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Stakeholder Perceptions of Digital Nutrition Education Modules on Infant Feeding in Home Visiting Programs.
J Nutr Educ Behav
January 2025
Department of Health Education and Behavior, University of Florida, Gainesville, FL. Electronic address:
Objective: Evaluate the usability and acceptability of a digital infant feeding module for use in a home visiting program.
Methods: Home visitors (n = 11) and mothers (n = 10) completed a qualitative interview while viewing a digital nutrition education module on infant feeding. Quantitative data were collected using the mHealth App Usability Questionnaire.
Healthcare Workers' Attitudes Toward Older Adults' Nutrition: A Descriptive Cross-Sectional Study in Italian Nursing Homes.
Geriatrics (Basel)
January 2025
Department of Health Sciences, University of Genova, 16132 Genoa, Italy.
Malnutrition is a widespread issue among older people, significantly impacting health outcomes. Nutritional interventions can improve health, but their success often depends on the attitudes and knowledge of healthcare workers. This study assesses healthcare workers' attitudes toward older people's nutrition using the validated Italian version of the Staff Attitudes to Nutritional Nursing Geriatric care scale (SANN-G), focusing on staff in nursing homes in Northern Italy.
View Article and Find Full Text PDFRefractory Severe Anti-SRP Myopathy that Improved with Long-term Rehabilitation Therapy: A Case Report.
Prog Rehabil Med
January 2025
Division of Rehabilitation Medicine, Gunma University Hospital, Maebashi, Japan.
Background: Immune-mediated necrotizing myopathy (IMNM) is a type of autoimmune myositis. Anti-signal recognition particle (SRP) antibodies are highly specific to this disease.
Case: A 76-year-old woman presented with a 4-month history of acute progressive limb muscle weakness and dysphagia.
Multimodal machine learning for analysing multifactorial causes of disease-The case of childhood overweight and obesity in Mexico.
Front Public Health
January 2025
Karolinska Institutet, Department of Medicine Solna, Division of Clinical Epidemiology, Stockholm, Sweden.
Background: Mexico has one of the highest global incidences of paediatric overweight and obesity. Public health interventions have shown only moderate success, possibly from relying on knowledge extracted using limited types of statistical data analysis methods.
Purpose: To explore if multimodal machine learning can enhance identifying predictive features from obesogenic environments and investigating complex disease or social patterns, using the Mexican National Health and Nutrition Survey.
U.S. State-Level Containment Policies Not Associated with Food Insecurity Changes During the Early COVID-19 Pandemic: A Multi-level Analysis.
Public Health Nutr
January 2025
Johns Hopkins Center for a Livable Future, Johns Hopkins University, Baltimore, MD, 21205, USA.
Objective: To investigate the relationship between United States (US) containment measures during the COVID-19 pandemic and household food insecurity.
Design: To investigate these relationships, we developed a framework linking COVID-related containment policies with different domains of food security, then used multilevel random effects models to examine associations between state-level containment policies and household food security. Our framework depicts theorized linkages between stringency policies and five domains of food security (availability, physical access, economic access, acceptability in meeting preferences, and agency, which includes both self-efficacy and infrastructure).
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