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10.1002/hec.4143 http://scihub22266oqcxt.onion/10.1002/hec.4143 32844495!7461444!32844495     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\32844495.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Health+Econ 2020 ; 29 (11): 1482-1494 Nephropedia Template TP {{tp|p=32844495|t=2020. The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences |pdf=|usr=}}{{32844495}} gab.com Text The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences JO: Health Econ http://www.kidney.de/pget.php?&tw=1&pmid=32844495 #FOAvip Mass media routinely present data on coronavirus disease 2019 (COVID-19) diffusion with graphs that use either a log scale or a linear scale. We show that the choice of the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID-19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predictions on its evolution, and have different policy preferences than when they are exposed to a linear scale. Consequently, merely changing the scale the data is presented on can alter public policy preferences and the level of worry about the pandemic, despite the fact that people are routinely exposed to COVID-19 related information. Providing the public with information in ways they understand better can help improving the response to COVID-19, thus, mass media and policymakers communicating to the general public should always describe the evolution of the pandemic using a graph on a linear scale, at least as a default option. Our results suggest that framing matters when communicating to the public. Twit Text FOAVip The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences ????Health Econ http://www.kidney.de/pget.php?&tw=1&pmid=32844495 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32844495 #FOAvip English Wikipedia <ref>{{Cite pmid|32844495}}</ref> The scale of COVID-19 graphs affects understanding, attitudes, and policy preferences #MMPMID32844495 Romano A; Sotis C; Dominioni G; Guidi S Health Econ 2020[Nov]; 29 (11): 1482-1494 PMID32844495show ga Mass media routinely present data on coronavirus disease 2019 (COVID-19) diffusion with graphs that use either a log scale or a linear scale. We show that the choice of the scale adopted on these graphs has important consequences on how people understand and react to the information conveyed. In particular, we find that when we show the number of COVID-19 related deaths on a logarithmic scale, people have a less accurate understanding of how the pandemic has developed, make less accurate predictions on its evolution, and have different policy preferences than when they are exposed to a linear scale. Consequently, merely changing the scale the data is presented on can alter public policy preferences and the level of worry about the pandemic, despite the fact that people are routinely exposed to COVID-19 related information. Providing the public with information in ways they understand better can help improving the response to COVID-19, thus, mass media and policymakers communicating to the general public should always describe the evolution of the pandemic using a graph on a linear scale, at least as a default option. Our results suggest that framing matters when communicating to the public. |*Health Knowledge, Attitudes, Practice[MESH] |*Mass Media[MESH] |Audiovisual Aids/*standards[MESH] |COVID-19/*epidemiology[MESH] |Double-Blind Method[MESH] |Humans[MESH] |Pandemics[MESH] |Policy[MESH] |SARS-CoV-2[MESH]The scale of COVID-19 graphs affects understanding, attitudes, and pol(epmc).pdf DeepDyve Pubget Overpricing