BACKGROUND: With so much content on social media platforms about COVID-19, determining which information is reliable can be a daunting task. Hence, this study is aimed to analyze various posts with regard to COVID-19 on various social media platforms for their reliability and also examined various factors that influence information reliability. MATERIALS AND METHODS: A cross-sectional study was conducted, with 934 samples related to coronavirus pandemic published on Twitter, Instagram, and Facebook using systematic random sampling. We adopted the criteria given by Paul Bradshaw and modified to assess the characteristics of the samples. Training and calibration of the investigators were carried out for 3 consecutive days before beginning the study. The data were analyzed using the Chi-square test and multinomial logistic regression to estimate the odds ratios. RESULTS: Out of 934 samples studied, only 570 (61%) were found to be reliable of which 243 (42.6%) were from Twitter, 117 (20.6%) from Instagram, and 210 (36.8%) from Facebook. We found that the reliability of the information on social media platforms is significantly influenced by network (odds: 1.32; 95% confidence interval [CI]: 1.16–1.52; P = 0.036), content (odds: 1.83; 95% CI: 1.69–1.92; P = 0.009), contextual update (odds: 1.41; 95% CI: 1.24–1.53) and age of the account (odds: 1.92; 95% CI: 1.64–2.09; P = 0.002). CONCLUSION: Our study shows that the reliability of the social media posts significantly depends on the network, contextual update, and age of the account. Hence, cross verifying the information from a reliable source is the need of the hour to prevent panic and mental distress.
BACKGROUND: Health-care workers (HCWs) are highly vulnerable to depression during an epidemic outbreak. Protecting the mental well-being of HCWs is a priority while battling with COVID-19. However, documentation on COVID-19-related depression among HCWs is scarce due to the limited availability of measuring scales. Hence, this study was purposed to develop a scale to measure depression relating to COVID-19 and evaluate its psychometric properties among HCWs. MATERIALS AND METHODS: A validation study was carried out among 320 HCWs including physicians of various medical specialties, dental specialists, and nurses in the year 2020. Exploratory factor analysis using Promax rotation with Kaiser normalization for the determination of factor structure was employed in data analysis using SPSS version 16 software. RESULTS: COVID-19 Depression Scale for HCWs (CDS-HW) demonstrated a two-component structure identified as “work-related anxiety” and “psychological distress.” The mean CDS-HW score of the study participants was observed to be 23.67 ± 2.82, and the scale demonstrated good internal consistency reliability (Cronbach's alpha: 0.741). CONCLUSION: CDS-HW is a rapidly administrable, valid, and reliable tool that can be used to measure COVID-19-related depression among HCWs.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.