COVID-19 blues: Lockdowns and mental health-related google searches in Latin America

Do behavioral drivers matter for healthcare decision-making during crises? A study of low-income women in El Salvador during the COVID-19 pandemic

Understanding health-seeking behaviors and their drivers is key for governments to manage health policies. A growing body of research explores the role of cognitive biases and heuristics in health and care-seeking behaviors, but little is known about how a context of heightened anxiety and uncertainty might influence these behavioral drivers. This study analyzes the association between four behavioral predictors-internal locus of control, impatience, optimism bias, and aspirations-and healthcare decisions among low-income women in El Salvador, controlling for other factors. We find positive associations between internal locus of control and preventive health behaviors during the COVID-19 pandemic. For instance, a one standard deviation increase in locus of control is associated with a 10% increase in an index measuring the use of masks, distancing, hand washing, and vaccination. Locus of control was also associated with women's use of preventive health services (one standard deviation improves the likelihood of having a hypertension test in the last six months by 5.8 percentage points). In a sub-sample of mothers, we find significant relationships between the four behavioral drivers and the decisions the mothers make for their children. However, we find these associations are less robust compared to the decisions they make for themselves. Some associations were stronger during the pandemic, suggesting that feelings of uncertainty and stress could amplify behavioral drivers' influence on health-related behaviors. This novel finding is relevant for designing policy responses for future shocks. JEL CODES: I12, D10, D91, I30.

Residential mobility restrictions and adverse mental health outcomes during the COVID-19 pandemic in the UK

During the COVID-19 pandemic, several governments tried to contain the spread of SARS-CoV-2, the virus that causes COVID-19, with lockdowns that prohibited leaving one's residence unless carrying out a few essential services. We investigate the relationship between limitations to mobility and mental health in the UK during the first year and a half of the pandemic using a unique combination of high-frequency mobility data from Google and monthly longitudinal data collected through the Understanding Society survey. We find a strong and statistically robust correlation between mobility data and mental health survey data and show that increased residential stationarity is associated with the deterioration of mental wellbeing even when regional COVID-19 prevalence and lockdown stringency are controlled for. The relationship is heterogeneous, as higher levels of distress are seen in young, healthy people living alone; and in women, especially if they have young children.

The COVID-19 pandemic and non-COVID-19 healthcare utilization in Mexico

OBJECTIVES

This study aimed to analyze the effects of the COVID-19 pandemic on non-COVID-19 healthcare utilization in Mexico, including oral health, mental health, communicable disease visits, health checkups, chronic degenerative disease visits, postpartum care, prenatal care, and family planning visits.

STUDY DESIGN

This was a retrospective ecological analysis during the COVID-19 pandemic. During the pandemic, the Mexican government recommended non-essential consultations be suspended or rescheduled to accommodate the new demand for healthcare services from COVID-19 patients.

METHODS

This study uses administrative data from Mexico's Ministry of Health from January 2017 to December 2022. These data cover 14,299 consultation units and 775 hospitals from the 32 Mexican States, all of which are public institutions. A difference-in-differences strategy and an event study specification are used to study the impacts of the pandemic on non-COVID-19 healthcare utilization.

RESULTS

The findings reveal a decrease in the utilization of all healthcare services: oral health (69%), mental health (27%), communicable diseases (46%), chronic degenerative diseases (36%), health checkups (62%), family planning (45%), prenatal care (36%), and postpartum care (44%). Furthermore, the event study indicates that most services follow a U-shaped trend, although only mental health services clearly return to prepandemic levels. The remainder of services remain below prepandemic levels at the end of 2022.

CONCLUSIONS

The 2020 pandemic had detrimental effects on non-COVID-19 healthcare utilization. The healthcare interruptions will likely impact short- and long-term morbidity and mortality. Programs intended to remediate these negative consequences may be of interest to public health policymakers.

Where I am from matters: factors influencing behavioral and emotional changes in autistic individuals during COVID-19 in Latin America

Background

The COVID-19 pandemic brought an increased incidence of disease and mortality in the world at large, making it a particularly salient and stressful life event. For those individuals residing in Latin America, the pandemic was met with fragmented healthcare systems, economic downturn, and sociopolitical crisis which puts autistic individuals at risk for more detrimental outcomes. Behavioral and emotional challenges experienced by autistic individuals at the beginning of the pandemic could later develop into more severe symptomatology as the pandemic progresses. The present study aimed to explore changes in dysregulated (overt and internalizing) behaviors and preoccupation with getting sick during the COVID-19 pandemic among autistic children in 7 Latin American countries.

Method

Sample consisted of 1,743 caregivers, residing in: Argentina (n = 677, 38.8%) Brazil (n = 156, 9%), Chile (n = 251, 14.4%), Dominican Republic (n = 171, 9.8%), Mexico (n = 126, 7.2%), Uruguay (n = 259, 14.9%) and Venezuela (n = 103, 5.9%). The majority of caregivers who completed the questionnaire were mothers (85.1%), and most had a male autistic child (81.6%). A series of independent sample t-tests were conducted to assess country differences in dysregulated behaviors and preoccupation with getting sick. Linear regressions were conducted to identify which demographic characteristics and micro-level contextual factors predicted dysregulated overt behaviors and psychological changes.

Results

Contextual factors, such as country of residence, were related to preoccupation with getting sick and dysregulated behavior. Particularly, residing in Mexico and Brazil were related to changes in preoccupation with getting sick and mental health concerns. Coexistence predicted dysregulated internalizing behaviors, while being older significantly predicted preoccupation with getting sick. Increased screen time only predicted anxiety.

Conclusion

Our findings highlight differences and predictions of behavioral challenges and psychological changes based on certain contextual factors and individual characteristics while experiencing severe life stressors such as a worldwide pandemic. This knowledge could help inform policies and decrees aimed at protecting those most vulnerable due to their increased difficulty adapting to change.

Mental health effects of social distancing in Switzerland

This analysis examines the effect of COVID-19 on public mental health in Switzerland. Following an event-study framework, we compare helpline call volume and duration before and after the outbreak of the first and second wave. The use of administrative phone-level data allows us to i) decompose the total effects into an intensive and extensive margin and ii) calculate a measure of unmet need. For the first wave, our results show that callers with a history of helpline contacts increase calls substantially. We also identify capacity constraints leading to unmet need for psychological counseling. Finally, we find no effects in the second wave, which might be explained by a number of factors including the absence of a lockdown and less restrictive social distancing measures.

Mental health effects of COVID-19 lockdowns: A Twitter-based analysis

We use a distinctive methodology that leverages a fixed population of Twitter users located in France to gauge the mental health effects of repeated lockdown orders. To do so, we derive from our population a mental health indicator that measures the frequency of words expressing anger, anxiety and sadness. Our indicator did not reveal a statistically significant mental health response during the first lockdown, while the second lockdown triggered a sharp and persistent deterioration in all three emotions. Our estimates also show a more severe deterioration in mental health among women and younger users during the second lockdown. These results suggest that successive stay-at-home orders significantly worsen mental health across a large segment of the population. We also show that individuals who are closer to their social network were partially protected by this network during the first lockdown, but were no longer protected during the second, demonstrating the gravity of successive lockdowns for mental health.

Understanding mental health conditions and key coping strategies utilized during major lockdowns in the Caribbean based on Google trends searches

The COVID-19 pandemic has prompted countries to implement extended Shelter in Place Orders (SIPOs) to restrict population movement and mitigate community spread. While these lockdown measures may be effective in containing the virus, they can substantially impact the population's well-being, potentially undermining their overall welfare. This study investigates whether major lockdowns implemented in the Caribbean produced differential changes in mental health among key English-Speaking Caribbean countries. More importantly, unlike past studies, we examine key coping strategies persons utilize during major lockdowns. Finally, this paper utilizes a novel near real-time high-frequency data source in Google Trends data analytics to assess mental health patterns and coping strategies among major Caribbean countries. Based on the results of difference-in-difference and event study models, we find positive and significant increases in searches for fear, depression, and suicide during key lockdown periods, which suggest negative mental health effects. Regarding coping strategies, searches for Zoom, learning, books, exercise, prayer, religion, and meditation increased, together with searches for addiction and marijuana. These results indicate the types of programs health administrators and policymakers can implement during lockdown periods to help local mental health communities, particularly among island communities.

A predictive model of perceived stress during the first wave of the COVID-19 pandemic in university students Ecuadorians

Background and objectives

The situation caused by the confinement due to the COVID-19 pandemic and the mobility restriction implemented by governments worldwide had a significant impact on people's routines. Stressors are known to increase emotional imbalance, uncertainty, and frustration in the general population. This study explores the factors that predispose to the risk of perceived stress from COVID-19 and determines the underlying mediating mechanisms in the Ecuadorian population.

Method

The cross-sectional study an incidental non-probabilistic sample of n = 977 participating student volunteers from the four regions of the Republic of Ecuador (68.6% women and 31.4% men). Data on emotional regulation (ERQ), perceived stress (PSS), active procrastination (APS), diagnosis and symptoms related to COVID-19, social isolation, coexistence, and a sociodemographic questionnaire (biological sex, marital status, and age) were recruited. Statistical analysis was based on a structural equation model.

Results

The risk of suffering perceived stress in the COVID-19 pandemic was higher for single women who have lived longer in social isolation, have lived with more people, have poor emotional regulation and high rates of procrastination. This structural model is similar in all Ecuadorian regions χ² = 21.54 (p = 0.760), RMSEA = 0.001 (95%CI, 0.00-0.02), CFI = 0.998; TLI = 0.999; SRMR = 0.020.

Discussion

Although our findings are consistent and revealing for the scientific community, the lack of discrimination of the data due to strict isolation measures, taken at different periods by the Ecuadorian government against positive cases of COVID-19, is discussed. The research was applied to the university population, it would be representative to extend the study to schools and colleges.

Conclusion

We consider this work as a starting point for the creation of preventive models against perceived stress in the university environment in the event of health emergencies.

Non-COVID-19 deaths in times of pandemic

BACKGROUND AND OBJECTIVE

To investigate the effect of the COVID-19 pandemic on non-COVID-19 deaths in Mexico.

METHODS

This study analyzes monthly administrative data on 15 different causes of death in Mexico from 2017 to 2020. The effects of the COVID-19 pandemic on non-COVID-19 deaths are conducted using a difference-in-differences methodology and an event study.

RESULTS

The evidence shows mixed results. There is an increase in six causes of death: diabetes (36.8%), hypertension (25.8%), heart attacks (40.9%), bronchitis- asthma (24.2%), anemia (28.6%) and prostate cancer (21.4%). There is a decrease in two causes of death: traffic accidents (8.8%) and HIV (13.8%). There are null effects for seven causes of death: breast cancer, cerebrovascular disease, malnutrition, alcohol-related liver disease, renal insufficiency, homicides and suicides.

CONCLUSIONS

The COVID-19 pandemic affected non-COVID-19 deaths caused by diseases that require intensive healthcare services. Conversely, this pandemic reduced social interactions, which contributed to a decrease on deaths such as traffic accidents.

Factors affecting access to healthcare for young people in the informal sector in developing countries: a systematic review

Background

Young people are increasingly seeking employment in the informal sector due to increasing global unemployment. However, the precarious nature of work in the informal sectors, coupled with the high risk of occupational hazards, calls for a greater need for effective healthcare for informal sector workers, particularly young people. In addressing the health vulnerabilities of informal workers, systematic data on the determinants of health is a persistent challenge. Therefore, the objective of this systematic review was to identify and summarise the existing factors that affect access to healthcare among young people from the informal sector.

Methods

We searched six data databases (PubMed, Web of Science, Scopus, ProQuest, Crossref, and Google Scholar), which was followed by hand searching. Then we screened the identified literature using review-specific inclusion/exclusion criteria, extracted data from the included studies and assessed study quality. Then we presented the results in narrative form, though meta-analysis was not possible due to heterogeneity in the study design.

Results

After the screening, we retrieved 14 studies. The majority were cross-sectional surveys and were conducted in Asia (n = 9); four were conducted in Africa, and one in South America. Samples ranged in size from 120 to 2,726. The synthesised results demonstrate that problems of affordability, availability, accessibility, and acceptability of healthcare were barriers to young informal workers seeking healthcare. We found social networks and health insurance as facilitators of access for this group of people.

Conclusion

To date, this is the most comprehensive review of the evidence on access to healthcare for young people in the informal sector. Our study finding highlights the key gaps in knowledge where future research could further illuminate the mechanisms through which social networks and the determinants of access to healthcare could influence the health and well-being of young people and thus inform policy development.

[Analysis with Google Trends and Our World in Data on Global Mental Health in the Context of the covid-19 Pandemic]

Introduction

During the covid-19 pandemic, mental health services were unable to cope with the high demand from the population, so many people chose to search the Internet for information that could help them cope with the psychological process they were experiencing at the time. The aim of this study was to characterize the global search trend for the term «psychiatry» in the context of covid-19 using Google Trends and Our World in Data.

Methods

Descriptive-cross-sectional study on global search trends for Psychiatry in the context of covid-19 under the terms «psychiatry», «depression», «anxiety», «stress», «insomnia» and «suicide» in the category of health, this was conducted over the period 2020-2021 and time graphs were generated.

Results

The term «psychiatry» remained at a consistently high relative search volume (between 60 and 90), with a significant and gradual search in the month of April. The relative search volume for «depression», «anxiety» and «stress» remained constant with some non-significant fluctuations over the period 2020-2021. The term «insomnia» was predominant between January and June 2020, gradually declining in April and remaining constant until October 2021. Finally, the term «suicide» had a fluctuating RBV between 60 and 100 during this period.

Conclusions

During the study period, the topics related to mental health and the speciality of psychiatry remained constant, with some fluctuating, but not outstanding variations.

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.

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.

Moderation of the association between COVID-19-related income loss and depression by receipt of financial support: Repeated cross-sectional surveys of young adults in Canada and France (2020-2021)

Background

To mitigate the adverse effects of the COVID-19 pandemic on financial resources, governments and family/friends mobilized financial support interventions (e.g., emergency aid funds) and assistance. However, little is known about how financial assistance alleviated mental health problems. This study aimed to investigate the moderating effect of financial support from the government or from family/friends on the association between income loss and depression among young adults.

Methods

Two online cross-sectional surveys among young adults ages 18-29 living in Canada and France were conducted in 2020 (n = 4,511) and 2021 (n = 3,329). Moderate-to-severe depressive symptoms were measured using the Patient Health Questionnaire-9 (cut-off score: ≥10). Two logistic regression models were performed for each survey with an interaction term between income loss and financial support (government or family/friends modeled separately), controlling for demographics.

Results

Overall, half reported depressive symptoms (2020/2021: 53.5%/45.6%), and over a third lost income (2020/2021: 10.2%/11.6% all income, 37.7%/21.6% some income). In 2020, 40.6% received government financial support (17.7% in 2021) while family/friends support was received by 12% (in both surveys). In both surveys, among those who received governmental financial support, income loss was associated with depression, whether participants lost all their income (e.g., 2020: Adjusted Odds Ratios (AOR) 1.75, 95% Confidence Interval [1.29-2.44]), or some of their income (e.g., 2020: AOR 1.45 [1.17-1.81]). However, among those who received family/friends financial support, income loss was no longer significantly associated with depression in both cycles, whether participants lost all their income (e.g., 2020: AOR 1.37 [0.78-2.40]), or some of their income (e.g., 2020: AOR 1.31 [0.86-1.99]).

Conclusions

Association between income loss and depression was moderated by receipt of family/friends financial support but not by receipt of government financial support. Financial support interventions may help to mitigate the negative effects of income loss on young adults mental health during periods of economic crisis.

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.

Estimation of Lockdowns' Impact on Well-Being in Selected Countries: An Application of Novel Bayesian Methods and Google Search Queries Data

Lockdowns introduced in connection with the COVID-19 pandemic have had a significant impact on societies from an economic, psychological, and health perspective. This paper presents estimations of their impact on well-being, understood both from the perspective of mental health and considering economic security and similar factors. This is not an easy task because well-being is influenced by numerous factors and the changes happen dynamically. Moreover, there are some obstacles when using the control group. However, other studies show that in certain cases it is possible to approximate selected phenomena with Google search queries data. Secondly, the econometric issues related to the suitable modeling of such a problem can be solved, for example, by using Bayesian methods. In particular, herein the recently gaining in popularity Bayesian structural time series and Bayesian dynamic mixture models are used. Indeed, these methods have not been used in social sciences extensively. However, in the fields where they have been used, they have been very efficient. Especially, they are useful when short time series are analyzed and when there are many variables that potentially have a significant explanatory impact on the response variable. Finally, 15 culturally different and geographically widely scattered countries are analyzed (i.e., Belgium, Brazil, Canada, Chile, Colombia, Denmark, France, Germany, Italy, Japan, Mexico, the Netherlands, Spain, Sweden, and the United Kingdom). Little evidence of any substantial changes in the Internet search intensity on terms connected with negative aspects of well-being and mental health issues is found. For example, in Mexico, some evidence of a decrease in well-being after lockdown was found. However, in Italy, there was weak evidence of an increase in well-being. Nevertheless, the Bayesian structural time series method has been found to fit the data most accurately. Indeed, it was found to be a superior method for causal analysis over the commonly used difference-in-differences method or Bayesian dynamic mixture models.

Characterizing Help-Seeking Searches for Substance Use Treatment From Google Trends and Assessing Their Use for Infoveillance: Longitudinal Descriptive and Validation Statistical Analysis

BACKGROUND

There is no recognized gold standard method for estimating the number of individuals with substance use disorders (SUDs) seeking help within a given geographical area. This presents a challenge to policy makers in the effective deployment of resources for the treatment of SUDs. Internet search queries related to help seeking for SUDs using Google Trends may represent a low-cost, real-time, and data-driven infoveillance tool to address this shortfall in information.

OBJECTIVE

This paper assesses the feasibility of using search query data related to help seeking for SUDs as an indicator of unmet treatment needs, demand for treatment, and predictor of the health harms related to unmet treatment needs. We explore a continuum of hypotheses to account for different outcomes that might be expected to occur depending on the demand for treatment relative to the system capacity and the timing of help seeking in relation to trajectories of substance use and behavior change.

METHODS

We used negative binomial regression models to examine temporal trends in the annual SUD help-seeking internet search queries from Google Trends by US state for cocaine, methamphetamine, opioids, cannabis, and alcohol from 2010 to 2020. To validate the value of these data for surveillance purposes, we then used negative binomial regression models to investigate the relationship between SUD help-seeking searches and state-level outcomes across the continuum of care (including lack of care). We started by looking at associations with self-reported treatment need using data from the National Survey on Drug Use and Health, a national survey of the US general population. Next, we explored associations with treatment admission rates from the Treatment Episode Data Set, a national data system on SUD treatment facilities. Finally, we studied associations with state-level rates of people experiencing and dying from an opioid overdose, using data from the Agency for Healthcare Research and Quality and the CDC WONDER database.

RESULTS

Statistically significant differences in help-seeking searches were observed over time between 2010 and 2020 (based on P<.05 for the corresponding Wald tests). We were able to identify outlier states for each drug over time (eg, West Virginia for both opioids and methamphetamine), indicating significantly higher help-seeking behaviors compared to national trends. Results from our validation analyses across different outcomes showed positive, statistically significant associations for the models relating to treatment need for alcohol use, treatment admissions for opioid and methamphetamine use, emergency department visits related to opioid use, and opioid overdose mortality data (based on regression coefficients having P≤.05).

CONCLUSIONS

This study demonstrates the clear potential for using internet search queries from Google Trends as an infoveillance tool to predict the demand for substance use treatment spatially and temporally, especially for opioid use disorders.

What's hot and what's not in lay psychology: Wikipedia's most-viewed articles

We studied views of articles about psychology on 10 language editions of Wikipedia from July 1, 2015, to January 6, 2021. We were most interested in what psychology topics Wikipedia users wanted to read, and how the frequency of views changed during the COVID-19 pandemic and lockdowns. Our results show that the topics of interest to people seeking psychological knowledge changed during the pandemic. In addition, the interests differ noticeably among the languages. We made two important observations. The first was that during the pandemic, people in most countries looked for new ways to manage their stress without resorting to external help. This is understandable, given the increased stress of lockdown and the limited amount of professional help available. We also found that academic topics, typically covered in university classes, experienced a substantial drop in traffic, which could be indicative of issues with remote teaching.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12144-022-03826-0.

Does trust in government improve Covid-19’s crisis management?

Countries have adopted several measures to control the spread of Covid-19. However, substantial differences remain in terms of performance in controlling the virus, potentially due to heterogeneity in citizen engagement with government measures. Although the literature documents the effects of trust in government on compliance with health restrictions related to the health crisis, little is said about the direct effect of trust in government on managing the Covid-19 crisis, defined as the number of cases and deaths. Drawing on this observation, this paper seeks to analyze the effect of pre–crisis ties, particularly trust in government, on crisis management, proxied by the number of Covid-19 cases and deaths per million population. We examine this question based on a sample of 41 countries for which data are available and using the Ordinary Least Squares (OLS) method. Results reveal that a high level of trust in government predicts better crisis management in terms of relatively low levels of cases and deaths. These results, which successfully pass a series of robustness tests, may vary according to level of contamination and increase with time. This paper, therefore, suggests that building trust between the public and the authorities, essentially governments and citizens, is essential for crisis management, taking the example of the Covid-19 pandemic.

Life under stay-at-home orders: a panel study of change in social interaction and emotional wellbeing among older Americans during COVID-19 pandemic

BACKGROUND

Recent research has shown the mental health consequence of social distancing during the COVID-19 pandemic, but longitudinal data are relatively scarce. It is unclear whether the pattern of isolation and elevated stress seen at the beginning of the pandemic persists over time. This study evaluates change in social interaction over six months and its impact on emotional wellbeing among older adults.

METHODS

We drew data from a panel study with six repeated assessments of social interaction and emotional wellbeing conducted monthly May through October 2020. The sample included a total of 380 White, Black and Hispanic participants aged 50 and over, of whom 33% had low income, who residing in fourteen U.S. states with active stay-at-home orders in May 2020. The analysis examined how change in living arrangement, in-person interaction outside the household, quality of relationship with family and friends, and perceived social support affected trajectories of isolation stress, COVID worry and sadness.

RESULTS

While their living arrangements (Odds Ratio [OR] = 0.95, 95% Confidence Interval [CI] = 0.87, 1.03) and relationship quality (OR = 0.94, 95% CI = 0.82, 1.01) remained stable, older adults experienced fluctuations in perceived social support (linear Slope b = -1.42, s.e. = 0.16, p < .001, quadratic slope b = 0.50, s.e. = 0.08, p < .001, cubic slope b = -0.04, s.e. = 0.01, p < .001) and increases in in-person conversations outside the household (OR = 1.19, 95% CI = 1.09, 1.29). Living with a spouse/partner stabilized isolation stress (change in linear slope b = 1.16, s.e. = 0.48, p < .05, in quadratic slope b = -0.62, s.e. = 0.26, p < .05, and in cubic slope = 0.09, s.e. = 0.04, p < .05) and COVID worry (change in quadratic slope b = -0.66, s.e. = 0.32, p < .05 and in cubic slope = 0.09, s.e. = 0.04, p < .05) over time. Individuals with better relationship quality with friends had decreased sadness over time (OR = 0.90, 95% CI = 0.82, 0.99). Changes in social support were associated with greater fluctuations in isolation stress and COVID worry.

CONCLUSIONS

During the pandemic, social interactions are protective and lack of stability in feeling supported makes older adults vulnerable to stress. Efforts should focus on (re)building and maintaining companionship and support to mitigate the pandemic's negative impact.

Financial Distress and Psychological Well-Being During the COVID-19 Pandemic

Objective: We examine the impact of financial distress caused by the COVID-19 pandemic on mental health and psychological well-being.

Methods: We analyze cross-sectional survey data (n = 2,545) from the Life during Pandemic study in Chile. We estimate linear probability models to analyze the relationship between economic fragility, financial distress, and psychological well-being.

Results: Our findings show unemployment and income loss are highly predictive of experiencing a range of financial problems, such as a lack of savings, as well as difficulties paying bills, consumer debt, and mortgage loans. In turn, financial distress leads to a higher prevalence of poor well-being and mental health deterioration, and sleep problems.

Conclusion: Expansion of mental health assistance services are needed, as new diagnosis of mental health conditions has increased, but treatment has not, pointing to a barrier in the access to some mental health care services during the pandemic. Policies designed with the objective of improving financial education are necessary to increase precautionary savings and financial resilience, and alleviate the psychological burden of debt in the future.

Lockdown Policies, Economic Support, and Mental Health: Evidence From the COVID-19 Pandemic in United States

During the COVID-19 pandemic, various lockdown policies were put in place by the governments in different countries and different levels, which effectively curbed the spread of the virus, but also cause substantial damage to the mental health of local residents. We use statistics provided by the Household Pulse Survey and OxCGRT between 23 April 2020 and 30 August 2021 to analyze the impact of lockdown on overall mental health levels in US states during the COVID-19 pandemic at the macro level. The results show that the lockdown policies implemented by the state governments lead to a deterioration in psychological conditions, and this relationship varies to some extent depending on the level of high-quality economic support, that the state governments implement to alleviate the symptoms of depression and anxiety associated with the lockdown. Therefore, we argue that although lockdown policies are necessary during the COVID-19 pandemic, further government efforts are needed to give high-quality economic and mental health support to mitigate the negative effects of lockdown on mental health.

Global trends of suicidal thought, suicidal ideation, and self-harm during COVID-19 pandemic: a systematic review

Background

Suicide is one of the leading causes of death. The current systematic review is done to know the trend of suicidal thoughts, suicidal ideation, and self-harm during COVID-19 pandemic.

Main text

The search was done by using PubMed, ScienceDirect, and Google Scholar databases. With the help of Mendeley portal, articles were retrieved on the basis of inclusion criteria like to know the risk factors, vulnerable group, complete article PDFs, prevention strategies, aims, results, and limitations. The shortlisted data from search was tabulated, and the PRISMA chart was framed based on the inclusion and exclusion criteria.

Result

Sixteen studies that satisfied the inclusion criteria were organized and selected. The variables and global scenario were considered in databases. It has been noticed that trends of suicidal thoughts, suicidal ideation, and self-harm remains the same in some countries like Japan, whereas in some countries like Bangladesh and France, trends of suicides had increased during the pandemic period. The probable cause could be lockdown, social isolation, and stoppage of recreational activities.

Conclusions

The trends of suicidal ideation, suicidal thoughts, and self-harm are more in vulnerable categories like health care professionals, university students, elderly individuals, and psychiatrically ill patients. In health care professional, it is due to the increased risk of contagion and watching deaths closely. In university students, it is due to the lack of recreational activities and social isolation. Among elderly, it is due to thinking themselves as overburden. The increase in suicidality in psychiatric ill patient admitted during COVID-19 pandemic is due to unknown cause.

Mental health concerns during the COVID-19 pandemic as revealed by helpline calls

Mental health is an important component of public health, especially in times of crisis. However, monitoring public mental health is difficult because data are often patchy and low-frequency^1-3. Here we complement established approaches by using data from helplines, which offer a real-time measure of 'revealed' distress and mental health concerns across a range of topics^4-9. We collected data on 8 million calls from 19 countries, focusing on the COVID-19 crisis. Call volumes peaked six weeks after the initial outbreak, at 35% above pre-pandemic levels. The increase was driven mainly by fear (including fear of infection), loneliness and, later in the pandemic, concerns about physical health. Relationship issues, economic problems, violence and suicidal ideation, however, were less prevalent than before the pandemic. This pattern was apparent both during the first wave and during subsequent COVID-19 waves. Issues linked directly to the pandemic therefore seem to have replaced rather than exacerbated underlying anxieties. Conditional on infection rates, suicide-related calls increased when containment policies became more stringent and decreased when income support was extended. This implies that financial relief can allay the distress triggered by lockdown measures and illustrates the insights that can be gleaned from the statistical analysis of helpline data.

The great crime recovery: Crimes against women during, and after, the COVID-19 lockdown in Mexico

This paper considers whether the COVID-19 stay-at-home order affected crimes targeting women. To answer this question, we use national municipal-level crime data from Mexico's National Public Security System. The NPSS reports sexual crimes, lapses in alimony, domestic violence, and femicides. Using the NPSS, we track monthly changes in crimes targeting women using an event-study design. Our results show that lapses in alimony, sexual crimes, and domestic violence follow a U-shaped trend. Each crime declined during the stay-at-home order, and then rose back to pre-COVID levels by October. Then, we analyze potential mechanisms for the reduction in crimes against women. We find that infection risk, victim-criminal match, and banning the sale of alcohol are related to higher declines in crime.