The Relationship Between Age and Mental Health Among Adults in Iran During the COVID-19 Pandemic

Mental health of individuals with pre-existing mental illnesses at the beginning of the COVID-19 pandemic: results of the German National Cohort (NAKO)

Background

The COVID-19 pandemic prompted a range of studies on mental health, with mixed results. While numerous studies reported worsened conditions in individuals with pre-existing mental disorders, others showed resilience and stability in mental health. However, longitudinal data focusing on the German population are sparse, especially regarding effects of age and pre-existing mental disorders during the early stages of the pandemic.

Objectives

To assess the interplay between psychiatric history, age, and the timing of the pandemic, with a focus on understanding how these factors relate to the severity of depression and anxiety symptoms.

Methods

Exploratory analyses were based on 135,445 individuals aged 20-72 years from the German National Cohort (NAKO). Depressive and anxiety symptoms were assessed before and after the first wave of the pandemic. Inferential statistical analyses and negative binomial regression models were calculated.

Results

Persons with a self-reported psychiatric history exhibited comparable levels of depression and anxiety symptom severity after the first wave of the pandemic compared to the time before. In contrast, individuals without a psychiatric history, particularly those in their 20s to 40s, experienced an increase in mental health symptom severity during the first wave of the pandemic.

Limitations

Analyses focuses on the first wave of the pandemic, leaving the long-term mental health effects unexplored.

Conclusion

Future research should consider age-specific and mental-health-related factors when addressing global health crises. Additionally, it is important to explore factors influencing resilience and adaptation, aiming to develop targeted interventions and informed policies for effective mental health management during pandemics.

Exploring the Association Between Structural Racism and Mental Health: Geospatial and Machine Learning Analysis

BACKGROUND

Structural racism produces mental health disparities. While studies have examined the impact of individual factors such as poverty and education, the collective contribution of these elements, as manifestations of structural racism, has been less explored. Milwaukee County, Wisconsin, with its racial and socioeconomic diversity, provides a unique context for this multifactorial investigation.

OBJECTIVE

This research aimed to delineate the association between structural racism and mental health disparities in Milwaukee County, using a combination of geospatial and deep learning techniques. We used secondary data sets where all data were aggregated and anonymized before being released by federal agencies.

METHODS

We compiled 217 georeferenced explanatory variables across domains, initially deliberately excluding race-based factors to focus on nonracial determinants. This approach was designed to reveal the underlying patterns of risk factors contributing to poor mental health, subsequently reintegrating race to assess the effects of racism quantitatively. The variable selection combined tree-based methods (random forest) and conventional techniques, supported by variance inflation factor and Pearson correlation analysis for multicollinearity mitigation. The geographically weighted random forest model was used to investigate spatial heterogeneity and dependence. Self-organizing maps, combined with K-means clustering, were used to analyze data from Milwaukee communities, focusing on quantifying the impact of structural racism on the prevalence of poor mental health.

RESULTS

While 12 influential factors collectively accounted for 95.11% of the variability in mental health across communities, the top 6 factors-smoking, poverty, insufficient sleep, lack of health insurance, employment, and age-were particularly impactful. Predominantly, African American neighborhoods were disproportionately affected, which is 2.23 times more likely to encounter high-risk clusters for poor mental health.

CONCLUSIONS

The findings demonstrate that structural racism shapes mental health disparities, with Black community members disproportionately impacted. The multifaceted methodological approach underscores the value of integrating geospatial analysis and deep learning to understand complex social determinants of mental health. These insights highlight the need for targeted interventions, addressing both individual and systemic factors to mitigate mental health disparities rooted in structural racism.

Prevention and control of violence and aggression in football fans: Implications for sport psychologists, fans, and policymakers

This research was conducted to design an interpretive structural model of factors affecting the prevention and control of violence and aggression in football fans. The statistical population of this study was entirely composed of sport experts, executive managers, sociologists, and management professors in Iran. Thirteen individuals were accordingly selected as the research sample using non-probability purposeful sampling. The effective factors were identified through library study and reviewing the theoretical foundations and research background. Confirming the content validity of these factors by considering experts' opinions, 14 factors were finally identified. The interrelationships between the factors were determined using Interpretive Structural Modeling (ISM), and network analysis based on Decision Making and Trial Evaluation Laboratory (DEMATEL) was also employed to measure their importance, ranking them accordingly. The factors were categorized into four levels according to ISM. The highest level (first level) includes "match day service quality," "fair refereeing," "consolidation of social ties," and "cognitive reconstruction of fans." The second level contains "design, protection, and security of stadiums," "patterning and identification," and "use of calming techniques." "Awareness and informing" and "anger control training" belong to the third level, while the lowest level (fourth level) includes "media," "fan organizations," "laws, regulations, and security solutions," "moral education or persuasion," and "teaching communication skills to fans." Among them, the last level is fundamental, influencing the other factors. The results obtained in this work can be used as a basis for policymaking to reduce violence and aggression among football fans.

Coping Strategies, well-being and inequalities during the COVID-19 pandemic period

As a response to the outbreak of the COVID-19 pandemic, governments around the globe have carried on strict lockdown measures affecting millions of jobs, public life, and the well-being of people. This study examines people's subjective well-being, such as the perception of the economic situation and mental well-being, who made adjustments to cope with the earning losses. We estimate the well-being cost, which is the money required to compensate people because of the reduction in earnings or employment loss and the coping strategy followed to bring their well-being to the levels of those who have not adopted any coping strategy. We examine two outcomes; the perception of the economic situation and a mental well-being index. We employ data from the ERF COVID-19 MENA Monitor Surveys for Egypt, Jordan, Morocco and Tunisia. The results show that coping strategies with earning losses impact well-being and are associated with high costs. In most cases, the coping strategies of borrowing from banks and selling assets present the highest well-being costs. Furthermore, the estimates highlight significant discrepancies across gender and types of workers, such as those employed in the informal sector and temporary contracts.

Supplementary information

The online version contains supplementary material available at 10.1007/s12144-023-04710-1.

Challenges and Implications of the COVID-19 Pandemic on Mental Health: A Systematic Review

The measures put in place to contain the rapid spread of COVID-19 infection, such as quarantine, self-isolation, and lockdown, were supportive but have significantly affected the mental wellbeing of individuals. The primary goal of this study was to review the impact of COVID-19 on mental health. An intensive literature search was conducted using PsycINFO, PsyciatryOnline, PubMed, and the China National Knowledge Infrastructure (CNKI) databases. Articles published between January 2020 and June 2022 were retrieved and appraised. Reviews and retrospective studies were excluded. One hundred and twenty-two (122) relevant articles that fulfilled the inclusion criteria were finally selected. A high prevalence of anxiety, depression, insomnia, and post-traumatic stress disorders was reported. Alcohol and substance abuse, domestic violence, stigmatization, and suicidal tendencies have all been identified as direct consequences of lockdown. The eminent risk factors for mental health disorders identified during COVID-19 include fear of infection, history of mental illness, poor financial status, female gender, and alcohol drinking. The protective factors for mental health include higher income levels, public awareness, psychological counseling, social and government support. Overall, the COVID-19 pandemic has caused a number of mental disorders in addition to economic hardship. This strongly suggests the need to monitor the long-term impact of the COVID-19 pandemic on mental health.

The impact of the COVID-19 pandemic on the mental health of children with psychiatric diagnoses - multidimensional CCPCA Model

BACKGROUND

The study aimed to assess the severity of symptoms of anxiety and depression in children with previously diagnosed psychiatric disorders during the COVID-19 pandemic in Poland.

METHODS

Online questionnaires were used to investigate three groups of subjects: patients with a psychiatric diagnosis, primary school pupils, and children from children's homes. A total of 167 children with their parents or guardians participated in the study. In addition to basic statistics, a multidimensional Centroid Class Principal Component Analysis (CCPCA) model was used.

RESULTS

It was found that the strongest fear of the coronavirus was experienced by children from children's homes, while the most severe depressive symptoms and state anxiety were observed among patients diagnosed with psychiatric disorders. Parental care by assisting with school education and lack of close contact with other people (less than two metres) at parents/guardians' work had the most potent protective effect in reducing the fear of COVID-19.

CONCLUSIONS

There is a need for further research in children and adolescents to develop effective strategies for protecting their mental well-being when faced with social isolation or disease.

Mental health symptoms during the COVID-19 pandemic in developing countries: A systematic review and meta-analysis

Background

This systematic review aims to 1) summarize the prevalence of anxiety, depression, distress, insomnia, and PTSD in the adult population during the first year of the COVID pandemic in developing countries and 2) uncover and highlight the uneven distribution of research on mental health in all developing countries across regions.

Methods

Several literature databases were systemically searched for meta-analyses published by September 22, 2021, on the prevalence rates of mental health symptoms in developing countries worldwide. We meta-analysed the raw data of the individual empirical results from the previous meta-analysis papers in developing countries in different regions.

Results

The prevalence rates of mental health symptoms were summarized based on 341 empirical studies with a total of 1 704 072 participants from 40 out of 167 developing countries in Africa, Asia (East, Southeast, South, and West), Europe, and Latin America. Comparatively, Africa (39%) and West Asia (35%) had the worse overall mental health symptoms, followed by Latin America (32%). The prevalence rates of overall mental health symptoms of medical students (38%), general adult students (30%), and frontline health care workers (HCWs) (27%) were higher than those of general HCWs (25%) and general populations (23%). Among five mental health symptoms, distress (29%) and depression (27%) were the most prevalent. Interestingly, people in the least developing countries suffered less than those in emergent and other developing countries. The various instruments employed lead to result heterogeneity, demonstrating the importance of using the well-established instruments with the standard cut-off points (eg, GAD-7, GAD-2, and DASS-21 for anxiety, PHQ-9 and DASS-21 for depression, and ISI for insomnia).

Conclusions

The research effort on mental health in developing countries during COVID-19 has been highly uneven in the scope of countries and mental health outcomes. This meta-analysis, the largest on this topic to date, shows that the mental health symptoms are highly prevalent yet differ across regions. The accumulated systematic evidence from this study can help enable the prioritization of mental health assistance efforts to allocate attention and resources across countries and regions.

Predicting Managers' Mental Health Across Countries: Using Country-Level COVID-19 Statistics

Background

There is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship.

Objective

We aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics.

Methods

A two-wave online survey of 406 managers from 26 countries was performed in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ-9) symptoms.

Findings

We found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers' anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms.

Conclusions

Cumulative COVID-19 statistics predicted managers' anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the most suitable single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.

Meta-Regression on the Heterogenous Factors Contributing to the Prevalence of Mental Health Symptoms During the COVID-19 Crisis Among Healthcare Workers

Objective

This paper used meta-regression to analyze the heterogenous factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) in China under the COVID-19 crisis.

Method

We systematically searched PubMed, Embase, Web of Science, and Medrxiv and pooled data using random-effects meta-analyses to estimate the prevalence rates, and ran meta-regression to tease out the key sources of the heterogeneity.

Results

The meta-regression results uncovered several predictors of the heterogeneity in prevalence rates among published studies, including severity (e.g., above severe vs. above moderate, p < 0.01; above moderate vs. above mild, p < 0.01), type of mental symptoms (PTSD vs. anxiety, p = 0.04), population (frontline vs. general HCWs, p < 0.01), sampling location (Wuhan vs. Non-Wuhan, p = 0.04), and study quality (p = 0.04).

Conclusion

The meta-regression findings provide evidence on the factors contributing to the prevalence rate of mental health symptoms of the general and frontline healthcare workers (HCWs) to guide future research and evidence-based medicine in several specific directions.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=220592, identifier: CRD42020220592.

Meta-analytic evidence of depression and anxiety in Eastern Europe during the COVID-19 pandemic

Objective

To perform a systematic and meta-analysis on the prevalence rates of mental health symptoms including anxiety and depression during the COVID-19 pandemic in the general population in Eastern Europe, as well as three select sub-populations: students, general healthcare workers, and frontline healthcare workers.

Data sources

Studies in PubMed, Embase, Web of Science, PsycINFO, and medRxiv up to 6 February 2021.

Eligibility criteria and data analysis

Prevalence rates of mental health symptoms in the general population and key sub-populations during the COVID-19 pandemic in Eastern Europe. Data were pooled using a random-effects meta-analysis to estimate the prevalence rates of anxiety and depression.

Results

The meta-analysis identifies and includes 21 studies and 26 independent samples in Eastern Europe. Poland (n = 4), Serbia (n = 4), Russia (n = 3), and Croatia (n = 3) had the greatest number of studies. To our knowledge, no studies have been conducted in eleven Eastern European countries including Hungary, Slovakia, and Slovenia. The pooled prevalence of anxiety in 18 studies with 22 samples was 30% (95% CI: 24-37%) pooled prevalence of depression in 18 studies with 23 samples was 27% (95% CI: 21-34%).

Implications

The cumulative evidence from the meta-analysis reveals high prevalence rates of clinically significant symptoms during the COVID-19 pandemic in Eastern Europe. The findings suggest evidence of a potential mental health crisis in Eastern Europe during the ongoing COVID-19 pandemic. Our synthesis also reveals a relative lack of studies in certain Eastern European countries as well as high heterogeneities among the existing studies, calling for more effort to achieve evidence-based mental healthcare in Eastern Europe.