Introduction: Patient education is an integral component of diabetes mellitus care. The emergence of different methods and characteristics of patient education has led to varying outcomes of quality of life (QoL). Herein, we systematically searched for published studies reporting patient education and its methods and characteristics for improving the QoL of patients with type 2 diabetes mellitus (T2DM).
Method: In this scoping review, eligible studies from six databases (PubMed, Scopus, Cochrane Library, Springer Link, Science Direct and Google Scholar) were identified. The keywords used in the search strategies were as follows: health education, health promotion, patient education, diabetes care, QoL, diabetes mellitus and type 2 diabetes mellitus. Two reviewers independently screened all references and full-text articles retrieved to identify articles eligible for inclusion.
Results: A total of 203 articles were identified in the initial search. Of them, 166 were excluded after screening the titles and abstracts. Further full-text screening led to the subsequent removal of 22 articles, leaving 15 articles eligible for data extraction.
Conclusion: There is a broad array of methods of patient education for improving the QoL of patients with T2DM. Self-management education with supplementary supervision and monitoring effectively improves QoL. Future studies must emphasise the application of holistic education covering psychological distress, diet plan, and physical health.
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http://dx.doi.org/10.51866/rv.208 | DOI Listing |
Updates Surg
January 2025
Alluri Sitarama Raju Academy of Medical Sciences, Eluru, India.
There is a growing importance for patients to easily access information regarding their medical conditions to improve their understanding and participation in health care decisions. Artificial Intelligence (AI) has proven as a fast, efficient, and effective tool in educating patients regarding their health care conditions. The aim of the study is to compare the responses provided by AI tools, ChatGPT and Google Gemini, to assess for conciseness and understandability of information provided for the medical conditions Deep vein thrombosis, decubitus ulcers, and hemorrhoids.
View Article and Find Full Text PDFTransplant Proc
January 2025
Department of Urology, Sun Yat-sen Memorial Hospital, Guangzhou, China. Electronic address:
This study evaluated the capability of three AI chatbots-ChatGPT 4.0, Claude 3.0, and Gemini Pro, as well as Google-in responding to common postkidney transplantation inquiries.
View Article and Find Full Text PDFJMIR Res Protoc
January 2025
University hospital Medical Information Network (UMIN) Center, The University of Tokyo Hospital, Tokyo, Japan.
Background: The Patient Education Materials Assessment Tool (PEMAT) is a reliable and validated instrument for assessing the understandability and actionability of patient education materials. It has been applied across diverse cultural and linguistic contexts, enabling cross-field and cross-national material quality comparisons. Accumulated evidence from studies using the PEMAT over the past decade underscores its potential impact on patient and public action.
View Article and Find Full Text PDFDental Press J Orthod
January 2025
Federal University of Minas Gerais, School of Dentistry, Department of Restorative Dentistry (Belo Horizonte/MG, Brazil).
Objective: To evaluate the quality of YouTube™ and TikTok™ videos as educational tools for patients with cleft lip and palate (CLP) as regards their care, and multidisciplinary treatment.
Methods: Videos were searched on YouTube™ and TikTok™ using four keywords. The reliability and quality of the first 60 videos for each keyword and platform were analyzed.
PLOS Glob Public Health
January 2025
Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, Washington, United States of America.
Many historical administrative documents, such as the 1940 census, have been digitized and thus could be merged with geographic data. Merged data could reveal social determinants of health, health and social policy milieu, life course events, and selection effects otherwise masked in longitudinal datasets. However, most exact boundaries of 1940 census enumeration districts have not yet been georeferenced.
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