With the emergence of personal health record (PHR) platforms becoming more widely available, this research focused on the development of privacy heuristics to assess PHRs regarding privacy. Existing sets of heuristics are typically not application specific and do not address patient-centric privacy as a main concern prior to undergoing PHR procurement. A set of privacy specific heuristics were developed based on a scoping review of the literature. An internet-based commercially available, vendor specific PHR application was evaluated using the derived set of privacy specific heuristics. The proposed set of privacy specific derived heuristics is explored in detail in relation to ISO 29100. The assessment of the internet-based commercially available, vendor specific PHR application indicated numerous violations. These violations were noted within the study. It is argued that the new derived privacy heuristics should be used in addition to Nielsen's well-established set of heuristics. Privacy specific heuristics could be used to assess PHR portal system-level privacy mechanisms in the procurement process of a PHR application and may prove to be a beneficial form of assessment to prevent the selection of a PHR platform with a poor privacy specific interface design.
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BMC Psychol
January 2025
Beijing Key Laboratory of Applied Experimental Psychology, Faculty of Psychology, National Demonstration Center for Experimental Psychology Education (Beijing Normal University), Beijing Normal University, Beijing, 100875, China.
An ongoing debate on the association between phonological processing and number knowledge concerns the extent to which they influence each other during early childhood. The current study aims to establish the direction of the developmental relationship between these two kinds of abilities at an early age. Eighty-two Chinese kindergarten children were followed from 5 to 6 years old with a one-year interval.
View Article and Find Full Text PDFCureus
December 2024
Medical Education, ABWA Medical College, Faisalabad, PAK.
Background: The inclusion of artificial intelligence in medical education, specifically through the use of ChatGPT (OpenAI, San Francisco, CA), has transformed learning and generated many ethical questions. This study aims to analyze the medical students' ethical concerns about using ChatGPT in medical education, focusing on privacy, accuracy, and professional integrity.
Methods: The study format was a cross-sectional survey distributed to 219 medical students at ABWA Medical College, Pakistan.
Obes Surg
January 2025
Research Center of Anesthesiology, National-Local Joint Engineering Research Centre of Translational Medicine of Anesthesiology, West China Hospital, Sichuan University, Chengdu, China.
This study evaluates the feasibility of ChatGPT-4 as a knowledge resource in bariatric surgery. Using a problem set of 30 questions covering key aspects of bariatric care, responses were reviewed by three bariatric surgery experts. ChatGPT-4 achieved strong performance, with 50% of responses scoring the highest possible rating for alignment with clinical guidelines.
View Article and Find Full Text PDFMol Diagn Ther
January 2025
Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan.
Background: In the diagnosis of sexually transmitted infections, there has been a demand for multiple molecular assays to rapidly and simultaneously detect not only pathogens but also drug resistance-associated mutations.
Methods: In this study, we developed a new rapid simultaneous molecular assay for the detection of Neisseria gonorrhoeae, Chlamydia trachomatis, Trichomonas vaginalis, Mycoplasma genitalium, and M. genitalium macrolide (23S rRNA gene, A2058/A2059) and fluoroquinolone (ParC gene, S83I) drug resistance-associated mutations in approximately 35 minutes.
BMC Nurs
January 2025
Nursing Administration, Faculty of Nursing, Helwan University, Cairo, Egypt.
Introduction: Artificial Intelligence (AI) is increasingly being integrated into healthcare, particularly through predictive analytics that can enhance patient care and operational efficiency. Nursing leaders play a crucial role in the successful adoption of these technologies.
Aim: This study aims to assess the readiness of nursing leaders for AI integration and evaluate their perceptions of the benefits of AI-driven predictive analytics in healthcare.
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