Associations of risk perception of COVID-19 with emotion and mental health during the pandemic

Background Although there are increasing concerns on mental health consequences of the COVID-19 pandemic, no large-scale population-based studies have examined the associations of risk perception of COVID-19 with emotion and subsequent mental health. Methods This study analysed cross-sectional and longitudinal data from the PsyCorona Survey that included 54,845 participants from 112 countries, of which 23,278 participants are representative samples of 24 countries in terms of gender and age. Specification curve analysis (SCA) was used to examine associations of risk perception of COVID-19 with emotion and self-rated mental health. This robust method considers all reasonable model specifications to avoid subjective analytical decisions while accounting for multiple testing. Results All 162 multilevel linear regressions in the SCA indicated that higher risk perception of COVID-19 was significantly associated with less positive or more negative emotions (median standardised β=-0.171, median SE=0.004, P<0.001). Specifically, regressions involving economic risk perception and negative emotions revealed stronger associations. Moreover, risk perception at baseline survey was inversely associated with subsequent mental health (standardised β=-0.214, SE=0.029, P<0.001). We further used SCA to explore whether this inverse association was mediated by emotional distress. Among the 54 multilevel linear regressions of mental health on risk perception and emotion, 42 models showed a strong mediation effect, where no significant direct effect of risk perception was found after controlling for emotion (P>0.05). Limitations Reliance on self-reported data. Conclusions Risk perception of COVID-19 was associated with emotion and ultimately mental health. Interventions on reducing excessive risk perception and managing emotional distress could promote mental health.

affects their emotions, and whether it will eventually lead to mental health problems (Ren et al., 2020).

Risk perception of COVID-19 is the cognitive response and assessment for the threat of the COVID-19 pandemic. Risk perception has two main dimensions
according to the psychometric paradigm (Slovic, 1987): "dread" which reflects the perceived lack of control and catastrophic potential, and "risk of the unknown" which refers to the unobservable of the hazard (Peters and Slovic, 1996;Siegrist et al., 2005). The emergence of the COVID-19 pandemic could seriously arouse these two psychological dimensions and make people feel threatened. Extensive evidence from previous research in psychology, clinical science and economics indicated that people perceive the risk cognitively and respond to it emotionally (Loewenstein et al., 2001); in other words, risk perceptions typically drive emotions and psychological distress (Loewenstein et al., 2001;Slovic et al., 2004;Leppin and Aro, 2009). In addition to the direct evidence, stress and motivational prioritisation may link risk perception to emotion and mental health. Consistent evidence has shown that risk perception has a remarkably positive association with the feeling of stress (Lopez-Vazquez, 2001;Lopez-Vazquez and Marvan, 2003). In this case, the threat of the pandemic will induce stress, which will in turn affect people's emotion and mental health according to the social stress theory and empirical evidence (Aneshensel, 1992;Kessler, 1997;Wu et al., 2020;Guidi et al., 2021). In addition, high risk perception of COVID-19 may reflect motivational prioritisation of the COVID-19 threat over other important life goals, needs and duties. This motivational preoccupation could cause emotional fluctuations following the pandemic escalation (Kopetz, 2017). Therefore, we propose that the risk perception of COVID-19 could be associated with emotion and mental health.
Emerging evidence from the previous pandemics (e.g., SARS, H1N1, Ebola) also implied that risk perception could be highly associated with public's emotional responses (Qian et al., 2003;Qian et al., 2005;Raude and Setbon, 2009;Bults et al., 2011;Yang, 2016). For example, Prati et al. (2011) found a positive association between perceived severity and affective response to the H1N1 pandemic in 2009. Yang and Chu (2018) also associated risk perception about the Ebola outbreak with some negative emotions like fear, anger, anxiety, disgust, and sadness.
In the context of the COVID-19 pandemic, the concerns of getting infected and the economic consequences have been proposed as two major aspects of risk perception of COVID-19 and assessed by several preliminary studies (Soiné et al., 2020;Bruine de Bruin, 2020).
Given the emotional strain during the pandemic, there is increasing concern about its impact on mental health (Burhamah et al. 2020;Planchuelo-Gómez et al., 2020).
A national survey in China at the initial stage of COVID-19 outbreak indicated that 27.9% of participants had symptoms of depression, and 31.6% had symptoms of anxiety (Shi et al., 2020). Another survey of US adults in April 2020 reported that 13.6% of participants had symptoms of serious psychological distress, which was substantially higher than the estimate in 2018 (3.9%); and 13.8% of participants frequently felt lonely (McGinty et al., 2020). Several preliminary studies have evaluated the risk perception of COVID-19 in relation to mental health. A survey by Ding et al. (2020) found that the risk perception of COVID-19 was associated with the level of depression. Teufel et al. (2020)

Since there are multiple items for each construct and various analytical options to test the association between risk perception and emotion or mental health, it is hard
to select one optimal model specification (i.e., which items to use and how many covariates to adjust for) objectively. In this regard, specification curve analysis (SCA) (Simonsohn et al., 2015;Orben and Przybylski, 2019)    As shown in Figure 3, the direct effect of risk perception on mental health is weaker after controlling for the average score of negative emotions (median standardised

Discussion
In this large-scale cross-country study of psychological impact of COVID-19, we found a robust association between risk perception and emotion. Consistent with the literature on emotional reactions during previous pandemic periods (Prati et al., 2011;Yang and Chu, 2018), higher risk perception was associated with higher levels of overall negative emotion and individual negative emotions (anxious, nervous, depressed, exhausted, lonely, bored; in descending order of the magnitude of association). In addition, risk perception had a slightly weaker but significant inverse association with the levels of overall positive emotion and individual positive emotions (relaxed, calm, content, happy, inspired, excited; in descending order of the magnitude of association). These findings imply that reducing unnecessary risk perception or avoiding excessive concern of the pandemic may be a candidate  (Davey and McGorry, 2019;Galea et al., 2020). In this regard, people should seek psychological or social support in time when suffering from long-lasting or severe emotional distress, either from professional staff or families/friends. On the other hand, although there is a gap between real risk and subjective risk perception, the risk perception was inevitably shaped by the risk environment to which an individual is exposed. Thus, special attention should be paid to the mental health issues of populations at high risk of COVID-19, such as healthcare workers (Cai et al., 2020;Zhou et al. 2020), carers of infected patients, residents in severely affected areas, and the elderly or those with existing comorbidities.
Furthermore, we found that the risk perception of economic consequences is also a remarkable factor associated with emotion and mental health, with an even larger effect estimate than the risk perception of getting infected. Despite the consistent evidence that elevating the risk perception of infection could increase the adoption of health behaviours (Floyd et al., 2000;Sheeran et al., 2014), especially during disease outbreaks (Bish and Michie, 2010;van der Weerd et al., 2011;Rudisill, 2013)   Only 34 countries with at least 200 participants are displayed. The size of bubbles was proportional to the sample size of the corresponding country. The dashed line in each plot was fitted by simple linear regression. Six negative emotions and six positive emotions were rated in 5-point scale from 1 (very slightly or not at all) to 5 (extremely); the average score for each of the two groups of emotion is shown on y axis in the two plots separately. Two items of risk perception of getting infected or suffering from economic consequences were in 7-point scale from 1 (exceptionally unlikely) to 7 (all but certain); the average score is shown on x axis in both plots.  The standardised β coefficients for the association of risk perception of COVID-19 with mental health after controlling for emotion in all 54 specifications (listed on x axis) are plotted as black dots (P<0.05) or red dots (P>0.05) at the upper half of the graph; the association of emotion with mental health in the same model specification was also plotted as blue dots (all P<0.001). The error bar (in grey) represents the corresponding standard error (SE). The dashed lines indicate the median standardised β coefficients for risk perception (median standardised β=-0.031, median SE=0.024, median sample size=1403) and emotion (median standardised β=0.534, median SE=0.025). At the lower half of the graph, the corresponding specifications for each level of the four model specification factors are displayed as squares.