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10.1016/j.sapharm.2020.06.004 http://scihub22266oqcxt.onion/10.1016/j.sapharm.2020.06.004 33317765!7836537!33317765     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Res+Social+Adm+Pharm 2021 ; 17 (1): 1859-1866 Nephropedia Template TP {{tp|p=33317765|t=2021. Optimistic bias and preventive behavioral engagement in the context of COVID-19 |pdf=|usr=}}{{33317765}} gab.com Text Optimistic bias and preventive behavioral engagement in the context of COVID-19 JO: Res Social Adm Pharm http://www.kidney.de/pget.php?&tw=1&pmid=33317765 #FOAvip BACKGROUND: The coronavirus (COVID-19) pandemic presents a global crisis. To remain safe, individuals must take preventive measures. Health behavior theories suggest that perceived risk is a key determinant of engagement in preventive behavior. People often underestimate their risk for disease compared with similar others', a phenomenon known as optimistic bias (OB). OBJECTIVE: This study aimed to explore how OB affected individuals' engagement in COVID-19 preventive behavior/intentions. Based on health behavior theories, this study considered risk perception and risk response as mediators of the relationship between OB and individuals' preventive health behaviors and intentions. METHODS: This study used a cross-sectional survey design. Online survey platforms were used to recruit U.S. adults. A total of 293 valid responses were included in the analyses. Multivariate regression analyses were conducted to determine the relationship of OB to the respondents' health information seeking intention and related behavioral outcomes. RESULTS: Results from the first regression model showed that OB was negatively related to risk perception. In other words, optimistically biased respondents perceived their risk of COVID-19 to be low. The second model demonstrated that perceived risk was related positively to affective responses to risk (e.g., worry and fear). That is, the lower their perceived risk of COVID-19, the less likely respondents were to feel anxiety and fear about this disease. Models 3 and 4 revealed positive relationships between risk response and respondents' intentions and behaviors. Finally, the results supported a fully mediated pathway: OB --> risk perception --> risk response --> information seeking intention and behavioral outcomes. CONCLUSIONS: The study findings suggest that by decreasing their perceived risk and subsequent responses, optimistic bias can undermine individuals' motivation to take precautions. To reduce this bias, the actual risk of COVID-19 should be reinforced. Twit Text FOAVip Optimistic bias and preventive behavioral engagement in the context of COVID-19 ????Res Social Adm Pharm http://www.kidney.de/pget.php?&tw=1&pmid=33317765 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33317765 #FOAvip English Wikipedia <ref>{{Cite pmid|33317765}}</ref> Optimistic bias and preventive behavioral engagement in the context of COVID-19 #MMPMID33317765 Park T; Ju I; Ohs JE; Hinsley A Res Social Adm Pharm 2021[Jan]; 17 (1): 1859-1866 PMID33317765show ga BACKGROUND: The coronavirus (COVID-19) pandemic presents a global crisis. To remain safe, individuals must take preventive measures. Health behavior theories suggest that perceived risk is a key determinant of engagement in preventive behavior. People often underestimate their risk for disease compared with similar others', a phenomenon known as optimistic bias (OB). OBJECTIVE: This study aimed to explore how OB affected individuals' engagement in COVID-19 preventive behavior/intentions. Based on health behavior theories, this study considered risk perception and risk response as mediators of the relationship between OB and individuals' preventive health behaviors and intentions. METHODS: This study used a cross-sectional survey design. Online survey platforms were used to recruit U.S. adults. A total of 293 valid responses were included in the analyses. Multivariate regression analyses were conducted to determine the relationship of OB to the respondents' health information seeking intention and related behavioral outcomes. RESULTS: Results from the first regression model showed that OB was negatively related to risk perception. In other words, optimistically biased respondents perceived their risk of COVID-19 to be low. The second model demonstrated that perceived risk was related positively to affective responses to risk (e.g., worry and fear). That is, the lower their perceived risk of COVID-19, the less likely respondents were to feel anxiety and fear about this disease. Models 3 and 4 revealed positive relationships between risk response and respondents' intentions and behaviors. Finally, the results supported a fully mediated pathway: OB --> risk perception --> risk response --> information seeking intention and behavioral outcomes. CONCLUSIONS: The study findings suggest that by decreasing their perceived risk and subsequent responses, optimistic bias can undermine individuals' motivation to take precautions. To reduce this bias, the actual risk of COVID-19 should be reinforced. |*Bias[MESH] |*Health Behavior[MESH] |Adolescent[MESH] |Adult[MESH] |Aged[MESH] |COVID-19/epidemiology/prevention & control/*psychology[MESH] |Cross-Sectional Studies[MESH] |Female[MESH] |Humans[MESH] |Male[MESH] |Middle Aged[MESH] |Optimism/*psychology[MESH] |Risk Assessment[MESH] |Surveys and Questionnaires[MESH]Optimistic bias and preventive behavioral engagement in the context of(epmc).pdf DeepDyve Pubget Overpricing