No abstract

Fear is an adaptive response in the presence of danger. However, when threat is uncertain and continuous, as in the current coronavirus (COVID-19) pandemic, fear can become chronic and burdensome. To better understand predictors of fear of the coronavirus, we conducted an online survey (N = 439) between March 14 and 17, 2020, which started three days after the World Health Organization declared the coronavirus outbreak a pandemic. Fear of the coronavirus was assessed with eight questions pertaining to different dimensions of fear (e.g., subjective worry, avoidance, preferential attention) and an open-ended question. The predictors included measures of psychological vulnerability factors (i.e., intolerance of uncertainty, worry, health anxiety), media exposure, and personal relevance (i.e., personal health, risk for loved ones, and risk control). We found that respondents reported a wide range of concerns relating to the coronavirus outbreak, such as the health of their loved ones, collapse of health care systems, and economic consequences. Four predictors for fear of the coronavirus were retained after backward selection in a simultaneous regression analysis: health anxiety, intolerance of uncertainty, media use, and risks for loved ones (R2 = .37). We discuss the relevance of our findings for managing people’s fear of the coronavirus.

In this report, we illustrate the considerable impact of researcher degrees of freedom with respect to exclusion of participants in paradigms with a learning element. We illustrate this empirically through case examples from human fear conditioning research, in which the exclusion of ‘non-learners’ and ‘non-responders’ is common – despite a lack of consensus on how to define these groups. We illustrate the substantial heterogeneity in exclusion criteria identified in a systematic literature search and highlight the potential problems and pitfalls of different definitions through case examples based on re-analyses of existing data sets. On the basis of these studies, we propose a consensus on evidence-based rather than idiosyncratic criteria, including clear guidelines on reporting details. Taken together, we illustrate how flexibility in data collection and analysis can be avoided, which will benefit the robustness and replicability of research findings and can be expected to be applicable to other fields of research that involve a learning element.

No abstract

Fear learning reflects the adaptive ability to learn to anticipate aversive events and to display preparatory fear reactions based on prior experiences. Usually, these learning experiences are modeled in the lab with pairings between a neutral conditioned stimulus (CS) and an aversive unconditioned stimulus (US) (i.e., fear conditioning via CS-US pairings). Nevertheless, for humans, fear learning can also be based on verbal instructions. In this review, we consider the role of verbal instructions in laboratory fear learning. Specifically, we consider both the effects of verbal instructions on fear responses in the absence of CS-US pairings as well as the way in which verbal instructions moderate fear established via CS-US pairings. We first focus on the available empirical findings about both types of effects. More specifically, we consider how these effects are moderated by elements of the fear conditioning procedure (i.e., the stimuli, the outcome measures, the relationship between the stimuli, the participants, and the broader context). Thereafter, we discuss how well different mental-process models of fear learning account for these empirical findings. Finally, we conclude the review with a discussion of open questions and opportunities for future research.

No abstract

No abstract

Since the outbreak of the coronavirus disease (COVID-19), several reports have shown that fear relating to COVID-19 has sharply increased. To measure fear of COVID-19, various questionnaires have been developed in parallel. However, fear concerning COVID-19 is not necessarily a uniform construct and the different questionnaires may cover diverse aspects. To examine the underlying structure of fear of COVID-19, we conducted structural equation modelling and network analyses on four scales in an online convenience sample ( N = 829). Particularly, the Fear of COVID-19 Scale (Ahorsu et al., 2020), the Fear of the Coronavirus Questionnaire (Mertens et al., 2020), and the COVID Stress Scales (Taylor, Landry, Paluszek, Fergus et al., 2020, Taylor, Landry, Paluszek, Rachor et al., 2020) were included in our study, along with a new scale that also assessed socio-economic worries relating to COVID-19. We found that fear of COVID-19 was best classified into four clusters: Fear of health-related consequences, fear of supplies shortages and xenophobia, fear about socio-economic consequences, and symptoms of fear (e.g., compulsions, nightmares). We also find that a central cluster of items centered on fear of health, which likely represents the core of fear of COVID-19. These results help to characterize fear due to COVID-19 and inform future research.