In laboratory studies, exposure to social norm messages conveying the typical eating behaviour of others has influenced participants' own consumption of food. Given the widespread use of social media, it is plausible that we are implicitly exposed to norms in our wider social circles, and that these influence our eating behaviour, and potentially, Body Mass Index (BMI). This study examined whether four perceived norms (perceived descriptive, injunctive, liking and frequency norms) about Facebook users' eating habits and preferences predicted participants' own food consumption and BMI. In a cross-sectional survey, men and women university students (n = 369; mean age = 22.1 years; mean BMI = 23.7) were asked to report their perceptions of Facebook users' consumption of, and preferences for, fruit, vegetables, energy-dense snacks and sugar sweetened beverages (SSBs), their own consumption of and preferences for these foods, and their BMI. Multiple linear regression revealed that perceived descriptive norms and perceived frequency norms about Facebook users' fruit and vegetable consumption were significant positive predictors of participants' own fruit and vegetable consumption (both ps < .01). Conversely, perceived injunctive norms about Facebook users' energy-dense snack and SSB consumption were significant positive predictors of participants' own snack and SSB consumption (both ps < .05). However, perceived norms did not significantly predict BMI (all ps > .05). These findings suggest that perceived norms concerning actual consumption (descriptive and frequency) and norms related to approval (injunctive) may guide consumption of low and high energy-dense foods and beverages differently. Further work is required to establish whether these perceived norms also affect dietary behaviour over time.
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http://dx.doi.org/10.1016/j.appet.2020.104611 | DOI Listing |
Health Expect
February 2025
Faculty of Communication, Culture and Society, Università della Svizzera italiana, Lugano, Switzerland.
Objectives: Grounded in the Health Empowerment Model, which posits that health literacy and patient empowerment are intertwined yet distinct constructs, this study investigates how the interplay of these factors influences attitudes toward seeking professional psychological help in members of online communities for mental health (OCMHs). This while acknowledging the multidimensionality of patient empowerment, encompassing meaningfulness, competence, self-determination, and impact.
Design And Methods: A cluster analysis of data gathered from 269 members of Italian-speaking OCMHs on Facebook has been performed.
PLoS One
January 2025
Department of Communication, University of Delaware, Newark, DE, United States of America.
This research expanded on prior work exploring the relationship between social media use, social support, and mental health by including the usage of social virtual reality (VR). In Study 1 (undergraduate students; n = 448) we examined divergent relationships between problematic social media use (e.g.
View Article and Find Full Text PDFFront Psychol
December 2024
Faculty of Sociology and Communication, Transilvania University of Brasov, Brașov, Romania.
Introduction: With the significant increase in the number of social media users, the degree of cyberbullying has also increased in a directly proportional manner. Cyberbullying manifests itself in the commission of psychological abuses, teenagers being the most vulnerable.
Methods: The purpose of our paper was to analyze how the phenomenon of cyberbullying manifests in terms of frequency on social media platforms, while taking into account factors such as gender, and elements related to the behavior/reactions of witnesses and victims.
Front Artif Intell
December 2024
Decision Support Systems Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, Athens, Greece.
Social media platforms, including X, Facebook, and Instagram, host millions of daily users, giving rise to bots automated programs disseminating misinformation and ideologies with tangible real-world consequences. While bot detection in platform X has been the area of many deep learning models with adequate results, most approaches neglect the graph structure of social media relationships and often rely on hand-engineered architectures. Our work introduces the implementation of a Neural Architecture Search (NAS) technique, namely Deep and Flexible Graph Neural Architecture Search (DFG-NAS), tailored to Relational Graph Convolutional Neural Networks (RGCNs) in the task of bot detection in platform X.
View Article and Find Full Text PDFJMIR Form Res
January 2025
Faculty of Dentistry, Department of Community Dentistry, Chulalongkorn University, 34 Henri Dunant Road, Pathumwan, Bangkok, 10330, Thailand, 66 02-2188543.
Background: As digitalization continues to advance globally, the health care sector, including dental practice, increasingly recognizes social media as a vital tool for health care promotion, patient recruitment, marketing, and communication strategies.
Objective: This study aimed to investigate the use of social media and assess its impact on enhancing dental care and practice among dental professionals in the Philippines.
Methods: A cross-sectional survey was conducted among dental practitioners in the Philippines.
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