Personal Information Research Articles

4.K. Scientific session: The realm of the information ecosystem and its public health impact

Abstract Workshop background As a field of science, study, practice, and policy, infodemic management has emerged during the Covid-19 pandemic but has since been emancipated and can be translated to any topic where information ecosystems play a vital role. In particular relevant to public health, infodemic managers have grown in the ranks of institutes of public health, academic institutions, UN agencies and civil society organizations, tackling outbreaks and public health issues as wide as mpox, Marburg, teen mental health, chronic diseases, seasonal influenza, Ebola and routine immunization. Aiming at improving public health strategies, they are responsible for exploring and investigating personal and organizational (health) information ecosystem, generating evidence, identifying patterns of communication and information flow, tackling the onset and distribution of circulating mis- and disinformation, better understanding information voids, and respond to citizen needs concerning information demands around emergencies. In this workshop, we will focus on several common challenges associated with implementing whole-of-society interventions and strategies for resilience to health misinformation. Solving these challenges, which often are too big just for the health system to solve, will sometimes require creativity, out-of-the-box thinking as well as cross-disciplinary perspectives and new partnerships. Infodemics are also a global challenge that can easily cross borders, which is why country-to-country discussions of experiences by participants is encouraged-while no previous infodemic management experience is required. Workshop objectives The workshop will be organized as a research symposium with five speakers from infodemic management, health information, and health literacy. They will provide a solid introduction to infodemic management from different perspectives and angles. (i) The first presentation will introduce a study on health information seeking and health literacy in midwife-led care and the modern information environment. (ii) The second presentation will discuss how fact-checking organizations can partner within public health for a healthier internet. (iii) The third presentation will focus on unravelling misinformation by investigating the associations between health literacy and resilience. (iv) The fourth presentation will present a novel web-platform for credible health information and tackling misinformation. (v) The fifth presentation focuses on the impact of misinformation on social media in the context of natural disasters. The format of this workshop will be 5x8-minute presentations, including Q&A with the audiences, followed by a 20-minute panel discussion, reflecting the relevance of the results to public health research, practice and policy. Key messages • Infodemic management seeks to quickly understand the public’s information and health needs improve future public health responses, especially during emergencies. • Whole-of-society approaches are needed to address and mitigate harms caused by infodemics by developing closer partnerships and understanding between health systems and the public.

Sociodemographic Factors Associated with the Utilization of Digital Health Technologies Among Informal Caregivers: A Nationwide Study in the USA, 2022.

Informal caregivers can leverage digital health technologies to support their own health while also assisting patients, particularly those with mental or physical challenges. This study investigated the sociodemographic factors associated with the use of digital health technology among informal caregivers. Data from the 2022 Health Information National Trends Survey (HINTS) were examined for this cross-sectional study. The survey identified key outcomes related to the use of online medical records, health apps, digital wearable health devices, and the digital sharing of health information with professionals, on social media, or with others facing similar health issues. Sociodemographic factors (gender, race/ethnicity, feelings of one's household income, education, and census division) were also analyzed. Weighted multivariable logistic regression models were employed. A total of 831 individuals were included, representing about 36,960,385 national informal caregivers in 2022. Caregivers with a high school education or less (vs. those with at least some college education) and non-Hispanic Black caregivers (vs. non-Hispanic White caregivers) were significantly less likely to be offered access to online medical records by their healthcare providers. Additionally, online medical record usage was lower among caregivers with high school education or less, but higher among caregivers aged 50-64 (vs. those aged 35-49). Caregivers with a high school education or less were less likely to use health apps and digital wearable health devices, but more likely to share personal health information on social media. Men caregivers, those aged 50-64 and over 65 (vs. the 35-49 age group), and caregivers who were dissatisfied with their income were less likely to use digital wearable health devices. The findings underscore disparities in the utilization of caregivers' digital health technology, particularly in digital wearable health devices. Recognizing and addressing these disparities are crucial for tailoring interventions to enhance equitable access to digital health technology among diverse informal caregiver populations.

The Evolution of Health Information Technology for Enhanced Patient-Centric Care in the United States: Data-Driven Descriptive Study.

Health information technology (health IT) has revolutionized health care in the United States through interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and electronic patient access to health information. This study aims to examine progress in health IT adoption and its alignment with the Office of the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health IT (ASTP's) mission to enhance health care through data access and exchange. This study leverages data on end users of health IT to capture trends in engagement in interoperable clinical care data exchange (ability to find, send, receive, and integrate information from outside organizations), e-prescribing, electronic public health reporting, and capabilities to enable patient access to electronic health information. Data were primarily sourced from the American Hospital Association Annual Survey IT Supplement (2008 to 2023), Surescripts e-prescribing use data (2008 to 2023), the National Cancer Institute's Health Information National Trends Survey (2014 to 2022), and the National Center for Health Statistics' National Electronic Health Records Survey (2009 to 2023). Since 2009, there has been a 10-fold increase in electronic health record (EHR) use among hospitals and a 5-fold increase among physicians. This enabled the interoperable exchange of electronic health information, e- prescribing, electronic public health data exchange, and the means for patients and their caregivers to access crucial personal health information digitally. As of 2023, 70% of hospitals are interoperable, with many providers integrated within EHR systems. Nearly all pharmacies and 92% of prescribers possess e-prescribing capabilities, an 85%-point increase since 2008. In 2013, 40% of hospitals and one-third of physicians allowed patients to view their online medical records. Patient access has improved, with 97% of hospitals and 65% of physicians possessing EHRs that enable patients to access their online medical records. As of 2022, three-fourths of individuals report being offered access to patient portals, and over half (57%) report engaging with their health information through their patient portal. Electronic public health reporting has also seen an increase, with most hospitals and physicians actively engaged in key reporting types. Federal incentives have contributed to the widespread adoption of EHRs and broad digitization in health care, while efforts to promote interoperability have encouraged collaboration across health care entities. As a result, interoperable clinical care data exchange, e-prescribing, electronic public health reporting, and patient access to health information have grown substantially over the past quarter century and have been shown to improve health care outcomes. However, interoperability hurdles, usability issues, data security concerns, and inequitable patient access persist. Addressing these issues will require collaborative efforts among stakeholders to promote data standardization, implement governance structures, and establish robust health information exchange networks.

Multidisciplinary approach to asylum seekers health assessment: a 5-year experience in Modena, Italy

Abstract Background Asylum seekers’ well-being represents a global health issue. They face significant challenges to their physical and mental health due to their migratory path. In the Modena province (Northern Italy), a multidisciplinary approach has been applied to the care of asylum seekers by Department of Public Health (DPH), with a team of specialists in infectious diseases, dermatology, gynaecology, obstetrics, psychology and preventive medicine. Asylum seekers receive a first visit, including medical and psychological assessment and screening for infectious diseases. Ad hoc pathways are also active for asylum seekers who need secondary-level care. This study aims to investigate the health status of asylum seekers referred to Modena Centre. Methods This cohort study enrolled asylum seekers hosted in Modena between November 2018 and May 2023. During the first visit, personal and anamnestic data were collected aided by cultural mediators, along with clinical assessment. Furthermore, Tuberculin-Skin-Test (TST) and blood tests for HBV-HCV-HIV-Syphilis were performed. Results A total of 646 migrants were included, 94% were males with a median age of 26 years (range: 15-50), the majority from Bangladesh (39%). Females were mostly from Ivory Coast (36%), median age of 30 years (range: 17-45). Most conditions were treated at the primary care level and were related to cutaneous disease (22%), only 11% of subjects required second-level diagnostics. Positive TSTs were 41% (N = 265). Of them, 55.5% (N = 147) also tested positive for QuantiFERON-TB. Screening for infectious diseases revealed positivity rates of 4% for HBsAg, 1% for HCVAb, 0.8% for HIV and 1.4% for TPPA+RPR. Conclusions The multidisciplinary approach is the innovative and strength point of this protocol for asylum seekers’ health ensuring prompt management of pathologies after their arrival. Moreover, data collection is useful for improving intake services and implementing public health programs for vulnerable individuals. Key messages • The innovation of this protocol for asylum seekers’ health lies in its multidisciplinary approach. • Clinical data collection will support health policies’ choices to protect vulnerable individuals.

User technology for AI-supported objective measurement of Work-related Quality of Life (MI-LQ)

Abstract Background Understanding and enhancing job satisfaction is crucial for improving Work-Related Quality of Life (WrQoL) in today’s office work environments. Our work uses multimodal data collection and analysis techniques to objectively assess WrQoL, thus mitigating respondent bias and survey fatigue. Leveraging machine learning (ML) and automated methods measuring WrQoL presents a promising approach in public health research, particularly concerning stress-related health outcomes. Methods Through a systematic literature search of 9,242 publications to identify WrQoL indicators, we selected over 100 publications for data extraction. A base model, including workload, commute, overtime, valence, and arousal was formulated. To amass a wide data set, Objective measurement tools (computers, smartphones, and wearables) complemented by questionnaire data. This data will inform ML algorithms to predict individual WrQoL indicators. Developed as an input/output data platform, an app-prototype will objectively assess WrQoL, facilitating a field study with office workers to refine the model. A mobile app prototype serves as a user interface and data relay for WrQoL metric analysis. Results Our research develops instruments for measuring WrQoL using smartphones, wearables, and specialized trackers for heart rate variability (HRV) analysis, alongside a software prototype for keyboard and mouse tracking for workload assessment of valence and arousal. Fitness trackers with photoplethysmography functionality are favored for HRV assessment. Conclusions The systematic search identified influences on WrQoL, translated into measurable indicators in a base model. Leveraging user tech for assessment and a ML and mobile app framework, this approach facilitates objective WrQoL determination. By presenting the relationship between digital service use and WrQoL indicators, this methodology promises new insights, informing stress and burnout prevention strategies within public health initiatives. Key messages • Progressive approach: ML-driven WrQoL assessment offers promising avenues for stress prevention in workplace health research. • Methodological Advancement: The novel framework for WrQoL assessment using digital tools contributes to effective workplace health promotion strategies, with potential for tailored interventions.

Double edged tech: navigating the public health and legal challenges of digital twin technology

Abstract This research addresses the legal challenges posed by the implementation of digital twin technology in public health. Digital twins are advanced computational models which aim to replicate human organ functions and biological processes. Their goal is to enable the simulation of the entire human body and to personalize the outputs with individual patient’s health data. Digital twin technology promises to bridge gap between personalized medicine and precision public health. This research is based on a comprehensive review of the current European and Swiss legal frameworks for medical devices and data protection that apply to digital twin technology. Within these frameworks, digital twins are in a grey area, as they are only considered as medical device software when applied to individuals. They also incorporate artificial intelligence, machine learning, and data analytics, which are already a source of legal concern in a healthcare setting, but their effective use in public health raises additional issues. Preliminary findings suggest significant shortcomings in the legal frameworks regarding data privacy, and the potential for increased surveillance by health insurance systems, which could lead to human rights violations. The public health application of digital twins would require global data analysis of sensitive personal information, raising further questions about the secure storage, transmission, and processing of this data. The study concludes that current legal frameworks must be future proofed to manage the complexities introduced by digital twins in public health. In particular, it suggests that regulatory oversight of medical devices needs to be significantly improved in order to safely harness the potential of digital twin technologies for public health. Finally, the new European Union health data space and the forthcoming EU AI act will also play important roles in the implementation of digital twin technologies. Key messages • Applying digital twin technology in public health faces considerable challenges, particularly the issues around data privacy, potential discrimination, and increased surveillance. • We need to adapt and strengthen existing legal frameworks to effectively manage the complexities introduced by digital twins, ensuring that these technologies can be safely used for public health.

1.B. Round table: Artificial Intelligence in Mobile Health Apps: Ethical, Legal, and Regulatory Challenges

Abstract Globally, governments and public health authorities are integrating Artificial Intelligence (AI) techniques in mobile apps to improve public health. For example, during the COVID-19 outbreak, AI-driven chatbots were deployed to provide immediate health information and advice. AI-based mobile apps are also used to support mental health or for preventive healthcare, such as personalized dietary recommendations. Moreover, the use of generative AI for public health purposes is rapidly increasing. In 2024, the WHO launched S.A.R.A.H - a generative AI chatbot designed to provide information on major health topics such as healthy lifestyles and mental health. By integrating AI, public institutions could potentially achieve better health outcomes, improve efficiency, and enhance access to healthcare. However, the rapid adoption of AI public health apps also raises significant ethical, legal, and regulatory challenges. The large amounts of sensitive personal data collected and processed by such apps may create issues for privacy, data protection, and cybersecurity. At the same time, the tendency of AI to exhibit biases may deepen existing health inequities. The new EU ‘digital’ legal framework does not directly address these challenges. This workshop aims to convene leading experts working on AI in health to address these issues. We bring together scholars from different disciplines (health law, health policy, bioethics, biosciences). The workshop objectives are twofold: (1) to critically assess the current landscape of AI in public health apps from a legal, ethical, and regulatory point of view, and (2) to lay the groundwork for policy recommendations on how to ensure the deployment of AI apps for public health in compliance with ethical principles and fundamental rights. First, the panel explores the differences in the data protection regulation of AI public health apps in the EU and the US (speaker: James Hazel). Second, it discusses how these apps are regulated under the new EU Artificial Intelligence Act (speaker: Hannah van Kolfschooten). Third, it investigates the consequences of the European Health Data Space regulation on how health data can be processed through public health apps (speaker: Mahsa Shabani). Finally, as the cross-border use of apps complicates regulatory efforts, it discusses the need for international cooperation in establishing and enforcing guidelines (speaker: Vasiliki Rahimzadeh). The workshop will be conducted as a round table discussion with 4 short presentations of 5 minutes each. Speakers first present a key challenge posed by AI in mobile health apps, and then suggest a potential regulatory solution. This will be followed by a dialogue between panelists and the audience to share best practices on how to regulate AI in mobile public health apps from a legal, ethical, and regulatory perspective. The input will be used to develop a submission for the Call for papers of BMC Bioinformatics. Key messages • As public institutions are increasingly integrating AI technologies into their mobile public health solutions, it is crucial to evaluate the ethical, legal, and regulatory implications. • In light of current gaps in the EU legal framework, we convene scholars from different disciplines and legal systems to design guidelines on the ethical use of AI mobile apps for public health. Speakers/Panelists James Hazel University of Amsterdam, Amsterdam, Netherlands Mahsa Shabani University of Amsterdam, Ghent University, Amsterdam, Netherlands Hannah van Kolfschooten University of Amsterdam, Amsterdam, Netherlands Vasiliki Rahimzadeh Baylor College of Medicine, Houston, USA Pramiti Parwani University of Amsterdam, Amsterdam, Netherlands

Experiences from the European Region: case studies and scenarios to inform ways forward in digital health

Abstract Member States in the WHO European Region face similar challenges when it comes to strengthening their HIS and implementing digital health solutions. From WHO/Europe’s work with its Member States, several important preconditions have become apparent for successful and sustainable digital transformation. Firstly, the importance of recognising that implementing digital tools is not a one-off investment, but that this takes a long-term vision including long-term budgeting. Having business continuity plans also is a key element of sustainable implementation of digital tools, that is often not adequately addressed in practice. Secondly, the importance of comprehensive strategic planning. Implementing digital tools is not only about software and hardware, but also about people and processes. Here it is also crucial for policymakers to understand that, to be able to harvest the benefits of data that are gathered by means of digital tools, resources for data processing and analysis also need to be made available. Last but not least, an important precondition for successful digital transformation is stakeholder involvement. Often, new software is developed without adequately involving the end-user, resulting in for example apps that do not meet patients’ needs. Or in electronic health record systems that are not user-friendly for the healthcare staff that need to enter the data, with incomplete and low quality information as a consequence. Stakeholder involvement is essential in strategic planning for digital health as well. Think for example about standardization and accreditation agencies, and institutes that will be secondary users of data for statistics and research. In this presentation, several case studies from across the European Region will be presented, illustrating how digital transformation in health can be successfully and sustainably implemented.

The Relationship between Fatalism and Hope Level in Surgical Cancer Patients: A Cross-Sectional Study

Aim: This study was conducted to determine the relationship between fatalism and level of hope in surgical cancer patients. Material and Methods: This descriptive study was conducted with the participation of 314 patients from the surgical clinics and oncology department of the Ondokuz Mayıs University Health Practice and Research Hospital between October 2021 and March 2023 in Turkey. All patients aged 18 and over who did not have communication problems, had cancer surgery, spread or radiation therapy, and did not agree to participate in the study were included in the study. Personal Information Form, Fatalism Tendency Scale, and Dispositional Hope Scale were used to collect data. Results: The mean age of participants was 59.45±10.16 (min-max:27-80). The mean Fatalism Tendency total score of patients was 82.8 ± 12.2, and the mean Dispositional Hope total score was 52.3 ± 7.2. It was determined that there was a significant difference between the Fatalism Tendency total score average, and the marital status, education level, place of residence, person living with, and seeing spirituality as important (p

Development of a Medical Device Lifecycle Research Database at the MFDS

Abstract So-called big data are potentially useful in the healthcare field and are of interest to researchers, industry, and government agencies. Over the past 10 years, Europe, the United States, and Asia have been making efforts to collect and systematically manage information on the entire process from clinical trials to follow-up management of medical devices (MD). We developed MD lifecycle research database at the Ministry of Food and Drug Safety (MFDS) of the Republic of Korea, consisting of 61 tables and 2,053 variables. The MFDS possesses statistical information on all MD, pharmaceuticals, foods, and human tissues produced and distributed. The information in the database is categorized according to four MD lifecycle phases-clinical trial, approval, production, and post-approval. For the clinical trial phase, the database contains information on planning and approval of clinical trial and non-clinical trial. The approval phase includes information on models, raw materials, quality, and changes, while the production phase stores information on production, import, export, supply and use. For the last step, follow-up management phase, provide information on post-marketing safety management, risk management, and administrative disposition. All four steps are linked based on primary key, so it is possible to understand information on the overall MD lifecycle. The MD Lifecycle Research Database will help strengthen the industry’s competitiveness in terms of cost-effectiveness in MD development and facilitate policy monitoring by improving its utilization in the public interest. This database contains information on all MD produced and distributed in Korea depending on the phases of the MD lifecycle, and data is easily accessible due to the lack risk of personal information exposure, so it can be widely used by individual researchers, industries, academia, and governments. Funding This research was supported by a grant (22063MFDS498) from ministry of food and drug safety in 2024. Key messages • We developed a medical device lifecycle database that enables tracking management according to the medical device lifecycle. • This database can be used as a scientific basis to ensure the safety, effectiveness, and efficiency of medical devices.

Attitudes and Related Factors of Women in Turkey Towards Cancer Screening: Analytical Cross-Sectional Study

Objective: This study aimed to examine women's attitudes and related factors towards cancer screening in Turkey. Methods: This analytical-cross-sectional study was conducted between June and September 2022. The universe of the study consisted of all women between the ages of 30-70 in Turkey, and the sample included 335 women. The data of the study were collected online with the “Personal Information Form’’ and “Attitude Scale for Cancer Screening”. Results: The average Attitude Scale for Cancer Screening total score of the women participating in the study was 84.36±14.55. Of the women who participated in the study, 33.1% did not perform breast self-examination, 63.1% did not perform clinical breast examination, 49.5% did not perform Pap smear and HPV-DNA testing, 60.9% did not perform mammography, 76.1% did not perform fecal occult blood testing and 93.8% did not perform colonoscopy. It was determined that education status, breast self-examination, clinical breast examination, Pap Smear and HPV-DNA test frequencies, and knowing the places where cancer screening was performed affected the Attitude Scale for Cancer Screening score averages (F = 8.729, p = 0.000). Conclusion: It was determined that the attitudes of the women participating in the study towards cancer screening were moderate. Several factors are done affect attitudes towards cancer screening.

Some legal aspects of personal data protection in the world—experience for Vietnam

Some legal aspects of personal data protection in the world—experience for Vietnam

Enhancing cross-border contact tracing in Europe: Lessons learned from COVID-19 and future directions

Abstract Introduction Health systems in the EU operate at the national level, granting Member States autonomy for outbreak preparedness and response within their territories whilst coordinating at EU level to combat serious cross-border threats. The EU’s Early Warning and Response System (EWRS) provides the platform to exchange personal data for contact tracing across 30/EEA countries and was extensively utilized during COVID-19. This study examines insights from EU/EEA countries and assesses the feasibility of integrating national digital systems with EWRS to increase its effectiveness. Methods A comparative case study surveyed representatives from 24 countries and interviewed nine, analyzing contact tracing processes, actors, digital technologies, and challenges/facilitators during COVID-19. Thematic analysis was complemented by two webinars engaging EU/EEA countries to validate findings and gather additional perspectives. Results EWRS was valued for safety and efficiency but faced challenges during peak pandemic periods due to the heavy manual workload. Integrating national digital systems with EWRS could enhance data quality, timeliness, and coordination between countries. However, countries have varied and incompatible digital contact tracing systems, limiting the feasibility of their integration with EWRS. Moreover, most countries organize contact tracing at the subnational level, with regional entities developing and managing their own digital technologies under national guidance. Smaller countries excluded, subnational contact tracing case management systems were often not integrated with each other to exchange personal data in an automated way at a national level. Conclusions While integrating national digital systems with EWRS could bolster efficiency of contact tracing across EU/EEA, the presence of diverse technologies and decentralized governance poses feasibility challenges. Other improvements are needed to enhance cross-border contact tracing during outbreaks. Key messages • Integrating national digital systems with EWRS promises enhanced efficiency for contact tracing across EU/EEA in line with Regulation (EU) 2022/2371 on serious cross-border threats to health. • Diverse technologies and decentralized governance pose feasibility challenges, underscoring the need for further enhancements in cross-border contact tracing in EU/EEA during large outbreaks.

Neural Synchrony of Minds and Machines: Hippocampal Mechanisms to Advance AI and Virtual Networks

Abstract Artificial intelligence (AI) predicts behavior by learning from user data collected through digitally mediated interfaces. Virtual spaces---such as online social networks---extend the physical world into virtual worlds, leveraging AI technologies to transform user behavior into digital assets by mimicking the brain’s reinforcement networks. Social media platforms utilize AI to manipulate user behavior through rewards that can diverge from the user’s intended goals. This misalignment fragments user behavior and cognition, resulting in virtual disembodiment. Presented is a conceptual mechanism based on the hippocampus to synchronize AI and the brain, synthesizing the user’s physical and mental presence in virtual spaces.

Multidimensional Indicator for Data Quality Assessment in Wireless Sensor Networks: Challenges and Opportunities

Wireless Sensor Networks (WSN) are equipped with numerous sensors that generate vast quantities of data, essential for operational efficiency and informed decision-making. However, the value of this data is contingent upon its suitability for the specific applications it serves. A significant challenge in WSNs is the selection of appropriate data quality dimensions and metrics necessary to construct robust Data Quality Indicators (DQI) and comprehensively assess data quality in various contexts. This systematic literature review seeks to identify the key data quality dimensions and the corresponding measurement metrics within WSNs, while exploring the use of multi-dimensional data quality criteria in developing DQI. A thorough search of SCOPUS and Web of Science databases yielded 475 potential research articles, from which 64 primary studies were selected for in-depth analysis. The findings highlight four key data quality dimensions in WSN: accuracy, timeliness, completeness, and consistency. However, choosing measurement metrics for each dimension requires an in-depth understanding of the data's context. Various approaches for obtaining DQI in WSN research were identified, including weighted linear average models and application-specific contextual information. Effective DQI incorporates weights to each dimension, reflecting the priorities of specific data users, and leverages contextual information pertinent to the sensors’ data. It is crucial to evaluate whether the data collected by WSNs meets established quality standards, a key aspect of WSN operation. These insights will aid in developing more robust and reliable WSNs, ensuring the provision of high-quality data essential for effective operation and decision-making.

Does telemedicine hold the key for reproductive health care? A quantitative examination of women's intentions toward use and accurate information disclosure.

To investigate women's perceptions of telemedicine for reproductive health care services, focusing on how perceived benefits and privacy risks influence their intentions to adopt telemedicine and their willingness to disclose personal health information. A cross-sectional survey was conducted. The study applied the privacy calculus theory to the context of telemedicine for reproductive health, using adapted, validated variables to develop the survey. Outcome variables included intentions to adopt telemedicine and willingness to disclose accurate personal health information. Data were collected in May and June 2023 using Qualtrics online panel services, targeting women across the United States who had not used telemedicine for reproductive health. The sample comprised 847 women aged 18 and older. Structural equation modeling was employed using AMOS v28.0 to test the hypothesized relationships between perceived benefits, perceived risks, and adoption intentions. The analysis controlled for age, household income, political affiliation, religious views, and prior births. Perceived benefits were positively related to intention to adopt telemedicine for reproductive care (β: 0.600, p < 0.001), and willingness to disclose accurate personal health information (β: 0.453, p < 0.001). Unexpectedly, perceived privacy risks were positively related to adoption intentions (β: 0.128, p < 0.001), but negatively related to willingness to disclose (β: -0.282, p < 0.001). Intentions to adopt were positively associated with willingness to disclose (β: 0.089, p < 0.05). Lastly, older women and women located in states with abortion restrictions expressed lower intentions to adopt. The model explained 40.2% of variance in intention to adopt and 38.3% of variance in willingness to disclose. The study demonstrates the importance of perceived benefits and privacy risks in driving telemedicine adoption and disclosure intentions among women in the reproductive health context. These findings suggest the need for targeted strategies to address privacy concerns and support telemedicine adoption, particularly in restrictive regulatory environments.

Conceptualizing the Implications of Artificial Intelligence (AI) Tools and Personalization Marketing on Consumer Purchase Intention: Insights from the Malaysian E-Commerce Market

Artificial intelligence (AI) has emerged as a powerful tool, enabling online retailers to offer highly personalized shopping experiences tailored to individual preferences and behaviors. As e-commerce continues to grow in Malaysia, understanding the influence of AI and personalization marketing on consumer purchase intentions has become increasingly important for businesses seeking to remain competitive. However, the rapid adoption of AI also raises concerns about data privacy, ethical AI usage, and compliance with emerging data protection regulations, such as Malaysia’s Personal Data Protection Act (PDPA). This study aims to explore the potential impact of artificial intelligence (AI) and personalization marketing on consumer purchase intention within the Malaysian e-commerce market. By reviewing previous literature and theoretical frameworks, the study explores how the use of AI tools including predictive analytics automation, and personalization experiences might influence consumer behavior in online shopping environments. The study adopts a quantitative approach, in which quota sampling will be used for the participant selection. A self-administered questionnaire with a five-point Likert scale will be employed to gather data from e-commerce users in Malaysia. The findings from this study have important implications for both e-commerce businesses and policymakers in Malaysia. For businesses, understanding which aspects of AI and personalization most influence consumer purchase intentions can help them strategically implement these technologies to enhance customer engagement and drive sales. For policymakers, the study highlights the need to consider ethical and legal issues, such as data privacy and policy issues, in the growing use of AI in the e-commerce market.

“Your friendly AI assistant”: the anthropomorphic self-representations of ChatGPT and its implications for imagining AI

AbstractThis study analyzes how ChatGPT portrays and describes itself, revealing misleading myths about AI technologies, specifically conversational agents based on large language models. This analysis allows for critical reflection on the potential harm these misconceptions may pose for public understanding of AI and related technologies. While previous research has explored AI discourses and representations more generally, few studies focus specifically on AI chatbots. To narrow this research gap, an experimental-qualitative investigation into auto-generated AI representations based on prompting was conducted. Over the course of a month, ChatGPT (both in its GPT-4 and GPT-4o models) was prompted to “Draw an image of yourself,” “Represent yourself visually,” and “Envision yourself visually.” The resulting data (n = 50 images and 58 texts) was subjected to a critical exploratory visual semiotic analysis to identify recurring themes and tendencies in how ChatGPT is represented and characterized. Three themes emerged from the analysis: anthropomorphism, futuristic/futurism and (social)intelligence. Importantly, compared to broader AI imaginations, the findings emphasize ChatGPT as a friendly AI assistant. These results raise critical questions about trust in these systems, not only in terms of their capability to produce reliable information and handle personal data, but also in terms of human–computer relations.

Cybersecurity threats and preparedness: Implications for dental schools.

Cybersecurity threats are a growing concern in healthcare, where digital systems now underpin patient care, financial management, and educational operations. A cybersecurity breach in a Dental school environment can have widespread consequences to the mission of the school-patient care, research, education and service. For dental school administrators, these risks highlight the necessity of robust cybersecurity measures. For student learners, the impact may include interruptions to their education. For patients, it could mean compromised personal data and reduced access to clinical care. While many sectors have responded to increasing cyber threats by enhancing their defenses, healthcare and dental schools, often lag in implementing necessary protections. This emphasizes the need for proactive measures, such as regular system audits, advanced encryption methods, and ongoing cybersecurity training for administrators and students alike, to mitigate future risks and safeguard institutional integrity.

Perbandingan Evaluasi Kerentanan Menggunakan Tenable Nessus Scanner dan Owasp Zed Attack Proxy untuk Meningkatkan Keamanan Sistem Informasi Kepegawaian di Universitas Merdeka Malang

This study aims to compare the vulnerability analysis between Tenable Nessus Scanner and OWASP Zed Attack Proxy (ZAP) for improving the security of the Human Resource Information System (HRIS) website at Universitas Merdeka Malang. The research methodology includes the use of both Nessus and OWASP ZAP tools to scan the HRIS website for potential vulnerabilities. The findings of this research indicate that OWASP ZAP identified several critical web application vulnerabilities such as the absence of Anti-CSRF tokens, lack of Content Security Policy (CSP) headers, and missing Anti-Clickjacking headers, which are essential for maintaining the security and integrity of user data. On the other hand, Nessus Scanner focused more on network and server infrastructure vulnerabilities. The results suggest that OWASP ZAP is more effective for web application security in this context. Recommendations are provided to address the identified vulnerabilities and enhance the overall security of the HRIS website.