Diabetes can cause several long-term complications. Knowledge about this disease can play an important role in reducing diabetes-related complications. In addition, the lack of awareness leads to misconceptions, which joined with inadequate knowledge, are relevant barriers to proper diabetes management. In this study, we aimed to assess the diabetes knowledge of a type 2 diabetes (T2D) population and identify major knowledge gaps, in order to prevent complications and to increase quality of life. In a cross-sectional, observational study in a convenience sample, we identified individuals diagnosed with T2D attending ambulatory visits from five health settings, older than 18 years, with a time diagnosis of at least 1 year, and attending multidisciplinary visits for at least 3 months. To assess the knowledge of T2D individuals, we applied the Portuguese version of the Diabetes Knowledge Test. The sample included a total of 1,200 persons, of whom almost half were female. The age range of the participants varied from 24 to 94 years old, and the mean age was 65.6 ± 11.4 years. Most of the sample had a level of education under secondary and lived with someone. In our sample, 479 (39.9%) were insulin-treated. The percentage of correct answers was 51.8% for non-insulin vs. 58.7% for insulin treated ( < 0.05). There were three items with a percentage of correct answers lower than 15%; the item with the lower value of correct answers was the one related to the identification of signs of ketoacidosis with only 4.4% of correct answers, the errors presented a random pattern; the item related to the identification of which food should not be used to treat low blood glucose with 11.9%, where 56.9% of the sample's participants considered that one cup of skim milk would be the correct answer (53.1% in non-insulin patients and 62.6% in insulin treated patients; < 0.001). The item regarding the knowledge of free food presented a 13.3% of correct answers (10.8% non-insulin group vs. 17.1% insulin group; < 0.01). Two of the three items with lower value of correct answers were related to glycemic control and health status monitoring, the other was related to diet and food.
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http://dx.doi.org/10.3389/fpubh.2024.1328001 | DOI Listing |
Sci Diabetes Self Manag Care
January 2025
School of Nursing, Capital Medical University, Beijing, China.
Purpose: The purpose of the study was to explore the facilitators and barriers of health behaviors in patients with type 2 diabetes (T2D), providing a reference for the development of health behavior interventions programs.
Methods: A qualitative descriptive research design was adopted, and interviews were conducted with 25 patients with T2D. The interview guide was developed based on the health action process approach theory.
Sensors (Basel)
January 2025
Phillip M. Drayer Electrical Engineering Department, Lamar University, Beaumont, TX 77705, USA.
Automated ultrasonic testing (AUT) is a critical tool for infrastructure evaluation in industries such as oil and gas, and, while skilled operators manually analyze complex AUT data, artificial intelligence (AI)-based methods show promise for automating interpretation. However, improving the reliability and effectiveness of these methods remains a significant challenge. This study employs the Segment Anything Model (SAM), a vision foundation model, to design an AI-assisted tool for weld defect detection in real-world ultrasonic B-scan images.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Automation, Southeast University, Nanjing 210096, China.
Transferring knowledge learned from standard GelSight sensors to other visuotactile sensors is appealing for reducing data collection and annotation. However, such cross-sensor transfer is challenging due to the differences between sensors in internal light sources, imaging effects, and elastomer properties. By understanding the data collected from each type of visuotactile sensors as domains, we propose a few-sample-driven style-to-content unsupervised domain adaptation method to reduce cross-sensor domain gaps.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Department of Information and Electronic Engineering, International Hellenic University, 57001 Nea Moudania, Greece.
Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Department of Immunobiology and Environment Microbiology, Medical University of Gdansk, 80-210 Gdansk, Poland.
Obesity and its related diseases, such as type 2 diabetes (T2DM), cardiovascular disease (CVD), and metabolic fatty liver disease (MAFLD), require new diagnostic markers for earlier detection and intervention. The aim of this study is to demonstrate the potential of metabolomics as a tool for identifying biomarkers associated with obesity and its comorbidities in every age group. The presented systematic review makes an important contribution to the understanding of the potential of metabolomics in identifying biomarkers of obesity and its complications, especially considering the influence of branched-chain amino acids (BCAAs), amino acids (AAs) and adipokines on the development of T2DM, MAFLD, and CVD.
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