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null (Ed.)Background The COVID-19 pandemic has caused several disruptions in personal and collective lives worldwide. The uncertainties surrounding the pandemic have also led to multifaceted mental health concerns, which can be exacerbated with precautionary measures such as social distancing and self-quarantining, as well as societal impacts such as economic downturn and job loss. Despite noting this as a “mental health tsunami”, the psychological effects of the COVID-19 crisis remain unexplored at scale. Consequently, public health stakeholders are currently limited in identifying ways to provide timely and tailored support during these circumstances. Objective Our study aims to provide insights regarding people’s psychosocial concerns during the COVID-19 pandemic by leveraging social media data. We aim to study the temporal and linguistic changes in symptomatic mental health and support expressions in the pandemic context. Methods We obtained about 60 million Twitter streaming posts originating from the United States from March 24 to May 24, 2020, and compared these with about 40 million posts from a comparable period in 2019 to attribute the effect of COVID-19 on people’s social media self-disclosure. Using these data sets, we studied people’s self-disclosure on social media in terms of symptomatic mental health concerns and expressions of support. We employed transfer learning classifiers that identified the social media language indicative of mental health outcomes (anxiety, depression, stress, and suicidal ideation) and support (emotional and informational support). We then examined the changes in psychosocial expressions over time and language, comparing the 2020 and 2019 data sets. Results We found that all of the examined psychosocial expressions have significantly increased during the COVID-19 crisis—mental health symptomatic expressions have increased by about 14%, and support expressions have increased by about 5%, both thematically related to COVID-19. We also observed a steady decline and eventual plateauing in these expressions during the COVID-19 pandemic, which may have been due to habituation or due to supportive policy measures enacted during this period. Our language analyses highlighted that people express concerns that are specific to and contextually related to the COVID-19 crisis. Conclusions We studied the psychosocial effects of the COVID-19 crisis by using social media data from 2020, finding that people’s mental health symptomatic and support expressions significantly increased during the COVID-19 period as compared to similar data from 2019. However, this effect gradually lessened over time, suggesting that people adapted to the circumstances and their “new normal.” Our linguistic analyses revealed that people expressed mental health concerns regarding personal and professional challenges, health care and precautionary measures, and pandemic-related awareness. This study shows the potential to provide insights to mental health care and stakeholders and policy makers in planning and implementing measures to mitigate mental health risks amid the health crisis.more » « less
Throughout history, urban agriculture practitioners have adapted to various challenges by continuing to provide food and social benefits. Urban gardens and farms have also responded to sudden political, economic, ecological, and social crises: wartime food shortages; urban disinvestment and property abandonment; earthquakes and floods; climate-change induced weather events; and global economic disruptions. This paper examines the effects on, and responses by, urban farms and gardens to the COVID-19 pandemic. The paper is based on data collected in the summer of 2020 at the onset of the pandemic when cities were struggling with appropriate responses to curb its spread. It builds on an international research project (FEW-meter) that developed a methodology to measure material and social benefits of urban agriculture (UA) in five countries (France, Germany, Poland, UK and USA) over two growing seasons, from a Food-Energy-Water nexus perspective. We surveyed project partners to ascertain the effects of COVID-19 on those gardens and farms and we interviewed policy stakeholders in each country to investigate the wider impacts of the pandemic on UA. We report the results with respect to five key areas: (1) garden accessibility and service provision during the pandemic; (2) adjustments to operational arrangements; (3) effects on production; (4) support for urban farms and gardens through the pandemic; and (5) thoughts about the future of urban agriculture in the recovery period and beyond. The paper shows that the pandemic resulted in multiple challenges to gardens and farms including the loss of ability to provide support services, lost income, and reductions in output because of reduced labor supply. But COVID-19 also created several opportunities: new markets to sell food locally; more time available to gardeners to work in their allotments; and increased community cohesion as neighboring gardeners looked out for one another. By illustrating the range of challenges faced by the pandemic, and strategies to address challenges used by different farms and gardens, the paper illustrates how gardens in this pandemic have adapted to become more resilient and suggests lessons for pandemic recovery and longer-term planning to enable UA to respond to future public health and other crises.more » « less
Despite considerable social scientific attention to the impacts of the COVID-19 pandemic on urbanized areas, very little research has examined its impact on rural populations. Yet rural communities—which make up tens of millions of people from diverse backgrounds in the United States—are among the nation’s most vulnerable populations and may be less resilient to the effects of such a large-scale exogenous shock. We address this critical knowledge gap with data from a new survey designed to assess the impacts of the pandemic on health-related and economic dimensions of rural well-being in the North American West. Notably, we find that the effects of the COVID-19 pandemic on rural populations have been severe, with significant negative impacts on unemployment, overall life satisfaction, mental health, and economic outlook. Further, we find that these impacts have been generally consistent across age, ethnicity, education, and sex. We discuss how these findings constitute the beginning of a much larger interdisciplinary COVID-19 research effort that integrates rural areas and pushes beyond the predominant focus on cities and nation-states.
The COVID-19 pandemic has resulted in heightened levels of depression, anxiety, and other mental health issues due to sudden changes in daily life, such as economic stress, social isolation, and educational irregularity. Accurately assessing emotional and behavioral changes in response to the pandemic can be challenging, but it is essential to understand the evolving emotions, themes, and discussions surrounding the impact of COVID-19 on mental health.
This study aims to understand the evolving emotions and themes associated with the impact of COVID-19 on mental health support groups (eg, r/Depression and r/Anxiety) on Reddit (Reddit Inc) during the initial phase and after the peak of the pandemic using natural language processing techniques and statistical methods.
This study used data from the r/Depression and r/Anxiety Reddit communities, which consisted of posts contributed by 351,409 distinct users over a period spanning from 2019 to 2022. Topic modeling and Word2Vec embedding models were used to identify key terms associated with the targeted themes within the data set. A range of trend and thematic analysis techniques, including time-to-event analysis, heat map analysis, factor analysis, regression analysis, and k-means clustering analysis, were used to analyze the data.
The time-to-event analysis revealed that the first 28 days following a major event could be considered a critical window for mental health concerns to become more prominent. The theme trend analysis revealed key themes such as economic stress, social stress, suicide, and substance use, with varying trends and impacts in each community. The factor analysis highlighted pandemic-related stress, economic concerns, and social factors as primary themes during the analyzed period. Regression analysis showed that economic stress consistently demonstrated the strongest association with the suicide theme, whereas the substance theme had a notable association in both data sets. Finally, the k-means clustering analysis showed that in r/Depression, the number of posts related to the “depression, anxiety, and medication” cluster decreased after 2020, whereas the “social relationships and friendship” cluster showed a steady decrease. In r/Anxiety, the “general anxiety and feelings of unease” cluster peaked in April 2020 and remained high, whereas the “physical symptoms of anxiety” cluster showed a slight increase.
This study sheds light on the impact of COVID-19 on mental health and the related themes discussed in 2 web-based communities during the pandemic. The results offer valuable insights for developing targeted interventions and policies to support individuals and communities in similar crises.
The health impacts of climate change are substantial and represent a primary motivating factor to mitigate climate change. However, the health impacts in economic models that estimate the social cost of carbon dioxide (SC‐CO2) have generally been made in isolation from health experts and have never been rigorously evaluated. Version 3.10 of the Framework for Uncertainty, Negotiation and Distribution (FUND) model was used to estimate the health‐based portion of current SC‐CO2estimates across low‐, middle‐, and high‐income regions. In addition to the base model, three additional experiments assessed the sensitivity of these estimates to changes in the socio‐economic assumptions in the model. Economic impacts from adverse health outcomes represent ∼8.7% of current SC‐CO2estimates. The majority of these health impacts (74%) were attributable to diarrhea mortality (from both low‐ and high‐income regions) followed by diarrhea morbidity (12%) and malaria mortality (11%); no other health impact makes a meaningful contribution to SC‐CO2estimates in current economic models. The results of the socio‐economic experiments show that the health‐based portion of SC‐CO2estimates are highly sensitive to assumptions regarding income elasticity of health effects, income growth, and use of equity weights. Improving the health‐based portion of SC‐CO2estimates could have substantial impacts on magnitude of the SC‐CO2. Incorporating additional health impacts not previously included in estimates of SC‐CO2will be a critical component of model updates. This effort will be most successful through coordination between economists and health researchers and should focus on updating the form and function of concentration‐response functions.