| Literature DB >> 34182609 |
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.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
FIGURE 1Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) diagram of literature search
Summary of literature
| Study | Purpose | Study design | Measurement scales | Participants ( | Data outcomes |
|---|---|---|---|---|---|
| Afshari et al., Iran | Identify resilience scores and demographic factors among nurses working in hospitals caring for COVID‐19 patients | Descriptive | CD‐RISC, demographic information questionnaire | 387 | CD‐RISC range 26–96 (mean = 61.18). 12% of sample had high resilience (>80). Pearson correlations between resilience and: Age ( |
| Altmayer et al., France | Comparison between regular staff and reinforcement staff's psychological status in a neuro ICU | Descriptive | HADS, PCL‐5, McGill Quality of Life Questionnaire‐ Revised (MQOL‐R), CD‐RISC10 | 69 | CD‐RISC scores regular staff (mean = 29) and reinforcement staff (mean = 28). |
| Awano et al., Japan | Assess anxiety, depression, resilience, and other psychiatric symptoms in healthcare workers during COVID‐19 | Descriptive | CD‐RISC 10, GAD‐7, CES‐D | 848 | Median CD‐RISC10 = 22; Spearman's correlation GAD7 and CDRISC |
| Balay‐odao et al., Saudi Arabia | Determine psychological burden and resilience among nurses, and the predictors of hospital preparedness in managing COVID‐19 patients | Cross‐ sectional | Hospital preparedness assessment tool, DASS‐21, resilience scale for nurses | 281 | Resilience scale mean = 4.03 (high). The addition of 1 year to the participant's age resulted in a 0.2 increase in resilience ( |
| Barzilay et al., United States | Explore anxiety, depression, and resilience scores in healthcare workers during the COVID‐19 pandemic | Descriptive | 21‐ item resilience survey and assessment of COVID‐19‐ related stress (worries), GAD7 and PHQ2 | 3,402 | Those 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 |
| Cai et al., China | Investigate psychological effects in healthcare workers during the COVID‐19 pandemic and associations between social support, resilience, and mental health. | Cross‐ sectional | SCL‐90, CD‐RISC, SSRS | 1,521 | Staff who did not experience a public health emergency before had significantly lower CD‐RISC scores than experienced staff |
| Catania et al., Italy | Explore issues with nursing management in the setting of the COVID‐19 pandemic via narratives of nurses | Qualitative descriptive | N/A | 23 | 6 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., Singapore | Explore nurses' experiences of working in the hospital during the COVID‐19 pandemic | Qualitative descriptive | N/A | 17 | Three main themes emerged: challenging moments of COVID, the professional role of the nurse, and support for nurses |
| Hu et al., China | Examine burnout, anxiety, depression, and fear and their associated factors among frontline nurses caring for COVID‐19 patients in Wuhan, China | Cross‐sectional, descriptive, correlational | MBI, SAS, SDS, FS‐HPs, GSS, SLS, MSPSS, CDRISC10 | 2014 | The participants had moderate levels of burnout: EE (mean = 23.44, |
| Huang et al., China | Determine levels of anxiety and associated risk factors in health care workers | Cross‐ sectional, observational | SAS, CD‐RISC | 364 | 16.2% of sample had resilience scores <50, 83.8% had scores >50. Resilience ( |
| Jose et al., India | Determine rates of burnout and resilience and their associated factors in nurses providing direct patient care in a tertiary care centre emergency departments | Descriptive, cross‐ sectional | MBI‐HSS, CD‐RISC | 120 | CDRISC range 43–97 (mean = 77.77, |
| Kilinc and Celik, Turkey | Determine the relationship between resilience and social support in nurses during the COVID‐19 pandemic in Turkey | Descriptive, cross‐ sectional | MSPSS, CD‐RISC, descriptive properties form | 370 | Mean CD‐RISC = 64.28 ( |
| Labrague and de los Santos, Philippines | Examine the relationship between resilience, social support and organizational support to reduce COVID‐19 anxiety in frontline nurses | Cross‐ sectional | COVID‐19 anxiety scale, BRCS, PSSQ, POS | 325 | BRCS mean = 4.190 ( |
| Lapum et al., Canada | Explore how nurses are emotionally affected by working in the acute care COVID‐19 setting | Narrative methodology | N/A | 20 | Themes that emerged: the emotional experience, the agency of emotions, and how emotions shape nursing and practice |
| Leng et al., China | Quantify the severity of nurses' PTSD symptoms and stress while caring for COVID‐19 patients and explore influencing factors on their psychological health | Cross‐ sectional | PTSD checklist‐civilian, PSS | 90 | Mean CD‐RISC = 79.34 ( |
| Li et al., China | Evaluate psychological well‐being and factors associated with PTSD among nurses during the COVID‐19 pandemic | Predictive | PSS, PCL‐5, CD‐RISC | 356 | Mean CD‐RISC = 59.6. Nurses with PTSD had significantly lower resilience than those without PTSD |
| Liang et al., China | Evaluate psychological symptoms in frontline healthcare workers in China during the COVID‐19 pandemic and compare to the general population. | Descriptive | PHQ9, GAD‐7, ISI, CDRISC‐10 | 899 frontline workers and 1,104 general population | Mean 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., China | Investigate resilience of nonlocal medical workers sent to support local medical workers fighting the COVID‐19 pandemic | Cross‐ sectional | CD‐RISC, HADS, SCSQ | 114 | Mean CDRISC = 67.04; RN resilience = 64.86, physician resilience = 67.78, other medical workers = 73.48. Resilience correlations (Pearson's |
| Liu et al., China | Describe the experiences of healthcare providers in the early stages of the COVID‐19 outbreak | Empirical phenomenological | N/A | 13 | Three 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 States | Understand nurses' lived experiences and levels of resilience during the COVID‐19 outbreak | Convergent mixed methods | BRCS | 43 | Mean BRCS = 14.4 ( |
| Lorente et al., Spain | Effect of sources of stress on nurses' psychological distress during the COVID‐19 pandemic and the mediating role of coping strategies and resilience | Cross‐sectional | Nursing stress scale (NSS), brief COPE scale, resilience scale, DASS‐21 | 421 | Resilience mean = 3.79 ( |
| Luceño‐Moreno et al., Spain | Analyse post‐traumatic stress, anxiety, and depression during the COVID‐19 pandemic | Cross‐ sectional | IES‐R, HADS, MBI‐HSS, BRS | 1,422 | Mean BRS = 3.02. Resilience was significantly correlated with: intrusion ( |
| Lyu et al., China | Explore how organizational identity and resilience affect work engagement in frontline nurses during the COVID‐19 pandemic | Associational | General information questionnaire, UWES, CD‐RISC, OIQ | 216 | CD‐RISC mean = 92.77 ( |
| Meybodi and Mohammadi Iran | Identify the components of spirituality that affect resilience in nurses caring for COVID‐19 patients | Qualitative descriptive | N/A | 11 | 7 themes identified: religious values, ethical orientation, wisdom, voluntary activities, self‐awareness, belief in otherworld, and patience and hope. |
| Nathiya et al., India | Investigate the psychological impact of the COVID‐19 pandemic on frontline workers and its associations to quality of life, resilience, and mental health outcomes | Descriptive, cross‐ sectional | IES‐R, CD‐RISC, ProQOL | 418 | Participants working in COVID‐19 areas had lower resilience (OR: 0.85, |
| Ou et al., China | Investigate psychological symptoms in nurses and assess the impact of hospital support interventions on their psychological symptoms | Cross‐ sectional | CD‐RISC, SCL‐90 | 92 | Mean CD‐RISC = 87.04 ( |
| Pang et al., China | Explore factors related to anxiety and depression in nurses fighting COVID‐19 in China | Cross‐ sectional | GAD‐7, PHQ9, CD‐RISC, SCSQ | 282 | Median CDRISC score = 81. CDRISC correlations to GAD‐7 (−0.379 |
| Resnick, United States | Explore long‐term care nurses' experiences during the COVID‐19 pandemic | Qualitative | N/A | 20 | Emotions 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 Kingdom | Explore UK nurses' experiences of working in a respiratory clinical area during the COVID‐19 pandemic | Cross‐sectional | RS14, GAD7, PHQ9 | 255 | Median score for resilience was 82 (range 14–98). Resilience had a significant negative correlation with both anxiety ( |
| Tsehay et al., Ethiopia | Report the prevalence of COVID‐19 related psychological distress in healthcare workers, factors associated with psychological distress, and their coping behaviours | Cross‐ sectional | Kessler psychological distress scale (K10), BRCS, SSRS | 423 | BRCS data: High |
| Yıldırım et al., Turkey | Examine the effects of resilience and fear in the relationship between perceived risk and mental health outcomes in health professionals caring for COVID‐19 patients | Correlational | DASS‐21, BRS | 204 | Resilience correlations with: Coronavirus fear ( |
| Yörük and Güler, Turkey | Determine the relationship between resilience, burnout, stress, and socio‐demographic variables with depression in nurses and midwives during the COVID‐19 pandemic | Cross‐ sectional | PSS, BDI, MBI‐HSS, RSA | 377 | Resilience mean = 124.87 ( |
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.
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FIGURE 2Employee emotion meter. Poll Everywhere (n.d.)