Current concerns regarding the health and environmental consequences associated with excessive meat consumption have underscored the importance of guiding consumers towards more sustainable diets. Given this perspective, this study seeks to evaluate the effectiveness of tailored informative messages in shaping consumer behaviour, particularly within the framework of replacing meat with mushroom-based alternatives. Additionally, it explores the factors influencing informative message effectiveness. An experimental online survey was conducted on a sample of 951 Italian consumers. Specifically, the sample was divided into three groups, of which 309 individuals formed the control group, 311 participants received informative messages on the health risks associated with red meat consumption, and 331 participants received informative messages emphasizing the environmental damages linked to red meat consumption. In both treatments, there was support for mushroom-based alternatives. Analyses included subgroup assessments, tests to verify treatments effectiveness, along with OLS regression to pinpoint variables influencing message effectiveness. The results underscore a fair positive impact of the two informative messages (mean scores: 8.75 for health message; 7.01 for environmental message). Noteworthy psychosocial variables, including lifestyle patterns, nutritional perceptions, and ecological attitudes, emerged as determinants in shaping consumers' food choices. While health-related messages exhibit marked influence, the nuanced landscape of diverse drivers and barriers necessitates judicious communication strategies. These insights bear significance for policymakers, health professionals, and marketers, offering guidance for interventions that effectively influence consumer behaviour toward more sustainable and healthier food practices.
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http://dx.doi.org/10.1016/j.appet.2024.107405 | DOI Listing |
Alzheimers Dement
December 2024
University of Southern California, San Diego, USA.
Background: Recruitment of demographically diverse participants into Alzheimer's disease (AD) clinical trials, encompassing both screening and randomization, remains a consistent and persistent challenge contributing to underrepresentation of certain groups. Despite the exciting prospects of identifying therapeutic interventions for biomarker-eligible, cognitively unimpaired individuals, these studies grapple with the inherent complexities of AD trials coupled with intricate and time-consuming screening processes. Addressing this the issue of underrepresentation necessitates concerted and intentional efforts that prioritize inclusivity and equitable access to enroll adults meeting study criteria, reflecting the demographic and social diversity of North America.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
Background: The prohibitive costs of drug development for Alzheimer's Disease (AD) emphasize the need for alternative in silico drug repositioning strategies. Graph learning algorithms, capable of learning intrinsic features from complex network structures, can leverage existing databases of biological interactions to improve predictions in drug efficacy. We developed a novel machine learning framework, the PreSiBOGNN, that integrates muti-modal information to predict cognitive improvement at the subject level for precision medicine in AD.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
National Ageing Research Institute, Melbourne, VIC, Australia.
Background: We have co-produced with carers of people with dementia (hereafter carers) a culturally tailored iSupport Virtual Assistant (VA), namely e-DiVA, to support English-, Bahasa- and Vietnamese-speaking carers in Australia, Indonesia, New Zealand and Vietnam. The presented research reports qualitative findings from the e-DiVA user-testing study.
Method: Family carers and healthcare professionals working in the field of dementia care were given the e-DiVA to use on their smartphone or handheld device for 1-2 weeks.
Alzheimers Dement
December 2024
University of Toronto, Toronto, ON, Canada.
Background: Since October, 2022 the Driving and Dementia Roadmap (DDR) (www.drivinganddementia.ca) - an online resource to support people with dementia (PWD), family/friend carers (FCs) and healthcare providers (HCPs) as they navigate the challenges of driving cessation - has been accessed by over 34,000 users.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
Background: Alzheimer's disease (AD) is a significant health concern affecting at least 10% of individuals aged 65 and older, with heightened risk in Black and Hispanic/Latino populations. Despite this prevalence, our analysis of University of California Los Angeles (UCLA) electronic health records (EHR) indicates that only 4% of patients aged 65 or older receive an AD diagnosis, with underdiagnosis more prevalent among Black and Hispanic/Latino patients compared to their white counterparts. To address this issue, we propose implementing a concise dementia screening tool (DST) in real-world clinical settings.
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