Food product labels can provide consumers with rich, specific, expert-certified product information. However, sources of label information differ. How do consumers then evaluate label trustworthiness of expert labels in comparison to other commonly used label types? We present results from a representative online survey (N = 10,000) of consumers in Japan, the USA, Germany, China and Thailand using professionally designed labels for four food types (milk, honey, oil, wine) and five different sources of food information (farmers, government/administration, producer associations, experts, and consumers). We tested label legibility through identification of the label information source and asked respondents to evaluate the trustworthiness of labels using a six-scale instrument ranging from overall label trust to purchase intent. Results show that label legibility varied between countries, with expert labels scoring lowest. Nevertheless, respondents correctly identifying all label information sources chose expert labels as the most or second-most trustworthy across all countries and food types, while consumer labels scored low. Demographic factors exhibited weak influence. Results suggest expert labels might play an important role as trusted sources of information in an increasingly complex global food system. Finally, we consider the implications of the study for a potential institutionalization of expert labels based on the Japanese context.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.fct.2020.111170 | DOI Listing |
Background: Recent advancements in automatic language and speech analysis, coupled with machine learning (ML) methods, showcase the effectiveness of digital biomarkers in non-invasively detecting subtle changes in cognitive status. While successfully distinguishing between Alzheimer's Disease (AD) and Normal Control (NC) individuals, classifying Mild Cognitive Impairment (MCI) proves to be a more challenging task. MCI can progress to AD or result from various factors, including affective disorders, necessitating multiple expert examinations for accurate detection.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
Background: Cerebral arterial dilatation, signifying outward vascular remodeling, is linked to a higher risk of Alzheimer's disease and a higher burden of white matter hyperintensities (WMH). Arterial dilatation may disrupt cerebral hemodynamics and lead to delayed blood arrival to the brain, which is itself linked to an increased burden of WMH. We examined if arterial dilatation was associated with blood arrival timing and if blood arrival timing mediated the effect of arterial dilatation on WMH burden.
View Article and Find Full Text PDFBiomed Eng Lett
January 2025
Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Unlabelled: A weight-bearing lateral radiograph (WBLR) of the foot is a gold standard for diagnosing adult-acquired flatfoot deformity. However, it is difficult to measure the major axis of bones in WBLR without using auxiliary lines. Herein, we develop semantic segmentation with a deep learning model (DLm) on the WBLR of the foot for enhanced diagnosis of pes planus and pes cavus.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Simulation and Graphics, Faculty of Computer Science, University of Magdeburg, Universitätsplatz 2 39106, Magdeburg, Germany; Department of Computational Medicine, Ilmenau University of Technology, Germany.
Purpose: This paper presents a deep learning-based multi-label segmentation network that extracts a total of three separate adipose tissues and five different muscle tissues in CT slices of the third lumbar vertebra and additionally improves the segmentation of the intermuscular fat.
Method: Based on a self-created data set of 130 patients, an extended Unet structure was trained and evaluated with the help of Dice score, IoU and Pixel Accuracy. In addition, the interobserver variability for the decision between ground truth and post-processed segmentation was calculated to illustrate the relevance in everyday clinical practice.
Neuroinformatics
January 2025
Consejo Nacional de Investigaciones Científicas y Técnicas, CONICET, Buenos Aires, Argentina.
Sulci are a fundamental part of brain morphology, closely linked to brain function, cognition, and behavior. Tertiary sulci, characterized as the shallowest and smallest subtype, pose a challenging task for detection. The diagonal sulcus (ds), located in a crucial area in language processing, has a prevalence between 50% and 60%.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!