A study on the assessment of risk management performance in maritime start-ups: evidence from China

Due to the COVID-19 pandemic, the international shipping market has been highly volatile, posing a serious threat to the survival and development of many maritime start-ups. With the development of the digital economy, digital transformation is affecting the evolution and upgrading of many traditional enterprises, including maritime enterprises. In the post-COVID-19 era, start-up small and medium-sized enterprises will need to consider the importance of enterprise risk management to achieve transformation and upgrading. The purpose of this study is to provide guidance for the establishment and upgrading of risk management systems for start-ups based on the identification of risk management strategies of maritime enterprises and the evaluation of their performance. The fuzzy analytic hierarchy process and importance-performance analysis methods were used to rank the operational risk, financial risk, market risk, innovation risk, and disaster risk according to sub-items and screen out the risk management schemes for priority improvements. Through empirical research, it was found that the financial risk and market risk response schemes have the lowest performance and need to be prioritised for improvement. This study argues that start-ups can appropriately challenge their risk management strategies to meet potential risk management needs based on their own circumstances.

Racial-ethnic disparities in psychological distress during the COVID-19 pandemic in the United States: the role of experienced discrimination and perceived racial bias.

BACKGROUND: Research on mental health disparities by race-ethnicity in the United States (US) during COVID-19 is limited and has generated mixed results. Few studies have included Asian Americans as a whole or by subgroups in the analysis. METHODS: Data came from the 2020 Health, Ethnicity, and Pandemic Study, based on a nationally representative sample of 2,709 community-dwelling adults in the US with minorities oversampled. The outcome was psychological distress. The exposure variable was race-ethnicity, including four major racial-ethnic groups and several Asian ethnic subgroups in the US. The mediators included experienced discrimination and perceived racial bias toward one's racial-ethnic group. Weighted linear regressions and mediation analyses were performed. RESULTS: Among the four major racial-ethnic groups, Hispanics (22%) had the highest prevalence of severe distress, followed by Asians (18%) and Blacks (16%), with Whites (14%) having the lowest prevalence. Hispanics' poorer mental health was largely due to their socioeconomic disadvantages. Within Asians, Southeast Asians (29%), Koreans (27%), and South Asians (22%) exhibited the highest prevalence of severe distress. Their worse mental health was mainly mediated by experienced discrimination and perceived racial bias. CONCLUSIONS: Purposefully tackling racial prejudice and discrimination is necessary to alleviate the disproportionate psychological distress burden in racial-ethnic minority groups.

Experience of Racial Discrimination was Associated with Psychological Distress and Worsening Sex Life Among Adult Americans During COVID-19.

The recent escalation of racism in the U.S. during the COVID-19 pandemic points to the importance of examining the association between experienced racism and sexual health. Based on data from a nationally representative survey conducted in the U.S. in October 2020 (n = 1,915), Chi-square tests and multivariable logistic regressions were estimated to examine the association between experience of racism and changes in sex life during the pandemic. We further performed a causal mediation analysis using the bootstrap technique to assess the mediating role of psychological distress in the observed association between the experience of racism and changes in sex life. Among the respondents, the proportions reporting better, worse, or no change in sex life were, respectively, 15%, 21%, and 64%. Experiencing racial discrimination during COVID-19 was significantly associated with worsening sex life (adjusted odd ratio [AOR] = 1.53; 95% confidence interval [CI] = 1.04, 2.25). Respondents with experienced racism were also more likely to report psychological distress (AOR = 1.68; 95% CI = 1.09, 2.59). About one-third (32.66%) of the observed association between experienced racism and worsening sex life was mediated through psychological distress. Addressing racism and its association with psychological distress has the potential to improve sexual health and reduce related racial and ethnic disparities.

Impact of the COVID-19 pandemic on cancer healthcare utilization in southwestern China on March 2021.

BACKGROUND: Oncological care has been disrupted worldwide during the COVID-19 pandemic. We aimed to quantify the long-term impact of the pandemic on cancer care utilization and to examine how this impact varied by sociodemographic and clinical factors in southwestern China, where the Dynamic Zero-COVID Strategy was implemented. This strategy mainly included lockdowns, stringent testing, and travel restrictions to prevent the spread of COVID-19. METHOD: We identified 859,497 episodes of the utilization of cancer care from electronic medical records between January 1, 2019, and March 31, 2021, from the cancer center of a tertiary hospital serving an estimated population of 8.4 million in southwestern China. Changes in weekly utilization were evaluated via segmented Poisson regression across service categories, stratified by cancer type and sociodemographic factors. RESULTS: A sharp reduction in utilization of in-person cancer services occurred during the first week of the pandemic outbreak in January 2020, followed by a quick rebound in February 2020. Although there were few COVID-19 cases from March 2020 until this analysis, the recovery of most in-person services was slow and remained incomplete as of March 31, 2021. The exceptions were outpatient radiation and surgery, which increased and exceeded pre-pandemic levels, particularly among lung cancer patients; meanwhile, telemedicine utilization increased substantially after the onset of the pandemic. Care disruptions were most prominent for women, rural residents, uninsured, and breast cancer patients. CONCLUSIONS: As of March 2021, despite few COVID-19 cases, the COVID-19 pandemic has had a strong and continuing impact on in-person oncology care utilization in southwestern China under the Dynamic Zero-COVID Strategy. Equitable and timely access to cancer care requires adjustment in strict policies for COVID-19 prevention and control, as well as targeted remedies for the most vulnerable populations during and beyond the pandemic. Future studies should monitor the long-term effects of the COVID-19 pandemic and response strategies on cancer care and outcomes.

Driving Factors and Scale Effects of Residents' Willingness to Pay for Environmental Protection under the Impact of COVID-19

In recent years, environmental degradation and the COVID-19 pandemic have seriously affected economic development and social stability. Addressing the impact of major public health events on residents' willingness to pay for environmental protection (WTPEP) and analyzing the drivers are necessary for improving human well-being and environmental sustainability. We designed a questionnaire to analyze the change in residents' WTPEP before and during COVID-19 and an established ordinary least squares (OLS), spatial lag model (SLM), spatial error model (SEM), geographically weighted regression (GWR), and multiscale GWR to explore driver factors and scale effects of WTPEP based on the theory of environment Kuznets curve (EKC). The results show that (1) WTPEP is 0–20,000 yuan before COVID-19 and 0–50,000 yuan during COVID-19. Residents' WTPEP improved during COVID-19, which indicates that residents' demand for an ecological environment is increasing;(2) The shapes and inflection points of the relationships between income and WTPEP are spatially heterogeneous before and during COVID-19, but the northern WTPEP is larger than southern, which indicates that there is a spatial imbalance in WTPEP;(3) Environmental degradation, health, environmental quality, and education are WTPEP's significant macro-drivers, whereas income, age, and gender are significant micro-drivers. Those factors can help policymakers better understand which factors are more suitable for macro or micro environmental policy-making and what targeted measures could be taken to solve the contradiction between the growing ecological environment demand of residents and the spatial imbalance of WTPEP in the future.

Mitochondria and cytochrome components released into the plasma of severe COVID-19 and ICU acute respiratory distress syndrome patients.

INTRODUCTION: Proteomic analysis of human plasma by LC-ESI-MS/MS has discovered a limited number of new cellular protein biomarkers that may be confirmed by independent biochemical methods. Analysis of COVID-19 plasma has indicated the re-purposing of known biomarkers that might be used as prognostic markers of COVID-19 infection. However, multiple molecular approaches have previously indicated that the SARS-COV2 infection cycle is linked to the biology of mitochondria and that the response to infections may involve the action of heme containing oxidative enzymes. METHODS: Human plasma from COVID-19 and ICU-ARDS was analyzed by classical analytical biochemistry techniques and classical frequency-based statistical approaches to look for prognostic markers of severe COVID-19 lung damage. Plasma proteins from COVID-19 and ICU-ARDS were identified and enumerated versus the controls of normal human plasma (NHP) by LC-ESI-MS/MS. The observation frequency of proteins detected in COVID-19 and ICU-ARDS patients were compared to normal human plasma, alongside random and noise MS/MS spectra controls, using the Chi Square (χ2) distribution. RESULTS: PCR showed the presence of MT-ND1 DNA in the plasma of COVID-19, ICU-ARDS, as well as normal human plasma. Mitochondrial proteins such as MRPL, L2HGDH, ATP, CYB, CYTB, CYP, NDUF and others, were increased in COVID-19 and ICU-ARDS plasma. The apparent activity of the cytochrome components were tested alongside NHP by dot blotting on PVDF against a purified cytochrome c standard preparation for H2O2 dependent reaction with luminol as measured by enhanced chemiluminescence (ECL) that showed increased activity in COVID-19 and ICU-ARDS patients. DISCUSSION: The results from PCR, LC-ESI-MS/MS of tryptic peptides, and cytochrome ECL assays confirmed that mitochondrial components were present in the plasma, in agreement with the established central role of the mitochondria in SARS-COV-2 biology. The cytochrome activity assay showed that there was the equivalent of at least nanogram amounts of cytochrome(s) in the plasma sample that should be clearly detectable by LC-ESI-MS/MS. The release of the luminol oxidase activity from cells into plasma forms the basis of a simple and rapid test for the severity of cell damage and lung injury in COVID-19 infection and ICU-ARDS.

Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US

The COVID-19 pandemic has resulted in more than 600 million confirmed cases worldwide since December 2021. Cardiovascular disease (CVD) is both a risk factor for COVID-19 mortality and a complication that many COVID-19 patients develop. This study uses Twitter data to identify the spatiotemporal patterns and correlation of related tweets with daily COVID-19 cases and deaths at the national, regional, and state levels. We collected tweets mentioning both COVID-19 and CVD-related words from February to July 2020 (Eastern Time) and geocoded the tweets to the state level using GIScience techniques. We further proposed and validated that the Twitter user registration state can be a feasible proxy of geotags. We applied geographical and temporal analysis to investigate where and when people talked about COVID-19 and CVD. Our results indicated that the trend of COVID-19 and CVD-related tweets is correlated to the trend of COVID-19, especially the daily deaths. These social media messages revealed widespread recognition of CVD's important role in the COVID-19 pandemic, even before the medical community started to develop consensus and theory supports about CVD aspects of COVID-19. The second wave of the pandemic caused another rise in the related tweets but not as much as the first one, as tweet frequency increased from February to April, decreased till June, and bounced back in July. At the regional level, four regions (Northeast, Midwest, North, and West) had the same trend of related tweets compared to the country as a whole. However, only the Northeast region had a high correlation (0.8–0.9) between the tweet count, new cases, and new deaths. For the second wave of confirmed new cases, the major contributing regions, South and West, did not ripple as many related tweets as the first wave. Our understanding is that the early news attracted more attention and discussion all over the U.S. in the first wave, even though some regions were not impacted as much as the Northeast at that time. The study can be expanded to more geographic and temporal scales, and with more physical and socioeconomic variables, with better data acquisition in the future.

Associations of racial and ethnic discrimination with adverse changes in exercise and screen time during the COVID-19 pandemic in the United States.

OBJECTIVES: During the coronavirus disease 2019 (COVID-19) pandemic, a growing prevalence of racial and ethnic discrimination occurred when many Americans struggled to maintain healthy lifestyles. This study investigated the associations of racial and ethnic discrimination with changes in exercise and screen time during the pandemic in the United States. METHODS: We included 2,613 adults who self-identified as non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, or Hispanic from the Health, Ethnicity, and Pandemic study, a cross-sectional survey conducted among a nationally representative sample of United States adults between October and November 2020. We assessed self-reported racial and ethnic discrimination by measuring COVID-19-related racial and ethnic bias and examined its associations with changes in exercise and screen time using multivariable logistic regression models. We analyzed data between September 2021 and March 2022. RESULTS: COVID-19-related racial and ethnic bias was associated with decreased exercise time among non-Hispanic Asian (odds ratio [OR], 1.46; 95% confidence interval [CI], 1.13 to 1.89) and Hispanic people (OR, 1.91; 95% CI, 1.32 to 2.77), and with increased screen time among non-Hispanic Black people (OR, 1.94; 95% CI, 1.33 to 2.85), adjusting for age, sex, education, marital status, annual household income, insurance, and employment status. CONCLUSIONS: Racial and ethnic discrimination may have adversely influenced exercise and screen time changes among racial and ethnic minorities during the COVID-19 pandemic in the United States. Further studies are needed to investigate the mechanisms through which racial and ethnic discrimination can impact lifestyles and to develop potential strategies to address racial and ethnic discrimination as a barrier to healthy lifestyles.

Enhancing COVID-19 Epidemic Forecasting Accuracy by Combining Real-time and Historical Data From Multiple Internet-Based Sources: Analysis of Social Media Data, Online News Articles, and Search Queries.

BACKGROUND: The SARS-COV-2 virus and its variants pose extraordinary challenges for public health worldwide. Timely and accurate forecasting of the COVID-19 epidemic is key to sustaining interventions and policies and efficient resource allocation. Internet-based data sources have shown great potential to supplement traditional infectious disease surveillance, and the combination of different Internet-based data sources has shown greater power to enhance epidemic forecasting accuracy than using a single Internet-based data source. However, existing methods incorporating multiple Internet-based data sources only used real-time data from these sources as exogenous inputs but did not take all the historical data into account. Moreover, the predictive power of different Internet-based data sources in providing early warning for COVID-19 outbreaks has not been fully explored. OBJECTIVE: The main aim of our study is to explore whether combining real-time and historical data from multiple Internet-based sources could improve the COVID-19 forecasting accuracy over the existing baseline models. A secondary aim is to explore the COVID-19 forecasting timeliness based on different Internet-based data sources. METHODS: We first used core terms and symptom-related keyword-based methods to extract COVID-19-related Internet-based data from December 21, 2019, to February 29, 2020. The Internet-based data we explored included 90,493,912 online news articles, 37,401,900 microblogs, and all the Baidu search query data during that period. We then proposed an autoregressive model with exogenous inputs, incorporating real-time and historical data from multiple Internet-based sources. Our proposed model was compared with baseline models, and all the models were tested during the first wave of COVID-19 epidemics in Hubei province and the rest of mainland China separately. We also used lagged Pearson correlations for COVID-19 forecasting timeliness analysis. RESULTS: Our proposed model achieved the highest accuracy in all 5 accuracy measures, compared with all the baseline models of both Hubei province and the rest of mainland China. In mainland China, except for Hubei, the COVID-19 epidemic forecasting accuracy differences between our proposed model (model i) and all the other baseline models were statistically significant (model 1, t198=-8.722, P<.001; model 2, t198=-5.000, P<.001, model 3, t198=-1.882, P=.06; model 4, t198=-4.644, P<.001; model 5, t198=-4.488, P<.001). In Hubei province, our proposed model's forecasting accuracy improved significantly compared with the baseline model using historical new confirmed COVID-19 case counts only (model 1, t198=-1.732, P=.09). Our results also showed that Internet-based sources could provide a 2- to 6-day earlier warning for COVID-19 outbreaks. CONCLUSIONS: Our approach incorporating real-time and historical data from multiple Internet-based sources could improve forecasting accuracy for epidemics of COVID-19 and its variants, which may help improve public health agencies' interventions and resource allocation in mitigating and controlling new waves of COVID-19 or other relevant epidemics.

Public trust of physicians in China improved since the COVID-19 pandemic Began.

RATIONALE: Public trust in physicians had declined in China for decades before the COVID-19 pandemic. During the COVID-19 pandemic, frontline physicians have experienced high work volume despite a high risk of COVID-19 infection. The willingness of physicians to treat COVID patients with a high risk of exposure to the infection may have improved public trust in physicians. OBJECTIVE: This study analyzes how public trust in physicians has changed since the pandemic started using a nationally representative survey. METHODS: We used the China Family Panel Studies (CFPS), with 179,123 respondents 10 years or older who were eligible to answer the question on public trust in physicians from 2012 to 2020. Public trust has been measured by an 11-point Likert scale. A quasi pre-post study design using a segmented regression impact model was used to evaluate the impact of the COVID-19 pandemic on public trust in physicians. RESULTS: At the start of the observation period, the average public trust score was 6.86 out of 10.00. The immediate unadjusted change of mean score for public trust during COVID-19 was significantly higher (Coef. = 0.361; 95% CI = 0.359, 0.364). Moreover, a significant increase in the unadjusted trend during the COVID-19 pandemic was observed in the mean score for public trust (Coef. = 0.005; 95% CI = 0.004, 0.006). The results were similar to the estimates obtained when we adjusted for demographic characteristics and health status. CONCLUSIONS: The mean score for public trust increased during the COVID-19 pandemic. This study provides a new perspective on restoring public trust in physicians, a significant concern of the Chinese healthcare system. During the COVID-19 pandemic, social and mainstream media helped to establish the "good doctor" image, which may have improved patients' trust in physicians. Improving health literacy through effective communication and education may help increase public trust in physicians.

Risk factors for pulmonary embolism in patients with COVID-19: a systemic review and meta-analysis.

PURPOSE: To detect the risk factors for pulmonary embolism (PE) in patients with COVID-19. METHODS: Studies were searched for in PubMed, Cochrane Library, Web of Science, and EMBASE. Two authors independently screened articles and extracted data. The data were pooled by meta-analysis and three subgroup analyses were performed. RESULTS: Of the 2210 articles identified, 27 studies were included. Pooled analysis suggested that males (odds ratio (OR) 1.49, 95% confidence interval (CI) 1.26-1.75, P = 0.000), obesity (OR 1.37, 95% CI 1.03-1.82, P = 0.033), mechanical ventilation (OR 3.34, 95% CI 1.90-5.86, P = 0.000), severe parenchymal abnormalities (OR 1.92, 95% CI 1.43-2.58, P = 0.000), ICU admission (OR 2.44, 95% CI 1.48-4.03, P = 0.000), and elevated D-dimer and white blood cell values (at two time points: hospital admission or closest to computed tomography pulmonary angiography) (P = 0.000) correlated with a risk for PE occurrence in COVID-19 patients. However, age and common comorbidities had no association with PE occurrence. Computed tomography pulmonary angiography, unclear-ratio/low-ratio, and hospitalization subgroups had consistent risk factors with all studies; however, other subgroups had fewer risk factors for PE. CONCLUSIONS: Risk factors for PE in COVID-19 were different from the classic risk factors for PE and are likely to differ in diverse study populations.

Mental Health Impacts of Working from Home after COVID-19: Does Gender Matter?

Background: The COVID-19 pandemic has led to various social distancing practices such as mandatory working from home, which aim to reduce the spread of SARS-CoV-2. The purpose of this study was to compare the mental health impacts between men and women being forced to work from home following a COVID-19 outbreak.Methods: This study analyzed data collected from two rounds of surveys conducted in four cities in China: Beijing, Chengdu, Changsha, and Wuhan. A total of 940 individual responses were analyzed in this study. Multiple linear regression and ordinal logistic models were used to analyze the relationship between being forced to work from The analysis showed that being forced to work from home was associated with worse mental health in men, but not among women. Married men reported better mental health compared with unmarried men, while the association between marital status and mental health was the opposite in women. Mental health was worse among those in higher job positions for both men and women. In addition, being forced to work from home was also associated with worse mental health among young, high-income men, and highly educated women.Conclusions: The impacts of the COVID-19 pandemic are far-reaching and amy persist for years. Furthermore, the number of workers who choose to work from home is expected to increase. The findings of this study can inform policy-making that will improve the mental health of employees working from home, with particular attention to men forced to work from home.

Geographical and Temporal Analysis of Tweets Related to COVID-19 and Cardiovascular Disease in the US.

The COVID-19 pandemic has resulted in more than 600 million confirmed cases worldwide since December 2021. Cardiovascular disease (CVD) is both a risk factor for COVID-19 mortality and a complication that many COVID-19 patients develop. This study uses Twitter data to identify the spatiotemporal patterns and correlation of related tweets with daily COVID-19 cases and deaths at the national, regional, and state levels. We collected tweets mentioning both COVID-19 and CVD-related words from February to July 2020 (Eastern Time) and geocoded the tweets to the state level using GIScience techniques. We further proposed and validated that the Twitter user registration state can be a feasible proxy of geotags. We applied geographical and temporal analysis to investigate where and when people talked about COVID-19 and CVD. Our results indicated that the trend of COVID-19 and CVD-related tweets is correlated to the trend of COVID-19, especially the daily deaths. These social media messages revealed widespread recognition of CVD's important role in the COVID-19 pandemic, even before the medical community started to develop consensus and theory supports about CVD aspects of COVID-19. The second wave of the pandemic caused another rise in the related tweets but not as much as the first one, as tweet frequency increased from February to April, decreased till June, and bounced back in July. At the regional level, four regions (Northeast, Midwest, North, and West) had the same trend of related tweets compared to the country as a whole. However, only the Northeast region had a high correlation (0.8-0.9) between the tweet count, new cases, and new deaths. For the second wave of confirmed new cases, the major contributing regions, South and West, did not ripple as many related tweets as the first wave. Our understanding is that the early news attracted more attention and discussion all over the U.S. in the first wave, even though some regions were not impacted as much as the Northeast at that time. The study can be expanded to more geographic and temporal scales, and with more physical and socioeconomic variables, with better data acquisition in the future.

Factors Affecting University Students' Sleep Quality during the Normalisation of COVID-19 Epidemic Prevention and Control in China: A Cross-Sectional Study

Background: Insufficient and poor-quality sleep have significant negative health consequences for university students in China. In this study, we aimed to assess the subjective sleep quality of university students during the normalisation of COVID-19 epidemic prevention and control in China and to identify key factors affecting their sleep quality. Materials and Methods: A cross-sectional survey was conducted among 1326 university students from Hubei Province, China. Latent profile analysis was conducted on the results of class-difference tests of sleep patterns. Multinomial logistic regression was used to explore the relationship between the influencing factors and three classes of sleep quality. Results: The overall score of sleep quality (9.18 ±3.22) among university students was assessed by using the PSQI scale, and 427 (32.20%) students reported poor sleep quality. Three distinct classes of sleep patterns were identified, namely, good sleepers (Class 1, 70.44%), poor sleep quality with less medication use (Class 2, 26.55%) and poor sleepers (Class 3, 3.01%). Conclusions: Compared with 'good sleepers', students having 'poor sleep quality with less hypnotic drug use' were influenced by their education stage, smoking habits, physical activity, depression and anxiety. Meanwhile, 'poor sleepers' may be affected by their age, origins, smoking habits, mental stress, depression and anxiety. Significant heterogeneity was confirmed in the sleep patterns of university students. Their behavioural lifestyles and mental health-related factors demonstrated different relationship patterns with sleep quality. Multiple sleep promotion interventions, including moderate aerobic exercises, psychological counselling and mindfulness training, should be regularly performed in groups to improve their sleep quality.

Anxiety and depression in dry eye patients during the COVID-19 pandemic: Mental state investigation and influencing factor analysis.

Objective: Investigate the anxiety and depression states among dry eye (DE) patients during the COVID-19 outbreak and analyze their influence factors. Methods: The study was conducted in a tertiary eye hospital in Tianjin, China from March-April 2021. Four hundred twenty-eight DE patients were tested with the Ocular Surface Disease Index, Short Healthy Anxiety Inventory, Hospital Anxiety and Depression Scale, and Pittsburgh Sleep Quality Index. Descriptive statistics was used to assess the difference between DE with depression or anxiety among different groups. And multiple linear regression was used to explore factors that influence anxiety and depression in DE patients. Results: The incidence rates of anxiety and depression among DE patients during COVID-19 were 27.34 and 26.87%, respectively. The proportion with comorbid anxiety and depression was 24.30%. Patients' education level (t = -3.001, P < 0.05; t = -3.631, P < 0.05), course of disease (t = 2.341, P < 0.05; t = 2.444, P < 0.05), health anxiety (t = 3.015, P < 0.05; t = 2.731, P < 0.05), and subjective sleep quality (t = 3.610, P < 0.05; t = 4.203, P < 0.05) had certain influences on anxiety and depression. Conclusion: The results showed that subjective symptoms of DE patients were related to depression and anxiety. Higher education, shorter disease duration, lower health anxiety levels, and better subjective sleep quality were associated with the reduced depressive and anxiety symptoms in DE patients. These findings could be deemed beneficial to the treatment and prevention of DE during the COVID-19 epidemic.

Racism Experience Among American Adults During COVID-19: A Mixed-Methods Study.

Purpose: Despite escalating racism in the United States during COVID-19, few studies have identified correlates of racism experience among Americans using nationally representative data. This study seeks to quantitatively identify correlates of racism experience and qualitatively categorize racism experience and its coping using nationally representative survey data. Methods: Based on data from the "Health, Ethnicity and Pandemic Survey" (N=2,506), a nationally representative survey conducted in October 2020, multivariable logistic regression was estimated to examine the association between self-reported racism experience and selected correlates. Thematic analysis was conducted to qualitatively classify types of racism experience and related coping strategies. Results: When asked whether they had been discriminated or unfairly treated during COVID-19 because of their racial/ethnic background, 19% non-Hispanic Asian and Black respondents said yes, followed by 15% among Hispanics and 3% among non-Hispanic Whites. Besides significant correlates of racism experience identified at the individual and household level, three contextual factors at the neighborhood or state level were associated with lower odds of racism experience, including living in a blue state (adjusted odds ratio [AOR]=0.69, 95% confidence interval [CI]: 0.50-0.95; reference category: red state), living in the top third of the neighborhoods in the sample in terms of racial diversity (AOR=0.65%, 95% CI: 0.42-0.99; reference: bottom third), and coming from neighborhoods with a median population age of 35-39 (AOR=0.67, 95% CI: 0.46-0.98; reference: younger than 35). Prevailing coping strategies against experienced racism included social avoidance, direct confrontation, seeking social and religious support, resorting to hobbies for relief, and taking legal actions. Conclusion: Racism experience is not only correlated with factors at individual level, it is also associated with contextual factors such as political climate, neighborhood diversity, and population age structure. Future efforts in supporting victims of racism might be more cost-effective by focusing on the identified vulnerable groups and related contextual factors.

Effectiveness of Social Needs Screening and Interventions in Clinical Settings on Utilization, Cost, and Clinical Outcomes: A Systematic Review.

Objective: This systematic review examined and synthesized peer-reviewed research studies that reported the process of integrating social determinants of health (SDOH) or social needs screening into electronic health records (EHRs) and the intervention effects in the United States. Methods: Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines, a systematic search of Scopus, Web of Science Core Collection, MEDLINE, and Cochrane Central Register of Clinical Trials was performed. English language peer-reviewed studies that reported the process of integrating SDOH or social needs screening into EHRs within the U.S. health systems and published between January 2015 and December 2021 were included. The review focused on process measures, social needs changes, health outcomes, and health care cost and utilization. Results: In total, 28 studies were included, and half were randomized controlled trials. The majority of the studies targeted multiple SDOH domains. The interventions vary by the levels of intensity of their approaches and heterogeneities in outcome measures. Most studies (82%, n=23) reported the findings related to the process measures, and nearly half (43%, n=12) reported outcomes related to social needs. By contrast, only 39% (n=11) and 32% (n=9) of the studies reported health outcomes and impact on health care cost and utilization, respectively. Findings on patients' social needs change demonstrated improved access to resources. However, findings were mixed on intervention effects on health and health care cost and utilization. We also identified gaps in implementation challenges to be overcome. Conclusion: Our review supports the current policy efforts to increase U.S. health systems' investment toward directly addressing SDOH. While effective interventions can be more complex or resource intensive than an online referral, health care organizations hoping to achieve health equity and improve population health must commit the effort and investment required to achieve this goal.