This study aimed to explore digital literacy among community-dwelling older adults in urban South Korea. A semistructured interview guide was developed using the Digital Competence ( 2.0 framework, which emphasizes the competencies for full digital participation in five categories: information and data literacy, communication and collaboration, content creation, safety, and problem-solving. The data were analyzed using combined inductive and deductive content analysis. Inductive analysis identified three main categories: perceived ability to use digital technology, responses to digital technology, and contextual factors. In the results of deductive analysis, participants reported varying abilities in using digital technologies for information and data literacy, communication or collaboration, and problem-solving. However, their abilities were limited in handling the safety or security of digital technology and lacked in creating digital content. Responses to digital technology contain subcategories of perception (positive or negative) and behavior (trying or avoidance). Regarding contextual factors, aging-related physical and cognitive changes were identified as barriers to digital literacy. The influence of families or peers was viewed as both a facilitator and a barrier. Our participants recognized the importance of using digital devices to keep up with the trend of digitalization, but their digital literacy was mostly limited to relatively simple levels.
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http://dx.doi.org/10.1097/CIN.0000000000001109 | DOI Listing |
J Med Internet Res
January 2025
Department of Psychiatry, Yongin Severance Hospital, Yongin, Republic of Korea.
Background: The COVID-19 pandemic has accelerated the digitalization of modern society, extending digital transformation to daily life and psychological evaluation and treatment. However, the development of competencies and literacy in handling digital technology has not kept pace, resulting in a significant disparity among individuals. Existing measurements of digital literacy were developed before widespread information and communications technology device adoption, mainly focusing on one's perceptions of their proficiency and the utility of device operation.
View Article and Find Full Text PDFComput Inform Nurs
January 2025
Author Affiliations: Duke University School of Nursing (Drs Lee, Silva, Yang, Hatch, and Shaw and Mss Pennington, Matters, and Urlichich); and Duke University School of Medicine (Dr Crowley), Durham, NC.
Digital health literacy is emerging as an important element in chronic illness management, yet its relationship with clinical outcomes remains unclear. Utilizing data from the ongoing EXpanding Technology-Enabled, Nurse-Delivered Chronic Disease Care trial, this cross-sectional, correlational study explored the association between digital health literacy, health literacy, and patient outcomes, specifically blood pressure and hemoglobin A1c levels in 76 patients managing comorbid type 2 diabetes and hypertension. Results indicate patients had moderate digital health literacy, which was not significantly correlated with health literacy (r = 0.
View Article and Find Full Text PDFHealthcare (Basel)
December 2024
Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-8585, Japan.
: Internet use positively impacts mental health in older adults, with health literacy (HL) playing a key role. While social networks may complement individual HL, the role of neighborhood relationships in this association, particularly by gender, remains unclear. This study examined how the association between HL and Internet use among older adults was modified by neighborhood relationships.
View Article and Find Full Text PDFJ Clin Nurs
January 2025
Department of Nursing, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Aim: To analyse how refined living arrangements, in the context of digital access, affect elderly healthcare resource utilisation and satisfaction with healthcare needs.
Design: A prospective cohort study. The study reporting is conformed to the STROBE checklist.
PLoS One
January 2025
Department of Pediatrics and Child Health, Makerere University, College of Health Sciences, Kampala, Uganda.
Background: Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, it has introduced new challenges and threats to medical education. We assessed the use of ChatGPT and other AI tools among medical students in Uganda.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!