Dr Fiona Yu

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.

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.

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 (¿ = 0.03, r2 = -0.28), number of family dependents (¿ = 0.03, r2 = -0.27), and years of nursing experience (¿ = 0.03, r2 = -0.27) were moderately negatively correlated with acute fatigue, while frequency of exercise per week (¿ = 0.01, r2 = -0.31) was moderately negatively correlated with chronic fatigue. Hospital A had higher chronic fatigue levels than Hospital B. Age (¿ < 0.01), age group (¿ = 0.03), shift schedule (¿ = 0.02), and nursing experience (¿ = 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.