Aims: This review aimed to systematically assess the findings of primary studies to identify the factors associated with nurse job satisfaction in rural and urban contexts while analysing the findings according to Herzberg's theory.Background: While there is evidence linking several factors to nurses' job satisfaction, gaps still exist in understanding the differences between factors affecting job satisfaction for nurses working in rural and urban settings. Design: Systematic review with narrative summary.Data sources: Six databases were used to identify original studies that discuss the factors associated with the nurse's job satisfaction between 1998–2018.Review methods: Two authors independently reviewed each study using the Joanna Briggs Institute's critical appraisal checklists. We used the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses statement to report and examine the study biases systematically.Results: A total of 38 studies were selected for this review. Physical working environment and authority and freedom were the most frequently reported factors associated with nurses’ job satisfaction. Several extrinsic, intrinsic, personal, and community factors were also found to be associated with nurses’ job satisfaction. Urban studies tended to focus on extrinsic factors, whereas there was more balance between the two sets of factors in rural studies.Conclusion: Both intrinsic and extrinsic factors play an essential role in nurses’ job satisfaction. Future research should use more robust research methods and pay more attention to contrasting rural and urban contexts. Herzberg's theory can provide conceptual clarity when investigating the factors associated with nurses’ job satisfaction.Impact: This review discussed the factors associated with nurses’ job satisfaction in rural and urban settings. The findings linked several extrinsic and intrinsic factors to nurses’ job satisfaction. Nursing management should search for the perfect blend of intrinsic and extrinsic factors based on nurses’ needs and organizational commitment to improve nurses’ job satisfaction.

Aims: To: (a) identify the differences and similarities in the extrinsic and intrinsic factors that influence job satisfaction among nurses in urban and rural Ontario; and (b) determine the impact of job satisfaction on nurses’ turnover intention among nurses working in rural and urban settings in Ontario.Design: Cross‐sectional correlational design was used for this study.Methods: Data were collected between May 2019–July 2019 in southern Ontario. Participants (N=349) completed the Acute Care Nurses’ Job Satisfaction Scale and The Anticipated Turnover Scale. A stratified sampling technique was used for recruiting the sample population and participants were given the option to respond either online or by mailed survey.Results: There was no significant difference between rural and urban nurses in either overall job satisfaction level or turnover intention. Peer support/work conditions, quality of supervision, and achievement/job interest/responsibility were significant predictors of job satisfaction. There was a significant difference between rural and urban nurses in terms of satisfaction from benefits and job security and the nurses’ job satisfaction levels correlated negatively with their turnover intention.Conclusion: Several extrinsic and intrinsic factors are associated with nurses’ job satisfaction in rural and urban settings. Developing strategies that improve satisfaction by modulating these specific factors may improve nurses’ job satisfaction and reduce turnover.Impact: This study discussed how working in a rural or urban hospital may affect nurses’ job satisfaction and turnover intention. The findings can help in improving nurses’ job satisfaction and inform workforce planning to increase nurses’ retention.

Background: The global healthcare landscape was profoundly impacted by the COVID-19 pandemic placing nurses squarely at the heart of this emergency. This review aimed to identify the factors correlated with nurses’ job satisfaction, the impact of their job satisfaction on both themselves and their patients, and to explore strategies that might have counteracted their job dissatisfaction during the COVID-19 pandemic.Methods: The Joanna Briggs Institute (JBI) methodology for systematic reviews of prevalence and incidence was used in this review. The electronic databases of CINAHL, MEDLINE, SCOPUS, PsycINFO and Academic Search Complete were searched between January 2020 to February 2023.Results: The literature review identified 23 studies from 20 countries on nurses’ job satisfaction during the COVID-19 pandemic. A pooled prevalence of 69.6% of nurses were satisfied with personal, environmental, and psychological factors influencing their job satisfaction. Job satisfaction improved psychological wellbeing and quality of life, while dissatisfaction was linked to turnover and mental health issues.Conclusion: This systematic review elucidates key factors impacting nurses’ job satisfaction during the COVID-19 pandemic, its effects on healthcare provision, and the potential countermeasures for job dissatisfaction. Core influences include working conditions, staff relationships, and career opportunities. High job satisfaction correlates with improved patient care, reduced burnout, and greater staff retention.Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023405947, the review title has been registered in PROSPERO and the registration number is CRD42023405947.

Background: The integration of artificial intelligence (AI) across different sectors, notably healthcare, is on the rise. However, a thorough exploration of AI's incorporation into nursing research, as well as its advantages and obstacles, is still lacking.Objective: The aim of this scoping review was to map the roles, benefits, challenges, and potentials for the future development and use of AI in the context of nursing research.Methods: An exhaustive search was conducted across seven databases: MEDLINE, PsycINFO, SCOPUS, Web of Science, CINAHL, Google Scholar, and ProQuest. Articles were additionally identified through manual examination of reference lists of the articles that were included in the study. The search criteria were restricted to articles published in English between 2010 and 2023. The Joanna Briggs Institute (JBI) approach for scoping reviews and the PRISMA‐ScR guidelines guided the processes of source selection, data extraction, and data presentation.Results: Twenty articles met the inclusion criteria, covering topics from ethical considerations to methodological issues and AI's capabilities in data analysis and predictive modeling.Conclusion: The review identified both the potentials and complexities of integrating AI into nursing research. Ethical and legal considerations warrant a coordinated approach from multiple stakeholders.Implication: The findings emphasized AI's potential to revolutionize nursing research, underscoring the need for ethical guidelines, equitable access, and AI literacy training to ensure its responsible and inclusive use.

Aim: To clarify the concept of quiet quitting in nursing practice. Design: Concept analysis using Walker and Avant's concept analysis methodology. Methods: The eight‐step method by Walker and Avant guided the concept analysis. Data Sources: A systematic literature search was conducted in CINAHL, PsycINFO, Scopus and MEDLINE without date restrictions, identifying 36 empirical and theoretical articles published in English. Results: Quiet quitting in nursing is defined by four key attributes: minimal compliance with job expectations, psychological and emotional detachment, withdrawal of discretionary effort and lingering in role despite dissatisfaction. Antecedents include unhealthy work environments, psychosocial strain (e.g., burnout, moral distress) and individual/demographic influences (e.g., age, coping strategies). Consequences include impaired team dynamics, reduced care quality and organisational decline and increased turnover intentions. Twenty‐five studies used validated measurement tools, notably the Quiet Quitting Scale. Conclusion: Quiet quitting is a subtle form of disengagement distinct from burnout and turnover. It reflects an adaptive coping response to sustained dissatisfaction and unmet expectations. It is both widespread and underrecognized, with implications for healthcare sustainability. Implications for Professional and Client Care: Understanding and addressing quiet quitting is essential for safeguarding professional standards, promoting nurse engagement and ensuring high‐quality patient care. Early identification and systemic reforms are critical to mitigating its impact. Impact: This study addresses the emerging challenge of nurse quit quitting. Findings can inform leadership, education and policy development globally, particularly in healthcare settings facing workforce strain, moral distress and retention challenges. Reporting Method: This article adheres to the PRISMA‐ScR reporting guidelines. Patient or Public Contribution: This study did not include patient or public involvement in its design, conduct, or reporting.