Associations of lockdown stringency and duration with Google searches for mental health terms during the COVID-19 pandemic: A nine-country study

Short-term changes in mental health help-seeking behaviors following exposure to multiple social stressors and a natural disaster

In 2020, unprecedented circumstances led to significant mental health consequences. Individuals faced mental health stressors that extended beyond the devastating impact of the COVID-19 pandemic, including widespread social unrest following the murder of George Floyd, an intense hurricane season in the Atlantic, and the politically divisive 2020 election. The objective of this analysis was to consider changes in help-seeking behavior following exposure to multiple social stressors and a natural disaster. Data from Crisis Text Line (CTL), a national text-based mental health crisis counseling service, was used to determine how help-seeking behavior changed in the wake of each event. Wilcoxon rank sum tests assessed changes in help-seeking behavior for each event in 2020 as compared to the same period in 2019. AutoRegressive Integrated Moving Average (ARIMA) models examined if changes in crisis conversation volumes following each event differed. Higher median conversation volumes noted for the COVID-19 pandemic (+1 to +5 conversations), Hurricane Laura (+1 to +7 conversations) and the 2020 Election (+1 to +26 conversations). ARIMA models show substantial increases in help-seeking behavior following the declaration of a national emergency for the COVID-19 pandemic (+4.3 to +38.2%) and following the 2020 election (+3 to +24.44%). Our analysis found that the mental health response following social stressors may be distinct from natural events, especially when natural disasters occur in the context of multiple social stressors. This analysis adds to the growing body of literature considering the mental health impact of exposure to multiple co-occurring societal stressors, like police violence and a global pandemic.

Does the COVID-19 pandemic lockdown affect risk attitudes?-Evidence from rural Thailand

Empirical research provides evidence on changes in individuals' risk attitudes after experiencing exogenous shocks. The global outbreak of the COVID-19 pandemic has had various adverse impacts on economies and households. This study utilizes the COVID-19 pandemic and the accompanying lockdown to explore its impact on risk attitudes in rural Thailand using a difference-in-difference (DiD) approach. Overall, we do not find evidence on considerable changes in the willingness to take risks of rural household members after experiencing a lockdown during the pandemic. However, a significant heterogenous effect is found between individuals working inside and outside the agricultural sector. Individuals working outside the agricultural sector have a statistically significant reduction in their willingness to take risks after experiencing a lockdown. Our study provides additional empirical evidence to understand the impact of shocks on rural households' risk attitudes. This sheds light on how policy designs can better help mitigate downward economic trends following exogenous shocks.

Marginal effects of public health measures and COVID-19 disease burden in China: A large-scale modelling study

China had conducted some of the most stringent public health measures to control the spread of successive SARS-CoV-2 variants. However, the effectiveness of these measures and their impacts on the associated disease burden have rarely been quantitatively assessed at the national level. To address this gap, we developed a stochastic age-stratified metapopulation model that incorporates testing, contact tracing and isolation, based on 419 million travel movements among 366 Chinese cities. The study period for this model began from September 2022. The COVID-19 disease burden was evaluated, considering 8 types of underlying health conditions in the Chinese population. We identified the marginal effects between the testing speed and reduction in the epidemic duration. The findings suggest that assuming a vaccine coverage of 89%, the Omicron-like wave could be suppressed by 3-day interval population-level testing (PLT), while it would become endemic with 4-day interval PLT, and without testing, it would result in an epidemic. PLT conducted every 3 days would not only eliminate infections but also keep hospital bed occupancy at less than 29.46% (95% CI, 22.73-38.68%) of capacity for respiratory illness and ICU bed occupancy at less than 58.94% (95% CI, 45.70-76.90%) during an outbreak. Furthermore, the underlying health conditions would lead to an extra 2.35 (95% CI, 1.89-2.92) million hospital admissions and 0.16 (95% CI, 0.13-0.2) million ICU admissions. Our study provides insights into health preparedness to balance the disease burden and sustainability for a country with a population of billions.

School closures and well-being-related topic searches on Google during the COVID-19 pandemic in Sub-Saharan Africa

BACKGROUND

Following the outbreak of the 2020 coronavirus, governments adopted non-pharmaceutical interventions (NPIs) to save lives. The NPIs have been deemed to have unintended consequences on mental health and well-being. This study aimed to estimate the impact of the COVID-19 pandemic-induced school closures on the relative search volumes (RSVs) of well-being-relevant topics in 30 low and lower- middle income countries in Sub-Saharan Africa.

METHODS

Google Trends search data, difference-in-differences and event study methods were used to evaluate the impact on the related search volume (RSV) of well-being related topic queries in Sub-Saharan Africa.

RESULTS

The results suggest positive and significant increases in the search intensity for anger, boredom, fear, sleep, exercise, and prayer. Contrary to other studies, we find no discernible effects on the relative search volumes (RSVs) on loneliness, sadness, and suicide.

CONCLUSION

Our findings suggest that the pandemic and the associated restrictions had a mixed effect on well-being-related searches. We recommend increased vigilance and proactive communication from the government and policy makers with the general population in times of emergencies when social policies that restrict lives and liberties need to be adopted.

Varieties of suffering in the clinical setting: re-envisioning mental health beyond the medical model

In this paper, we argue for the need to rethink mental health beyond the medical model because much of human suffering cannot be diagnosed by the DSM-5. During the pandemic and post-pandemic, people have learned to accept the fact that no one is immune from suffering. Given the universality and complexity of human suffering, it is natural for people to wrestle with existential questions such as "Why struggle when all life end in death?" and "How can one flourish when life is so hard?" Existential positive psychology (EPP or PP2.0) was developed to address these existential concerns. After explaining the inherent limitations of the medical model and the need for EPP as an alternative vision for mental health, we provide illustrative clinical cases to demonstrate the advantages of this broader existential framework for both case conceptualization and interventions. According to EPP, mental illness is reconceptualized as both deficiency in knowledge and skills in coping with the demands of life and deficiency in meeting the basic needs for livelihood and mental health, the Soul's yearnings for faith, hope, and love. Finally, we introduce integrative meaning therapy as a therapeutic framework which can equip people with the needed skills to achieve healing, wholeness, and total wellbeing.

Google Trends for health research: Its advantages, application, methodological considerations, and limitations in psychiatric and mental health infodemiology

The high utilization of infodemiological tools for psychiatric and mental health topics signals the emergence of a new discipline. Drawing on the definition of infodemiology by Eysenbach, this emerging field can be termed “psychiatric and mental health infodemiology,” defined as the science of distribution and determinants of information in an electronic medium, including the internet, or in a population to inform mental health services and policies. Since Google Trends is one of its popular tools, this minireview describes its advantages, application, methodological considerations, and limitations in psychiatric and mental health research. The advantage of Google Trends is the nature of its data, which may represent the actual behavior rather than their users' stated preferences in real-time through automatic anonymization. As such, it can provide readily available data about sensitive health topics like mental disorders. Therefore, Google Trends has been used to explore public concerns, interests, and behaviors about psychiatric and mental health phenomena, service providers, and specific disciplines. In this regard, several methodological can be considered by studies using Google Trends, including documenting their exact keywords, query category, time range, location, and date of retrieval. Likewise, its limitations should be accounted for in its interpretation, including restricted representation of people who use the Google search engine, limited validity in areas with low internet penetration or freedom of speech, does not provide absolute search volumes, unknown sampled queries, and limited transparency in its algorithm, especially the terms and idioms it subsumes under its “topic” keywords.

The road to postpandemic recovery in the USA: a repeated cross-sectional survey of multidimensional well-being over two years

OBJECTIVES

Examine differences in multidimensional well-being from before (January 2020) to three timepoints during the COVID-19 pandemic (June 2020, January 2021, January 2022).

STUDY DESIGN

Repeated cross-sectional design.

METHODS

Nationally representative cross-sectional cohorts of US adults completed the Secure Flourish Index before (January 2020 cohort: N = 1010) and during the COVID-19 pandemic (June 2020 cohort: N = 3020; January 2021 cohort: N = 3366; January 2022 cohort: N = 2598). We estimated differences in indicators, domains, and composite well-being between the January 2020 cohort and each of the subsequent cohorts. We also explored whether changes in well-being between January 2020 and January 2022 varied based on age, gender, and race/ethnicity.

RESULTS

Initial declines in well-being observed by June 2020 were largely followed by a return to prepandemic levels in January 2022, with some exceptions. Notably, general declines in mental health have persisted through to January 2022. On the other hand, there was evidence of general improvements in character & virtue that exceeded prepandemic levels in January 2022. Young adults and racial/ethnic minorities reported lower financial & material stability in January 2022 compared to before the COVID-19 pandemic.

CONCLUSIONS

Although there are promising signs that the well-being of US adults has mostly recovered to prepandemic levels, a coordinated response is urgently needed to support population mental health and the financial security of vulnerable groups. As society continues the journey toward postpandemic recovery, continued tracking of multidimensional well-being will be important for making informed decisions about public health priorities.

Psychological Impact of COVID-19 Lockdown and Its Evolution: A Case Study Based on Internet Searching Data during the Lockdown of Wuhan 2020 and Shanghai 2022

It has been three years since the initial outbreak of COVID-19 in Wuhan, China, which incurred huge damage both physically and psychologically on human's normal life. As a prevention measure, the lockdown was first adopted by Wuhan, then by a long list of Chinese cities and many other major cities around the world. Lockdown is the most restrictive social distancing strategy, turning out effective in mitigating the spreading of COVID-19 on the community level, which, however, cuts off all social interactions and isolates healthy people from each other. The isolated nature of the lockdown could induce severe mental health issues, forming one major source of depression and domestic violence. Given the potential side effect, a comprehensive investigation based on reliable data sources is needed to evaluate the real psychological impact of COVID-19 lockdown and its evolution over time, particularly in the time when the Omicron variant, known for its low death risk, dominates the pandemic. Based on the Baidu Searching Index data collected for Wuhan and Shanghai, two major cities in China that suffered from long-lasting (over two months) lockdowns in 2020 and 2022, respectively, it is found that the major psychological issue during the lockdown period is not induced by the spreading of COVID-19, but by the execution of lockdown. With the deepening of knowledge about COVID-19 and the decrease in the death risk, the psychological impact of lockdown keeps increasing, while the impact of virus spreading becomes less important and even irrelevant to depression and domestic violence issues. The findings reveal that from the psychological perspective, the negative effect of lockdown already overweighs the positive one, which is especially true for the Omicron variant provided its almost ignorable death risk. Therefore, it is necessary to re-evaluate the yield and cost of lockdown for those countries where the COVID-19 pandemic has not yet come to an end.

Impact of COVID-19 on public social life and mental health: a statistical study of google trends data from the USA

The COVID-19 pandemic has caused a significant disruption in the social lives and mental health of people across the world. This study aims to asses the effect of using internet search volume data. We categorize the widely searched keywords on the internet in several categories, which are relevant in analyzing the public mental health status. Corresponding to each category of keywords, we conduct an appropriate statistical analysis to identify significant changes in the search pattern during the course of the pandemic. Binary segmentation method of changepoint detection, along with the combination of ARMA-GARCH models are utilized in this analysis. It helps us detect how people's behavior changed in phases and whether the severity of the pandemic brought forth those shifts in behaviors. Interestingly, we find that rather than the severity of the outbreak, the long duration of the pandemic has affected the public health status more. The phases, however, align well with the so-called COVID-19 waves and are consistent for different aspects of social and mental health. We further observe that the results are typically similar for different states as well.