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10.1093/her/cyaa030 http://scihub22266oqcxt.onion/10.1093/her/cyaa030 33090215!7665482!33090215     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 253.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Health+Educ+Res 2020 ; 35 (5): 490-503 Nephropedia Template TP {{tp|p=33090215|t=2020. Modelling the antecedent factors that affect online fake news sharing on COVID-19: the moderating role of fake news knowledge |pdf=|usr=}}{{33090215}} gab.com Text Modelling the antecedent factors that affect online fake news sharing on COVID-19: the moderating role of fake news knowledge JO: Health Educ Res http://www.kidney.de/pget.php?&tw=1&pmid=33090215 #FOAvip We proposed a conceptual model combining three theories: uses and gratification theory, social networking sites (SNS) dependency theory and social impact theory to understand the factors that predict fake news sharing related to COVID-19. We also tested the moderating role of fake news knowledge in reducing the tendency to share fake news. Data were drawn from social media users (n = 650) in Nigeria, and partial least squares was used to analyse the data. Our results suggest that tie strength was the strongest predictor of fake news sharing related to COVID-19 pandemic. We also found perceived herd, SNS dependency, information-seeking and parasocial interaction to be significant predictors of fake news sharing. The effect of status-seeking on fake news sharing, however, was not significant. Our results also established that fake news knowledge significantly moderated the effect of perceived herd, SNS dependency, information-seeking, parasocial interaction on fake news sharing related to COVID-19. However, tie strength and status-seeking effects were not moderated. Twit Text FOAVip Modelling the antecedent factors that affect online fake news sharing on COVID-19: the moderating role of fake news knowledge ????Health Educ Res http://www.kidney.de/pget.php?&tw=1&pmid=33090215 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33090215 #FOAvip English Wikipedia <ref>{{Cite pmid|33090215}}</ref> Modelling the antecedent factors that affect online fake news sharing on COVID-19: the moderating role of fake news knowledge #MMPMID33090215 Apuke OD; Omar B Health Educ Res 2020[Oct]; 35 (5): 490-503 PMID33090215show ga We proposed a conceptual model combining three theories: uses and gratification theory, social networking sites (SNS) dependency theory and social impact theory to understand the factors that predict fake news sharing related to COVID-19. We also tested the moderating role of fake news knowledge in reducing the tendency to share fake news. Data were drawn from social media users (n = 650) in Nigeria, and partial least squares was used to analyse the data. Our results suggest that tie strength was the strongest predictor of fake news sharing related to COVID-19 pandemic. We also found perceived herd, SNS dependency, information-seeking and parasocial interaction to be significant predictors of fake news sharing. The effect of status-seeking on fake news sharing, however, was not significant. Our results also established that fake news knowledge significantly moderated the effect of perceived herd, SNS dependency, information-seeking, parasocial interaction on fake news sharing related to COVID-19. However, tie strength and status-seeking effects were not moderated. |*Betacoronavirus[MESH] |*Coronavirus Infections[MESH] |*Pandemics[MESH] |*Pneumonia, Viral[MESH] |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |COVID-19[MESH] |Deception[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Nigeria[MESH] |Online Systems[MESH] |SARS-CoV-2[MESH] |Social Media[MESH]Modelling the antecedent factors that affect online fake news sharing (epmc).pdf DeepDyve Pubget Overpricing