https://cronfa.swan.ac.uk/Record/cronfa54196/Download/54196__17493__47815979be224dde9a7b3f9b037ce7ec.pdf

Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science.

Background
During the COVID-19 pandemic general medical complications have received the most attention, whereas only few studies address the potential direct effect on mental health of SARS-CoV-2 and the neurotropic potential. Furthermore, the indirect effects of the pandemic on general mental health are of increasing concern, particularly since the SARS-CoV-1 epidemic (2002–2003) was associated with psychiatric complications.

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COVID-19 pandemic and mental health consequences: Systematic review of the current evidence.

Background Along with its high infectivity and fatality rates, the 2019 Corona Virus Disease (COVID-19) has caused universal psychosocial impact by causing mass hysteria, economic burden and financial losses. Mass fear of COVID-19, termed as “coronaphobia”, has generated a plethora of psychiatric manifestations across the different strata of the society. So, this review has been undertaken to define psychosocial impact of COVID-19. Methods Pubmed and GoogleScholar are searched with the following key terms- “COVID-19”, “SARS-CoV2”, “Pandemic”, “Psychology”, “Psychosocial”, “Psychitry”, “marginalized”, “telemedicine”, “mental health”, “quarantine”, “infodemic”, “social media” and” “internet”. Few news paper reports related to COVID-19 and psychosocial impacts have also been added as per context. Results Disease itself multiplied by forced quarantine to combat COVID-19 applied by nationwide lockdowns can produce acute panic, anxiety, obsessive behaviors, hoarding, paranoia, and depression, and post-traumatic stress disorder (PTSD) in the long run. These have been fueled by an “infodemic” spread via different platforms of social media. Outbursts of racism, stigmatization, and xenophobia against particular communities are also being widely reported. Nevertheless, frontline healthcare workers are at higher-risk of contracting the disease as well as experiencing adverse psychological outcomes in form of burnout, anxiety, fear of transmitting infection, feeling of incompatibility, depression, increased substance-dependence, and PTSD. Community-based mitigation programs to combat COVID-19 will disrupt children’s usual lifestyle and may cause florid mental distress. The psychosocial aspects of older people, their caregivers, psychiatric patients and marginalized communities are affected by this pandemic in different ways and need special attention. Conclusion For better dealing with these psychosocial issues of different strata of the society, psychosocial crisis prevention and intervention models should be urgently developed by the government, health care personnel and other stakeholders. Apt application of internet services, technology and social media to curb both pandemic and infodemic needs to be instigated. Psychosocial preparedness by setting up mental organizations specific for future pandemics is certainly necessary.

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Psychosocial impact of COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has caused enormous psychological impact worldwide. We conducted a systematic review and meta-analysis on the psychological and mental impact of COVID-19 among healthcare workers, the general population, and patients with higher COVID-19 risk published between 1 Nov 2019 to 25 May 2020. We conducted literature research using Embase, PubMed, Google scholar and WHO COVID-19 databases. Among the initial search of 9207 studies, 62 studies with 162,639 participants from 17 countries were included in the review. The pooled prevalence of anxiety and depression was 33% (95% confidence interval: 28%-38%) and 28% (23%-32%), respectively. The prevalence of anxiety and depression was the highest among patients with pre-existing conditions and COVID-19 infection (56% [39%-73%] and 55% [48%-62%]), and it was similar between healthcare workers and the general public. Studies from China, Italy, Turkey, Spain and Iran reported higher-than-pooled prevalence among healthcare workers and the general public. Common risk factors included being women, being nurses, having lower socioeconomic status, having high risks of contracting COVID-19, and social isolation. Protective factors included having sufficient medical resources, up-to-date and accurate information, and taking precautionary measures. In conclusion, psychological interventions targeting high-risk populations with heavy psychological distress are in urgent need.

The psychological and mental impact of coronavirus disease 2019 (COVID-19) on medical staff and general public - A systematic review and meta-analysis.

The aim of this paper was to review the literature on adolescent psychiatric disorders related to the COVID-19 pandemic and lockdown Stressful life events, extended home confinement, brutal grief, intrafamilial violence, overuse of the Internet and social media are factors that could influence the mental health of adolescents during this period The COVID-19 pandemic could result in increased psychiatric disorders such as Post-Traumatic Stress, Depressive, and Anxiety Disorders, as well as grief-related symptoms Adolescents with psychiatric disorders are at risk of a break or change in their care and management; they may experience increased symptoms The COVID-19 pandemic and lockdown may have a negative impact on the mental health of adolescents, although there is still no data on the long term impact of this crisis Adolescents' individual, familial, and social vulnerability, as well as individual and familial coping abilities, are factors related to adolescent mental health in times of crisis Adolescents are often vulnerable and require careful consideration by caregivers and healthcare system adaptations to allow for mental health support despite the lockdown Research on adolescent psychiatric disorders in times of pandemics is necessary, as such a global situation could be prolonged or repeated

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Adolescent psychiatric disorders during the COVID-19 pandemic and lockdown.

COVID-19 (Corona Virus Disease 2019) has significantly resulted in a large number of psychological consequences. The aim of this study is to explore the impacts of COVID-19 on people’s mental health, to assist policy makers to develop actionable policies, and help clinical practitioners (e.g., social workers, psychiatrists, and psychologists) provide timely services to affected populations. We sample and analyze the Weibo posts from 17,865 active Weibo users using the approach of Online Ecological Recognition (OER) based on several machine-learning predictive models. We calculated word frequency, scores of emotional indicators (e.g., anxiety, depression, indignation, and Oxford happiness) and cognitive indicators (e.g., social risk judgment and life satisfaction) from the collected data. The sentiment analysis and the paired sample t-test were performed to examine the differences in the same group before and after the declaration of COVID-19 on 20 January, 2020. The results showed that negative emotions (e.g., anxiety, depression and indignation) and sensitivity to social risks increased, while the scores of positive emotions (e.g., Oxford happiness) and life satisfaction decreased. People were concerned more about their health and family, while less about leisure and friends. The results contribute to the knowledge gaps of short-term individual changes in psychological conditions after the outbreak. It may provide references for policy makers to plan and fight against COVID-19 effectively by improving stability of popular feelings and urgently prepare clinical practitioners to deliver corresponding therapy foundations for the risk groups and affected people.

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The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users.

Background: During the COVID-19 pandemic, residential lockdowns were implemented in numerous cities in China to contain the rapid spread of the disease. Although these stringent regulations effectively slowed the spread of COVID-19, they may have posed challenges to the well-being of residents.
Objective: This study aims to explore the effects of residential lockdown on the subjective well-being (SWB) of individuals in China during the COVID-19 pandemic.
Methods: The sample consisted of 1790 Sina Weibo users who were residents of cities that imposed residential lockdowns, of which 1310 users (73.18%) were female, and 3580 users who were residents of cities that were not locked down (gender-matched with the 1790 lockdown residents). In both the lockdown and nonlockdown groups, we calculated SWB indicators during the 2 weeks before and after the enforcement date of the residential lockdown using individuals’ original posts on Sina Weibo. SWB was calculated via online ecological recognition, which is based on established machine learning predictive models.
Results: The interactions of time (before the residential lockdown or after the residential lockdown) × area (lockdown or nonlockdown) in the integral analysis (N=5370) showed that after the residential lockdown, compared with the nonlockdown group, the lockdown group scored lower in some negative SWB indicators, including somatization (F1,5368=13.593, P .05), while that of residents in developed areas changed.
Conclusions: These findings increase our understanding of the psychological impact and cost of residential lockdown during an epidemic. The more negative changes in the SWB of residents in developed areas imply a greater need for psychological intervention under residential lockdown in such areas.

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Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis

Background: Many methods have been proposed to automatically identify the presence of mental illness, but these have mostly focused on one specific mental illness. In some non-professional scenarios, it would be more helpful to understand an individual's mental health status from all perspectives. Methods: We recruited 100 participants. Their multi-dimensional psychological symptoms of mental health were evaluated using the Symptom Checklist 90 (SCL-90) and their facial movements under neutral stimulation were recorded using Microsoft Kinect. We extracted the time-series characteristics of the key points as the input, and the subscale scores of the SCL-90 as the output to build facial prediction models. Finally, the convergent validity, discriminant validity, criterion validity, and the split-half reliability were respectively assessed using a multitrait-multimethod matrix and correlation coefficients. Results: The correlation coefficients between the predicted values and actual scores were 0.26 and 0.42 (P < 0.01), which indicated good criterion validity. All models except depression had high convergent validity but low discriminant validity. Results also indicated good levels of split-half reliability for each model [from 0.516 (hostility) to 0.817 (interpersonal sensitivity)] (P < 0.001). Conclusion: The validity and reliability of facial prediction models were confirmed for the measurement of mental health based on the SCL-90. Our research demonstrated that fine-grained aspects of mental health can be identified from the face, and provided a feasible evaluation method for multi-dimensional prediction models.

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Identifying Psychological Symptoms Based on Facial Movements.

Backgrounds: With the rapid spread of COVID-19, strict home confinement has been implemented in most parts of Chinese regions. Millions of people were not allowed to leave their homes except for special reasons. Home confinement plays an essential role in curbing pandemic and promoting preventive behaviors, but it may affect individuals' mental health as well. Objects: The objective of this study was to explore the psychological impacts of home confinement. Materials and Methods: We collected more than 150,360 Weibo messages from 5,370 Chinese active users, and then extracted psycho-linguistic features from these messages. Psycho-linguistic analysis was carried out using the 2 (confinement vs. non-confinement) x 2 (before vs. after confinement) repeated measure analysis of variance (RM ANOVA). Results: The results showed that the frequency of positive emotion words was remarkably decreased during home confinement [F (1,5368) = 7.926, p = 0.005, eta2 = 0.001]. In high-endemic subgroup, home confinement also reduced the frequency of exclusion words [F (1,3445) = 4.518, p = 0.034, eta2 = 0.001] and inhibition words [F (1,3445) = 10.154, p = 0.001, eta2 = 0.003]. Conclusion: Home confinement caused a decline in the use of positive emotion words. This indicates that home confinement can increase the frequency of negative emotions. The changes of exclusion words and inhibition words in high-endemic areas may be related to the high epidemic threat and the urgent need for social distancing in these areas.

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Exploring the Psychological Effects of COVID-19 Home Confinement in China: A Psycho-Linguistic Analysis on Weibo Data Pool

Adolescents who face social distress in real life are often accompanied by interaction anxiousness. To avoid direct social activities, they prefer to indulge in social networks to satisfy their psychological needs for interpersonal communication. Sina Weibo, China's leading social media platform, has a markedly young user base. It provides a rich sample of adolescents with interaction anxiousness and conditions for real-time monitoring. In this study, various word categories, such as perception of spatial distance and positional relationships, morality, and emotion, showed a significant relationship with interaction anxiousness. Furthermore, prediction models were established based on the original Weibo data of 839 active Sina Weibo users through a variety of machine learning algorithms to predict the scores of users' interaction anxiousness. The results showed that the performance of the prediction model established by the fully connected neural network was the best, and both criterion validity and split-half reliability were good (rcriterionvalidity = 0.30, rsplit − halfreliability = 0.76). This study confirms the validity of the prediction model of interaction anxiousness based on social media behavior data, provides a feasible solution to examine adolescents' interaction anxiousness, and provides a scientific basis for more targeted mental health interventions.

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Yilin Wang

Papers

The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users.

Subjective Well-Being of Chinese Sina Weibo Users in Residential Lockdown During the COVID-19 Pandemic: Machine Learning Analysis

Identifying Psychological Symptoms Based on Facial Movements.

Exploring the Psychological Effects of COVID-19 Home Confinement in China: A Psycho-Linguistic Analysis on Weibo Data Pool

Prediction model of interaction anxiousness based on Weibo data