Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S

Racism and the mental health of East Asian diasporas in North America: a scoping review

BACKGROUND

The COVID-19 pandemic heightened anti-Asian racism towards East Asian diasporas in North America. Experiences of racism encountered by East Asian communities have been documented to negatively impact their mental health.

METHODS

A scoping review was undertaken following Arksey and O'Malley's (2005) methodology to (a) map the foci of literature on racism and the mental health of East Asian diasporas in North America and (b) identify gaps in the current literature.

RESULTS

A total of 1309 articles were identified in May 2021. Based on the inclusion criteria, 35 records were included. Two distinct mental health foci were found: mental health outcomes and mental healthcare access and utilization. The majority (n = 22) of the articles focused on racism at the interpersonal level. Six articles provided anti-racism solutions at the individual level, such as overcoming biases. Five articles targeted anti-racism solutions from both the individual and institutional levels, while 1 article addressed barriers at the institutional level, such as dismantling sanctioned power hierarchies.

CONCLUSION

The expanding knowledge base on COVID-19-related racial discrimination is reminiscent of previous literature examining the history of anti-Asian racism in North America. Greater attention is needed to navigate impactful anti-racism solutions for East Asian populations' mental health in North America.

Stressors during the COVID-19 pandemic in international students: a qualitative study

BACKGROUND

The coronavirus disease 2019 (COVID-19) pandemic has exacerbated mental health problems worldwide; however, research on the stressors experienced by international students during the COVID-19 pandemic remains limited.

METHODS

Semi-structured interviews were conducted with 20 international students (male, 8; female, 12; average age, 31.5 years) at Hiroshima University, Japan. Inductive thematic analysis was performed using NVivo software to identify how international students (1) perceived and experienced stress and (2) describe the specific stressors they faced during the COVID-19 pandemic.

RESULTS

The findings revealed that international students experienced multiple stressors during the COVID-19 pandemic, including extrapersonal (e.g., financial pressure), interpersonal (e.g., social commentary and perceived xenophobia against foreigners), and intrapersonal (e.g., fear of infection) stressors.

CONCLUSIONS

Results revealed that during the COVID-19 pandemic, foreign students experienced stress from various sources. Although this global pandemic has ended, similar public health crises may occur in the future. Examination of the sources of stress faced by international students during the pandemic can help us obtain valuable lessons for responding to future global crises. These findings can provide better policy support, resource allocation, and mental health assistance for the international student community during future crises.

The impact of resilience and coping strategies on depressive symptoms among Korean American older adults during COVID-19

OBJECTIVES

This study examined how resilience and coping strategies were associated with depressive symptoms among Korean American older adults during COVID-19. The prevalent depressive symptoms and low use of mental health services in this population have raised significant concerns among healthcare professionals. Therefore, this study aims to understand the relationships between resilience and coping types on depressive symptoms and provide valuable insights into addressing these issues within this ethnic group.

METHOD

A cross-sectional survey was conducted with 132 Korean American older adults. Hierarchical linear regression analyses were performed to assess the effect of sociodemographic factors (age, gender, marital status, years of living in the U.S., self-rated health, financial security), resilience, and coping strategies (problem-focused coping, emotion-focused coping, avoidant coping) on depressive symptoms. Next, the interactions between resilience and three coping strategies for depressive symptoms were tested.

RESULTS

The findings show that depressive symptoms were associated with financial security and avoidant coping. Also, resilience interacted with avoidant coping and emotion-focused coping. Among the participants with low resilience, depressive symptoms increased rapidly when avoidant and emotion-focused coping strategies increased, respectively.

CONCLUSION

This study emphasizes the importance of culturally tailored interventions to promote resilience and decrease avoidant and emotion-focused coping among Korean American older adults.

Academic-related stressors predict depressive symptoms in graduate students: A machine learning study

BACKGROUND

Graduate students face higher depression rates worldwide, which were further exacerbated during the COVID-19 pandemic. This study employed a machine learning approach to predict depressive symptoms using academic-related stressors.

METHODS

We surveyed students across four graduate programs at a Federal University in Brazil between October 15, 2021, and March 26, 2022, when most activities were restricted to taking place online due to the pandemic. Through an online self-reported screening, participants rated ten academic stressors and completed the Patient Health Questionnaire (PHQ-9). Machine learning analysis tested whether the stressors would predict depressive symptoms. Gender, age, and race and ethnicity were used as covariates in the predictive model.

RESULTS

Participants (n=172), 67.4 % women, mean age: 28.0 (SD: 4.53) fully completed the online questionnaires. The machine learning approach, employing an epsilon-insensitive support vector regression (Ɛ-SVR) with a k-fold (k=5) cross-validation strategy, effectively predicted depressive symptoms (r=0.51; R2=0.26; NMSE=0.79; all p=0.001). Among the academic stressors, those that made the greatest contribution to the predictive model were "fear and worry about academic performance", "financial difficulties", "fear and worry about academic progress and plans", and "fear and worry about academic deadlines".

CONCLUSIONS

This study highlights the vulnerability of graduate students to depressive symptoms caused by academic-related stressors during the COVID-19 pandemic through an artificial intelligence methodology. These findings have the potential to guide policy development to create intervention programs and public health initiatives targeted towards graduate students.

"Am I the only one who will Spread the Virus?": Impact of Public Stigma Towards the East Asian Population Living in Spain Related to COVID-19

Previous studies have suggested that COVID-19 led to an increase in stigma towards the Asian population with a negative impact on their health. This study aims to explore this phenomenon and its impact on health through the qualitative analysis of semi-structured interviews conducted with 26 people of Asian origin living in Spain from September 2020 to September 2021. Among the results, it was found that, prior to the pandemic, discrimination was mostly verbal. After the outbreak of the pandemic, some participants, who were blamed and referred to as "COVID", experienced fear and physical aggression. Among the health effects, mental and social disturbances such as feeling like "permanent foreigners", worrying about being stigmatized or fear of interacting with others were prominent. The main protective factor was the support network, including education and community cohesion as main determinants. Future research is needed to analyse the evolution of this stigma after the pandemic and to explore in detail its impact on health.

Machine learning applications in studying mental health among immigrants and racial and ethnic minorities: an exploratory scoping review

BACKGROUND

The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By examining the published literature, this review aims to explore the current applications of ML in MH research, with a particular focus on its use in studying diverse and vulnerable populations, including immigrants, refugees, migrants, and racial and ethnic minorities.

METHODS

From October 2022 to March 2024, Google Scholar, EMBASE, and PubMed were queried. ML-related, MH-related, and population-of-focus search terms were strung together with Boolean operators. Backward reference searching was also conducted. Included peer-reviewed studies reported using a method or application of ML in an MH context and focused on the populations of interest. We did not have date cutoffs. Publications were excluded if they were narrative or did not exclusively focus on a minority population from the respective country. Data including study context, the focus of mental healthcare, sample, data type, type of ML algorithm used, and algorithm performance were extracted from each.

RESULTS

Ultimately, 13 peer-reviewed publications were included. All the articles were published within the last 6 years, and over half of them studied populations within the US. Most reviewed studies used supervised learning to explain or predict MH outcomes. Some publications used up to 16 models to determine the best predictive power. Almost half of the included publications did not discuss their cross-validation method.

CONCLUSIONS

The included studies provide proof-of-concept for the potential use of ML algorithms to address MH concerns in these special populations, few as they may be. Our review finds that the clinical application of these models for classifying and predicting MH disorders is still under development.

Community-Based Mental Health Challenges and Implications: Examining Factors Influencing Distress and Help-Seeking Behaviors among Korean American Church Leaders and Members in Greater Los Angeles

There is limited research on the factors that impact mental distress among Korean American (KA) church leaders even though their unique social situation can create many barriers to seeking mental health assistance. This study compared factors impacting mental distress and help-seeking behaviors between KA church leaders (CLs) and church members (CMs) in the greater Los Angeles area. The respondents (N = 243) were mostly female, married, educated, first-generation immigrants with a mean age of 47.9 years (SD = 19.7). The Hopkins Symptoms Checklist 10 was used to measure anxiety and depression. Hierarchal linear regressions showed that health status exerted the strongest effect on both anxiety and depression among CLs and CMs. Beyond health status, education (only for depression), informal resource use, and resiliency impacted mental distress scores for CLs. Only resiliency and religious coping predicted depression scores among CMs. To effectively reach this population, community-based organizations and behavioral health specialists should consider collaborating with churches to promote and provide essential mental health support. Our findings also highlight that the needs of church leaders (CLs) and church members (CMs) differ, which should guide the development of culturally tailored interventions that build on the resilience of both groups.

Trends in Racial Discrimination Experiences for Asian Americans During the COVID-19 Pandemic

BACKGROUND

Asian Americans (AAs) are experiencing increased rates of anti-Asian racism during COVID-19. Experiences of racism, whether personal or collective, constitute stress and psychosocial trauma that negatively impact mental and physical health.

OBJECTIVES

Examine subgroup differences in rates of personal experience of discrimination and COVID-related collective racism and how each is associated with mental and physical health for AAs.

METHODS

Nationally representative data from the 2021 Asian American and Native Hawaiian/Pacific Islander COVID-19 Needs Assessment Project were used to estimate prevalence rates of discrimination and average COVID-related collective racism scores for AAs (unweighted N = 3478). We conducted logistic and linear regression models to examine subgroup differences by sociodemographic factors. We also conducted hierarchical logistic regression models to examine associations between racism and psychological distress and health decline.

RESULTS

Twenty-four percent of AAs (95% CI: 21.6, 25.6) reported experiencing discrimination during the first year of the COVID-19 pandemic. Subgroup analyses revealed that Chinese, younger adults, and AAs who completed the survey in an Asian language were significantly more likely to experience discrimination compared to their counterparts. For COVID-related collective racism, subgroup analyses revealed that Chinese, women, and adults ages 25-44 were more likely to report experiences of collective racism compared to their counterparts. Both discrimination and collective racism were independently associated with negative mental and physical health.

CONCLUSION

Discrimination and COVID-related collective racism are associated with negative mental and physical health outcomes for AAs. Results point to vulnerable AA subgroups and the need for targeted public health efforts to address racism in the context of COVID-19.

Mental Health Needs Among Asian and Asian American Adults During the COVID-19 Pandemic

Objective:

Disaggregated data on the mental health of Asian/Asian American people are needed to inform public health interventions related to reports of racism during the COVID-19 pandemic. We describe the prevalence of psychological distress and unmet mental health needs among Asian/Asian American adults during the COVID-19 pandemic across various sociodemographic subgroups.

Methods:

We used cross-sectional, weighted data from the US-based 2021 Asian American and Native Hawaiian/Pacific Islander COVID-19 Needs Assessment Study (unweighted n = 3508) to estimate prevalence rates of psychological distress and unmet mental health needs, overall and by nativity status. We conducted population-weighted multivariable logistic regression analyses to examine sociodemographic factors associated with these mental health outcomes.

Results:

About one-third (1419 of 3508) of Asian/Asian American adults (32.9%; 95% CI, 30.6%-35.2%) reported psychological distress; odds of psychological distress were increased among adults who were female, trans, and nonbinary; aged 18-44 years; US-born; Cambodian; multiracial; and low income. Of those reporting psychological distress (638 of 1419), 41.8% (95% CI, 37.8%-45.8%) reported unmet mental health needs; unmet mental health needs were highest among Asian/Asian American adults who were aged 18-24 years; Korean, Japanese, and Cambodian; US-born female; non–US-born young adults; and non–US-born with ≥bachelor’s degree.

Conclusions:

The mental health of Asian/Asian American people is an important public health concern, with some groups more vulnerable and in need of services than others. Mental health resources need to be designed for vulnerable subgroups, and cultural and systemic barriers to mental health care need to be addressed.

Is emotional support the key to improving emotion regulation? A machine learning approach

BACKGROUND

According to the emotion regulation process, situation selection comprises actions that increase or decrease the likelihood of being in contexts that foster a certain type of emotion, positive or negative. This concept is complemented by the social basis theory, which starts with the assumption that the primary ecology of humans is characterized by its social components. Thus, reduced access to social relationships increases cognitive and physiological effort, which leads to a decrease in well-being.

PARTICIPANTS AND PROCEDURE

In order to make a joint assessment of both concepts, the study used supervised machine learning models to analyze the associations between selected variables of social support, emotion regulation, coping, and several psychological symptoms (somatization, obsession-compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism). For this purpose, an Argentine sample (N = 812, M age = 44.35, female = 435) was collected through the Internet, nested cross-validations were performed with 8 different learning algorithms and Shapley values were computed for the predictive models that minimized the test errors.

RESULTS

The results showed that adaptive strategies have considerable effects on maladaptive strategies, but they do not have significant effects on symptoms. Contrariwise, social support variables have significant effects on symptoms, while they do not have major effects on maladaptive strategies.

CONCLUSIONS

It is concluded that the main function of regulatory flexibility does not appear to be a better adaptation to situations, but rather the maintenance of adequate levels of social support, i.e. emotional support received, perception of available emotional support, and perceived comprehension. Further implications are discussed, and a hypothetical model proposed.

Coronavirus disease (COVID-19) cases analysis using machine-learning applications

Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.

The Short-Term Consequences of COVID-19 on Mental Health: State of the Art from Available Studies

Since the outbreak of the COVID-19 pandemic, the consequences on mental health have been found to be considerable, with potential effects on the general population and in high-risk groups, with a variety of physiopathological mechanisms [...].

Racial Discrimination as a Cumulative Risk Factor Affecting Parental Stress on the Psychological Distress of Korean Americans (Both US- and Foreign-Born) amid COVID-19: Structural Equation Modeling

This study examined the relationships of parental stress and racial discrimination to the psychological distress of Korean Americans (both US- and foreign-born) during the COVID-19 pandemic. It also explored whether racial discrimination moderated the effect of parental stress on psychological distress. Using primary data collected between May 24, 2020, and June 14, 2020, via an online questionnaire, confirmatory factor analysis and structural equation models were conducted on 339 Korean American parents. Results indicated that parental stress and racial discrimination were associated with parental psychological distress. However, when the sample was divided by parental sex, racial discrimination played as a moderator, the interaction of discrimination, and parenting stress was associated with more psychological distress only for mothers. Based on the study results, we recommended that policymakers should consider policies and programs that can reduce racism to make up for the public health crisis associated with COVID-19; clinical practitioners also need to provide appropriate virtual mental/physical health services and interventions that can decrease parental stress and psychological distress amid COVID-19.

A Review Study on the Trends of Psychological Challenges, Coping Ways, and Public Support During the COVID-19 Pandemic in the Vulnerable Populations in the United States

Background

The COVID-19 pandemic resulted in significant mortality and morbidity in the United States. The mental health impact during the pandemic was huge and affected all age groups and population types. We reviewed the existing literature to understand the present trends of psychological challenges and different coping strategies documented across different vulnerable sections of the United States population. This rapid review was carried out to investigate the trends in psychological impacts, coping ways, and public support during the COVID-19 pandemic crisis in the United States.

Materials and Methods

We undertook a rapid review of the literature following the COVID-19 pandemic in the United States. We searched PubMed as it is a widely available database for observational and experimental studies that reported the psychological effects, coping ways, and public support on different age groups and healthcare workers (HCWs) during the COVID-19 pandemic.

Results

We included thirty-five studies in our review and reported data predominantly from the vulnerable United States population. Our review findings indicate that COVID-19 has a considerable impact on the psychological wellbeing of various age groups differently, especially in the elderly population and HCWs. Review findings suggest that factors like children, elderly population, female gender, overconcern about family, fear of getting an infection, personality, low spirituality, and lower resilience levels were at a higher risk of adverse mental health outcomes during this pandemic. Systemic support, higher resilience levels, and adequate knowledge were identified as protecting and preventing factors. There is a paucity of similar studies among the general population, and we restricted our review specifically to vulnerable subgroups of the population. All the included studies in our review investigated and surveyed the psychological impacts, coping skills, and public support system during the COVID-19 pandemic.

Conclusion

The evidence to date suggests that female gender, child and elderly population, and racial factors have been affected by a lack of support for psychological wellbeing. Further, research using our hypothesized framework might help any population group to deal with a pandemic-associated mental health crisis, and in that regard, analysis of wider societal structural factors is recommended.

Leisure Satisfaction Changes and Stress-coping during the Pandemic

Objectives: Leisure engagement has been considered as a salient stress-coping strategy. However, during the COVID-19 pandemic, people's leisure engagement has been restricted due to COVID-19- related regulations and policies. Moreover, many Asian immigrants, including Korean immigrants in the US, have been exposed to additional challenges (e.g., discrimination and harassment), which negatively affected their leisure experiences. Methods: in this study, we categorized participants into 3 groups based on their leisure satisfaction changes before and during the pandemic and compared the groups regarding COVID-19 risk perception, stress-coping, and life satisfaction. Results: The Maintained or Increased Group (MIG) scored significantly lower stress than the Highly Decreased group (HDG); the MIG scored significantly higher life satisfaction than both the Slightly Decreased Group (SDG) and the HDG. Conclusion: The research demonstrated the importance of satisfactory leisure experience to cope with stress and be satisfied with their life in a stressful life event.

Lived experiences of Asian Canadians encountering discrimination during the COVID-19 pandemic: a qualitative interview study

BACKGROUND

Asian Canadians have experienced increased cases of racialized discrimination after the first emergence of SARS-CoV-2 in China. This study examined how the COVID-19 pandemic has affected Asian Canadians' sense of safety and belonging in their Canadian (i.e., geographical) communities.

METHODS

We applied a qualitative description study design in which semistructured interviews were conducted from Mar. 23 to May 27, 2021. Purposive and snowball sampling methods were used to recruit Asian Canadians diverse in region, gender and age. Interviews were conducted through Zoom videoconference or telephone, and independent qualitative thematic analysis in duplicate was used to derive primary themes and subthemes.

RESULTS

Thirty-two Asian Canadians (median age 35 [interquartile range 24-46] yr, 56% female, 44% East Asian) participated in the study. We identified 5 predominant themes associated with how the COVID-19 pandemic affected the participants' sense of security and belonging to their communities: relation between socioeconomic status (SES) and exposure to discrimination (i.e., how SES insulates or exposes individuals to increased discrimination); politics, media and the COVID-19 pandemic (i.e., the key role that politicians and media played in enabling spread of discrimination against and fear of Asian people); effect of discrimination on mental and social health (i.e., people's ability to interact and form meaningful relationships with others); coping with the impact of discrimination (i.e., the way people appraise and move forward in identity-threatening situations); and implications for sense of safety and sense of belonging (i.e., people feeling unable to safely use public spaces in person, including the need to remain alert in anticipation of harm, leading to distress and exhaustion).

INTERPRETATION

During the COVID-19 pandemic, Asian Canadians in our study felt unsafe owing to the uncertain, unexpected and unpredictable nature of discrimination, but also felt a strong sense of belonging to Canadian society and felt well connected to their Asian Canadian communities. Future work should seek to explore the influence of social media on treatment of and attitudes toward Asian Canadians.

Exploring Factors and Associate Responses for Anxiety in the Coronavirus Disease 2019 Pandemic: A Web-Based Survey in Japan

Background and Objectives

Anxiety plays an important role in psychology. An exploration of anxiety and its associated reactions may provide insight into measures for addressing mental health problems caused by the coronavirus disease 2019 (COVID-19) pandemic. Data from this study provide potential correlational responses to anxiety.

Methods

A cross-sectional study using data collected via an online self-reported questionnaire was conducted in Japan during the COVID-19 pandemic. Using the State-Trait Anxiety Inventory (STAI-6), we assessed anxiety levels and explored the relationship between anxiety STAI-6 score, sources of COVID-19 information, the influences of COVID-19, social anxiety symptoms, discrimination, and evaluation of the government.

Results

A total of 4,127 participants were included in the analysis. The level of anxiety was not equally distributed across the general population with respect to age, gender, educational level, occupation, income, presence of underlying disease, and location (p < 0.05). The number of sources of information on COVID-19 had a positive correlation with the STAI-6 score (Spearman’s rho = 0.176, p < 0.001). The influence of the pandemic was correlated with moderate–severe anxiety. A high level of anxiety added to social anxiety (Spearman’s rho = 0.04, p < 0.05) and discriminatory behavior (Spearman’s rho = 0.11, p < 0.01). Being female (Estimate = 0.926) and from a non-emergency area (Estimate = −0.308) was related to higher STAI scores, and higher education (Estimate = −0.305), and income (Estimate = −0.168) decreased the STAI score. The respondents who had a lower evaluative score of the preventive activities undertaken by the national and local governments had higher STAI-6 scores.

Conclusion

Our findings provide statistical evidence for the associated reaction of anxiety and that anxiety reactions may vary in predictable ways. Further studies should focus on the strategic interventions that may decrease the associated responses to anxiety, to address mental health issues due to the pandemic.

The Impact of Racial and Non-racial Discrimination on Health Behavior Change Among Visible Minority Adults During the COVID-19 Pandemic

INTRODUCTION

Pre-pandemic health behavior has been put forward as a reason for excess COVID-19 infection and death in some racialized groups. At the same time, scholars have labeled racism the other pandemic and argued for its role in the adverse COVID-19 outcomes observed. The purpose of this study was to examine the impact of discrimination on health behavior change among racialized adults in the early stages of the pandemic.

METHODS

Data were collected from 210 adults who identified as a visible minority in Alberta, Canada, in June 2020. The Everyday Discrimination Scale (Short Version) was adapted to examine past-month experiences. Four questions asked if alcohol/cannabis use and stress eating had significantly increased, and if sleep and exercise had significantly decreased in the past month. Logistic regression models examined associations between discrimination attributed to racial and non-racial causes and health behavior change adjusted for covariates.

RESULTS

The majority of adults (56.2%) reported past-month discrimination including 26.7% who attributed it to their race. Asian adults reported more racial discrimination and discrimination due to people believing they had COVID-19 than other visible minorities. Racial discrimination during the pandemic was strongly associated with increased substance use (OR: 4.0, 95% CI 1.2, 13.4) and decreased sleep (OR: 7.0, 95% CI 2.7, 18.4), and weakly associated with decreased exercise (OR: 2.2, 95% CI 1.1, 4.5). Non-racial discrimination was strongly associated with decreased sleep (OR: 4.8, 95% CI 1.8, 12.5).

CONCLUSION

Racial discrimination may have a particularly important effect on intensifying adverse health behavior changes among racialized adults during a time of global crisis.

Application of artificial intelligence in COVID-19 medical area: a systematic review

BACKGROUND

Coronavirus disease 2019 (COVID-19) has caused a large-scale global epidemic, impacting international politics and the economy. At present, there is no particularly effective medicine and treatment plan. Therefore, it is urgent and significant to find new technologies to diagnose early, isolate early, and treat early. Multimodal data drove artificial intelligence (AI) can potentially be the option. During the COVID-19 Pandemic, AI provided cutting-edge applications in disease, medicine, treatment, and target recognition. This paper reviewed the literature on the intersection of AI and medicine to analyze and compare different AI model applications in the COVID-19 Pandemic, evaluate their effectiveness, show their advantages and differences, and introduce the main models and their characteristics.

METHODS

We searched PubMed, arXiv, medRxiv, and Google Scholar through February 2020 to identify studies on AI applications in the medical areas for the COVID-19 Pandemic.

RESULTS

We summarize the main AI applications in six areas: (I) epidemiology, (II) diagnosis, (III) progression, (IV) treatment, (V) psychological health impact, and (VI) data security. The ongoing development in AI has significantly improved prediction, contact tracing, screening, diagnosis, treatment, medication, and vaccine development for the COVID-19 Pandemic and reducing human intervention in medical practice.

DISCUSSION

This paper provides strong advice for using AI-based auxiliary tools for related applications of human diseases. We also discuss the clinicians' role in the further development of AI. They and AI researchers can integrate AI technology with current clinical processes and information systems into applications. In the future, AI personnel and medical workers will further cooperate closely.

Associations between accessibility to health care service, social support, and Korean Americans' mental health status amid the COVID-19 pandemic

Background

While previous studies have examined the relationships between social support and health care accessibility among ethnic minority populations, studies on Korean Americans remain scarce. Therefore, this study aims to assess the relationship between Korean Americans’ mental health, accessibility to health care, and how they perceive the level of social support during the COVID-19 pandemic.

Method/result

We distributed online surveys to Korean Americans from May 24, 2020, to June 14, 2020, generating 790 responses from participants residing in 42 states. Binary Logistic and Ordinary Least Square regression analyses revealed that poor mental health was associated with language barriers inhibiting Korean Americans’ access to COVID-19-related information. Their perceived social support from family members and close friends was positively associated with mental health.

Conclusion

Our findings recommend that equipping community health care services with translators or interpreters is necessary. Additionally, health practitioners and staff should be trained to utilize telehealth tools to effectively treat individuals with mental health problems. American policymakers and health care professionals need to understand and address the unique hardships Korean Americans experience amid COVID-19.

Mental health and resilience during the coronavirus pandemic: A machine learning approach

Objective

This study explored risk and resilience factors of mental health functioning during the coronavirus disease (COVID‐19) pandemic.

Methods

A sample of 467 adults (M age = 33.14, 63.6% female) reported on mental health (depression, anxiety, posttraumatic stress disorder [PTSD], and somatic symptoms), demands and impacts of COVID‐19, resources (e.g., social support, health care access), demographics, and psychosocial resilience factors.

Results

Depression, anxiety, and PTSD rates were 44%, 36%, and 23%, respectively. Supervised machine learning models identified psychosocial factors as the primary significant predictors across outcomes. Greater trauma coping self‐efficacy and forward‐focused coping, but not trauma‐focused coping, were associated with better mental health. When accounting for psychosocial resilience factors, few external resources and demographic variables emerged as significant predictors.

Conclusion

With ongoing stressors and traumas, employing coping strategies that emphasize distraction over trauma processing may be warranted. Clinical and community outreach efforts should target trauma coping self‐efficacy to bolster resilience during a pandemic.

Pandemic-related racial discrimination and its health impact among non-Indigenous racially minoritized peoples in high-income contexts: a systematic review

This study aims to review articles reporting the perspectives and experiences of pandemic-related discrimination among racially minoritized peoples in high-income contexts. We searched online databases (Medline, EMBASE, PsycINFO, Web of Science, and ProQuest) for peer-reviewed articles published between January 2002 and October 2020. Eligible studies reported either quantitative or qualitative accounts of pandemic-related discrimination from the perspectives of racially minoritized peoples in high-income contexts. Two authors screened 30% of titles/abstracts, and all full-text articles. Each article included for extraction underwent a quality assessment by two reviewers. Data were extracted and categorized thematically using NVivo 12, followed by a secondary analysis informed by critical race theory. Of the 1289 articles screened, 16 articles from five countries met the inclusion criteria. Racial discrimination is heightened during pandemic periods, due to the social association of specific racial groups with pandemic diseases including COVID-19, SARS (Asian), H1N1 (Hispanic) and Ebola (African). Fear based responses to racially minoritized peoples during pandemic periods included verbal/physical abuse, hypersurveillance, and avoidance, often occurring in public spaces. Pandemic-related racism had subsequent impacts on mental health and health care accessibility. Various coping strategies, including community support, avoidance, and problem solving, were documented in response to racial discrimination. Racialized discrimination and violence is a serious threat to the health and wellbeing of racially minoritized peoples, particularly due to its increase during pandemic periods. Racism must be recognized as a public health issue, and efforts to address its increased impact in pandemic contexts should be made, including ensuring that adequate representation of racially minoritized groups is present in policy, planning, and implementation.

COVID-19 related discrimination in Japan: A preliminary analysis utilizing text-mining

To assess the general Japanese population's thoughts on coronavirus disease of 2019 related discrimination by Tweets.Tweets were retrieved from search queries using the keywords "health care providers and discrimination (no hashtags)" and "corona and rural area (no hashtags)" via the Twitter application programming interface. Subsequently, a text-mining analysis was conducted on tokenized text data. R version 4.0.2 was used for the analysis.In total, 51,906 tweets for "corona and health care providers", 59,560 tweets for "corona and rural" were obtained between the search period of July 29, 2020 and September 30, 2020. The most common 20 words from the tokenized text data were translated to English. Word clouds with the original Japanese words are presented.Tweets for corona and health care providers did not suggest significant evidence of discrimination toward health care providers on Twitter. Results for corona and rural area, however, showed the unexpected word "murahachibu" (an outmoded word meaning ostracism), suggesting persistent strong social pressure to prevent bringing the disease to the community. This kind of pressure may not be supported by scientific facts. These results demonstrate the need for continued educational efforts to disseminate factual information to the public.

Experience of and Worry About Discrimination, Social Media Use, and Depression Among Asians in the United States During the COVID-19 Pandemic: Cross-sectional Survey Study

BACKGROUND

The COVID-19 outbreak has spurred increasing anti-Asian racism and xenophobia in the United States, which might be detrimental to the psychological well-being of Asian people living in the United States.

OBJECTIVE

We studied three discrimination-related variables, including (1) experience of discrimination, (2) worry about discrimination, and (3) racism-related social media use during the COVID-19 pandemic among Asians in the United States. We examined how these three variables were related to depression, and how the association between racism-related social media use and depression was moderated by personal experience of and worry about racial discrimination.

METHODS

A web-based, cross-sectional survey was conducted. A total of 209 people (mean age 33.69, SD 11.31 years; 96/209, 45.93% female) who identified themselves as Asian and resided in the United States were included in the study.

RESULTS

Experience of discrimination (β=.33, P=.001) and racism-related social media use (β=.14, P=.045) were positively associated with depressive symptoms. Worry about discrimination (β=.13, P=.14) was not associated with depression. Worry about discrimination moderated the relationship between racism-related social media use and depression (β=-.25, P=.003) such that a positive relationship was observed among those who had low and medium levels of worry.

CONCLUSIONS

The present study provided preliminary evidence that experience of discrimination during the COVID-19 pandemic was a risk factor of depressive symptoms among Asian people in the United States. Meanwhile, racism-related social media use was found to be negatively associated with the well-being of US Asians, and the relationship between social media use and depression was significantly moderated by worry about discrimination. It is critical to develop accessible programs to help US Asians cope with racial discrimination both in real lives and on social media during this unprecedented health crisis, especially among those who have not been mentally prepared for such challenges.

Parental stress of Korean immigrants in the U.S.: Meeting Child and Youth's educational needs amid the COVID-19 pandemic

This study investigates Korean immigrants' parental stress amid the COVID-19 pandemic, especially when they experience difficulties trying to meet their children's educational needs. Korean immigrant parents residing in the U.S. were invited to complete an online survey through purposive sampling. The final sample included a total of 341 Korean immigrant parents from 42 U.S. states. Three models of Ordinary Least Squares (OLS) regressions were conducted to examine the associations between parent-reported difficulties meeting the children's educational needs, parental stress, and the immigrant parents' resilience and social support. Findings indicate that parents' difficulties meeting their children's educational needs in general as well as language barriers were associated with increased parental stress. Moreover, parents' resilience and social support also significantly decreased parental stress levels. Implications for practice, policy, and future research are presented.

Clinical outcomes and risk factors for COVID-19 among migrant populations in high-income countries: A systematic review

BACKGROUND

Migrants in high-income countries may be at increased risk of COVID-19 due to their health and social circumstances, yet the extent to which they are affected and their predisposing risk factors are not clearly understood. We did a systematic review to assess clinical outcomes of COVID-19 in migrant populations, indirect health and social impacts, and to determine key risk factors.

METHODS

We did a systematic review following PRISMA guidelines (PROSPERO CRD42020222135). We searched multiple databases to 18/11/2020 for peer-reviewed and grey literature on migrants (foreign-born) and COVID-19 in 82 high-income countries. We used our international networks to source national datasets and grey literature. Data were extracted on primary outcomes (cases, hospitalisations, deaths) and we evaluated secondary outcomes on indirect health and social impacts and risk factors using narrative synthesis.

RESULTS

3016 data sources were screened with 158 from 15 countries included in the analysis (35 data sources for primary outcomes: cases [21], hospitalisations [4]; deaths [15]; 123 for secondary outcomes). We found that migrants are at increased risk of infection and are disproportionately represented among COVID-19 cases. Available datasets suggest a similarly disproportionate representation of migrants in reported COVID-19 deaths, as well as increased all-cause mortality in migrants in some countries in 2020. Undocumented migrants, migrant health and care workers, and migrants housed in camps have been especially affected. Migrants experience risk factors including high-risk occupations, overcrowded accommodation, and barriers to healthcare including inadequate information, language barriers, and reduced entitlement.

CONCLUSIONS

Migrants in high-income countries are at high risk of exposure to, and infection with, COVID-19. These data are of immediate relevance to national public health and policy responses to the pandemic. Robust data on testing uptake and clinical outcomes in migrants, and barriers and facilitators to COVID-19 vaccination, are urgently needed, alongside strengthening engagement with diverse migrant groups.

Mental Well-Being of Chinese Immigrants in the Netherlands during the COVID-19 Pandemic: A Survey Investigating Personal and Societal Antecedents

The COVID-19 pandemic has profoundly impacted people’s lives worldwide, with negative consequences for mental health and well-being. Antecedents of mental health and well-being in times of COVID-19 have been underresearched, especially among minority groups. Therefore, an online survey was conducted investigating the personal and societal antecedents of mental well-being among Chinese immigrants in the Netherlands (N = 268). Constructs included perceived decrease of mental well-being and attitude toward the Netherlands as dependent variables and a range of potential antecedents as independent variables. Results show that participants judged the Chinese COVID-19 situation significantly more positively than the Dutch situation. Five antecedents of decreased mental well-being were found: financial concerns, social isolation, feelings of lost time, experienced racism, and distrust of Dutch COVID-19 information and figures. The antecedents of participants’ attitude toward the Netherlands were largely different: missing China, perceived difficulty of traveling to China, distrust of Dutch government measures, trust in Chinese government measures, and distrust of Dutch COVID-19 information and figures. Fear of the virus itself did not significantly affect either of the dependent variables. The results call for a broad perspective on factors associated with mental well-being and for special attention for minority groups in the societal dynamics.

Addressing psychological resilience during the coronavirus disease 2019 pandemic: a rapid review

PURPOSE OF REVIEW

The mental health toll on populations exposed to COVID-19 is alarming, and there is a need to address this with urgency. This current review provides insights on how individuals, communities, and specific populations, such as healthcare workers and patients are leveraging pre-COVID-19 and peri-COVID-19 factors to reinforce their psychological resilience during the global public health crisis.

RECENT FINDINGS

Examination of the extant literature indicated that populations around the world rely often on support from their loved-ones, closed significant others, outdoor and physical activities, and spirituality to cope with the COVID-19-related distress. Increased sense of meaning/purpose since the COVID-19 pandemic was also reported.

SUMMARY

A portion of publications provided intervention models to reinforce resilience among specific populations during the COVID-19 pandemic. Nevertheless, it is not convincing that some of these models can be applied universally. Additionally, it is important to note that in this category, translational data was scarce.