Principal investigator: Eduarda Miller de Figueiredo
Article title: COVID-19, LOCKDOWNS AND WELL-BEING:
Evidence from Google Trends
Article authors: Abel Brodeur, Andrew E. Clark, SarahFleche and Nattavudh Powdthavee
Sample size: It varies depending on the search term.
Location of the interventionCountries in Europe and the United States
Sector: Health
Type of interventionEffects of movement restrictions on the well-being of the population.
Main variable of interestboredom, contentment, divorce, commitment, irritability, loneliness,
panic, sadness, sleep, stress, suicide, well-being and worry
Assessment methodDifferences-within-differences
Policy Problem
The COVID-19 pandemic demanded a rapid response from all countries to save as many lives as possible in the short and medium term. To this end, most European countries and the United States imposed lockdowns on their residents, following the guidelines of epidemiological models to contain the spread of the virus (Ferguson et al., 2020).
These restrictions on movement have effects on GDP, levels of trust in governments, education, and the well-being of the population. The byproducts of lockdown include unemployment, social isolation, and lack of freedom, which are risk factors for mental health and unhappiness (Leigh-Hunt et al., 2017).
Assessment Context
There is some ongoing research regarding the evolution of population well-being during the pandemic. However, to fully assess this effect, data prior to the pandemic and lockdown are needed. In most existing studies, such data is unavailable.
To circumvent this data problem, the authors analyze Google Trends data between January 1, 2009, and April 10 in countries that introduced a full lockdown by the end of the period. This is because Google search indicators provide accurate and representative information about current user search behavior and sentiment. Furthermore, Google Trends shows aggregated measures of search activity in a given location and is therefore less vulnerable to small sample bias (Baker and Fradkin, 2017).
In this way, the article contributed to the literature by documenting the impacts of social restriction on the mental health of the population.
Policy Details
Google Trends data provides an unfiltered sample of searches performed on Google. A search term query in Google Trends returns searches for an exact search term, while a topic query includes searches related to terms, regardless of the term.
Therefore, it provides an index for the intensity of searches for topics or search terms over the period in question and in a requested geographic area. This index ranges from 0 to 100, where 100 is the day with the most searches on the topic and 0 indicates that a given day had no search volume for the specific term.
In this research, the authors used the following search terms for topics related to well-being between January 1, 2019, and April 10, 2020: boredom, contentment, divorce, commitment, irritability, loneliness, panic, sadness, sleep, stress, suicide, well-being, and worry. These topics are derived from different items in the General Health Questionnaire (GHQ).[1].
Therefore, the authors have a database of these topics for the countries that introduced a lockdown at the end of the period considered, namely: Austria, Belgium, France, Ireland, Italy, Luxembourg, Portugal, Spain, the United Kingdom, and the United States.
Methodology Details
The daily data for 2019 were obtained in a separate request from the daily data for 2020. Therefore, the authors needed to rescale both series to the same 0-100 scoring scale factor in order to compare them.
To do this, the respective weekly research interest weightings were first calculated for all weeks of the period, aggregating them to calculate the weekly average of searches for the topic in the country. cFrom this, the daily data was resized for each separate period by multiplying the 2019 weekly average by the 2019 weekly research interest weight, repeating the process for the 2020 period. Finally, the values were normalized between 0 and 100.
Assuming that, in the absence of lockdown, Google user behavior would have evolved in the same way as in the year prior to the lockdown, the authors use a Difference-in-Differences (DiD) estimator to estimate the combined effect of the Covid-19 pandemic and lockdowns on well-being-related searches. This was done by comparing pre- and post-lockdown searches in 2020 to pre- and post-lockdown searches from the same period in 2019, thus ensuring that seasonal variations between countries were not influencing the findings. Since the psychological effects of the lockdown may have begun from the moment the policy was announced to the public, the authors consider the date the restriction was announced as the "lockdown date".
In the DiD model, the authors used Google search topics related to well-being as the dependent variable, including fixed effects for country, state, year, week, and day. Additionally, the lagged number of new Covid-19 deaths per day per million in the country or state was also controlled for.
To test for the immediate structural disruption caused by the lockdown, the study also performs a Regression Discontinuity Analysis (RDD) to identify potential breaks in two series – pre- and post-lockdown. The dependent variable is the absolute distance in days from the announcement of the "stay at home" order: negative for days before and positive for days after. Thus, the date of the actual or counterfactual announcement is defined as day zero.
Results
Searches for "boredom" in Europe saw a sharp increase around the date of the announcement in 2020, while in the United States, which began lockdown later, this search started 10 days before the announcement. This pattern was only observed in 2020, with no abrupt change during the same period in 2019.
It was also possible to observe a notable increase in searches for "loneliness" in Europe after the lockdown, which was not observed in the United States. On the other hand, both countries saw an increase in searches for "sadness" around one to two weeks after the lockdown.
The Difference-in-Differences estimation demonstrates that the lockdown variable produced a significant increase in the search intensity for "boredom" in both locations, with this increase being significant at the 1% level. A significant increase was also observed in searches for "loneliness," "worry," and "sadness."
Another observed result was the statistically significant decreases in "stress," "suicide," and "divorce" in both locations. However, no effect was found on "sleep" in the European countries. Regarding the topic of "well-being," the results diverge between locations. In the US, a positive effect was observed in the intensity of research related to the topic, but in Europe it had a negative effect.
When the authors divided Europe into early and late lockdowns, with the late group comprising Ireland, Portugal, and the United Kingdom, they found a positive effect on relative well-being in the late group. Thus, they observed that the effect of lockdown on well-being measures is often more positive in countries with late lockdowns. Therefore, those who entered late lockdowns may be less stressed, but the public health benefits were more strongly observed in countries that entered an early lockdown.
The results of the Regression Discontinuity Analysis (RDD) demonstrated that the immediate effect of the lockdown is an increase in searches for "boredom" and "compromise" and a reduction in searches for "panic." However, there was little short-term impact on "stress," "sadness," "suicide," and "worry."
Lessons in Public Policy
Despite the need expressed by governments for society to stay home to save lives, evidence suggests that people's mental health has been affected during the first weeks of lockdown. Therefore, it is clear that it is necessary to emphasize the benefits of lockdown for public health, ensuring that there will be appropriate support to help those who struggle most with the lockdown, which, according to Oswald and Powdthavee (2020), begins with the younger generations.
Reference
BRODEUR, Abel et al. COVID-19, lockdowns and well-being: Evidence from Google Trends. Journal of public economics, vol. 193, p. 104346, 2021.
[1] General Health Questionnaire (GHQ).
