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The psychosocial impact on frontline nurses of caring for patients with COVID-19 during the first wave of the pandemic in New York City

Background Infectious disease pandemics, such as COVID-19, have dramatically increased in the last several decades. Purpose To investigate the personal and contextual factors associated with the psychological functioning of nurses responding to COVID in the New York City area. Method Cross sectional data collected via a 95-item internet-based survey sent to an email list of the 7,219 nurses employed at four hospitals. Findings 2,495 nurses responded (RR 35%). The more that nurses cared for COVID patients as well as experienced home-work conflict and work-home conflict the higher the nurses' depression and anxiety. When asked what has helped the nurses to carry out their care of patients the most common responses were support from and to co-workers, training in proper PPE, and support from family/friends. Discussion Understanding the potential triggers and vulnerability factors can inform the development of institutional resources that would help minimize their impact, reducing the risk of psychological morbidity.

The psychosocial impact on frontline nurses of caring for patients with COVID-19 during the first wave of the pandemic in New York City Background Emerging and re-emerging infectious disease pandemics have dramatically increased in the last several decades (Smith et al., 2014 Available online at www.sciencedirect.com N u r s O u t l o o k 6 9 ( 2 0 2 1 ) 7 4 4 À7 5 4 www.nursingoutlook.org Disease (2014)) (Ross et al., 2015) and SARS-CoV-2 (COVID-19) (2020).
As the nation's largest healthcare profession, nurses play a significant role in responding to disasters, such as pandemics. Studies consistently show that many nurses feel they are under-prepared to respond effectively (Speroni et al., 2015;Van Devanter et al., 2017). In a study of New York City (NYC) nurses responding to a hospital evacuation due to Superstorm Sandy, nurses reported considerable psychosocial challenges in responding to the disaster due to limited prior disaster experience, training, and education (VanDevanter et al., 2017). A number of studies in the US have shown that nurses responding to disasters experience anxiety, depression and stress (Li et al., 2015;VanDevanter et al., 2017;von Strauss et al., 2017). Global studies have shown that health care workers, in general, are at high risk for developing mental health symptoms, as a result of their exposure to disaster (Mamidipalli et al., 2020). The purpose of this study was to investigate the personal and contextual factors associated with the psychological functioning of nurses responding to the COVID-19 pandemic.
This study was conducted from May through July 2020, in NYC, during the first US wave of the COVID-19 pandemic. The virus, first reported in Wuhan, China in December 2019, quickly spread to other regions of China (Schumaker, 2020). As a result, it was assumed that the virus was most likely to enter the US through West Coast cities and some early cases did. However, due to viral spread from China to Europe, the early major port of US COVID-19 entry was largely through NYC international airports bringing travelers from Europe. The first COVID-19 case in New York State (NYS) was reported on March 1, 2020 (West, 2020). By March 23 there were 21,000 cases statewide, with 12,305 in NYC. Throughout the spring of 2020 NYS had more cases of COVID-19 than any state in the US. The health care infrastructure of the region was unprepared for the scope and intensity of the care needs for the affected population. Registered Nurses (RNs) were the largest group of health professionals responding to the pandemic (Choi et al., 2020).

Theoretical Framework
The nature of the nursing profession increases the risk of encountering situations of personal risk and, multiple causality events, such as the COVID-19 pandemic, that generate role demands which may impede or conflict with personal lives and family responsibilities. Resiliency theory provides the conceptual framework for understanding the personal and contextual factors impacting the psychological functioning of hospital RNs caring for patients during the months-long surge in COVID-19 illness. This conceptual framework focuses attention on the promotive factors À personal characteristics (assets) and social/environmental protective factors (resources) that can positively affect RNs' coping (short-term) and the adaptation, restoration, and recovery process (long term) (Fergus & Zimmerman, 2005), as well as, identifying the vulnerability and risk factors that can adversely impact current functioning or impede post-event recovery (Fergus & Zimmerman, 2005;Garmezy et al., 1984;Rutter, 1987Rutter, , 2006Zimmerman, 2013). The resilience framework guided our selection of variables included in this study. In this investigation we examined the shortterm impact of various promotive factors (assets and resources) on the RNs' psychological functioning. A long term follow-up is necessary to fully test the model.

Design
Our approach was cross-sectional, using an internetbased survey. In addition to the quantitative survey, participants were given the opportunity to write-in further comments at the end of the survey.

Setting
The study was conducted at the NYU Langone Health System (NYULH), which includes four hospitals in the NYC area: a major medical center hospital, an urban community teaching hospital, a suburban community teaching hospital and an urban specialty hospital that was converted into a COVID-19 hospital, when all elective surgery was stopped in the early stages of the COVID-19 pandemic. Also included were a rehabilitation facility and the ambulatory care sites that are part of the system.

Sample
All RNs who were employed by NYULH on May 5, 2020 were included. Surveys were sent to 7,219 RNs; 2,495 responded, for a response rate of 35%. Ten surveys were eliminated because the respondents were LPNs and two other surveys were eliminated because respondents did not indicate that they had a professional nursing degree leaving 2,483 respondents. Of these about 1,600 completed more than half of the survey items.

Data Collection
With collaboration from NYULH, all RNs at these sites were contacted by email inviting them to participate in an online anonymous survey. Researchers were blinded to the individual email addresses. Following the Total Design Method (Dillman et al., 2014), we used multiple email reminders. We sent an alert email, an email with a link to the survey and two reminder emails each with a link to the survey. Respondents were anonymous; therefore, reminders were sent to all RNs whether or not they had responded to an earlier request. We collected the survey data between May 27, 2020 and July 11, 2020. Respondents entered their survey responses N u r s O u t l o o k 6 9 ( 2 0 2 1 ) 7 4 4 À7 5 4 electronically into a RED CAP survey located on a secure NYU drive. The survey data were then downloaded to another NYU secure drive and cleaned. The study was approved by the New York University School of Medicine Institutional Review Board.

Measures
Data were collected using a 95-item survey. Items and scales were from our previous work on disasters (Van Devanter et al., 2017), the Newly Licensed Registered Nurse survey (Kovner et al., 2007), and a small advisory group of RNs from NYULH. The survey was pilot tested with two RNs not associated with NYULH. Based on the pilot test small changes were made. These nurses estimated that the survey would take about 15 minutes to complete. In addition to basic demographic data we assessed psychosocial morbidity, variables that have been identified as important outcomes in prior studies of RNs and other health care workers responding to disasters, such as anxiety and depression, as well as, the stressors, strains, assets and resources that are constructs of Resiliency Theory.
Anxiety was measured using the Generalized Anxiety Disorder 2 Item scale (Kroenke et al., 2007). Depression was measured using the PHQ-2 Screener for depressive disorders (Kroenke et al., 2003). These are count measures with options ranging from 0 to 3, with zero being "not at all" and three being "nearly every day." Variables from the resilience framework included potential personal assets (mastery, prior disaster experience, family support) and strains (personal or home life issues, home-work conflict), as well as, contextual resources, situational stressors and strains (or lack thereof) such as workÀrelated characteristics (shift work, organizational support and constraints, work-group support, new unit support, cared for COVID-19 patients, RN-physician relations, temporary housing, work-home conflict). See Appendix A for a list of all scales, sample items and scoring instructions. Individual item such as "NYU Langone has made sufficient supportive services available to nursing staff" and forced choice lists of items such as "How has the COVID-19 pandemic impacted your person or home life (check all that apply)" were developed by the authors. For the analyses we counted the number items checked in each list.

Data Analysis
Data were analyzed using SPSS. The number of items in the scales varied from 3 (Work-Life conflict) to 8 (Organizational constraints). In our sample, all scales had Cronbach Alphas of .82 or above.
Descriptive statistics were computed. We analyzed data for normality using the Shapiro-Wilks test. Both anxiety and depression were skewed. For variables that did not satisfy the normality assumption, the nonparametric bivariate rho (Spearman) correlation test was performed. We corrected for the effects of multiple correlations on potentially related variables by performing multivariate partial correlations on variables found to be significant in the bivariate analysis. For the multivariate partial correlation analysis, variables that did not satisfy the normality assumption were transformed using the ranks of the values to achieve normality.

Findings
The sociodemographic characteristics of respondents are shown in Table 1 and are similar to those of the most recent RN National Sample Survey (NSS) (U. S. Department of Health and Human Services, 2019) with the exception of first professional degree and age. Baccalaureate graduates made up 77.2% of our sample and only 39.2% in the NSS sample. In the NSS, 50% of respondents were less than 50 years old, and in our sample more than 50% were less than 40 years old. However, in terms of highest degree the samples were similar; 22.7% of our and 19.3% in the NSS had a masters or higher degree (not shown). Sixty-eight percent of our respondents were white, while in the NSS sample 73.3% were white. The large majority (87.7%) of our respondents were non-Nurse Practitioner clinical RNs. Characteristics of the RNs' work life are shown in Table 2. Almost 75% of the respondents worked in an inpatient setting with 25.1% working in ICUs. More than 75% did not have any prior epidemic experience or experience with the most recent natural disaster, Superstorm Sandy, which impacted the functioning of a number of hospitals in the NYC metropolitan region and required the sudden evacuation and temporary closure of the NYULH major medical center (Van Devanter et al., 2017). More than half of the respondents had been assigned to a new unit as part of NYULH's response to the pandemic. Of those, 75.9% thought that they had received sufficient support from staff at the new unit. Most RNs had cared for COVID-19 patients at least for a few days and the majority having cared for COVID-19 patients all or most days. RNs experienced COVID-19's impact not only at work but in their home life as well (Table 3). In addition to specific forced choice items, we included a scale that measures work-family conflict, the degree to which the respondent's job interferes with their home life (mean 3.31; SD 1.63; range 1-5) and the scale that measures family-work conflict, the degree to which home life interferes with their job (mean 1.62; SD 1.09; range 1-5). Only 16.5% of the RNs wrote that COVID-19 has no or minor impact on their personal or home life. Almost half of the RNs reported needing to self-isolate and more than 18% resided in some temporary place (NYULH provided housing, usually hotel space near the hospital for any RN who wanted or needed to isolate from their family). Fully 29% of the RNs had a family member or close friend who was critically ill or died from COVID-19 and for most of those RNs, they were unable to be with those family members or friends during their illness or when they died. When asked what has helped them to carry out their care of patients, the most common responses were co-worker support, training in proper Personal Protective Equipment (PPE), support from family/friends, providing support to others, and previous infectious disease patient care experience.
The mean score for anxiety was 1.97 (s.d. 1.81) and median of 2.0 (Interquartile Range (0.0-3.0). About 27.4% of the RNs scored 3 or higher, which is cut off score for further evaluation for anxiety. The data were skewed (two items; range 0-3). The mean score for depression was 1.42 (s.d. 1.57) and the median was 1.0 (Interquartile Range 0.0-2.0). About 16.5% of the RNs scored 3 or higher, which is the cut off score for further evaluation for depression.
For the multivariate analyses, we first controlled for demographic variables. Table 4 shows the relationship between the control variables and both anxiety and depression. We report medians and interquartile ranges because the data are skewed. Anxiety scores were higher for younger RNs compared to older RNs, White RNs compared to Black and Asian RNs, those working in the ICU compared to other sites, clinical nurses compared to managers, and those with Baccalaureate degrees compared to other degrees. RNs without children had higher anxiety scores than those with children. Although the median anxiety score for married/partnered RNs compared to widowed, divorced, and never married was identical, the ranges varied with married RNs having a lower range.
There were fewer differences in depression among the RNs. Younger nurses scored higher on the depression scale than older RNs. Nurses in ICUs were more likely to be depressed than those working in other sites as were RNs with a baccalaureate degree. Table 5 shows the Spearman Partial Nonparametric correlations between variables of interest and depression and anxiety, while controlling for the control variables described above (e.g., age, race, work location and role, and educational background). In terms of level of anxiety and Assets and Resources consistent with the resilience framework, higher scores of quality of physician-nurse work relations were associated with less anxiety. More support is associated with less anxiety, as was NYULH support services. More assets and resources were associated with less anxiety as was residing in temporary housing. More mastery was associated with less anxiety.
In terms of stressors and strains consistent with the resilience framework, more stress was associated with more anxiety as was higher frequency of caring for COVID-19 patients. More organizational constraints, as well as, higher number of ways in which COVID impacted one's home life was associated with more anxiety. More work-home and home-work conflict was associated with more anxiety, as well as, having a family member die and higher number of ongoing issues due to COVID-19.
Relationships with depression followed a similar pattern. In terms of assets and resources, consistent with the resilience framework, the higher the perceived quality of physician-nurse relations the lower the depression level. Higher perceived NYULH support services was also associated with a lower depression level, as was residing in temporary housing. The strongest relationship was between higher mastery scores and lower depression scores.  N u r s O u t l o o k 6 9 ( 2 0 2 1 ) 7 4 4 À7 5 4 In terms of stressors and strains, knowing that COVID-19 patients were being cared for in the RNs hospital, as well as, the higher the frequency of caring for COVID-19 patients were associated with higher levels of depression. Higher frequency of organizational constraints and personal impacts were associated with higher levels of depression. Greater work-home and home-work conflict were associated with high levels of depression. Having a. family member or friend die from COVID-19 and other ongoing personal issues were also associated with higher levels of depression.

Discussion
The COVID-19 pandemic is a public health crisis. Since the World Health Organization (WHO) designated "the novel coronavirus outbreak a public health emergency of international concern (PHEIC)" on January 30, 2020, (WHO, 2020), the pandemic has continued unabated with the number of COVID-19 related mortality and morbidity in the US and world-wide at high levels. The virus's impact on the public health infrastructure continues to mount. RNs, primary front-line workers in the COVID-19 pandemic, encounter not only the stresses and risk of a serious and potentially fatal health condition, but also the increased risk of a mental health impact. The pandemic has subjected RNs, and other front-line healthcare workers, to situations of unparalleled stress, as routine roles and responsibilities are disrupted and there is a necessity to work outside of their normal routine.
Coping with this changed work environment, one that is now a site for exposure to life threatening infection, presents a challenge the health care work force may be ill-prepared to address. This daunting task is complicated further by concerns not only about personal risk but also worry about infecting family members and others in their social network. These situational factors increase the risk for psychological morbidity and burnout. Indeed, there is growing recognition that a critical part of the public health response to the COVID-19 pandemic should be supporting the mental health of the healthcare workers (Chew et al., 2020;Walton et al., 2020).
Although it not possible to fully eliminate the risk of psychosocial morbidity, an achievable goal is to promote the factors that can build and sustain resiliency in the health care workforce. Understanding the potential triggers and vulnerability factors (e.g. stresses and strains) that contribute to psychological morbidity, such as depression and anxiety in the nursing workforce, can inform the development of institutional resources and services that would help reduce or minimize their impact, thereby, reducing the risk of psychological morbidity.
A review of the limited early studies that explored the COVID-related psychological morbidity experienced by healthcare workers, primarily nursing and medical personnel, noted that in addition to depression and anxiety symptoms, extensive stress-related strain was reported as well (Bohlken et al., 2020); as we have observed in the present investigation. Consistent with the strategies to decrease morbidity are both peer and institutional support including temporary housing. Similarly decreasing organizational constraints such as insufficient protective gear and incorrect directions is likely to decrease morbidity.
In a rapid review and meta-analysis of the occurrence, prevention and management of the adverse psychological impact of emerging virus outbreaks (e.g. SARS, MERS, Ebola, H1N1, H7N9, as well as, COVID-19) on healthcare workers, consistent with the resilience framework, the factors associated with reduced psychological morbidity included situational and psychosocial resources, such as access to adequate PPE, clear communication, adequate rest and practical as well as emotional support (Kisely et al., 2020). The importance of social support in promoting resilience was noted in a review of COVID-19-related research (Bohlken et al., 2020). These finding echo the relationships we have observed in the present study.
We observed that institutional resources and support (i.e., adequacy of PPE, sufficient communication, supportive staff relationships and sufficient supportive services) were associated with lower levels of anxiety and depression in the nursing workforce. It also merits noting that institutional resources devoted to professional development were particularly important. We found that training in the proper donning, doffing, and disposal of PPE was one of the top factors the majority of RNs identified as having helped them in caring for patients with COVID-19. Of concern, less than one quarter of the RNs in this study reported that their professional nursing education, the foundational resource for the nursing workforce, was helpful in caring for this patient population. Given the health care challenges posed by the emergence of this highly, infectious agent, this nursing education issue merits further attention.
An important concept in resiliency theory is stressrelated growth and psychological thriving À the triumphs and opportunity for personal growth one may achieve by living through and coping with an adverse experience, facing a profound challenge or adapting to a changed reality (Calhoun and Tedeschi, 2010;O'Leary & Ickovics, 1995;Park, 1998). Those who have successfully endured this type of strengths-building experience, emerge better enabled to psychologically recover from future events, continuing to grow and function, e.g. thrive, even when faced with additional hardships (Ledesma, 2014;O'Leary, 1998). These benefits or gains include acquisition of newly developed skills and knowledge, a sense of mastery or increased confidence, a strengthening of personal relationships and a changed philosophy of life (Carver, 2010; Calhoun, 1996). Long-term follow-up is required to determine the extent to which frontline RNs will experience stress-related growth and psychological thriving in the post COVID-19 pandemic era,. However, the potential for such a positive outcome in the future, supports the value of maintaining adequate, evidence-based, institutional resources to facilitate and maintain resilience in the healthcare workforce, ensuring their readiness to respond to future public health emergencies.

Author Contribution
Christine Kovner: 1) substantial contributions to conception and design, acquisition of data, and analysis and interpretation of data; 2) drafting the article or revising it critically for important intellectual content; and 3) final approval of the version to be published Victoria Raveis: 1) substantial contributions to conception and design, acquisition of data, or analysis and interpretation of data; 2) revising it critically for important intellectual content; and 3) final approval of the version to be published Nancy Van Devanter: 1) substantial contributions to conception and design, and interpretation of data; 2) revising it critically for important intellectual content; and 3) final approval of the version to be published Gary Yu: 1) substantial contributions to acquisition of data, analysis and interpretation of data; 2) final approval of the version to be published Kimberly Glassman: 1) substantial contributions to conception and design, acquisition of data, and interpretation of data; 2) revising it critically for important intellectual content, 3) final approval of the version to be published Laura Ridge: 1) substantial contributions to conception and interpretation of data; and 2) final approval of the version to be published Acknowledgment This work was supported by NYU Langone Hospitals. We would like to thank Debra Albert, DNP, MBA, RN, NEA-BC, Senior Vice President for Patient Care Services How often do you find it difficult or impossible to do your job because of conflicting job demands? (7) 1 = Never, 2 = less than once a month, 3 = 1-3 days per month, 4 = 1-2 days per week, 5 = 3-4 days per week, 6 = 5 or more days per week How often did you experience your job keep you from spending the amount of time you would like to spend with your family? (3) 1 = Never, 2 = less than once a month, 3 = 1-3 days per week, 4 = 1-2 days per week, 5 = 3-4 days per week, 6 = 5 or more days per week 3.31 (1.63) 0.88 Family-Work conflict (degree to which the respondent's job interferes with their homelife) How often did you experience your home-life interfered with your job or career (3) 1 = Never, 2 = less than once a month, 3 = 1-3 days per week, 4 = 1-2 days per week, 5 = 3-4 days per week, 6 = 5 or more days per week 1-6, 1-not at all to 6-very much 1.55 (0.83) 0.82 N u r s O u t l o o k 6 9 ( 2 0 2 1 ) 7 4 4 À7 5 4