Perceived-stigma level of COVID-19 patients in China in the early stage of the epidemic: A cross-sectional research

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Abstract

Objective To investigate the perceived-stigma level of COVID-19 patients in the early stage of the epidemic and analysed related factors and correlations that affected the stigma levels. Methods The COVID-19 patients were selected using the convenience sampling method. Perceived-stigma level was evaluated using the Social Impact Scale (SIS). Frequency was used to describe the general information and disease investigation status of COVID-19 patients; mean and standard deviation were used for describing stigma levels, Wilcoxon signed-ranks test (nonparametric test) was applied for pairwise comparison. Kruskal-Wallis nonparametric test for grade data, and Dwass-Steel-Critchlow-Fligner test for multiple comparative analysis. Multiple linear regression analysis was performed, and statistically significant indicators in single-factor analysis were included to investigate the independent factors of stigma. The p<0.05 was considered statistically significant. Results SIS score of the 122 COVID-19 patients averaged 57.37±9.99 points. There were statistically significant differences in perceived-stigma levels among patients of different ages (p = 0.008), occupation (p <0.001), marital status (p = 0.009), and disease severity (p = 0.020). Multivariate logistic regression analysis revealed that age was the main influencing factor of stigma (p<0.05). Conclusions The overall perceived-stigma level of COVID-19 patients in the early stage of the epidemic was moderate. Younger, unmarried, and severely ill patients had a higher level of perceived-stigma, with age being the main factor. More attention should be given to the young COVID-19 patients.

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APA

Lin, B., Zhong, G., Liang, Z., Huang, J., Wang, X., & Lin, Y. (2021). Perceived-stigma level of COVID-19 patients in China in the early stage of the epidemic: A cross-sectional research. PLoS ONE, 16(10 October). https://doi.org/10.1371/journal.pone.0258042

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