Literature DB >> 34182609

Healthcare worker resilience during the COVID-19 pandemic: An integrative review.

Rachel G Baskin1, Robin Bartlett2.   

Abstract

AIM: The purpose of this review was to examine resilience among healthcare workers during the coronavirus-disease-2019 (COVID-19) pandemic.
BACKGROUND: The COVID-19 pandemic has caused an unprecedented strain on healthcare workers internationally. Rising infection rates, inadequate personal protective equipment, and the lack of availability of hospital beds has resulted in further deterioration of the already-fragile mental health of healthcare workers. Resilient workers have lower rates of burnout and improved patient outcomes. EVALUATION: PubMed and the Cumulative Index to Nursing and Allied Health Literature databases were searched using the terms resilience, nurse and COVID-19 to identify studies on resilience during the COVID-19 pandemic. Results were organized by outcome measures for comparison. KEY ISSUES: Resilience scores among frontline healthcare workers worldwide during the COVID-19 pandemic in the studies reviewed were overall found to be in the moderate range. Data from the United States showed a decrease in nurse resilience, whereas participants from China had increased resilience compared with pre-pandemic levels.
CONCLUSIONS: Building resilience in nurses and other healthcare workers can serve as a protective factor against negative outcomes related to the job, including burnout, anxiety and depression, and can improve patient outcomes. IMPLICATIONS FOR NURSING MANAGEMENT: Strategies for building resilience in healthcare workers are discussed.
© 2021 John Wiley & Sons Ltd.

Entities:  

Keywords:  COVID-19; burnout; health personnel; psychological; resilience, psychological; review (publication type)

Mesh:

Year:  2021        PMID: 34182609      PMCID: PMC8420188          DOI: 10.1111/jonm.13395

Source DB:  PubMed          Journal:  J Nurs Manag        ISSN: 0966-0429            Impact factor:   4.680


INTRODUCTION

The coronavirus‐disease‐2019 (COVID‐19) pandemic has caused an unprecedented strain on healthcare systems and healthcare workers around the world. Rising infection rates, inadequate personal protective equipment, and the lack of availability of hospital beds has resulted in further deterioration of the already‐fragile mental health of healthcare workers (Firew et al., 2020). The negative state of healthcare worker mental health was documented prior to the COVID‐19 pandemic (National Academies of Sciences, Engineering, and Medicine, 2019). Being a healthcare worker during a pandemic comes with a myriad of stressors beyond those typically experienced. According to the National Academies of Sciences, Engineering, and Medicine (2021) Future of Nursing 2020–2030 report, nurses' well‐being is affected by the demands of the job, which in turn affects their work. Resilience is defined as the ability to positively adapt to traumatic or adverse experiences (Luthar & Cicchetti, 2000). Resilience can be measured using various tools, including the Connor–Davidson Resilience Scale (CD‐RISC) 25‐item version and 10‐item version (CD‐RISC10). Davidson (2018) recommended that scores be interpreted based on the quartiles of scores obtained from the general population. Scores within the first quartile are considered low resilience scores, the second and third quartiles are considered intermediate resilience scores, and scores in the fourth quartile are considered high resilience scores (Davidson, 2018). Based on the United States (U.S.) general population, a score of 73 or below indicates low resilience, and a score of 91 or higher indicates high resilience (Connor & Davidson, 2003; Davidson, 2018). The CD‐RISC 25‐item scale had a Cronbach's alpha value of 0.89 in the general population, indicating good internal reliability (Connor & Davidson, 2003). “When stress overpowers resilience, performance … can degrade” (National Academies of Sciences, Engineering, and Medicine, 2019, p. 42). With the challenges of the pandemic and their effect on healthcare workers, it is imperative that leaders and healthcare institutions understand the current state of healthcare worker resilience and burnout. Understanding the broad range of effects associated with the pandemic will inform leaders as they plan for helping healthcare personnel manage current and future challenges associated with their work. Prior to the COVID‐19 pandemic, burnout was occurring at alarming rates of 35%–54% among nurses and physicians (National Academies of Sciences, Engineering, and Medicine, 2019). The inverse relationship between resilience and burnout has been established in previous studies (Colville et al., 2015; Guo et al., 2018; Rushton et al., 2015). Interventions aimed at building resilience in healthcare workers can help to decrease rates of burnout, therefore improving patient safety (Garcia et al., 2019) and decreasing hospital‐acquired infections (Cimiotti et al., 2012; Van Bogaert et al., 2014) and medication errors (Van Bogaert et al., 2014). Not only does resilience correlate negatively with burnout, but there is also evidence of its inverse relationship with post‐traumatic stress disorder (PTSD), further elevating the importance of resilience among health care workers (Rodríguez‐Rey et al., 2019; Schäfer et al., 2018). Previous systematic reviews related to the COVID‐19 pandemic have looked at the effects of the pandemic on mental health outcomes including depression, anxiety and fear in nurses and other healthcare workers (da Silva & Neto, 2021; de Pablo et al., 2020; Sheraton et al., 2020). None of these reviews have measured resilience, an important factor associated with burnout prevention (National Academies of Sciences, Engineering, and Medicine, 2019). The purpose of this integrative review was to examine resilience in healthcare workers during the COVID‐19 pandemic. Based on the results of this review, methods of increasing nurse resilience will be discussed.

METHODS

This integrative review was conducted to identify levels of resilience among healthcare workers during the COVID‐19 pandemic, because resilience is associated with burnout and patient outcomes. Methodology by Whittemore and Knafl (2005) was the guiding framework for this integrative review. The review process is made up of five stages: problem identification, literature search, data evaluation, data analysis and presentation (Whittemore & Knafl, 2005). The Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement was utilized to guide the search methodology (Moher et al., 2009). Two searches were performed in December 2020 and February 2021 for relevant published articles from 2019 forward. The Cumulative Index to Nursing and Allied Health Literature (CINAHL) and PubMed databases were searched using the terms: nurse, resilience, and COVID‐19 (or coronavirus, 2019‐ncov, sars‐cov‐2, or cov‐19 in CINAHL). Articles were limited to those published in English, available in full‐text, and from peer‐reviewed journals. Per PRISMA guidelines, eligible articles were screened for relevance to the review, and duplicates were removed (Moher et al., 2009). Studies were considered eligible for inclusion if they explored resilience either quantitatively or qualitatively in frontline healthcare workers specifically during the COVID‐19 pandemic. Articles were excluded if they were not empirical research, if the data reported were not collected during the COVID‐19 pandemic, and if resilience was not measured. Some of the studies also reported on burnout among healthcare workers, psychological outcomes including PTSD, anxiety and depression, and some reported on work engagement. Figure 1 shows the PRISMA flow diagram and demonstrates how many articles were reviewed at each stage of the search process (Moher et al., 2009). Eligible articles were exported to a computer‐based software (Zotero) for screening of abstracts, then for full‐text article review (Zotero.org, n.d.). Data within the full‐text articles were searched for measurement of resilience using a formal tool (if a quantitative design). Means and/or correlation values were examined. Due to different resilience tools being utilized by the studies included in this review, scores had to be converted to low resilience, moderate resilience and high resilience for comparison. Results of Pearson correlations and regression analyses were also reviewed to identify relationships of resilience to other variables studied during the pandemic including anxiety, depression, work engagement and others.
FIGURE 1

Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) diagram of literature search

Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) diagram of literature search

RESULTS

A total of 191 articles were screened for inclusion criteria between the two searches; 32 were selected for this review (Figure 1). The studies were conducted from countries worldwide, including China (n = 11) (Cai et al., 2020; Hu et al., 2020; Huang et al., 2020; Leng et al., 2020; Li et al., 2020; Liang et al., 2020; Lin et al., 2020; Liu et al., 2020; Lyu et al., 2020; Ou et al., 2020; Pang et al., 2021), Italy (n = 1) (Catania et al., 2020), Iran (n = 2) (Afshari et al., 2021; Meybodi & Mohammadi, 2020), France (n = 1) (Altmayer et al., 2020), Japan (n = 1) (Awano et al., 2020), Saudi Arabia (n = 1) (Balay‐odao et al., 2021), the United States, (n = 3) (Barzilay et al., 2020; LoGuidice & Bartos, 2021; Resnick, 2020), Singapore (n = 1) (Goh et al., 2020), India (n = 2) (Jose et al., 2020; Nathiya et al., 2021), Turkey (n = 3) (Kılınç & Çelik, 2020; Yıldırım et al., 2020; Yörük & Güler, 2020), the Philippines (n = 1) (Labrague & de los Santos, 2020), Canada (n = 1) (Lapum et al., 2020), Spain (n = 2) (Lorente et al., 2020; Luceño‐Moreno et al., 2020), the United Kingdom (n = 1) (Roberts et al., 2021) and Ethiopia (n = 1) (Tsehay et al., 2020). A summary of the articles included in this integrative review and their results can be found in Table 1.
TABLE 1

Summary of literature

StudyPurposeStudy designMeasurement scalesParticipants (n)Data outcomes
Afshari et al., IranIdentify resilience scores and demographic factors among nurses working in hospitals caring for COVID‐19 patientsDescriptiveCD‐RISC, demographic information questionnaire387CD‐RISC range 26–96 (mean = 61.18). 12% of sample had high resilience (>80). Pearson correlations between resilience and: Age (r = 0.61*), work experience (r = 0.572*), and level of education (r = 0.514*).
Altmayer et al., FranceComparison between regular staff and reinforcement staff's psychological status in a neuro ICUDescriptiveHADS, PCL‐5, McGill Quality of Life Questionnaire‐ Revised (MQOL‐R), CD‐RISC1069CD‐RISC scores regular staff (mean = 29) and reinforcement staff (mean = 28).
Awano et al., JapanAssess anxiety, depression, resilience, and other psychiatric symptoms in healthcare workers during COVID‐19DescriptiveCD‐RISC 10, GAD‐7, CES‐D848Median CD‐RISC10 = 22; Spearman's correlation GAD7 and CDRISC r = −0.27***; CESD & CDRISC r = −0.43***
Balay‐odao et al., Saudi ArabiaDetermine psychological burden and resilience among nurses, and the predictors of hospital preparedness in managing COVID‐19 patientsCross‐ sectionalHospital preparedness assessment tool, DASS‐21, resilience scale for nurses281Resilience scale mean = 4.03 (high). The addition of 1 year to the participant's age resulted in a 0.2 increase in resilience (p = 0.027).
Barzilay et al., United StatesExplore anxiety, depression, and resilience scores in healthcare workers during the COVID‐19 pandemicDescriptive21‐ item resilience survey and assessment of COVID‐19‐ related stress (worries), GAD7 and PHQ23,402Those who had higher resilience scores had lower COVID‐19 related worries than participants with lower resilience scores. Higher resilience scores were associated with lower generalized anxiety*** and depression***.
Cai et al., ChinaInvestigate psychological effects in healthcare workers during the COVID‐19 pandemic and associations between social support, resilience, and mental health.Cross‐ sectionalSCL‐90, CD‐RISC, SSRS1,521Staff who did not experience a public health emergency before had significantly lower CD‐RISC scores than experienced staff***. CD‐RISC scores in ‘fresh staff’ = 67.73 (SD = 14.85), vs. experienced staff = 75.36 (SD = 13.27).
Catania et al., ItalyExplore issues with nursing management in the setting of the COVID‐19 pandemic via narratives of nursesQualitative descriptiveN/A236 themes that emerged: organizational and logistic change; leadership models adopted to manage the emergency; changes in nursing approaches; personal protective equipment (PPE) issues; physical and psychological impact on nurses; and team value/spirit.
Goh et al., SingaporeExplore nurses' experiences of working in the hospital during the COVID‐19 pandemicQualitative descriptiveN/A17Three main themes emerged: challenging moments of COVID, the professional role of the nurse, and support for nurses
Hu et al., ChinaExamine burnout, anxiety, depression, and fear and their associated factors among frontline nurses caring for COVID‐19 patients in Wuhan, ChinaCross‐sectional, descriptive, correlationalMBI, SAS, SDS, FS‐HPs, GSS, SLS, MSPSS, CDRISC102014The participants had moderate levels of burnout: EE (mean = 23.44, SD = 13.80), DP (mean = 6.77, SD = 7.05), and PA (mean = 34.83, SD = 9.95). Mean CD‐RISC = 26.14 (SD = 7.33). Resilience was significantly correlated (r) with the following: EE = −0.325***, DP = −0.208***, PA = 0.436***, anxiety = −0.427***, depression = −0.554***, and fear = −0.121***.
Huang et al., ChinaDetermine levels of anxiety and associated risk factors in health care workersCross‐ sectional, observationalSAS, CD‐RISC36416.2% of sample had resilience scores <50, 83.8% had scores >50. Resilience (b = −0.349***) was protective for the development of anxiety.
Jose et al., IndiaDetermine rates of burnout and resilience and their associated factors in nurses providing direct patient care in a tertiary care centre emergency departmentsDescriptive, cross‐ sectionalMBI‐HSS, CD‐RISC120CDRISC range 43–97 (mean = 77.77, SD = 12.41). 47.5% of the sample had high resilience. Significant correlations between resilience and EE (r = −.252 * ) and resilience and reduced personal accomplishment (r = −0.313**) were identified.
Kilinc and Celik, TurkeyDetermine the relationship between resilience and social support in nurses during the COVID‐19 pandemic in TurkeyDescriptive, cross‐ sectionalMSPSS, CD‐RISC, descriptive properties form370Mean CD‐RISC = 64.28 (SD = 15.99). Pearson's correlation (r) between CD‐RISC and MSPSS was 0.424***.
Labrague and de los Santos, PhilippinesExamine the relationship between resilience, social support and organizational support to reduce COVID‐19 anxiety in frontline nursesCross‐ sectionalCOVID‐19 anxiety scale, BRCS, PSSQ, POS325BRCS mean = 4.190 (SD = 0.687). Pearson's correlation (r) between anxiety and resilience was −0.217*** resilience predicted COVID‐19 anxiety (β = −0.151, p = 0.008).
Lapum et al., CanadaExplore how nurses are emotionally affected by working in the acute care COVID‐19 settingNarrative methodologyN/A20Themes that emerged: the emotional experience, the agency of emotions, and how emotions shape nursing and practice
Leng et al., ChinaQuantify the severity of nurses' PTSD symptoms and stress while caring for COVID‐19 patients and explore influencing factors on their psychological healthCross‐ sectionalPTSD checklist‐civilian, PSS90Mean CD‐RISC = 79.34 (SD = 11.98). PTSD scores ranged from 17–42 (mean = 24.62, SD = 6.68).
Li et al., ChinaEvaluate psychological well‐being and factors associated with PTSD among nurses during the COVID‐19 pandemicPredictivePSS, PCL‐5, CD‐RISC356Mean CD‐RISC = 59.6. Nurses with PTSD had significantly lower resilience than those without PTSD***.
Liang et al., ChinaEvaluate psychological symptoms in frontline healthcare workers in China during the COVID‐19 pandemic and compare to the general population.DescriptivePHQ9, GAD‐7, ISI, CDRISC‐10899 frontline workers and 1,104 general populationMean CD‐RISC10 medical workers in Hubei province = 26.36, vs. Hubei gen pop = 25.80; mean CD‐RISC10 medical workers other regions = 27.47 vs. other region gen pop = 26.35.
Lin et al., ChinaInvestigate resilience of nonlocal medical workers sent to support local medical workers fighting the COVID‐19 pandemicCross‐ sectionalCD‐RISC, HADS, SCSQ114Mean CDRISC = 67.04; RN resilience = 64.86, physician resilience = 67.78, other medical workers = 73.48. Resilience correlations (Pearson's r): anxiety = −0.498*, depression = −0.47*, active coping = 0.733*, and passive coping = 0.012.*
Liu et al., ChinaDescribe the experiences of healthcare providers in the early stages of the COVID‐19 outbreakEmpirical phenomenologicalN/A13Three themes were identified: being responsible for the patients' well‐being, challenges of working on COVID‐19 wards, and resilience despite the challenges
LoGuidice and Bartos, United StatesUnderstand nurses' lived experiences and levels of resilience during the COVID‐19 outbreakConvergent mixed methodsBRCS43Mean BRCS = 14.4 (SD = 2.3). 9 participants were highly resilient copers, 19 were medium resilient copers, and 15 were low resilient copers. Themes from the qualitative analysis: restorative self‐care. Proud to be a nurse, the never‐ending sanitize cycle, how nurses bridge the gap in family ties, and ‘what's the protocol today? And where is the research?’
Lorente et al., SpainEffect of sources of stress on nurses' psychological distress during the COVID‐19 pandemic and the mediating role of coping strategies and resilienceCross‐sectionalNursing stress scale (NSS), brief COPE scale, resilience scale, DASS‐21421Resilience mean = 3.79 (SD = 0.83). Resilience was negatively and significantly correlated to: insufficient preparation (−0.19***), fear of infection (−0.12, p = 0.016), problem focused coping (0.28***), and emotion focused coping (0.43***).
Luceño‐Moreno et al., SpainAnalyse post‐traumatic stress, anxiety, and depression during the COVID‐19 pandemicCross‐ sectionalIES‐R, HADS, MBI‐HSS, BRS1,422Mean BRS = 3.02. Resilience was significantly correlated with: intrusion (r = −0.361**), avoidance (r = −0.324**), hyperarousal (r = −0.434**), posttraumatic stress (r = −0.412**), anxiety (r = −0.461**), depression (r = −0.460**), EE (r = −0.324**), DP (r = −0.161**), and PA (r = 0.259**).
Lyu et al., ChinaExplore how organizational identity and resilience affect work engagement in frontline nurses during the COVID‐19 pandemicAssociationalGeneral information questionnaire, UWES, CD‐RISC, OIQ216CD‐RISC mean = 92.77 (SD = 13.06). A significant positive correlation was found between nurses' resilience and work engagement (r = 0.491**)
Meybodi and Mohammadi IranIdentify the components of spirituality that affect resilience in nurses caring for COVID‐19 patientsQualitative descriptiveN/A117 themes identified: religious values, ethical orientation, wisdom, voluntary activities, self‐awareness, belief in otherworld, and patience and hope.
Nathiya et al., IndiaInvestigate the psychological impact of the COVID‐19 pandemic on frontline workers and its associations to quality of life, resilience, and mental health outcomesDescriptive, cross‐ sectionalIES‐R, CD‐RISC, ProQOL418Participants working in COVID‐19 areas had lower resilience (OR: 0.85, p = 0.009). Resilience scores as follows: COVID‐19 unit (mean = 35.79, SD = 13.2), ICU (mean = 35.54, SD = 12.5), ED (mean = 42.3, SD = 11.1), comparison unit (mean = 48.37, SD = 9.6). Correlations between resilience and: Satisfaction (0.63), burnout (−0.469**), stress (−0.297**), avoidance (−0.392**), and hyperarousal (−0.433**).
Ou et al., ChinaInvestigate psychological symptoms in nurses and assess the impact of hospital support interventions on their psychological symptomsCross‐ sectionalCD‐RISC, SCL‐9092Mean CD‐RISC = 87.04 (SD = 22.78).
Pang et al., ChinaExplore factors related to anxiety and depression in nurses fighting COVID‐19 in ChinaCross‐ sectionalGAD‐7, PHQ9, CD‐RISC, SCSQ282Median CDRISC score = 81. CDRISC correlations to GAD‐7 (−0.379**) and PHQ‐9 (−0.375**) were both significant.
Resnick, United StatesExplore long‐term care nurses' experiences during the COVID‐19 pandemicQualitativeN/A20Emotions expressed by participants included: exhaustion, helpless, sad, hopeful, grateful, and supported. Participants requested more PPE and education on its use. Participants also provided self‐care recommendations.
Roberts et al., United KingdomExplore UK nurses' experiences of working in a respiratory clinical area during the COVID‐19 pandemicCross‐sectionalRS14, GAD7, PHQ9255Median score for resilience was 82 (range 14–98). Resilience had a significant negative correlation with both anxiety (r = −0.316***) and depression (r = −0.372***).
Tsehay et al., EthiopiaReport the prevalence of COVID‐19 related psychological distress in healthcare workers, factors associated with psychological distress, and their coping behavioursCross‐ sectionalKessler psychological distress scale (K10), BRCS, SSRS423BRCS data: High n = 14 (3.4%), moderate n = 98 (23.7%), and low n = 301 (72.9%). K10 > 20 = 42%.
Yıldırım et al., TurkeyExamine the effects of resilience and fear in the relationship between perceived risk and mental health outcomes in health professionals caring for COVID‐19 patientsCorrelationalDASS‐21, BRS204Resilience correlations with: Coronavirus fear (r = −0.33**), depression (r = −0.36**), stress (r = −0.43**), and anxiety (r = −0.38**) were significant. Correlations between perceived risk and resilience was r = −0.19.
Yörük and Güler, TurkeyDetermine the relationship between resilience, burnout, stress, and socio‐demographic variables with depression in nurses and midwives during the COVID‐19 pandemicCross‐ sectionalPSS, BDI, MBI‐HSS, RSA377Resilience mean = 124.87 (SD = 18.43). Correlations between resilience and: perceived stress (r = −0.23***). Depression (r = −0.51***), PA (r = 0.33***), DP (r = −0.25***) and EE (r = −0.26***). High psychological resilience was found to be protective against depression risk (OR: 0.95***, 95% CI: 0.93–0.96).

Abbreviations: BDI, Beck Depression Inventory; BRCS, Brief Resilient Coping Scale; BRS, Brief Resilience Scale; CD‐RISC, Connor–Davidson Resilience Scale; CES‐D, Center for Epidemiologic Studies Depression Scale; DASS‐21, Depression, Anxiety, and Stress Scale‐21; DP, depersonalization; EE, emotional exhaustion; FS‐HPs, Fear Scale for Healthcare Professionals; GAD‐7, Generalized Anxiety Disorder Scale, 7‐item; GSS, General Self‐efficacy Scale; HADS, Hospital Anxiety and Depression Scale; IES‐R, Impact of Event Scale‐ Revised; ISI, Insomnia Severity Index; MBI, Maslach Burnout Inventory/MBI‐HSS, Human Services Survey; MSPSS, Multidimensional Scale of Perceived Social Support; OIQ, Organizational Identity Scale; PA, personal accomplishment; PCL‐5, Post‐traumatic Stress Disorder Checklist for the DSM‐5; PHQ2, Patient Health Questionnaire 2; PHQ9, Patient Health Questionnaire 9; POS, Perceived Organizational Support; ProQOL, Professional Quality of Life Scale; PSS, Perceived Stress Scale; PSSQ, Perceived Social Support Questionnaire; RS14, Resilience Scale‐14 items; SAS, Self‐Rating Anxiety Scale; SCL‐90, Symptom Checklist‐90; SCSQ, Simplified Coping Style Questionnaire; SDS, Self‐Rating Depression Scale; SLS, Skin Lesion Scale; SSRS, Social Support Rating Scale; UWES, Utrecht Work Engagement Scale.

p < 0.05.

p < 0.01.

p < 0.001.

Summary of literature Abbreviations: BDI, Beck Depression Inventory; BRCS, Brief Resilient Coping Scale; BRS, Brief Resilience Scale; CD‐RISC, Connor–Davidson Resilience Scale; CES‐D, Center for Epidemiologic Studies Depression Scale; DASS‐21, Depression, Anxiety, and Stress Scale‐21; DP, depersonalization; EE, emotional exhaustion; FS‐HPs, Fear Scale for Healthcare Professionals; GAD‐7, Generalized Anxiety Disorder Scale, 7‐item; GSS, General Self‐efficacy Scale; HADS, Hospital Anxiety and Depression Scale; IES‐R, Impact of Event Scale‐ Revised; ISI, Insomnia Severity Index; MBI, Maslach Burnout Inventory/MBI‐HSS, Human Services Survey; MSPSS, Multidimensional Scale of Perceived Social Support; OIQ, Organizational Identity Scale; PA, personal accomplishment; PCL‐5, Post‐traumatic Stress Disorder Checklist for the DSM‐5; PHQ2, Patient Health Questionnaire 2; PHQ9, Patient Health Questionnaire 9; POS, Perceived Organizational Support; ProQOL, Professional Quality of Life Scale; PSS, Perceived Stress Scale; PSSQ, Perceived Social Support Questionnaire; RS14, Resilience Scale‐14 items; SAS, Self‐Rating Anxiety Scale; SCL‐90, Symptom Checklist‐90; SCSQ, Simplified Coping Style Questionnaire; SDS, Self‐Rating Depression Scale; SLS, Skin Lesion Scale; SSRS, Social Support Rating Scale; UWES, Utrecht Work Engagement Scale. p < 0.05. p < 0.01. p < 0.001. Overall, resilience scores among frontline healthcare workers during the COVID‐19 pandemic in the studies reviewed were in the moderate range (CD‐RISC range = 35.54–92.77) (Afshari et al., 2021; Cai et al., 2020; Jose et al., 2020; Kilinc & Celik, 2020; Leng et al., 2020; Li et al., 2020; Lin et al., 2020; Lyu et al., 2020; Nathiya et al., 2021; Ou et al., 2020; Pang et al., 2021). In two studies conducted in Asia, physicians had higher resilience scores than nurses (Awano et al., 2020; Lin et al., 2020), and support staff had the highest resilience scores (mean = 73.48) compared with doctors (mean = 67.78) and nurses (mean = 64.86) (Lin et al., 2020). Frontline workers, (e.g., doctors, nurses and ancillary staff) had lower CD‐RISC10 scores than non‐frontline workers (median = 18 and median = 23, respectively; = 0.061) (Awano et al., 2020). Nurses on the frontline reported emotions across a spectrum from negative to positive: from sadness, hopelessness and exhaustion to hopeful, grateful, and supported (Resnick, 2020). Resilience scores had statistically significant (p < 0.05 or smaller) inverse relationships with PTSD (Li et al., 2020; Luceño‐Moreno et al., 2020), anxiety (Awano et al., 2020; Barzilay et al., 2020; Hu et al., 2020; Labrague & de los Santos, 2020; Lin et al., 2020; Luceño‐Moreno et al., 2020; Pang et al., 2020; Roberts et al., 2020; Yıldırım et al., 2020) and depression (Awano et al., 2020; Barzilay et al., 2020; Hu et al., 2020; Lin et al., 2020; Luceño‐Moreno et al., 2020; Pang et al., 2021; Roberts et al., 2021; Yıldırım et al., 2020; Yörük & Güler, 2020). Roughly half of nurses reported moderate to high burnout, and those who had higher burnout scores reported lower resilience scores (Hu et al., 2020). There were statistically significant (p < 0.05 or smaller) negative correlations between resilience and the burnout subscales emotional exhaustion and depersonalization, and a positive correlation with the burnout subscale personal accomplishment (Hu et al., 2020; Jose et al., 2020; Luceño‐Moreno et al., 2020; Yörük & Güler, 2020). Spending more than 50% of work time with COVID‐19 patients was associated with higher burnout scores among healthcare workers compared to those who worked with COVID‐19 patients less than 25% of the time (Firew et al., 2020). Work engagement had a moderate correlation with nurse resilience (r = 0.491, p < 0.01) (Lyu et al., 2020). One nurse reported that building resilience while working during the pandemic was essential (Resnick, 2020). Nurses in Italy reported the anxiety they experienced was related to infection control processes, risk of infecting loved ones, and the distress of watching colleagues suffer, and even die, from COVID‐19 (Catania et al., 2020). These nurses also emphasized that the presence of teamwork increased resilience and their drive to overcome the challenges that the COVID‐19 pandemic presented to them (Catania et al., 2020).

DISCUSSION

The findings from this review confirmed what has been reported in previous studies in terms of the existence of an inverse relationship between resilience and burnout (Colville et al., 2015; Guo et al., 2018; Rushton et al., 2015). The articles included in this review also provided insight on the strength and direction of the relationships between resilience and other variables including work engagement (r = 0.491, p < 0.01) (Lyu et al., 2020), social support (r = 0.424, p < 0.001) (Kılınç & Çelik, 2020), PTSD (r = −0.412, p < 0.01) (Luceño‐Moreno et al., 2020), anxiety (r = −0.27, p < 0.001) (Awano et al., 2020) and depression (r = −0.43, p < 0.001) (Awano et al., 2020) during the COVID‐19 pandemic. These results can inform future studies of interventions aimed at increasing resilience to improve mental health outcomes in healthcare workers, which could also improve patient outcomes. Six of the 12 studies (50%) that measured resilience in this review using the CD‐RISC reported resilience scores below the 25th percentile (score of less than 74) based on U.S. population values (Afshari et al., 2021; Cai et al., 2020; Kilinc & Celik, 2020; Li et al., 2020; Lin et al., 2020; Nathiya et al., 2021). However, because the majority (n = 27; 84%) of studies were conducted in Europe and Asia, the lower mean resilience score of 59.99 in the Chinese population may be a better comparison value. Connor and Davidson (2003) reported that the mean CD‐RISC (resilience) score in the general U.S. population was 80.4, which is considered intermediate or moderate. The mean CD‐RISC in a Chinese population in Hong Kong was 59.99 (SD = 13.92) (Ni et al., 2015); therefore, moderate and high resilience scores would be a lower number in that population compared to the U.S. population. According to Ni et al. (2015), low scores of resilience in the Chinese population were 53 or below, whereas high resilience scores were 72 and above. Davidson (2018) noted that because scores on the CD‐RISC tool depend on geographic location of the sample, results should be interpreted with caution. This makes comparing results of international studies throughout the COVID‐19 pandemic more challenging. The mean CD‐RISC score among Chinese nurses in a study prior to the COVID‐19 pandemic was 63.52 (Guo et al., 2018), and the mean CD‐RISC score in Australian operating room nurses was 75.9 (Gillespie et al., 2007). Mean resilience scores in Chinese nurses during the pandemic ranged from 51 for those with PTSD to 73.5 for those without PTSD (Li et al., 2020). Whereas Chinese nurses showed an increased level of resilience during the pandemic, nurses in the United States had lower resilience scores compared with studies conducted prior to the pandemic. The mean 10‐item CD‐RISC score in nurses in the U.S. pre‐pandemic was 32.08 (Kelly et al., 2021), compared to a mean CD‐RISC10 score of 29.74 during the COVID‐19 pandemic (Petzel, 2021). Thus, on the basis of the studies to date, during the COVID‐19 pandemic, nurses around the world are reporting moderate resilience scores. Given the previously established link between lower resilience and burnout, and between burnout and both poorer quality of care and patient outcomes, it is critical that nurses, nurse and other leaders, healthcare organizations, and governments prioritize providing support and other resources to healthcare workers. It is particularly important that support and other resources be provided to those in front line positions, especially during a uniquely challenging time like a pandemic. Some limitations of this integrative review are that the COVID‐19 pandemic is still occurring, so it is difficult to fully capture its effects. The CD‐RISC manual (Davidson, 2018) states that resilience scores can be influenced by the region from which the data were obtained. Therefore, looking at data gathered from around the world can provide important insights into understanding this phenomenon during the pandemic, but differences in cultures and healthcare systems do not make the findings generalizable. The use of different measurement scales for resilience made comparing the findings across studies challenging. In addition, only two databases were used in this search, and the limitations of full‐text and articles written in English contributed to the number of articles available for this integrative review. Finally, grey literature was not included.

IMPLICATIONS FOR NURSING MANAGEMENT

The National Academies of Sciences, Engineering, and Medicine Initiative for Clinician Wellbeing and Resilience suggests that interventions to improve well‐being and decrease burnout should be provided not only at the individual level, but also at the organizational level (2019). In the Future of Nursing 2020–2030 report, the National Academies of Sciences, Engineering, and Medicine (2021) emphasized that nurse leaders need to be vigilant and build a long‐term strategy to address nurse well‐being in the aftermath of stress and trauma created by the COVID‐19 pandemic. Nurse leaders bear a responsibility to create an inclusive, safe work environment and implement policies to protect nurses (National Academies of Sciences, Engineering, and Medicine, 2021). Taylor (2019) described three levels of addressing nurse resilience: primary, secondary and tertiary. Primary interventions focus on building resilience through coping and communication skills, whereas secondary interventions should include evaluating levels of burnout and providing support for those who are at risk for or experiencing burnout. Lastly, tertiary level interventions should target nurses who have surpassed their resilience threshold and need support and healing in order to safely return to work. At this time, there is insufficient experimental data reported on strategies that will strengthen nurse and healthcare worker resilience (Cameron & Brownie, 2010; Delgado et al., 2017; National Academies of Sciences, Engineering, and Medicine, 2019). At the individual level, nurse managers can gauge the current emotional state of staff members on their units, which can be done, for example, by using a mood meter at a monthly staff meeting or at other times (Figure 2). Nurse leaders should remind staff that they are allowed to express feelings and concerns openly (Tomlin et al., 2020) and aim to destigmatize seeking help for mental health issues (Institute for Healthcare Improvement Multimedia Team, 2020).
FIGURE 2

Employee emotion meter. Poll Everywhere (n.d.)

Employee emotion meter. Poll Everywhere (n.d.) Another strategy for promoting individual nurse resilience is promoting expression of gratitude. This may be a useful strategy to improve nurse well‐being (Kim et al., 2019). Resources for how to build one's expression of gratitude can be found throughout the Internet and in popular books. An example of an Internet resource is PositivePsychology.com. Many exercises for building gratitude can be found on their website (https://positivepsychology.com/gratitude-exercises/). Tomlin et al. (2020) discussed phases of the COVID‐19 pandemic and the interventions that healthcare organizations can employ to build resilience among their workers based on the current phase. The phases of the pandemic they discussed are preparation, pre‐phase, initial and core phases, and the end and longer term phases (Tomlin et al., 2020). The preparation phase and pre‐phase refer to the time before any cases of COVID‐19 have occurred in the practice area. This transitions to the initial and core phases once the first and subsequent cases have been diagnosed. The end and longer term phases refer to when the pandemic has ended and there is a transition into the effects of the aftermath of the pandemic (Tomlin et al., 2020). Worldwide, we are well beyond the preparation phase that occurred before the first case of COVID‐19 emerged. Many countries are currently in the core phase, where they are experiencing continued (and sometimes rising) cases of COVID‐19. However, with widespread availability of effective COVID‐19 vaccines in some countries, these may be approaching the end phase. Organizational responses during the core phase should include providing timely and evidence‐based information on COVID‐19 to workers, visible leadership throughout the organization, and ensuring staff autonomy in decision making where appropriate (Institute for Healthcare Improvement Multimedia Team, 2020; Tomlin et al., 2020). This could be done by giving staff members the option to participate in decision making, such as selecting the type of eye protection the healthcare organization will provide for staff members to wear during patient care activities. Unit resilience can be built if nursing leaders and managers encourage a sense of coherence among members of the interdisciplinary team (Institute for Healthcare Improvement Multimedia Team, 2020), which can be done through peer support or assigning mentors (Tomlin et al., 2020). In an attempt to negate pessimistic feelings among staff members, nurse leaders can inquire about what is working well for them at the present time (Institute for Healthcare Improvement Multimedia Team, 2020) and overall as they deal with the challenges of the pandemic. As we remain hopeful to quickly move from the core phase to the end phase at the conclusion of the pandemic, healthcare organizations and leaders need to allow staff time to process their feelings. The end phase is the time for healthcare organizations to thank and reward staff members, as well as recognize staff members who are demonstrating signs of post‐traumatic stress and provide them with appropriate mental health resources (Tomlin et al., 2020). A comprehensive brochure that describes symptoms and useful treatments can be found on the National Institute for Mental Health's website at nimh.nih.gov/health/publications/ptsd‐listing.shtml. Colleaga, an open access healthcare knowledge repository, keeps a list of organizations throughout the world who provide information about PTSD, as well as a list of resources accessible via the Internet. Their PTSD list can be found at colleaga.org/article/list‐ptsd‐organizations‐and‐resources.

CONCLUSIONS

The findings from this review revealed that during the COVID‐19 pandemic, nurses have reported lower resilience scores than physicians and other healthcare workers. Nurses who had higher resilience scores experienced fewer negative mental health outcomes including anxiety, depression and PTSD. The results from this integrative review showed that, on average, nurses and healthcare workers exhibited moderate levels of resilience during the COVID‐19 pandemic. Even with moderate resilience scores, healthcare workers are not immune to the negative psychological effects of working during a pandemic. It is critical for nurse and other healthcare leaders to identify and provide ways to build resilience among healthcare workers, with a particular focus on how to increase resilience in nurses. Going forward, interventions designed to build resilience should be studied by nurse researchers to identify their impact on resilience scores among nurses and other healthcare workers, and the impact of resilience on patient outcomes. In addition, as identified by the National Academies of Sciences, Engineering, and Medicine (2019), organizational interventions must be explored to address the challenges of the effect of nurse burnout on the provision of quality healthcare. COVID‐19 has exacerbated challenges in an already fragile healthcare system. According to the National Academies of Sciences, Engineering, and Medicine (2019), individual worker resilience is one mediating factor between health system factors (e.g., excessive workload, inadequate staffing, work distraction and organizational culture) and worker burnout/professional well‐being. Because resilience among healthcare workers has been further challenged by the pandemic, it is critical that strategies to enhance worker resilience, both from the individual and the healthcare systems levels, be designed and tested.

CONFLICT OF INTEREST

None.

FUNDING SOURCES

None.

ETHICAL STATEMENT

IRB submission was exempt due to this research being a review of publicly available data.
  56 in total

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Authors:  Brigid M Gillespie; Wendy Chaboyer; Marianne Wallis; Peter Grimbeek
Journal:  J Adv Nurs       Date:  2007-07-02       Impact factor: 3.187

2.  Nursing unit teams matter: Impact of unit-level nurse practice environment, nurse work characteristics, and burnout on nurse reported job outcomes, and quality of care, and patient adverse events--a cross-sectional survey.

Authors:  Peter Van Bogaert; Olaf Timmermans; Susan Mace Weeks; Danny van Heusden; Kristien Wouters; Erik Franck
Journal:  Int J Nurs Stud       Date:  2013-12-30       Impact factor: 5.837

3.  Lessons from Italian front-line nurses' experiences during the COVID-19 pandemic: A qualitative descriptive study.

Authors:  Gianluca Catania; Milko Zanini; Mark Hayter; Fiona Timmins; Nicoletta Dasso; Giulia Ottonello; Giuseppe Aleo; Loredana Sasso; Annamaria Bagnasco
Journal:  J Nurs Manag       Date:  2020-11-15       Impact factor: 3.325

4.  Identifying the components of spirituality affecting the resilience of nurses.

Authors:  Alireza Rajabipoor Meybodi; Masoumeh Mohammadi
Journal:  J Nurs Manag       Date:  2020-12-30       Impact factor: 3.325

Review 5.  Nurses' resilience and the emotional labour of nursing work: An integrative review of empirical literature.

Authors:  Cynthia Delgado; Dominic Upton; Kristen Ranse; Trentham Furness; Kim Foster
Journal:  Int J Nurs Stud       Date:  2017-02-12       Impact factor: 5.837

6.  Nurse staffing, burnout, and health care-associated infection.

Authors:  Jeannie P Cimiotti; Linda H Aiken; Douglas M Sloane; Evan S Wu
Journal:  Am J Infect Control       Date:  2012-08       Impact factor: 2.918

7.  Anxiety, Depression, and Resilience of Healthcare Workers in Japan During the Coronavirus Disease 2019 Outbreak.

Authors:  Nobuyasu Awano; Nene Oyama; Keiko Akiyama; Minoru Inomata; Naoyuki Kuse; Mari Tone; Kohei Takada; Yutaka Muto; Kazushi Fujimoto; Yu Akagi; Momoko Mawatari; Akihiro Ueda; Junko Kawakami; Junko Komatsu; Takehiro Izumo
Journal:  Intern Med       Date:  2020-11-01       Impact factor: 1.271

8.  Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

Authors:  David Moher; Alessandro Liberati; Jennifer Tetzlaff; Douglas G Altman
Journal:  PLoS Med       Date:  2009-07-21       Impact factor: 11.069

9.  Protecting the front line: a cross-sectional survey analysis of the occupational factors contributing to healthcare workers' infection and psychological distress during the COVID-19 pandemic in the USA.

Authors:  Tsion Firew; Ellen D Sano; Jonathan W Lee; Stefan Flores; Kendrick Lang; Kiran Salman; M Claire Greene; Bernard P Chang
Journal:  BMJ Open       Date:  2020-10-21       Impact factor: 2.692

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1.  Resilience Enhancement Online Training for Nurses (REsOluTioN): Protocol for a Pilot Randomized Controlled Trial.

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2.  The Validity and Reliability of the Chula COVID-19 Psychosocial Home Isolation Evaluation Tool (CCPHIET).

Authors:  Paul Thisayakorn; Napat Sirinimnualkul; Yanin Thipakorn; Jirada Prasartpornsirichoke; Chumpol Suraphaphairoj; Gompol Suwanpimolkul; Tippamas Taechawiwat; Jose R Maldonado
Journal:  Cureus       Date:  2022-05-22

3.  Marital Status and Gender Differences as Key Determinants of COVID-19 Impact on Wellbeing, Job Satisfaction and Resilience in Health Care Workers and Staff Working in Academia in the UK During the First Wave of the Pandemic.

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4.  Individual and Work Factors Associated with Psychosocial Health of Registered Nurses During the Covid-19 Pandemic: A Mixed Methods Study.

Authors:  Amy Witkoski Stimpfel; Lauren Ghazal; Lloyd Goldsamt; Victoria Vaughan Dickson
Journal:  J Occup Environ Med       Date:  2022-01-25       Impact factor: 2.306

5.  How did SARS-CoV-2 changed the landscape in cancer care.

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Journal:  Eur J Oncol Nurs       Date:  2022-02-28       Impact factor: 2.588

6.  Resilience during Crisis and the Role of Age: Involuntary Telework during the COVID-19 Pandemic.

Authors:  Susanne Scheibe; Jessica De Bloom; Ton Modderman
Journal:  Int J Environ Res Public Health       Date:  2022-02-04       Impact factor: 3.390

7.  Promoting and Risk Factors of Nurses' Hardiness Levels during the COVID-19 Pandemic: Results from an Italian Cohort.

Authors:  Samuele Baldassini Rodriguez; Yari Bardacci; Khadija El Aoufy; Marco Bazzini; Christian Caruso; Gian Domenico Giusti; Andrea Mezzetti; Stefano Bambi; Andrea Guazzini; Laura Rasero
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8.  Exploring nurse perceptions and experiences of resilience: a meta-synthesis study.

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Journal:  BMC Nurs       Date:  2022-01-19

Review 9.  Healthcare worker resilience during the COVID-19 pandemic: An integrative review.

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