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10.12659/MSM.925877 http://scihub22266oqcxt.onion/10.12659/MSM.925877 33040074!7559373!33040074     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 249.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Med+Sci+Monit 2020 ; 26 (ä): e925877 Nephropedia Template TP {{tp|p=33040074|t=2020. Factors Affecting Infection Control Behaviors to Prevent COVID-19: An Online Survey of Nursing Students in Anhui, China in March and April 2020 |pdf=|usr=}}{{33040074}} gab.com Text Factors Affecting Infection Control Behaviors to Prevent COVID-19: An Online Survey of Nursing Students in Anhui, China in March and April 2020 JO: Med Sci Monit http://www.kidney.de/pget.php?&tw=1&pmid=33040074 #FOAvip BACKGROUND The pandemic of coronavirus disease 2019 (COVID-19) has become a major public health challenge all over the world. People's knowledge, attitudes, and preventive behaviors about diseases affect the degree of adherence to control measures. This study aimed to survey the affecting factors of COVID-19 prevention behavior among nursing students in China. MATERIAL AND METHODS Six-hundred thirteen nursing students in Anhui, China participated in an online survey from March 30 to April 5, 2020. The survey collected demographic information, electronic health (eHealth) literacy, COVID-19-related knowledge, attitudes, and prevention behavior data using descriptive analysis and multinomial logistic regression to analyze the data. RESULTS The mean age of study participants was 20.88 years, of which 31.8% were male (n=613). Television (84.9%) and WeChat (79.6%) were the major sources of their information. Nursing students had good knowledge (14.68+/-2.83), had positive attitudes (4.03+/-0.59), had good practices (3.92+/-0.65), and had basic eHealth literacy (30.45+/-6.90). Nursing students with higher eHealth literacy (odds ratio [OR]=0.89, P<0.01), good knowledge (OR=0.89, P<0.01), and positive attitudes (OR=0.24, P<0.01) took more preventive behaviors. Students living in the countryside (OR=0.09, P<0.01) and of a young age (OR=1.51, P<0.05) seldom took preventive actions. Men, compared with women, were less likely to take preventive measures. (OR=1.44, P<0.05). CONCLUSIONS Good eHealth literacy, good knowledge, and a positive attitude were the most important variables that affected the prevention behavior against COVID-19. Targeted health education should be conducted for male students and students living in the countryside by providing reliable and effective online sources. Twit Text FOAVip Factors Affecting Infection Control Behaviors to Prevent COVID-19: An Online Survey of Nursing Students in Anhui, China in March and April 2020 ????Med Sci Monit http://www.kidney.de/pget.php?&tw=1&pmid=33040074 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33040074 #FOAvip English Wikipedia <ref>{{Cite pmid|33040074}}</ref> Factors Affecting Infection Control Behaviors to Prevent COVID-19: An Online Survey of Nursing Students in Anhui, China in March and April 2020 #MMPMID33040074 Yuan T; Liu H; Li XD; Liu HR Med Sci Monit 2020[Oct]; 26 (ä): e925877 PMID33040074show ga BACKGROUND The pandemic of coronavirus disease 2019 (COVID-19) has become a major public health challenge all over the world. People's knowledge, attitudes, and preventive behaviors about diseases affect the degree of adherence to control measures. This study aimed to survey the affecting factors of COVID-19 prevention behavior among nursing students in China. MATERIAL AND METHODS Six-hundred thirteen nursing students in Anhui, China participated in an online survey from March 30 to April 5, 2020. The survey collected demographic information, electronic health (eHealth) literacy, COVID-19-related knowledge, attitudes, and prevention behavior data using descriptive analysis and multinomial logistic regression to analyze the data. RESULTS The mean age of study participants was 20.88 years, of which 31.8% were male (n=613). Television (84.9%) and WeChat (79.6%) were the major sources of their information. Nursing students had good knowledge (14.68+/-2.83), had positive attitudes (4.03+/-0.59), had good practices (3.92+/-0.65), and had basic eHealth literacy (30.45+/-6.90). Nursing students with higher eHealth literacy (odds ratio [OR]=0.89, P<0.01), good knowledge (OR=0.89, P<0.01), and positive attitudes (OR=0.24, P<0.01) took more preventive behaviors. Students living in the countryside (OR=0.09, P<0.01) and of a young age (OR=1.51, P<0.05) seldom took preventive actions. Men, compared with women, were less likely to take preventive measures. (OR=1.44, P<0.05). CONCLUSIONS Good eHealth literacy, good knowledge, and a positive attitude were the most important variables that affected the prevention behavior against COVID-19. Targeted health education should be conducted for male students and students living in the countryside by providing reliable and effective online sources. |*Internet[MESH] |*Students, Nursing[MESH] |*Surveys and Questionnaires[MESH] |Betacoronavirus/*physiology[MESH] |COVID-19[MESH] |China[MESH] |Coronavirus Infections/*epidemiology/*prevention & control[MESH] |Female[MESH] |Health Behavior[MESH] |Health Knowledge, Attitudes, Practice[MESH] |Humans[MESH] |Logistic Models[MESH] |Male[MESH] |Pandemics/*prevention & control[MESH] |Pneumonia, Viral/*epidemiology/*prevention & control[MESH] |SARS-CoV-2[MESH] |Statistics, Nonparametric[MESH]Factors Affecting Infection Control Behaviors to Prevent COVID-19: An (epmc).pdf DeepDyve Pubget Overpricing