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Predicted probabilities of economic hardships during COVID-19 affecting depression complaints. (A) Marginal effect of workload change on feelings of depression. (B) Marginal effect of workload change on feelings of depression by ISEI level. (C) Marginal effect of income loss on feelings of depression. (D) Marginal effect of income loss on feelings of depression by ISEI level. (E). Marginal effect of job loss on feelings of depression. (F) Marginal effect of job loss on feelings of depression by ISEI level. Marginal effects are drawn from logit regressions with country-random intercepts. Estimates are adjusted for age, age squared, gender, migration background, partner (in household), employment status, firm size, urbanicity, and timing/survey week number. Interval bars represent 95% CIs (two-tailed tests).

Predicted probabilities of economic hardships during COVID-19 affecting depression complaints. (A) Marginal effect of workload change on feelings of depression. (B) Marginal effect of workload change on feelings of depression by ISEI level. (C) Marginal effect of income loss on feelings of depression. (D) Marginal effect of income loss on feelings of depression by ISEI level. (E). Marginal effect of job loss on feelings of depression. (F) Marginal effect of job loss on feelings of depression by ISEI level. Marginal effects are drawn from logit regressions with country-random intercepts. Estimates are adjusted for age, age squared, gender, migration background, partner (in household), employment status, firm size, urbanicity, and timing/survey week number. Interval bars represent 95% CIs (two-tailed tests).

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Significance This study measures the impact of the COVID-19 lockdowns on workers’ economic hardship and mental health. In data representative of the active labor force, we document two interconnected layers of rapidly exacerbating inequalities. We find that occupational ranking is highly predictive of experiencing a range of instant economic hardsh...

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... control variables that are used to optimize our estimates of occupational effects yield several noteworthy associations with rapidly emerging mental health complaints (SI Appendix, Fig. S4). Net of the main ISEI association, being an employer instead of an employee, significantly increases the chance of depression complaints (+23.0 percentage points). Also, living in a large city significantly increases the likelihood of developing health anxiety (+8.1 percentage points), as contrasted with small cities or towns. ...
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... also tested a model that additionally controlled for respondents' history of depression or anxiety (SI Appendix, Fig. S4). Including this self-reported indicator of life course mental health noticeably attenuates the ISEI associations, yet they persist as strong significant predictors of having developed mental health complaints in the spring of 2020. This means that the steep occupational prestige gradients in the reported psychological well-being (Fig. ...
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... Hardship and Feelings of Depression. Multivariable models were fitted to test the hypothesized positive relationship between economic hardship during the COVID-19 lockdown and mental health complaints. The results for recent onset depressive feelings are plotted in Fig. 4, organized by economic hardship ...
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... shown in Fig. 4A, the predicted probabilities of depression feelings are substantially higher for workers who experienced a sudden decreased workload (28.8%) as compared to their counterparts who maintained stability in employment (20.2%). In other words, deviating from regular work hours during the COVID-19 economic crash yields a 1.5 relative risk of ...
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... feelings are substantially higher for workers who experienced a sudden decreased workload (28.8%) as compared to their counterparts who maintained stability in employment (20.2%). In other words, deviating from regular work hours during the COVID-19 economic crash yields a 1.5 relative risk of stating feelings of depression. The adjacent Fig. 4B predicts the marginal effects by occupational prestige level. While the gaps between the workload categories remain statistically nonsignificant within each level, the point estimates are noticeably higher and farther separated in the lowest ISEI tertiles. This suggests that the positive associations between experiencing a decreased ...
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... within each level, the point estimates are noticeably higher and farther separated in the lowest ISEI tertiles. This suggests that the positive associations between experiencing a decreased workload during the COVID-19 lockdowns and feelings of depression were somewhat stronger among the most vulnerable socioeconomic groups in the labor market. Fig. 4C plots the point estimates of the probability of depression feelings for income loss, holding maintaining a stable income during the lockdown as the reference category. Fig. 4C indicates a significantly (P < 0.001) higher chance of feelings of depression in the case of an instant loss of income (33.2%) as compared to maintaining income ...
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... a decreased workload during the COVID-19 lockdowns and feelings of depression were somewhat stronger among the most vulnerable socioeconomic groups in the labor market. Fig. 4C plots the point estimates of the probability of depression feelings for income loss, holding maintaining a stable income during the lockdown as the reference category. Fig. 4C indicates a significantly (P < 0.001) higher chance of feelings of depression in the case of an instant loss of income (33.2%) as compared to maintaining income (21.5%), net of the control variable matrices. Importantly, as shown in Fig. 4D, the effects vary in magnitude across occupational prestige levels. The probability estimates of ...
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... for income loss, holding maintaining a stable income during the lockdown as the reference category. Fig. 4C indicates a significantly (P < 0.001) higher chance of feelings of depression in the case of an instant loss of income (33.2%) as compared to maintaining income (21.5%), net of the control variable matrices. Importantly, as shown in Fig. 4D, the effects vary in magnitude across occupational prestige levels. The probability estimates of depression feelings for losing income are progressively higher at lower levels of ISEI. Furthermore, the predicted probability gap of depression feelings appears larger in the lower and middle ISEI tertiles (although not statistically ...
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... 4D, the effects vary in magnitude across occupational prestige levels. The probability estimates of depression feelings for losing income are progressively higher at lower levels of ISEI. Furthermore, the predicted probability gap of depression feelings appears larger in the lower and middle ISEI tertiles (although not statistically significant). Fig. 4 E and F presents the main effect and modification by occupational prestige level, respectively, of experiencing job loss on reporting feeling depressed. We find that losing one's job during the COVID-19 economic crash is predictive of a 16.6 percentage point higher predicted probability of feelings of depression than job retention ...
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... adjusted for timing of the survey (T) through its week number. The significant associations between ISEI and mental health complaints persisted after further adjusting the prediction models of mental health indicators for respondents' history of depression or anxiety. Slight deviations from these matrices are indicated accordingly in SI Appendix, Fig. ...

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... The current study draws upon the theoretical framework of the Risk Information Seeking and Processing (RISP) model [10] in examining the relationship between media use, emotions, perceived risks, and preventive behavior. The RISP model aims to understand how individuals seek, process, and utilize risk information in the context of health communication. ...
... The RISP model proposes various elements that may influence how individuals search for and comprehend risk information, as well as how these processes ultimately shape the behaviors individuals may choose when confronted with a particular health risk. The model predicts that people who engage in more effortful information-seeking and processing are more likely to develop risk-related cognitions, attitudes, and behaviors that are more stable over time [10]. ...
... According to the RISP model, motivations for information-seeking interact with perceptions of different risk communication channels to shape how individuals interpret risk information [10]. Risk information delivered via the media during major incidents may affect emotional responses and risk perceptions [24]. ...
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As a result of the COVID-19 pandemic, media consumption has begun playing a more significant role in shaping public perceptions and well-being. The current study examines the effects of risk perception, economic situation, and negative emotions during the COVID-19 pandemic on preventive behaviors, while focusing on the mediating role of media exposure levels. An online survey was conducted during the 2020 outbreak of COVID-19 in Israel. SEM analysis results show that during the pandemic, media exposure increased with negative emotions levels, increased with higher exposure to the pandemic and increased as the economic impact of the pandemic increased. In addition, preventive behavior increased with media exposure. Moreover, the media exposure variable was found to mediate the effect of negative emotions and of the perceived risk of being infected with coronavirus on preventive behavior. Implications for government policy are discussed.
... Our study has various implications, both theoretical and practical. For the theoretical part, combined with previous findings Sun & Zhou, 2023;Witteveen & Velthorst, 2020), we indicated that adolescents' symptoms could be stable across these three trauma exposures, while the negative emotions play an important part in their network structure. Thus, theoretical studies could be conducted in the future to investigate more precise differences between adolescents and adults and the underlying reasons in this field. ...
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Objective: The aim of this study is to conduct network analysis to identify the posttraumatic stress disorder (PTSD) symptoms network structures in adolescents across three types of trauma events. Method: After screening 20,802 students aged 10–18 years old from 27 schools, our analysis enrolled 2,234 traumatized students who were exposed to accidents (n = 622), natural disasters (n = 211), and any severe disease (n = 1,401). We conducted a network analysis to compare the PTSD symptom structures across three types of trauma events. Results: Our findings reveal that negative emotional symptoms, such as trauma-related negative emotions, are central symptoms in adolescents across three exposures. Strong connections (i.e., trauma-related amnesia [D1] and blame of self or others [D3]) in the network were observed in the accident exposure group. Furthermore, the overall network structures in adolescents may be across exposures while the strength in edges varied in different traumas. Negative connections (i.e., nightmares [B2] and blame of self or others [D3]) showed up in disease and disaster exposure groups, while there was no negative connection in the accident exposure group. Conclusions: Future studies should pay more attention to central symptoms like negative trauma-related emotions, which could be a target symptom of PTSD related to accidents, natural disasters, and any severe disease among adolescents.
... A large body of evidence suggests that a decrease in economic conditions is associated with an increase in suicide rates [24,25]. The research conducted by Witteveen and Velthorst [26] shows that losing a job involuntarily without warning increases the likelihood of experiencing depressive or anxious symptoms. Babiak [27] found that employed people are less likely to engage in violent behavior, possibly because they are afraid of losing their jobs. ...
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... Financial stress is considered a risk factor for adverse mental health. One study from Thailand found that the risk of depressive symptoms or anxiety doubled among those who perceived financial stress in the pandemic [29], and this is also supported by other studies [30][31][32][33]. Although the absolute level of PIPS regarding the people's own financial situation was low compared to PIPS in other domains, our findings on socioeconomic inequalities in this respect can help identify target groups that could particularly benefit from financial support or regulations protecting employees from job and income loss in pandemic situations in order to prevent financial stress. ...
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Background Psychosocial stress is considered a risk factor for physical and mental ill-health. Evidence on socioeconomic inequalities with regard to the psychosocial consequences of the COVID-19 pandemic in Germany is still limited. We aimed to investigate how pandemic-induced psychosocial stress (PIPS) in different life domains differed between socioeconomic groups. Methods Data came from the German Corona-Monitoring nationwide study – wave 2 (RKI-SOEP-2, November 2021–February 2022). PIPS was assessed using 4-point Likert scales with reference to the following life domains: family, partnership, own financial situation, psychological well-being, leisure activity, social life and work/school situation. Responses were dichotomised into “not stressed/slightly stressed/rather stressed” (0) versus “highly stressed” (1). The sample was restricted to the working-age population in Germany (age = 18–67 years, n = 8,402). Prevalence estimates of high PIPS were calculated by sex, age, education and income. Adjusted prevalence ratios (PRs) were estimated using Poisson regression to investigate the association between education/income and PIPS; high education and income were the reference groups. Results The highest stress levels were reported in the domains social life and leisure activity. Women and younger participants reported high stress levels more frequently. The highest inequalities were found regarding people’s own financial situation, and PIPS was higher in low vs. high income groups (PR 5.54, 95% CI 3.61–8.52). Inequalities were also found regarding partnerships with higher PIPS in low vs. high education groups (PR 1.68, 95% CI 1.13–2.49) – and psychological well-being with higher PIPS in low vs. high income groups (PR 1.52, 95% CI 1.14–2.04). Conclusion Socioeconomic inequalities in PIPS were found for different life domains. Generally, psychosocial support and preventive interventions to help people cope with stress in a pandemic context should be target-group-specific, addressing the particular needs and circumstances of certain socioeconomic groups.
... It has been observed that, although most people had adjusted to COVID-19, levels of anxiety, depression, and stress remained high for respondents who experienced a deterioration in income. The studies also confirm that anxiety, depression, and stress levels were high for economically vulnerable sections of the population [23,24] particularly in developing countries [25][26][27]. ...
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The COVID-19 pandemic has left an indelible mark on societies worldwide, challenging governments to respond swiftly and effectively to mitigate its impact. India, with its vast population and complex healthcare landscape, faced unique challenges in formulating and implementing a pandemic response strategy. The article examines India's policy response to the COVID-19 pandemic and explores the valuable lessons it offers for shaping a more resilient and prepared society in a post-COVID world. It provides a comprehensive analysis of India's multifaceted approach to managing the pandemic, highlighting key elements such as lockdowns, testing and contact tracing, healthcare infrastructure, vaccination drives, and economic relief measures. By delving into both the successes and shortcomings of these policies, it seeks to extract valuable insights for policymakers and public health officials globally. As the world transitions into a post-COVID era, the lessons learned from India's experience offer a roadmap for building stronger healthcare systems, improving disaster preparedness, and enhancing social safety nets. The article underscores the importance of proactive governance, community engagement, data-driven decision-making, and international collaboration in the face of global health crises. The paper demonstrates that India's journey through the pandemic provides a wealth of knowledge that can inform policy development, foster greater resilience, and help societies better navigate the uncertainties of a post-COVID world. By reflecting on the successes and challenges of India's response, this article offers actionable insights for shaping a more equitable, sustainable, and prepared society in the wake of the COVID-19 pandemic.
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... The coronavirus disease 2019 (COVID- 19) pandemic and societal measures imposed to contain its spread have been accompanied by severe socio-economic and health-related burdens worldwide [1][2][3]. A large body of literature on the pandemic's initial effects, declared a global pandemic accompanied by recommendations for social isolation in March 2020 [4], shows an increase in population-level anxiety, depression, psychological distress, suicidal ideation, and loneliness [5][6][7][8][9][10][11], with most severe and enduring impairments in individuals of younger age, female sex, and lower socio-economic status (SES) [7,10,[12][13][14][15][16][17][18][19][20][21][22]. The majority of these studies has focused on identifying the role of demographic characteristics and socioeconomic living conditions as risk factors for mental health challenges. ...
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The coronavirus disease 2019 (COVID-19) pandemic was accompanied by an increase in mental health challenges including depression, stress, loneliness, and anxiety. Common genetic variants can contribute to the risk for psychiatric disorders and may present a risk factor in times of crises. However, it is unclear to what extent polygenic risk played a role in the mental health response to the COVID-19 pandemic. In this study, we investigate whether polygenic scores (PGSs) for mental health-related traits can distinguish between four resilience-vulnerability trajectories identified during the COVID-19 pandemic and associated lockdowns in 2020/21. We used multinomial regression in a genotyped subsample (n = 1316) of the CovSocial project. The most resilient trajectory characterized by the lowest mental health burden and the highest recovery rates served as the reference group. Compared to this most resilient trajectory, a higher value on the PGS for the well-being spectrum decreased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.3%). Conversely, a higher value on the PGS for neuroticism increased the odds for individuals to be in one of the more vulnerable trajectories (adjusted R-square = 0.2%). Latent change in mental health burden extracted from the resilience-vulnerability trajectories was not associated with any PGS. Although our findings support an influence of PGS on mental health during COVID-19, the small added explained variance suggests limited utility of such genetic markers for the identification of vulnerable individuals in the general population.
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... The number of people complaining of stress, depression, and lethargy was also found to increase as economic difficulties overlapped with the ongoing instability, including infection risk. Studies conducted in six European countries illustrated that economic difficulties caused by unemployment, reduced incomes, and shortened working hours adversely affected mental health [9]. While the deepening employment insecurity due to COVID-19 was strongly associated with depression in the United States [10]. ...
... Since financial stress affects mental health, even in COVID-19 situations there have been many discussions about whether financial support, as well as psychological intervention, could help reduce anxiety and depression in the general population [9,11,26]. Small business owners, self-employed people, and workers in unstable jobs who had experienced various difficulties due to social distancing and business restriction policies during COVID-19 showed a significant improvement in negative mental health states in some studies [9,27,28]. In light of these prior studies, the present research sought to analyse how implementing South Korea's financial assistance program affected mental health during the COVID-19 pandemic and explore how that effect varied by employment status. ...
... Since financial stress affects mental health, even in COVID-19 situations there have been many discussions about whether financial support, as well as psychological intervention, could help reduce anxiety and depression in the general population [9,11,26]. Small business owners, self-employed people, and workers in unstable jobs who had experienced various difficulties due to social distancing and business restriction policies during COVID-19 showed a significant improvement in negative mental health states in some studies [9,27,28]. In light of these prior studies, the present research sought to analyse how implementing South Korea's financial assistance program affected mental health during the COVID-19 pandemic and explore how that effect varied by employment status. ...
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Background COVID-19 has created tensions across different sectors of the society, but the impact has been unequal. Vulnerable people have been most affected, especially those with insecure employment and who have experienced economic hardships due to unemployment and lost wages. The combination of social change and economic hardships due to the pandemic increases the risk of poor mental health. Some countries have utilized financial assistance to alleviate economic hardships caused by COVID-19, and in South Korea, the central and local governments have implemented COVID-19 financial assistance. This study analysed the impact of financial assistance on mental health associated with working status during the COVID-19 pandemic in South Korea. Methods The participants of this study were randomly selected from residents of Gyeonggi-do after being proportionally allocated by resident registration population status. A total of 1,000 adult males and females aged 19 years or older in Gyeonggi-do who received financial assistance from the central and local governments were selected. A retrospective pre–post-study design was applied, and mental health surveys including the Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item scale (GAD-7) were applied. Results The results show that depression scores averaged 5.5 and anxiety scores averaged 4.4 before COVID-19 Financial Assistance. It is similar to the national average of 5.1 and 4.5 respectively at that time. After the assistance, depression scores dropped to 4.5, and anxiety scores dropped to 3.2. Before the assistance, depression and anxiety were higher among temporary day labourers with less job security, and they showed the most significant improvement in mental health. For full-time workers, there was no significant change in anxiety or depression after receiving the assistance. Conclusions Financial assistance can provide material resources and also positively affect mental health. In particular, it had a greater impact on the relatively vulnerable groups, such as those in unstable employment.