The increasing access to online health information and the use of this information for self-medication or self-diagnosis can foster a discounting of the epistemic authority of experts, as well as an over-reliance on laypersons' expertise. However, the emerging cognitive bias-the overconfidence effect-is poorly investigated in the sociological field. This study offers a novel contribution to the role of overconfidence bias in online health information-seeking behavior and self-care practices. A cross-sectional study was conducted through an online survey on a sample of 783 Italian university students. Univariate linear regression and stepwise multiple linear regression analysis were performed on the collected data. The findings suggest that overconfidence and self-care practices are predictors of health information seeking online. The multiple linear regression model revealed that the association between overconfidence bias and online health information seeking is mediated by self-care behaviors. Therefore, the overconfidence effect influences health information seeking to the extent that the search for information is aimed at self-care practices. This study could trigger further research on implementing the overconfidence effect and self-care in theoretical models of health information seeking.
Bertolazzi, A., Lombi, L., Lovari, A., Ducci, G., D'Ambrosi, L., I Know That I Know: Online Health Information Seeking, Self-Care and the Overconfidence Effect, <<SOCIOLOGICAL FORUM>>, 2023; (38/3): 793-812. [doi:10.1111/socf.12925] [https://hdl.handle.net/10807/245154]
I Know That I Know: Online Health Information Seeking, Self-Care and the Overconfidence Effect
Lombi, Linda;
2023
Abstract
The increasing access to online health information and the use of this information for self-medication or self-diagnosis can foster a discounting of the epistemic authority of experts, as well as an over-reliance on laypersons' expertise. However, the emerging cognitive bias-the overconfidence effect-is poorly investigated in the sociological field. This study offers a novel contribution to the role of overconfidence bias in online health information-seeking behavior and self-care practices. A cross-sectional study was conducted through an online survey on a sample of 783 Italian university students. Univariate linear regression and stepwise multiple linear regression analysis were performed on the collected data. The findings suggest that overconfidence and self-care practices are predictors of health information seeking online. The multiple linear regression model revealed that the association between overconfidence bias and online health information seeking is mediated by self-care behaviors. Therefore, the overconfidence effect influences health information seeking to the extent that the search for information is aimed at self-care practices. This study could trigger further research on implementing the overconfidence effect and self-care in theoretical models of health information seeking.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.