Effects of disaster-related traumatic events on worry about radiation and COVID-19: A decade after the Fukushima nuclear power plant accident.

Community residents exposed to nuclear power plant (NPP) accidents have long-term worry about the effects of radiation. After the 2011 Fukushima NPP accident, those who experienced traumatic events during the Great East Japan Earthquake (GEJE) tended to have greater worry about radiation. Along with the prolonged worry about radiation, there may also be cognitive changes caused by the traumatic events. We hypothesized that if there were cognitive changes underlying the prolonged worry about radiation, those who experienced the traumatic events would tend to have greater worry about other issues unrelated to radiation. We examined the effects of the traumatic events during the GEJE on community residents' worry about radiation and COVID-19 a decade after the Fukushima NPP accident. Using the data of a longitudinal questionnaire survey following a random sample of 4900 community residents outside the evacuation zone in Fukushima, this study analyzed 774 responses (15.8%). The traumatic events consisted of (1) injury, (2) injury or death of a family member, and (3) the loss of a house or other property. We developed a mediation model drawing paths from the traumatic events to worry about radiation and COVID-19, including posttraumatic stress symptoms (PTSS) as a mediator, using structural equation modeling. The traumatic events directly affected worry about radiation. Although it did not directly affect worry about COVID-19, it did so indirectly through worry about radiation and PTSS. Traumatic events can increase trauma-related worry independently of PTSS and increase trauma-unrelated worry indirectly through trauma-related worry and PTSS.

Heterogeneity in COVID-19 pandemic-induced lifestyle stressors predicts future mental health in adults and children in the US and UK.

INTRODUCTION: Identifying predictors of mental health symptoms after the initial phase of the pandemic may inform the development of targeted interventions to reduce its negative long-term mental health consequences. In the current study, we aimed to simultaneously evaluate the prospective influence of life change stress, personal COVID-19 impact, prior mental health, worry about COVID-19, state-level indicators of pandemic threat, and socio-demographic factors on mood and anxiety symptoms in November 2020 among adults and children in the US and UK. METHODS: We used a longitudinal cohort study using the Coronavirus Health Impact Survey (CRISIS) collected at 3 time points: an initial assessment in April 2020 ("April"), a reassessment 3 weeks later ("May"), and a 7-month follow-up in November 2020 ("November"). Online surveys were collected in the United States and United Kingdom by Prolific Academic, a survey recruitment service, with a final sample of 859 Adults and 780 children (collected via parent report). We found subtypes of pandemic-related life change stress in social and economic domains derived through Louvain Community Detection. We assessed recalled mood and perceived mental health prior to the pandemic, worries about COVID-19, personal and family impacts of COVID-19, and socio-demographic characteristics. We used a conditional random forest approach to predict November mood states using these data from April and May and to rank the variable importance of each of the predictor items. RESULTS: Levels of mood symptoms in November 2020 measured with the circumplex model of affect. We found 3 life change stress subtypes among adults and children: Lower Social/Lower Economic (adults and children), Higher Social/Higher Economic (adults and children), Lower Social/Higher Economic (adults), and Intermediate Social/Lower Economic (children). Overall, mood symptoms decreased between April and November 2020, but shifting from lower to higher-stress subtypes between time points was associated with increasing symptoms. For both adults and children, the most informative predictors of mood symptoms in November identified by conditional random forest models were prior mood and perceived mental health, worries about COVID, and sources of life change. DISCUSSION: The relative importance of these predictors was the most prominent difference in findings between adults and children, with lifestyle changes stress regarding friendships being more predictive of mood outcomes than worries about COVID in children. In the US, objective state-level indicators of COVID-19 threat were less predictive of November mood than these other predictors. We found that in addition to the well-established influences of prior mood and worry, heterogeneous subtypes of pandemic-related stress were differentially associated with mood after the initial phase of the pandemic. Greater research on diverse patterns of pandemic experience may elucidate modifiable targets for treatment and prevention.

The Coronavirus Health and Impact Survey (CRISIS) reveals reproducible correlates of pandemic-related mood states across the Atlantic.

The COVID-19 pandemic and its social and economic consequences have had adverse impacts on physical and mental health worldwide and exposed all segments of the population to protracted uncertainty and daily disruptions. The CoRonavIruS health and Impact Survey (CRISIS) was developed for use as an easy to implement and robust questionnaire covering key domains relevant to mental distress and resilience during the pandemic. Ongoing studies using CRISIS include international studies of COVID-related ill health conducted during different phases of the pandemic and follow-up studies of cohorts characterized before the COVID pandemic. In the current work, we demonstrate the feasibility, psychometric structure, and construct validity of this survey. We then show that pre-existing mood states, perceived COVID risk, and lifestyle changes are strongly associated with negative mood states during the pandemic in population samples of adults and in parents reporting on their children in the US and UK. These findings are highly reproducible and we find a high degree of consistency in the power of these factors to predict mental health during the pandemic.