Unfounded—conspiracy and health—beliefs about COVID-19 have accompanied the pandemic worldwide. Here, we examined cross-nationally the structure and correlates of these beliefs with an 8-item scale, using a multigroup confirmatory factor analysis. We obtained a two-factor model of unfounded (conspiracy and health) beliefs with good internal structure (average CFI = 0.98, RMSEA = 0.05, SRMR = 0.04), but a high correlation between the two factors (average latent factor correlation = 0.57). This model was replicable across 50 countries (total N = 13,579), (...) as evidenced by metric invariance between countries (CFI = 0.96, RMSEA = 0.06, SRMS = 0.07) as well as scalar invariance across genders (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03) and educational levels (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03). Also, lower levels of education, more fear of COVID-19, and more cynicism were weakly associated with stronger conspiracy and health beliefs. The study contributes to knowledge about the structure of unfounded beliefs, and reveals the potential relevance of affective (i.e., fear of COVID-19) and cognitive (i.e., cynicism) factors along with demographics, in endorsing such beliefs. In summary, we obtained cross-cultural evidence for the distinctiveness of unfounded conspiracy and health beliefs about COVID-19 in terms of their structure and correlates. (shrink)

Unfounded—conspiracy and health—beliefs about COVID-19 have accompanied the pandemic worldwide. Here, we examined cross-nationally the structure and correlates of these beliefs with an 8-item scale, using a multigroup confirmatory factor analysis. We obtained a two-factor model of unfounded (conspiracy and health) beliefs with good internal structure (average CFI = 0.98, RMSEA = 0.05, SRMR = 0.04), but a high correlation between the two factors (average latent factor correlation = 0.57). This model was replicable across 50 countries (total N = 13,579), (...) as evidenced by metric invariance between countries (CFI = 0.96, RMSEA = 0.06, SRMS = 0.07) as well as scalar invariance across genders (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03) and educational levels (CFI = 0.98, RMSEA = 0.04, SRMS = 0.03). Also, lower levels of education, more fear of COVID-19, and more cynicism were weakly associated with stronger conspiracy and health beliefs. The study contributes to knowledge about the structure of unfounded beliefs, and reveals the potential relevance of affective (i.e., fear of COVID-19) and cognitive (i.e., cynicism) factors along with demographics, in endorsing such beliefs. In summary, we obtained cross-cultural evidence for the distinctiveness of unfounded conspiracy and health beliefs about COVID-19 in terms of their structure and correlates. (shrink)

Individual differences in mental accounting have rarely been studied, and empirical evidence regarding the relation between mental accounting and personality characteristics is scarce. The present paper reports three studies applying a Likert-type scale to assess the extent individuals engage in mental accounting practices. In each study, the five items of the measure loaded on a single dimension and had acceptable reliability, with a Cronbach’s α between.72 and.77. Study 1 (N = 165) regards the mental processing of prior losses in the (...) theater-ticket problem (Tversky and Kahneman 1981). Study 2 (N = 114) is based on prior work on income source effects (Fogel 1997) and analyzes mental accounting of prior gains. In both studies, individual differences in mental accounting moderated the effects of the experimental treatments. In an explorative survey conducted for Study 3 (N = 373), the extent of engaging in mental accounting was found to be positively correlated with being female, with conscientiousness, and financial literacy, and negatively related with education and non-planning impulsivity. Identification of individual differences and their correlates adds to existing evidence for some of the core assumptions of mental accounting theory. A practical implication of the findings is that providers of financial services must take individual differences into account when designing trainings and supportive tools for money management. (shrink)