donation among students are facilitated by altruism, incentives including milestone awards, knowledge, motivation, transport, peer pressure and individual health status. Common barriers cited included: negative experiences with the blood donation process, fear, unsupported environment, poor incentives, privacy issues and the donation activities starting late than scheduled. While there have been efforts to motivate students to donate blood, significant barriers to blood donation still exist. Intensifying education and awareness campaigns may help dispel misconceptions and fears surrounding donation experiences and blood usage. Also, continuing with the provision of appropriate incentives including milestone awards may also encourage students.

Balancing privacy and public health: The impact of South Africa's cannabis legalization

The Cannabis for Private Purposes Act, enacted in South Africa in 2024, marks a significant shift in national drug policy by legalizing private cannabis use while aiming to balance individual privacy rights with public health and safety. This paper examines the Act’s impacts on socioeconomic dynamics, public health, and crime within South Africa, a context shaped by poverty, inequality, and strained healthcare resources. The study highlights potential economic benefits, such as job creation and formal market opportunities, alongside risks, including increased pressure on mental health services and complex implications for crime and gender-based violence. Drawing from government reports, recent studies, and international case comparisons, the analysis reveals how legalization might reduce the burden on the criminal justice system while also introducing challenges in public safety and healthcare capacity. The findings emphasize the need for robust governance frameworks that prioritize health system preparedness, social protections, and crime prevention. The discussion provides targeted policy recommendations for government agencies, healthcare providers, and law enforcement, addressing the importance of public education, regulatory oversight, and mental health support. This study offers valuable insights into the nuanced consequences of cannabis legalization in an emerging economy, contributing to global discussions on drug policy. By aligning policy with the realities of public health and safety, South Africa can leverage the potential benefits of legalization while mitigating its social costs.

Kewenangan Mahkamah Agung dalam Publikasi Pada Putusan Perkara Privat

This study examines the Supreme Court's authority to publish rulings on private cases and its impact on individuals' privacy rights. This authority, framed by transparency and data protection principles, is grounded in the right to public information per the Indonesian Constitution and Law No. 14 of 2008. However, publishing decisions in sensitive cases, such as divorce and domestic violence, risks violating individual privacy. This research addresses the urgent need to balance transparency and privacy by analyzing the legal basis and limitations on the Court’s authority. Through normative legal methods and legislative analysis, this study reviews key guidelines, including Supreme Court Decision No. 2-144/KMA/SK/VIII/2022, to recommend privacy protections for sensitive information in judicial rulings. Findings indicate that, despite a general obligation to disclose court decisions, exceptions must be made for sensitive data to safeguard privacy, contributing to a nuanced approach to judicial transparency.

Understanding the Role of Personalisation in Augmented Reality Applications for Enhancing User Experience

Purpose: The purpose of the study is to have an understanding about the impact of augmented reality (AR) on user experience in case of a makeup app. This article tries to explore how personalisation, an AR process, impacts the various aspects of user experience (pragmatic quality, hedonic quality by stimulation, hedonic quality by identification and attractiveness). This study also evaluates the moderating role of privacy concern on the relationship of personalisation and user experience. Methodology: This research empirically analyses data from an experiment conducted in a controlled lab setting with 200 valid responses from users of a makeup app, which incorporates AR technology. SPSS and SmartPLS4 were used for the analysis. Findings: The results show that personalisation significantly impacts the user experience, particularly in terms of enhancing pragmatic quality. However, the results did not show a moderating effect of privacy concerns on the relationship of personalisation and user experience. Implications: This research offers marketers a foundation on leveraging AR technology in enhancing the app experience. It also contributes to the AR literature by understanding the interplay of personalisation, privacy concern and user experience. Originality/Value: This study examines how personalisation in AR distinctly shapes the user experience. It also addresses the contemporary dilemma of privacy concerns, investigating whether marketers should prioritise enhancing personalisation or exercise caution to uphold user privacy. While previous studies related to AR and user experience have been conducted in Western contexts, this study is unique in its kind in India.

A community-based analysis of security practices regarding over-the-counter skincare products in nationwide retail drug stores.

Access to over-the-counter (OTC) skincare products is critical for managing a wide range of dermatologic conditions, yet recent trends in urban retail stores may jeopardize this accessibility and exacerbate healthcare disparities. However, the emerging trend of securing skincare products behind security glass in urban retail environments poses significant risks to healthcare equity and accessibility. Herein, we aim to quantify the prevalence of skincare products behind security glass in pharmacies within a 25-mile radius of Times Square, New York City. An observational, cross-sectional study was conducted, selecting 50 pharmacies from a total of 389 identified in the target radius. Digital photographs of skincare product aisles were taken, and the percentage of products secured behind glass was calculated for various categories and brands. The study found significant disparities in the availability of skincare products, with significantly higher percentages of products behind security glass in pharmacies located in urban areas compared to suburban regions. Among the four brands analyzed, Olay, L'Oréal, La Roche-Posay, and Vichy, there was no significant difference in the proportion of products behind security glass. Barriers to accessing skincare products, such as physical restrictions, time constraints, stigma, and privacy issues, may hinder individuals from obtaining necessary treatments, leading to potential delays in care and poorer health outcomes. Our study underscores the urgent need for dermatologists and healthcare policymakers to advocate for alternative security measures that do not compromise product accessibility. Facilitating easier access to OTC skincare products could dramatically improve treatment adherence and patient outcomes, particularly in urban settings where disparities are most pronounced.

The Role of Social Media in Enhancing Communication among Individuals: Prospects and Problems

This study is a discussion about the role that social media plays in enhancing communication among individuals, highlighting its prospects and related challenges. This research examines the impact of social media on improving communication among individuals and its prospects and challenges. This study had taken an integrated approach of secondary data analysis methodology through an extensive systematic review of the existing literature, along with the Canadian Research Data Collection (CREDC) national web-survey, to collect the attitudinal and behavioral insight of social media users on different platforms like Facebook, Twitter, and LinkedIn considering theoretical frameworks like Social Presence Theory and Media Richness Theory. Further, this conceptual review used PRISMA guidelines to examine how social media improves communication. Eligibility and exclusion criteria ensured peer-reviewed article selection and credibility. Study reveals that social media platforms significantly enhance interpersonal communication by fostering increased interconnectedness, more accessible information, and community formation. Notably, while these digital environments have considerable benefits, such as the facilitation of learning and support networks, they are also fraught with challenges, including misinformation, privacy concerns, and potential adverse effects on mental health. These findings therefore have dual approaches to reaping the benefits of social media in communication: the promotion of user education to reduce misinformation and building up digital literacy, while there is also a need to consider regulations that will protect against violation of privacy and cyberbullying. It is at this point that stakeholders will, arguably, have fewer difficulties in making use of social media to continue developing active citizenship and rich interpersonal relationships. Future research is encouraged to further explore the implications of emerging technologies on social media communication practices.

Consumer Adoption of Internet of ThingsIoT

ABSTRACTThe Internet of Things (IoT), a pivotal technology in enhancing user connectivity, faces a paradox: its widespread potential yet limited consumer adoption. This study addresses this dichotomy by synthesizing a large‐scale meta‐analytic structural equation modeling (MASEM) and hierarchical linear meta‐analysis (HiLMA) of 2736 effect sizes from 52,629 respondents across 138 studies. We propose an integrated and heterogeneous model, underpinned by appraisal theory and the technology acceptance model (TAM), to explain the dynamics of IoT adoption among consumers across heterogeneous settings. Our findings reveal that consumers' primary appraisals of IoT, influenced significantly by hedonic motivation and social influence, are instrumental in forming perceptions of IoT's ease of use and usefulness. These perceptions subsequently guide consumers in navigating the complexities of IoT, such as privacy, risk, and trust issues. These layered appraisals inform consumers' attitudes and intentions toward IoT adoption, wherein its efficacy is heightened in contexts involving critical services versus non‐critical ones, in Eastern versus Western regions, within healthcare rather than fashion sectors, and among more experienced and younger demographics, particularly students over the general public. The study also underscores the distinct impact of branded IoT devices over unbranded ones, delineating a heterogeneous understanding of IoT adoption. Therefore, the interpretation of heterogeneities in the combination of effect sizes from extant studies is a seminal attempt to address the IoT paradox by demonstrating which factors explain the variations in the relationship between attitude and intention toward IoT from the consumer's perspective.