98%
921
2 minutes
20
People's accessibility to nutrition information is now near universal due to internet access, and the information available varies in its scientific integrity and provider expertise. Understanding the information-seeking behaviours of the public is paramount for providing sound nutrition advice. This research aims to identify who learners in a nutrition-focused Massive Open Online Course (MOOC) turn to for nutrition information, and how they discuss the information they find. A multi-methods approach explored the information-seeking and sharing behaviours of MOOC learners. Summative content analysis, and an exploratory, inductive, qualitative approach analysed learners' posts in MOOC discussion forums. From 476 posts, the majority (58.6%) of nutrition information sources learners reported were from websites. Providers of nutrition information were most commonly (34%) tertiary educated individuals lacking identifiable nutrition qualifications; 19% had no identifiable author information, and only 5% were from nutrition professionals. Qualitative themes identified that learners used nutrition information to learn, teach and share nutrition information. Consistent with connectivist learning theory, learners contributed their own sources of nutrition information to discussions, using their own knowledge networks to teach and share information. Nutrition professionals need to understand the principles of connectivist learning behaviours in order to effectively engage the public.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146568 | PMC |
http://dx.doi.org/10.3390/nu12030750 | DOI Listing |
JMIR Res Protoc
September 2025
Department of Food Science and Technology, Kaunas University of Technology, Kaunas, Lithuania.
Background: Fermented foods vary significantly by food substrate and regional consumption patterns. Although they are consumed worldwide, their intake and potential health benefits remain understudied. Europe, in particular, lacks specific consumption recommendations for most fermented foods.
View Article and Find Full Text PDFJ Anim Sci
September 2025
Centre for Veterinary Systems Transformation and Sustainability, Clinical Department for Farm Animals and Food System Science, University of Veterinary Medicine Vienna, Vienna 1210, Austria.
It is helpful for diagnostic purposes to improve our current knowledge of gut development and serum biochemistry in young piglets. This study investigated serum biochemistry, and gut site-specific patterns of short-chain fatty acids (SCFA) and expression of genes related to barrier function, innate immune response, antioxidative status and sensing of fatty and bile acids in suckling and newly weaned piglets. The experiment consisted of two replicate batches with 10 litters each.
View Article and Find Full Text PDFJAMA Pediatr
September 2025
Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill.
Nutr Health
September 2025
Independent researcher, Rome, Italy.
Artificial intelligence (AI) is increasingly applied in nutrition science to support clinical decision-making, prevent diet-related diseases such as obesity and type 2 diabetes, and improve nutrition care in both preventive and therapeutic settings. By analyzing diverse datasets, AI systems can support highly individualized nutritional guidance. We focus on machine learning applications and image recognition tools for dietary assessment and meal planning, highlighting their potential to enhance patient engagement and adherence through mobile apps and real-time feedback.
View Article and Find Full Text PDFEchocardiography
September 2025
Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Objectives: To explore the relationships between cardiac parameters and body composition indices, identifying predictors of subclinical cardiac systolic dysfunction.
Methods: Using anthropometric and serological parameters, echocardiography, and body composition analysis, this study evaluated metabolic profiles, cardiac remodeling patterns, and body composition characteristics in young adult obese patients, while quantifying the correlations between cardiac parameters and body composition indices. Subclinical left ventricular systolic dysfunction was defined as global longitudinal strain (GLS) < 18%.