Symptom characteristics of health care workers seeking outpatient psychiatric care during the COVID-19 pandemic.

BACKGROUND: Though there is a growing body of research establishing a broad negative psychological impact of COVID-19 among healthcare workers (HCWs), there are comparably fewer studies evaluating symptom presentation and clinical diagnoses among treatment-seeking HCWs. The present report seeks to fill this gap in the literature by establishing the prevalence of anxiety, depression, post-traumatic stress, alcohol misuse, and well-being among treatment-seeking HCWs. METHOD: Data were collected from 421 treatment-seeking HCWs in an outpatient hospital-based mental health setting. Both self-report measures and semi-structured interviews were utilized to assess symptom severity and render psychiatric diagnosis at intake. RESULTS: Adjustment disorders were the most prevalent diagnosis at 44.2%. Of the 347 who completed self-report measures, over 47% endorsed moderate-to-severe depressive symptoms, with 13% endorsing suicidal ideation (SI). Fifty-eight percent scored in the moderate-to-severe range for anxiety, and 19% screened positive for COVID-related post-traumatic stress disorder. Further analyses revealed that those in medical support roles endorsed significantly greater depression symptoms relative to other groups and also reported SI at greater frequency. Medical trainees also endorsed SI at higher frequencies. CONCLUSIONS: These findings are consistent with previous research on the adverse impact of COVID-19 stressors on HCWs' mental health. We further identified vulnerable groups that are underrepresented in the literature. These findings highlight the need for targeted outreach and intervention among overlooked HCWs populations.

A Longitudinal Cohort Study of Factors Impacting Healthcare Worker Burnout in New York City During the COVID-19 Pandemic.

OBJECTIVE: This study aimed to longitudinally examine the prevalence and correlates of burnout in frontline healthcare workers (FHCWs) during COVID-19 in New York City. METHODS: A prospective cohort study of 786 FHCWs at Mount Sinai Hospital was conducted during the initial COVID surge in April to May 2020 (T1) and November 2020 to January 2021 (T2) to assess factors impacting burnout. RESULTS: Burnout increased from 38.9% to 44.8% ( P = 0.002); 222 FHCWs (28.3%) had persistent burnout, 82 (10.5%) had early burnout, and 129 (16.5%) had delayed burnout. Relative to FHCWs with no burnout ( n = 350; 44.7%), those with persistent burnout reported more prepandemic burnout (relative risk [RR], 6.67), less value by supervisors (RR, 1.79), and lower optimism (RR, 0.82), whereas FHCWs with delayed burnout reported more prepandemic burnout (RR, 1.75) and caring for patients who died (RR, 3.12). CONCLUSION: FHCW burnout may be mitigated through increasing their sense of value, support, and optimism; treating mental health symptoms; and counseling regarding workplace distress.

Longitudinal Mental Health Outcomes of Third-year Medical Students Rotating Through the Wards During COVID-19.

This study investigated third year medical students' psychological well-being during clinical rotations at Mount Sinai hospitals in New York City during the COVID-19 pandemic. All students (n = 147) starting rotations (psychiatry, surgery, obstetrics-gynecology, neurology, pediatrics, and medicine) could participate in quarterly, online, anonymous surveys comprised of validated screeners for: psychological symptoms, risk, coping, and protective factors, demographics, COVID-19 worries, and stressful clerkship-related events. Associations between variables were examined with Chi-squared, Fisher's exact, t-, Wilcoxon Rank Sum, one-way ANOVA, and McNemar tests. Significant univariate predictors of psychological distress were included in stepwise multivariable linear regression models. The baseline survey was completed by 110 (74.8%) students; ninety-two (62.6%) completed at least one other survey. During the year, 68 (73.9%) students screened positive for depression, anxiety, or PTSD. The prevalence of psychiatric symptoms peaked in June 2020 without significant changes in average scores over time. COVID-19 worries decreased over time but did not influence psychological symptoms at year-end. Eighty-three students (90.2%) experienced stressful clerkship-related events, which were traumatic and/or COVID-19-related for 26 (28.3%) and 22 students (24.0%), respectively. Baseline psychological distress, childhood emotional abuse, and resilience predicted depression, anxiety, and/or PTSD by year-end. This study highlights the importance of recognizing psychological distress and implementing interventions to support students' well-being.

Transdiagnostic Psychiatric Symptoms, Burnout, and Functioning in Frontline Health Care Workers Responding to the COVID-19 Pandemic: A Symptomics Analysis.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic has led to an increased risk of psychiatric symptoms among frontline health care workers (FHCWs). In the current study, a novel "symptomics" approach was employed to examine the association between acute transdiagnostic symptoms of posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and generalized anxiety disorder (GAD) and burnout and work and relationship difficulties in FHCWs at an urban tertiary care hospital in New York City. METHODS: Symptoms of COVID-19-related PTSD (4-item PTSD Checklist-5), MDD (Patient Health Questionnaire-8), GAD (Generalized Anxiety Disorder-7), burnout (Single-Item Mini-Z Burnout Assessment), and functional difficulties (Brief Inventory of Psychosocial Functioning) were assessed. Relative importance analyses were conducted to identify PTSD, MDD, and GAD symptoms associated with burnout and functional difficulties. RESULTS: The total number of eligible participants included 6,026 presumed FHCWs, of which 3,360 (55.8%) completed the survey and 2,579 (76.8%) of whom endorsed directly treating patients with COVID-19 and provided sufficient responses to our outcome variables for analysis. Feeling tired/having little energy, being easily annoyed or irritable, and feeling nervous, anxious, or on edge were most strongly associated with burnout; feeling tired/having little energy accounted for the greatest amount of explained variance (> 15%). Negative expectations of oneself or the world, trouble concentrating, and feeling easily annoyed or irritable were most strongly associated with work difficulties; negative expectations of oneself or the world accounted for the greatest amount of explained variance (> 9%). Feeling easily annoyed or irritable, negative expectations about oneself or the world, and feeling bad about oneself were most strongly associated with relationship difficulties; feeling easily annoyed or irritable accounted for the greatest amount of explained variance (> 10%). CONCLUSIONS: Results of this study underscore the importance of a transdiagnostic, symptom-based approach when examining associations between acute psychopathology and burnout and functional difficulties in FHCWs. Further work is needed to determine if early interventions aimed at ameliorating specific psychiatric symptoms may help mitigate risk for peri- and posttraumatic burnout and functional difficulties in this population.

Neuropsychiatric Consequences of COVID-19 Pandemic: A Synthetic Review from a Global Perspective.

Some research suggests that distress, secondary to isolation and fear following COVID-19 infection, can negatively affect the long-term more than the COVID-19 infection itself. This narrative review aims to provide a global view on the neuropsychiatric consequences of COVID-19 that can be ascribed to several factors, ranging from the direct effect of infection, to the body's responses against the infection, or to the psychological sequelae of social isolation, unemployment, and fear for one's health and livelihood. Current findings show that the more severe the respiratory infection, the more likely are central nervous system (CNS) complications regarding the infection itself. The immune reactions to the infection may result in symptoms similar to chronic fatigue as well as neurocognitive deficits, which last long after the infection is gone. An increase in symptoms of depression, anxiety, and trauma-related stress may also follow upon economic fears and isolation from friends and family. The consequences of the pandemic are not limited to adults; children learning remotely and away from classmates and routine activities may develop adjustment disorders, acute stress disorder, and a variety of manifestations of grief. A summary of case reports suggests that COVID-19-related stress, economic recession, and political unrest increase the risk of suicidal behaviors and acts of violence. However, it is unknown whether manifestations of mental disorders result from social causes or whether CNS complications may be responsible.

Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers.

Objective: To determine whether a machine learning model can detect SARS-CoV-2 infection from physiological metrics collected from wearable devices. Materials and Methods: Health care workers from 7 hospitals were enrolled and prospectively followed in a multicenter observational study. Subjects downloaded a custom smart phone app and wore Apple Watches for the duration of the study period. Daily surveys related to symptoms and the diagnosis of Coronavirus Disease 2019 were answered in the app. Results: We enrolled 407 participants with 49 (12%) having a positive nasal SARS-CoV-2 polymerase chain reaction test during follow-up. We examined 5 machine-learning approaches and found that gradient-boosting machines (GBM) had the most favorable validation performance. Across all testing sets, our GBM model predicted SARS-CoV-2 infection with an average area under the receiver operating characteristic (auROC) = 86.4% (confidence interval [CI] 84-89%). The model was calibrated to value sensitivity over specificity, achieving an average sensitivity of 82% (CI ±âˆ¼4%) and specificity of 77% (CI ±âˆ¼1%). The most important predictors included parameters describing the circadian heart rate variability mean (MESOR) and peak-timing (acrophase), and age. Discussion: We show that a tree-based ML algorithm applied to physiological metrics passively collected from a wearable device can identify and predict SARS-CoV-2 infection. Conclusion: Applying machine learning models to the passively collected physiological metrics from wearable devices may improve SARS-CoV-2 screening methods and infection tracking.

A prospective study of transdiagnostic psychiatric symptoms associated with burnout and functional difficulties in COVID-19 frontline healthcare workers.

OBJECTIVE: Frontline healthcare workers (FHCWs) responding to the COVID-19 pandemic develop posttraumatic stress disorder (PTSD), major depressive disorder (MDD) and generalized anxiety disorder (GAD) symptoms. Such symptoms are associated with burnout, occupational and relational difficulties. In the current study, we examined the prospective association between acute transdiagnostic COVID-19-related PTSD, MDD, and GAD symptoms at pandemic outset, and burnout and functional difficulties several months later in FHCWs in New York City. METHODS: Wave 1 symptoms of COVID-19-related PTSD, MDD, and GAD, were assessed in 787 FHCWs from April 14 to May 11th, 2020. Burnout and occupational difficulties were assessed at wave 1 and wave 2, approximately 7 months later. RESULTS: After adjusting for wave 1 burnout, wave 1 MDD symptoms, particularly sleep difficulties, loss of interest, and feeling tired/having little energy, collectively explained 42% incremental variance in this outcome. After adjusting for wave 1 work difficulties, MDD and PTSD symptoms, particularly feeling tired/having little energy, loss of interest, and negative expectations of self/world, collectively explained 42% incremental variance in this outcome. After adjusting for wave 1 relationship difficulties, MDD, GAD, and PTSD symptoms, particularly depressed mood, irritability, and appetite disturbance, explained 26% incremental variance in this outcome. CONCLUSIONS: Results highlight psychiatric symptoms assessed during the acute phase of the COVID-19 pandemic that may help predict burnout and work and relationship difficulties in FHCWs. Early interventions aimed at ameliorating transdiagnostic symptoms of MDD, PTSD, and GAD may help mitigate risk for burnout and functional difficulties in this population.

A prospective cohort study of the psychological consequences of the COVID-19 pandemic on frontline healthcare workers in New York City.

OBJECTIVES: We sought to describe the course and correlates of psychological distress in frontline healthcare workers (FHCWs) during the COVID-19 pandemic in New York City (NYC). METHODS: A prospective cohort study of FHCWs at the Mount Sinai Hospital was conducted during the initial 2020 surge (T1) and 7 months later (T2). Psychological distress [i.e., positive screen for pandemic-related post-traumatic stress disorder (PTSD), major depressive disorder (MDD), and/or generalized anxiety disorder (GAD)], occupational and personal exposures to COVID-19, coping strategies, and psychosocial characteristics were assessed. Four courses of psychological distress response were identified: no/minimal, remitted, persistent, and new-onset. Multinomial logistic regression and relative importance analyses were conducted to identify factors associated with courses of distress. RESULTS: Of 786 FHCWs, 126 (16.0%) FHCWs had persistent distress; 150 (19.1%) remitted distress; 35 (4.5%) new-onset distress; and 475 (60.4%) no/minimal distress. Relative to FHCWs with no/minimal distress, those with persistent distress reported greater relationship worries [19.8% relative variance explained (RVE)], pre-pandemic burnout (18.7% RVE), lower dispositional optimism (9.8% RVE), less emotional support (8.6% RVE), and feeling less valued by hospital leadership (8.4% RVE). Relative to FHCWs with remitted symptoms, those with persistent distress reported less emotional support (29.7% RVE), fewer years in practice (28.3% RVE), and psychiatric history (23.6% RVE). CONCLUSIONS: One-fifth of FHCWs in our study experienced psychological distress 7 months following the COVID-19 surge in NYC. Pandemic-related worries, pre-pandemic burnout, emotional support, and feeling valued by leaders were linked to persistent distress. Implications for prevention, treatment, and organizational efforts to mitigate distress in FHCWs are discussed.

Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study.

BACKGROUND: Changes in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. OBJECTIVE: We performed an evaluation of HRV collected by a wearable device to identify and predict COVID-19 and its related symptoms. METHODS: Health care workers in the Mount Sinai Health System were prospectively followed in an ongoing observational study using the custom Warrior Watch Study app, which was downloaded to their smartphones. Participants wore an Apple Watch for the duration of the study, measuring HRV throughout the follow-up period. Surveys assessing infection and symptom-related questions were obtained daily. RESULTS: Using a mixed-effect cosinor model, the mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats (SDNN), an HRV metric, differed between subjects with and without COVID-19 (P=.006). The mean amplitude of this circadian pattern differed between individuals during the 7 days before and the 7 days after a COVID-19 diagnosis compared to this metric during uninfected time periods (P=.01). Significant changes in the mean and amplitude of the circadian pattern of the SDNN was observed between the first day of reporting a COVID-19-related symptom compared to all other symptom-free days (P=.01). CONCLUSIONS: Longitudinally collected HRV metrics from a commonly worn commercial wearable device (Apple Watch) can predict the diagnosis of COVID-19 and identify COVID-19-related symptoms. Prior to the diagnosis of COVID-19 by nasal swab polymerase chain reaction testing, significant changes in HRV were observed, demonstrating the predictive ability of this metric to identify COVID-19 infection.

Moral distress in frontline healthcare workers in the initial epicenter of the COVID-19 pandemic in the United States: Relationship to PTSD symptoms, burnout, and psychosocial functioning.

INTRODUCTION: Little is known about the relationship between moral distress and mental health problems. We examined moral distress in 2579 frontline healthcare workers (FHCWs) caring for coronavirus disease 2019 (COVID-19) patients during the height of the spring 2020 pandemic surge in New York City. The goals of the study were to identify common dimensions of COVID-19 moral distress; and to examine the relationship between moral distress, and positive screen for COVID-19-related posttraumatic stress disorder (PTSD) symptoms, burnout, and work and interpersonal functional difficulties. METHOD: Data were collected in spring 2020, through an anonymous survey delivered to a purposively-selected sample of 6026 FHCWs at Mount Sinai Hospital; 2579 endorsed treating COVID-19 patients and provided complete survey responses. Physicians, house staff, nurses, physician assistants, social workers, chaplains, and clinical dietitians comprised the sample. RESULTS: The majority of the sample (52.7%-87.8%) endorsed moral distress. Factor analyses revealed three dimensions of COVID-19 moral distress: negative impact on family, fear of infecting others, and work-related concerns. All three factors were significantly associated with severity and positive screen for COVID-19-related PTSD symptoms, burnout, and work and interpersonal difficulties. Relative importance analyses revealed that concerns about work competencies and personal relationships were most strongly related to all outcomes. CONCLUSION: Moral distress is prevalent in FHCWs and includes family-, infection-, and work-related concerns. Prevention and treatment efforts to address moral distress during the acute phase of potentially morally injurious events may help mitigate risk for PTSD, burnout, and functional difficulties.

The Psychiatric Burden on Medical Students in New York City Entering Clinical Clerkships During the COVID-19 Pandemic.

For medical students first entering the clinical space in July 2020, the unique challenges related to the coronavirus pandemic threatened to amplify the psychological distress associated with clerkship rotations. This study aimed to characterize the mental health of third-year medical students starting clinical clerkships in the midst of a pandemic by assessing symptoms of major depressive disorder (MDD), generalized anxiety disorder (GAD), and posttraumatic stress disorder (PTSD) as well as risk, coping, and protective factors associated with psychological outcomes. Of 147 third-year medical students at the Icahn School of Medicine at Mount Sinai in New York City, 110 (75%) participated in this prospective survey-based study with 108 included in the final analysis. 43 (39.8%) respondents screened positive for symptoms of either MDD, GAD, or PTSD. Multiple regression analyses revealed that greater overall symptom severity was associated with more avoidant coping, more traumatic events witnessed, poorer student and leisure functioning, lower trait emotional stability, and lower social support. Worries related to COVID-19 did not significantly influence outcome variables. To better understand the role of the pandemic on psychological outcomes in third-year medical students, additional research should focus on the trajectory of these outcomes over the year during the coronavirus pandemic.

COVID-19 Pandemic Support Programs for Healthcare Workers and Implications for Occupational Mental Health: A Narrative Review.

This narrative review aims to summarize initiatives developed during the COVID-19 pandemic to support healthcare workers' emotional well-being within the context of a pre-existing framework of occupational mental health guidelines. This occupational mental health framework integrates principles from multiple disciplines to optimize prevention and management of mental health issues among employees. We conducted an online search on Medline/PubMed, Cochrane Library, and Embase for studies that reported on design or execution of medical institution-based interventions, aiming to support healthcare worker mental health during the COVID-19 pandemic. Inclusion criteria was intentionally broad in order to incorporate as many types of interventions at varying stages of development or evaluation. We included 31 studies in our review that reported on newly designed psychological support interventions for healthcare workers (HCW) during the COVID-19 pandemic. We found that most programs commonly supported HCW mental health through offering one or more of the following initiatives: expanded basic need resources/services, additional workplace training programs that bolstered professional preparedness while also indirectly boosting HCW emotional health, and/or expanded psychological support programs, such as peer support programs, psychoeducational or counseling services. Most programs, however, did not consider methods to ensure program longevity or sustainability. The COVID-19 pandemic has underscored the acuity of HCW mental health issues and is likely to leave long lasting mental health strains among HCW. This pandemic is a critical point in time to catalyze much needed progress in reducing stigma and expanding HCW mental health care access.

Psychological Consequences Among Residents and Fellows During the COVID-19 Pandemic in New York City: Implications for Targeted Interventions.

PURPOSE: To examine the psychological impact of the COVID-19 pandemic on medical trainees (residents and fellows) working at Mount Sinai Hospital (MSH) in New York City (NYC), the initial epicenter of the United States pandemic. METHOD: The authors administered a survey to 991 trainees in frontline specialties working at MSH in NYC between April and May 2020. The instrument assessed symptoms of major depressive disorder, generalized anxiety disorder, COVID-19-related posttraumatic stress disorder, and burnout. Psychiatric screens were aggregated into 1 composite measure, and meeting criteria on any of the 3 scales was considered a positive screen for psychiatric symptoms. The survey also assessed COVID-19-related exposures, worries, coping strategies, and desired interventions. Multivariable logistic regressions were conducted to identify factors associated with psychiatric symptoms and burnout. RESULTS: Of the 560 respondents (56.6% response rate), 29.7% screened positive for psychiatric symptoms and 35.8% screened positive for burnout. History of a mental illness, COVID-19-related duties and personal/career worries, and coping by substance use were associated with increased likelihood of screening positive for psychiatric symptoms. Positive emotion-focused coping and feeling valued by supervisors were associated with decreased likelihood. Internal medicine and surgical specialties, a history of mental illness, increased duty hours, duty-related worries, personal/career worries, coping via self-blame and venting, and coping via substance use were associated with higher odds of burnout. Feeling valued by supervisors was associated with decreased burnout odds. The most common crisis-related needs included access to personal protective equipment, food provisions, and financial support. CONCLUSIONS: Psychological distress and burnout affected approximately one-third of trainees sampled during the height of the pandemic in NYC. As the pandemic surged beyond NYC, these findings suggest that interventions should include addressing basic needs, promoting leadership affirmation, moderating duty hours, supporting trainees financially, and enhancing mental health support.

Factors Associated With Longitudinal Psychological and Physiological Stress in Health Care Workers During the COVID-19 Pandemic: Observational Study Using Apple Watch Data.

BACKGROUND: The COVID-19 pandemic has resulted in a high degree of psychological distress among health care workers (HCWs). There is a need to characterize which HCWs are at an increased risk of developing psychological effects from the pandemic. Given the differences in the response of individuals to stress, an analysis of both the perceived and physiological consequences of stressors can provide a comprehensive evaluation of its impact. OBJECTIVE: This study aimed to determine characteristics associated with longitudinal perceived stress in HCWs and to assess whether changes in heart rate variability (HRV), a marker of autonomic nervous system function, are associated with features protective against longitudinal stress. METHODS: HCWs across 7 hospitals in New York City, NY, were prospectively followed in an ongoing observational digital study using the custom Warrior Watch Study app. Participants wore an Apple Watch for the duration of the study to measure HRV throughout the follow-up period. Surveys measuring perceived stress, resilience, emotional support, quality of life, and optimism were collected at baseline and longitudinally. RESULTS: A total of 361 participants (mean age 36.8, SD 10.1 years; female: n=246, 69.3%) were enrolled. Multivariate analysis found New York City's COVID-19 case count to be associated with increased longitudinal stress (P=.008). Baseline emotional support, quality of life, and resilience were associated with decreased longitudinal stress (P<.001). A significant reduction in stress during the 4-week period after COVID-19 diagnosis was observed in the highest tertial of emotional support (P=.03) and resilience (P=.006). Participants in the highest tertial of baseline emotional support and resilience had a significantly different circadian pattern of longitudinally collected HRV compared to subjects in the low or medium tertial. CONCLUSIONS: High resilience, emotional support, and quality of life place HCWs at reduced risk of longitudinal perceived stress and have a distinct physiological stress profile. Our findings support the use of these characteristics to identify HCWs at risk of the psychological and physiological stress effects of the pandemic.

Resilience in the age of COVID-19

SUMMARYResilience is broadly defined as the ability to bounce back from adversity or trauma. Recent advances in resilience research have shifted away from merely describing individual characteristics towards focusing on the complex interactions between individuals and their dynamic personal, community and cultural contexts. It is clear that resilience involves both neurobiological and cultural processes. Neurobiological contributions include genes, epigenetics, stress-response systems, the immune system and neural circuitry. Culture helps to elucidate collective systems of belief and accepted positive adaptations. Importantly, resilience can also be affected by evidence-based interventions and deliberate practice on the part of the individual. This review seeks to understand resilience as a complex and active process that is shaped by neurobiological profiles, developmental experiences, cultural and temporal contexts, and practical training. It uses the COVID-19 pandemic as a case example to better understand individual and group responses to tragedy. We suggest practical recommendations to help populations around the world cope and recover from the global threat of COVID-19.

A Resilience-Building App to Support the Mental Health of Health Care Workers in the COVID-19 Era: Design Process, Distribution, and Evaluation.

BACKGROUND: The COVID-19 pandemic has resulted in increased strain on health care systems and negative psychological effects on health care workers (HCWs). This is anticipated to result in long-term negative mental health effects on the population, with HCWs representing a particularly vulnerable group. The scope of the COVID-19 pandemic necessitates the development of a scalable mental health platform to provide services to large numbers of at-risk or affected individuals. The Mount Sinai Health System in New York City was at the epicenter of the pandemic in the United States. OBJECTIVE: The Center for Stress, Resilience, and Personal Growth (CSRPG) was created to address the current and anticipated psychological impact of the pandemic on the HCWs in the health system. The mission of the Center is to support the resilience and mental health of employees through educational offerings, outreach, and clinical care. Our aim was to build a mobile app to support the newly founded Center in its mission. METHODS: We built the app as a standalone digital platform that hosts a suite of tools that users can interact with on a daily basis. With consideration for the Center's aims, we determined the overall vision, initiatives, and goals for the Wellness Hub app, followed by specific milestone tasks and deliverables for development. We defined the app's primary features based on the mental health assessment and needs of HCWs. Feature definition was informed by the results of a resilience survey widely distributed to Mount Sinai HCWs and by the resources offered at CSRPG, including workshop content. RESULTS: We launched our app over the course of two phases, the first phase being a "soft" launch and the second being a broader launch to all of Mount Sinai. Of the 231 HCWs who downloaded the app, 173 (74.9%) completed our baseline assessment of all mental health screeners in the app. Results from the baseline assessment show that more than half of the users demonstrate a need for support in at least one psychological area. As of 3 months after the Phase 2 launch, approximately 55% of users re-entered the app after their first opening to explore additional features, with an average of 4 app openings per person. CONCLUSIONS: To address the mental health needs of HCWs during the COVID-19 pandemic, the Wellness Hub app was built and deployed throughout the Mount Sinai Health System. To our knowledge, this is the first resilience app of its kind. The Wellness Hub app is a promising proof of concept, with room to grow, for those who wish to build a secure mobile health app to support their employees, communities, or others in managing and improving mental and physical well-being. It is a novel tool offering mental health support broadly.

Psychological Impact of the COVID-19 Pandemic on Frontline Health Care Workers During the Pandemic Surge in New York City.

BACKGROUND: This study sought to assess the magnitude of and factors associated with mental health outcomes among frontline health care workers (FHCWs) providing care during the Spring 2020 COVID-19 pandemic surge in New York City. METHODS: A cross-sectional, survey-based study over 4 weeks during the Spring 2020 pandemic surge was used to assess symptoms of COVID-19-related posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and generalized anxiety disorder (GAD) in 2,579 FHCWs at the Mount Sinai Hospital. Participants were additionally asked about their occupational and personal exposures to COVID-19. Multivariable logistic regression and relative importance analyses were conducted to identify factors associated with these outcomes. RESULTS: A total of 3,360 of 6,026 individuals completed the survey (55.8% participation), with 2,579 (76.8%) analyzed based on endorsing frontline responsibilities and providing information related to the three outcomes. 1,005 (39.0%) met criteria for symptoms of COVID-19-related PTSD, MDD, or GAD. 599 (23.3%) screened positively for PTSD symptoms, 683 (26.6%) for MDD symptoms, and 642 (25.0%) for GAD symptoms. Multivariable analyses revealed that past-year burnout was associated with the highest risk of developing symptoms for COVID-19-related PTSD (odds ratio [OR] = 2.10), MDD (OR = 2.83), and GAD (OR = 2.68). Higher perceived support from hospital leadership was associated with a lowest risk of all outcomes [PTSD (OR = 0.75), MDD (OR = 0.72), and GAD (OR = 0.76). CONCLUSION: In this large sample of FHCWs providing care during the 2020 NYC pandemic surge, 39% experienced symptoms of COVID-19-related PTSD, MDD, and/or GAD and pre-pandemic burnout as well as leadership support were identified as the most highly associated factors. These findings suggest that interventions aimed at reducing burnout and augmenting support from hospital leadership may be appropriate targets to mitigate the risk for developing further psychopathology in this population and others working in the midst of crisis.

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, effective methods to meet these needs are lacking. OBJECTIVE: The aims of this study were to analyze the electronic health records (EHRs) of patients who tested positive for COVID-19 and were admitted to hospitals in the Mount Sinai Health System in New York City; to develop machine learning models for making predictions about the hospital course of the patients over clinically meaningful time horizons based on patient characteristics at admission; and to assess the performance of these models at multiple hospitals and time points. METHODS: We used Extreme Gradient Boosting (XGBoost) and baseline comparator models to predict in-hospital mortality and critical events at time windows of 3, 5, 7, and 10 days from admission. Our study population included harmonized EHR data from five hospitals in New York City for 4098 COVID-19-positive patients admitted from March 15 to May 22, 2020. The models were first trained on patients from a single hospital (n=1514) before or on May 1, externally validated on patients from four other hospitals (n=2201) before or on May 1, and prospectively validated on all patients after May 1 (n=383). Finally, we established model interpretability to identify and rank variables that drive model predictions. RESULTS: Upon cross-validation, the XGBoost classifier outperformed baseline models, with an area under the receiver operating characteristic curve (AUC-ROC) for mortality of 0.89 at 3 days, 0.85 at 5 and 7 days, and 0.84 at 10 days. XGBoost also performed well for critical event prediction, with an AUC-ROC of 0.80 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. In external validation, XGBoost achieved an AUC-ROC of 0.88 at 3 days, 0.86 at 5 days, 0.86 at 7 days, and 0.84 at 10 days for mortality prediction. Similarly, the unimputed XGBoost model achieved an AUC-ROC of 0.78 at 3 days, 0.79 at 5 days, 0.80 at 7 days, and 0.81 at 10 days. Trends in performance on prospective validation sets were similar. At 7 days, acute kidney injury on admission, elevated LDH, tachypnea, and hyperglycemia were the strongest drivers of critical event prediction, while higher age, anion gap, and C-reactive protein were the strongest drivers of mortality prediction. CONCLUSIONS: We externally and prospectively trained and validated machine learning models for mortality and critical events for patients with COVID-19 at different time horizons. These models identified at-risk patients and uncovered underlying relationships that predicted outcomes.