98%
921
2 minutes
20
Background: Slowing the spread of the novel coronavirus (COVID-19) requires behavioral changes such as physical distancing (e.g., staying a 6-foot distance from others, avoiding mass gatherings, reducing houseguests), wearing masks, reducing trips to nonessential business establishments, and increasing hand washing. Like other health behaviors, COVID-19 related behaviors may be related to risk representations. Risk representations are the cognitive responses a person holds about illness risk such as, identity (i.e., label/characteristics of risk), cause (i.e., factors causing condition), timeline (i.e., onset/duration of risk), consequences (i.e., intrapersonal/interpersonal outcomes), behavioral efficacy (i.e., if and how the condition can be controlled/treated), and illness risk coherence (i.e., extent to which representations, behaviors, and beliefs are congruent). The current study applies the Common-Sense Model of Self-Regulation (CSM-SR) to evaluate how risk representations may relate to COVID-19 protective and risk behaviors.
Methods: Participants include 400 workers from Amazon's Mechanical Turk aged ≥ 18 years and US residents. Participants completed an online survey measuring risk representations (B-IPQ) and COVID-19 related behaviors, specifically, physical distancing, hand washing, and shopping frequency.
Results: Risk coherence, consequences, timeline, emotional representation, and behavioral efficacy were related to risk and protective behaviors.
Conclusions: Risk representations vary in their relationship to COVID-19 risk and protective behaviors. Implications include the importance of coherent, targeted, consistent health communication, and effective health policy in mitigating the spread of COVID-19.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032317 | PMC |
http://dx.doi.org/10.1007/s12529-021-09970-4 | DOI Listing |
Cien Saude Colet
August 2025
Instituto de Medicina Social Hesio Cordeiro, Universidade do Estado do Rio de Janeiro. R. São Francisco Xavier 524, Maracanã. 20550-900 Rio de Janeiro RJ Brasil.
In this article an analysis of the preventive campaigns against cervical cancer (CC) and human papillomavirus (HPV) vaccination developed by the National Cancer Institute (INCA) of the Ministry of Health was conducted, in addition to some campaigns produced by non-governmental organizations and private institutions, from 2014 to 2020. From a socio-anthropological point of view, the objective was to understand how these health technologies trigger and produce gender representations. Seven categories of analysis were developed ("Generationality of care", "Schooling", "Childhood and Youth", "Gamification", "Health risk", "Men's health" and "Neutrality") that permitted discussion of the themes that emerged in graphic pieces.
View Article and Find Full Text PDFBMC Musculoskelet Disord
September 2025
Department of Clinical Sciences at Danderyds Hospital, Department of Orthopedic Surgery, Karolinska Institutet, Stockholm, 182 88, Sweden.
Background: This study evaluates the accuracy of an Artificial Intelligence (AI) system, specifically a convolutional neural network (CNN), in classifying elbow fractures using the detailed 2018 AO/OTA fracture classification system.
Methods: A retrospective analysis of 5,367 radiograph exams visualizing the elbow from adult patients (2002-2016) was conducted using a deep neural network. Radiographs were manually categorized according to the 2018 AO/OTA system by orthopedic surgeons.
J Med Internet Res
September 2025
Artificial Intelligence and Mathematical Modeling Lab, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
Background: The H5N1 avian influenza A virus represents a serious threat to both animal and human health, with the potential to escalate into a global pandemic. Effective monitoring of social media during H5N1 avian influenza outbreaks could potentially offer critical insights to guide public health strategies. Social media platforms like Reddit, with their diverse and region-specific communities, provide a rich source of data that can reveal collective attitudes, concerns, and behavioral trends in real time.
View Article and Find Full Text PDF