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Health misinformation on social media threatens public health. A critical question that sheds light on the propagation of health misinformation across social media platforms revolves around identifying the specific types of social media users susceptible to this issue. This study provides an initial insight into this matter by examining the underlying psychological mechanism that renders users susceptible to health misinformation.

In this study, we developed an integrated model of susceptibility to health misinformation, drawing on the motivation-opportunity-ability theory and the elaboration likelihood model. We collected the data from a sample of 342 social media users in China. Furthermore, the fuzzy-set qualitative comparative analysis was adopted to examine the proposed model and uncover the causal recipes associated with susceptibility to health misinformation.

The results indicated that there are three configural types of users that are susceptible to health misinformation: the health-consciousness core-driven type, the popularity-driven core type and the dual-driven type characterized by both high health consciousness and information popularity. Among these, high health-consciousness and the reliance on information popularity-based pathways emerge as pivotal factors influencing susceptibility to health misinformation.

This study contributes to the social media literature by identifying various psychological traits that lead to social media users’ susceptibility to health misinformation. Additionally, the study provides comprehensive guidance on how to mitigate the spread of health misinformation.

In this study, a formula is derived for the period specific beta (market risk) for a portfolio of financial assets that has been formed on the basis of directional forecasts. This is an important contribution to the literature since measuring the risk of an actively managed portfolio is problematic due to the fact that managers may change fund risk conditional on market expectations. The period‐specific nature of the measure is a significant advantage since historical fund returns are not required and the beta is not influenced by prior fund returns' deviations from the bench mark. The methodology employed allows for the development of a time series of fund betas that permits investigation into a number of important empirical issues. This study is also of practical interest from the perspective of risk management and for both portfolio performance and attribution. Finally, there are many active strategies based on directional forecasts and the approach used here encompasses a significant proportion of these.