Abstract
In order to inform understanding of the public’s health information management during the COVID-19 pandemic, we applied a modification of TMIM from a serial mediation model to a conditional process model (moderated mediation). In doing so, the current study attempted to refine some of the relational propositions of the original TMIM with a focus on efficacy while addressing the distinction between a mediator and a moderator in a behavioral decision model. Findings from an online survey of U.S. adults (n = 488) demonstrated that anxiety can positively motivate evaluation of information seeking during the COVID-19 pandemic context, a unique context of application for TMIM. Efficacy was found to be qualified as an individual difference variable that moderates the relationships of uncertainty perception and health decision. Our newly proposed conditional process framework of the TMIM opens research directions in health information-seeking and encourages researchers to continuously incorporate updated methodological thought and approach in applying and building communication theory.
Disclosure Statement
In accordance with Taylor & Francis policy and our ethical obligation as researchers, we are reporting that we have no financial and/or business interests with any parties that may be affected by the research reported in the enclosed paper.
Notes
1 There is an increasing consensus that defining and testing mediation in terms of the reduction of the association between an independent variable and a dependent variable while controlling for the supposed mediator may mislead the causal relationships in a model and is unnecessarily conservative. The notion of “partial mediation” is largely dependent on the covariance-reduction perspective and Zhao et al. (Citation2010) proposed an alternative framework to consider either complementary or competitive mediation instead of partial mediation. See Zhao et al. (Citation2010).