Resilience has been recognised as a skill set in enhancing nurses’ psychological well-being. However, numerous resilience studies using various measures have produced a heterogeneous body of literature on factors associated with resilience. This review aimed to identify the personal and work-related factors associated with resilience among nurses. A search was conducted in September 2025 across six databases: CINAHL, MEDLINE, PsycINFO, Embase, the Cochrane Library, and Scopus, and we collated systematic reviews published from inception through September 2025. Systematic reviews were included if they: (1) included nurses working in a clinical setting, (2) studied resilience and its associated factors, and (3) involved cross-sectional studies as their primary studies. An umbrella review was conducted using a narrative analysis approach guided by Self-Determination Theory and Conservation of Resources theory, combined with an overlap analysis. The JBI critical appraisal checklist was utilised to assess the quality of systematic reviews. Nine systematic reviews were included. Sixteen resilience-related factors were identified across three domains: demographics, negative psychology, and positive psychology. Sex, age, marital status, education, years of nursing experience, and income were associated with nurse resilience. Burnout, emotional exhaustion, stress, anxiety, depression, and posttraumatic stress disorder were negatively related to resilience. Coping skills, self-efficacy/perceived control, overall psychosocial health, and interpersonal and organisational support were positively associated with resilience. Resilience interventions should be developed and implemented, accounting for interactions among individuals, workplaces, and organisations to enhance nurses’ psychological well-being and ultimately increase nurse retention.

BACKGROUND:Nursing shortages and increased workforce turnover have significantly increased nurses' workloads, thus increasing the risk of burnout and stress, particularly during the COVID-19 pandemic. A systematic review published in 2019 suggested that resilience could act as a buffer to adversity; however, the factors associated with resilience during and after this global pandemic have not been identified. OBJECTIVES:To identify personal and work-related factors associated with nurse resilience, including the period during and after the COVID-19 pandemic. DESIGN:Systematic review. DATA SOURCES:The search was conducted between January and February 2024 in the following databases: CINAHL Plus, MEDLINE (Ovid), PsycINFO, EMBASE, and Scopus, using the key terms 'resilience', 'hardiness', 'work', 'employ', 'occupation', 'job', and 'nursing'. REVIEW METHODS:Quantitative studies with English full text, published between 2018 and 2024, were selected if they assessed resilience and its associated factors among nurses providing direct patient care. Two authors independently completed the data selection process. Studies with quality assessment grades of 3 or above were included for final analysis. A meta-analysis was utilised for the mean resilience levels from studies using the same measures of resilience, and a narrative synthesis was performed for the demographic and work-related factors. RESULTS:Fifty-nine cross-sectional studies with a quality assessment score of 3 or above were included. Forty-seven studies were included in a meta-analysis, which reported an estimated mean resilience level of 20.69 using a random-effects model (95 % CI [18.53, 22.85], z = 18.79, p < 0.0001, I2 = 95.1 %). Twenty studies with the Connor Davidson Resilience Scale (CD-RISC)-25 and five with the CD-RISC-10 were meta-analysed for the mean resilience levels of 62.85 (95 % CI: [55.60, 70.10], z = 16.97, p < 0.0001, I2 = 31.70 %) and 26.34 (95 % CI: [20.85, 31.83], p < 0.0001, I2 = 0 %), respectively. A low mean resilience level was identified. Sixteen demographic factors were identified as associated with resilience. Twenty job demand factors negatively associated with resilience were determined and categorised into exhaustion, psychological factors, and work challenges. Thirty-two job resource factors positively related to resilience were identified and classified into the following categories: psychological factors, leadership, work performance, well-being and quality of life, and social and organisational support. CONCLUSIONS:Understanding the job demand and resource factors can help organisations minimise the risks and develop institutional strategies to protect nurses from the negative impact of COVID-19 or future pandemics on nurses' well-being.

Background: Various trials are investigating the effect of digital and face-to-face interventions on nurse resilience; however, it remains unclear whether these interventions have immediate, short-term or long-term effects. Objective: The objective of the systematic review is to identify the types of interventions and assess the immediate (<3 months), short-term (3-6 months), and long-term (>6 months) effects of these interventions on nurse resilience. Design: This systematic review was registered in the International Prospective Register of Systematic Reviews (Registered Number: CRD 42023434924), and results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. Methods: Data were collated from the databases of CINAHL, Cochrane Library, Embase (OVID), Medline, and Scopus between March and May 2023. The research protocol was determined following the framework of population, exposure, outcomes, and type of study. The articles with full text published between 2000 and 2023 were included. Studies were included if they (1) involved the nurses who provided patient care directly, (2) utilised digital or face-to-face interventions, (3) reported resilience outcomes, and (4) were randomised controlled trials or clinical trials. The JBI critical appraisal tool was utilised to assess the risk of bias for the studies collected. Results: A total of 18 studies met the criteria and were analysed. Pooled results demonstrated that digital interventions had a statistically significant positive effect on nurse resilience at 4-5-month follow-ups (standardised mean difference [SMD] = 0.71; 95 % CI = 0.13, 1.29; P = 0.02) compared to no interventions. Additionally, pooled data showed no effect on nurse resilience at all the follow-ups, compared to no interventions. No significant results were observed in comparisons of digital or face-to-face interventions between the intervention and control groups. Conclusions: The review assessed digital and face-to-face resilience interventions in nurses across 18 trials. Digital methods showed a short-term impact within 4-5 months, whilst face-to-face interventions had no effect during follow-ups. Realistic expectations, ongoing support, and tailored interventions are crucial for nurse resilience enhancement.

PurposeLimited evidence exists regarding a group of nurses' physical activity patterns and association with resilience. Less is known about the physical activity health paradox in nurses (the positive health effects of leisure time physical activity vs the negative health effects of occupational physical activity). This study aimed to explore the profiles of intensive care nurses' physical activity behaviours and associations with resilience, following a developed study-specific job demands–recovery framework.Design/methodology/approachA cross-sectional study was conducted with intensive care unit (ICU) nurses to explore their physical activity profiles and associations with resilience. The Connor-Davidson Resilience Scale 25 (CD-RISC 25) was used to assess resilience, and accelerometry was utilised to record participants' four-day activity (two workdays, two non-workdays). Hierarchical cluster analysis was employed to define groups of nurses by activity behaviours.FindingsParticipants (N = 93) were classified as low actives (n = 19), standers (n = 36), sitters (n = 31) and movers (n = 7). During two 12-h shifts, movers had the highest mean level of dynamic standing and the lowest mean level of sitting. During two non-workdays, movers had the highest mean level of walking as well as the lowest mean level of sitting and sleep time.Originality/valueThe uniqueness of this study was that it analysed ICU nurses' physical activity profiles and associations with resilience using identified clusters. However, the small number of participants limited this study's ability to determine significant relationships between resilience and the grouped physical activity profiles.

Aim and objectives To describe intensive care unit (ICU) nurses' physical work activity behavioural patterns over 12 hr using dual accelerometry, following a job demands-recovery framework. Background Limited studies utilised accelerometry to objectively analyse nurses' physical workloads. Little is known about intensive care nurses' physical activity patterns during a 12-hr shift. Design A cross-sectional study was conducted with intensive care nurses from four units in Auckland, New Zealand. Methods Each participant wore two Axivity AX3 accelerometers to measure physical activity during a 12-hr day or night shift. An online survey captured participants' demographic information. R software (version 3.6.1) and SPSS version 26 were utilised for data analysis. The STROBE was followed. Results A total of 102 nurses were included in this study. A high level of light intensity activity behaviours (standing, dynamic standing, walking) was observed throughout the day shifts, with no higher intensity behaviours identified. Activity levels were highest at the beginning of shifts and followed a consistent pattern, with an additional peak around midday for day shifts and at the end of the shift for night shifts. Observable differences were seen between day and night shifts with a greater prevalence of sitting and lying during night shifts. Standing, dynamic standing, sitting, lying and walking were significant factors in the differences of the physical work behaviours between the day shift nurses and the night shift nurses. Significant differences in dynamic standing and lying were found between ICUs. Conclusions Intensive care nurses' physical work activity involved a large amount of standing and dynamic standing during a 12-hr shift. The overall physical workload during a 12-hr day shift was significantly higher than that during a 12-hr night shift. Relevance to clinical practice Results may help managers attain a better understanding of nurses' physical workloads during a 12-hr shift.

Aim and objectives To assess intensive care nurses' resilience and identify associated personal factors and physical activity behaviours using a job demands-recovery framework. Background Currently, there is inconsistent evidence as to whether nurse resilience is associated with personal factors or with physical activity at work or during leisure time. Design A cross-sectional study was conducted with nurses from four intensive care units in Auckland, New Zealand. Methods An online survey was conducted to collect nurses' personal information and assess their resilience levels using the Connor-Davidson Resilience Scale 25. Participants were nurses working at least 32 hr fortnightly and providing direct patient care. Physical activity was objectively measured using a pair of accelerometers worn on the back and thigh over four consecutive days (two workdays followed by two nonworkdays). Bivariable and multivariable regression were used to identify personal factors and physical activity behaviours associated with resilience (followed the STROBE checklist). Results A total of 93 nurses were included in the study. The participants' average resilience level was low. Resilience was positively associated with the objectively measured physical job demands factors: occupational physical activity, moderate-to-vigorous physical activity at work and dynamic standing at work. Resilience was negatively associated with one objectively measured recovery factor: sleep during leisure time. In multivariable modelling, being married and moderate-to-vigorous physical activity at work were positively associated with resilience, while not having religious beliefs and sleep during leisure time were negatively associated with resilience. Conclusions Resilient nurses have a greater tolerance to high physical activity at work and lower sleep duration during leisure time. Strategies are needed to improve intensive care nurses' resilience levels. Relevance to clinical practice Results may help managers gain a better understanding of the ICU nurses' characteristics associated with resilience, leading them to develop strategies for improving ICU nurse resilience.

BACKGROUND:Nursing shortages have profoundly impacted hospitals and consequently increased financial expenditure, resulting in work overload, thus augmenting nurses' stress and burnout levels. Studies have found that resilience helps nurses reduce the effects of stress and burnout. However, the factors associated with nurse resilience are yet to be determined. OBJECTIVES:This systematic review aims to identify the associated personal and work-related factors of nurse resilience. DESIGN:This systematic review has been registered in the international prospective register of systematic reviews (Registered Number: CRD 42018094080). Results are reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol. DATA SOURCES:The systematic search was undertaken between March and April 2018 in five databases: CINAHL Plus, MEDLINE (Ovid), PsycINFO, EMBASE, and Scopus. The searched terms combined in each database were: resilience, hardiness, work, employ, occupation, job, and nursing. REVIEW METHODS:Full-text English articles published between 2000 and 2018 were included. Studies were also included if they involved: (1) nurses who provided direct patient care, (2) resilience and its associated factors, (3) an empirical quantitative study, and (4) a quality assessment grade of 'good' or 'fair'. Two authors carried out the study eligibility and quality assessment independently. A narrative synthesis was utilised following the Job Demands-Resources model to identify the factors of job demands and resources, which were associated with nurse resilience. RESULTS:A total of 38 articles met the criteria and were systematically reviewed and narratively synthesised. Various resilience scales utilised in these studies made it unfeasible to synthesise the evidence using a meta-analysis. Inconsistencies exist when examining personal and work-related factors. Job demands (stress, burnout, posttraumatic stress disorder, and workplace bullying) were negatively associated with resilience, while job resources (coping skills, self-efficacy, social support, job satisfaction, job retention, and general wellbeing) were positively related to resilience. Using a quality assessment tool, 23 studies were rated as 'Good', 15 were assessed as 'Fair', and 20 were found to have a risk of bias. CONCLUSIONS:Understanding nurse resilience can proactively help nurses identify or prevent potential problems, thus fostering job resources and ultimately achieving personal and professional growth. Increased nurse resilience can help nurses reduce emotional exhaustion, increase work engagement, and enhance function when facing workplace challenges. This can assist nurses to establish strategies to deal with adversity and attenuate the effects of job demands. Further research is needed to explore nurse resilience and develop a consistent instrument for measuring resilience.

Aim: To assess 12-h shift Intensive Care Unit (ICU) nurses' fatigue and identify the associated demographic factors. Background: Literature reveals inconsistencies as to whether 12-h shifts decrease or increase nurse fatigue levels. Methods: A cross-sectional survey of 67 ICU nurses working 12-h shifts was undertaken to determine their fatigue levels in two hospitals. The Occupational Fatigue Exhaustion/Recovery Scale (OFER), Spearman's correlation, ANOVA, t-tests, and Chi-Square were used for analyses. Results: 57 out of 67 participants experienced low to moderate chronic fatigue; 36 of those exhibited low to moderate acute fatigue levels; 46 reported low to moderate inter-shift fatigue. Age (rho = 0.03, r(2) = 0.28), number of family dependents (rho = 0.03, r(2) = 0.27), and years of nursing experience (rho = 0.03, r(2) = 0.27) were moderately negatively correlated with acute fatigue, while frequency of exercise per week (rho = 0.01, r(2) = 0.31) was moderately negatively correlated with chronic fatigue. Hospital A had higher chronic fatigue levels than Hospital B. Age (rho < 0.01), age group (rho = 0.03), shift schedule (rho = 0.02), and nursing experience (rho = 0.03) were significantly related to the difference in chronic fatigue levels between the two hospitals. Conclusions: More than half of the 12-h shift ICU nurses studied in both hospitals had low to moderate fatigue levels. Age, number of family dependents, years of nursing experience, and frequency of exercise per week were identified as key factors associated with fatigue. The difference in chronic fatigue levels between hospitals suggests that implementing more support for younger and/or less experienced nurses, better strategies for retaining more experienced nurses, and fewer rotating shifts could help reduce fatigue.