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10.1177/08901171211017286 http://scihub22266oqcxt.onion/10.1177/08901171211017286 33980069!ä!33980069 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       Am+J+Health+Promot 2021 ; 35 (8): 1078-1083 Nephropedia Template TP {{tp|p=33980069|t=2021. Understanding the Effects of Individual and State-Level Factors on American Public Response to COVID-19 |pdf=|usr=}}{{33980069}} gab.com Text Understanding the Effects of Individual and State-Level Factors on American Public Response to COVID-19 JO: Am J Health Promot http://www.kidney.de/pget.php?&tw=1&pmid=33980069 #FOAvip PURPOSE: To examine multilevel predictors on American public response to COVID-19. DESIGN: Multilevel study. SETTING: A national survey was conducted by Qualtrics from August 24 to September 11, 2020. The state-level variables were constructed on data from multiple sources. SUBJECTS: 2,440 respondents 18 years and older from all 50 states and D.C. MEASURES: The outcome variable is the public response to COVID-19 measured by threat perception, behavioral adjustment, and policy support. The predictors include individual-level sociodemographic factors and state-level indicators about public health conditions, political context, and economic recovery. ANALYSIS: Multilevel structural equation modeling is used for statistical estimation. RESULTS: People from states with more COVID-19 cases (beta = 0.020, p < 0.1), mandatory face mask policies (beta = 0.069, p < 0.05), and liberal governments (beta = 0.002, p < 0.05) are more likely to respond while people from states whose economies have recovered closer to the pre-pandemic level are less likely to do so (beta = -0.005, p < 0.05). Regarding individual-level predictors, older people (beta = 0.005, p < 0.001) and people with better education (beta = 0.029, p < 0.01), leaning toward the Democrat Party (beta = 0.066, p < 0.001) and liberal political ideology (beta = 0.094, p < 0.001), and have stronger generalized trust (beta = 0.033, p < 0.001) are more likely to respond than their counterparts. CONCLUSION: Differences in the public response to the pandemic stem from variations in individual characteristics and contextual factors of states where people live. These findings contribute to the rapidly growing literature and have implications for public health policies. Twit Text FOAVip Understanding the Effects of Individual and State-Level Factors on American Public Response to COVID-19 ????Am J Health Promot http://www.kidney.de/pget.php?&tw=1&pmid=33980069 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33980069 #FOAvip English Wikipedia <ref>{{Cite pmid|33980069}}</ref> Understanding the Effects of Individual and State-Level Factors on American Public Response to COVID-19 #MMPMID33980069 Hao F; Shao W Am J Health Promot 2021[Nov]; 35 (8): 1078-1083 PMID33980069show ga PURPOSE: To examine multilevel predictors on American public response to COVID-19. DESIGN: Multilevel study. SETTING: A national survey was conducted by Qualtrics from August 24 to September 11, 2020. The state-level variables were constructed on data from multiple sources. SUBJECTS: 2,440 respondents 18 years and older from all 50 states and D.C. MEASURES: The outcome variable is the public response to COVID-19 measured by threat perception, behavioral adjustment, and policy support. The predictors include individual-level sociodemographic factors and state-level indicators about public health conditions, political context, and economic recovery. ANALYSIS: Multilevel structural equation modeling is used for statistical estimation. RESULTS: People from states with more COVID-19 cases (beta = 0.020, p < 0.1), mandatory face mask policies (beta = 0.069, p < 0.05), and liberal governments (beta = 0.002, p < 0.05) are more likely to respond while people from states whose economies have recovered closer to the pre-pandemic level are less likely to do so (beta = -0.005, p < 0.05). Regarding individual-level predictors, older people (beta = 0.005, p < 0.001) and people with better education (beta = 0.029, p < 0.01), leaning toward the Democrat Party (beta = 0.066, p < 0.001) and liberal political ideology (beta = 0.094, p < 0.001), and have stronger generalized trust (beta = 0.033, p < 0.001) are more likely to respond than their counterparts. CONCLUSION: Differences in the public response to the pandemic stem from variations in individual characteristics and contextual factors of states where people live. These findings contribute to the rapidly growing literature and have implications for public health policies. |*COVID-19[MESH] |Aged[MESH] |Humans[MESH] |Pandemics[MESH] |SARS-CoV-2[MESH] |Sociodemographic Factors[MESH] |Trust[MESH]Understanding the Effects of Individual and State-Level Factors on Ame(epmc).pdf DeepDyve Pubget Overpricing