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To investigate the relationship between nursing ethical leadership style, work environment (workload, interpersonal conflicts) and patients' objective nursing-sensitive outcomes (accidental falls, pressure ulcers, nosocomial infections, restraints and deaths).
Nationwide multicentre cross-sectional multilevel survey.
Validated self-report scales were used to assess nurses' perceptions of ethical leadership, workload and interpersonal conflict. Nursing staffing and objective patient' nursing-sensitive outcomes were measured at the ward level. Descriptive and inferential analyses were conducted. Structural equation modelling examined the relationships among these variables based on Donabedian's conceptual framework.
Data from 2349 nurses across 158 wards in 25 Italian acute care hospitals were analysed. The multilevel model showed an excellent fit. Ethical leadership was negatively associated with both workload and interpersonal conflict. Workload was significantly linked to higher rates of pressure ulcers, falls and deaths in patients. Ethical leadership was indirectly associated with improved patient outcomes through reduced workload.
Head nurses' ethical leadership has a pivotal role in shaping the work environment and enhancing nursing-sensitive outcomes by reducing workload and fostering positive interpersonal dynamics. These findings emphasise the need for healthcare organisations to invest in ethical leadership development as a critical strategy for improving care quality and promoting better patient outcomes.
These findings emphasise the need for healthcare organisations to invest in ethical leadership development as a critical strategy for improving care quality and promoting safer, more effective patient outcomes.
The study adhered to The Strengthening the Reporting of Observational Studies in Epidemiology checklist.
This study did not include patient or public involvement.
Cultivating moral values and principles in leadership enables leaders to effectively communicate these values to their staff. Addressing unethical behaviours, fostering open dialogue about organisational ethics, and supporting leaders in the ethical decision-making process contribute to a healthier nurses' work environment. Healthcare organisations investing in the development and promotion of ethical leaders improve care quality.
The study was registered in the research registry (www.researchregistry.com) under the record number (researchregistry7418), following a published protocol.
The study aimed to translate the PUKAT 2.0 tool from English to Italian. This was an adaptation and validation study; the validity of the Italian version was determined through content validity, item validity and construct validity. The reliability of the instrument was assessed by conducting a test–retest analysis on a sample of 62 nurses. The I-CVI indices were above the threshold of 0.78 for 91% of the questions, and according to the S-CVI index, 96% of the evaluators agreed that the questionnaire was highly relevant. The overall values for item difficulty were good, with two items being too difficult and none being too easy. The item discriminant index was overall good and reasonable, low for four items. The overall ICC was poor to moderate with a value of 0.48 (95% CI 0.26–0.65). The instrument has proven to be a good starting point although not yet completely reliable, as it clearly requires more basic preparation on the part of the staff, further modifications regarding the reliability and clarity of the questions and more training of the nursing staff if it is to be used in the Italian context.
In early stage non-small cell lung cancer (NSCLC), recurrence is frequent despite surgery and systemic treatments. Observational studies suggest that physical exercise and nutrition could improve outcomes, such as survival and treatment tolerance; however, solid evidence is lacking. The STARLighT trial aims to assess the effects of a telehealth-delivered combined exercise and nutrition intervention on clinical, biological and patient-reported outcomes in early stage NSCLC.
STARLighT is a multicentre master protocol study conducted in Italy, comprising two cohorts of patients affected by early stage NSCLC (stages IB–IIIA) epidermal growth factor receptor and anaplastic lymphoma kinase wild type. Cohort A will include 46 patients with resectable NSCLC receiving neoadjuvant treatment and will exploit a single-arm phase II design. Cohort B will enrol 268 patients undergoing adjuvant treatment (including as a part of a perioperative strategy) and proposes a randomised controlled phase III design. Patients in Cohort A and those allocated to the interventional arm in Cohort B will receive a tailored telehealth-delivered exercise and nutritional intervention. The control group will receive the usual care plus educational material. For cohort A, two coprimary endpoints are set: pathological complete response and quality of life, whereas the primary endpoint for cohort B is 2-year disease-free survival. Secondary and exploratory endpoints include a series of clinical (eg, overall survival and safety), biological (immune–inflammatory markers, gut microbiota and transcriptomics) and patient-reported outcomes (eg, sleep habits, physical activity, anxiety and depression and distress) evaluations.
The study is approved by the Ethics Committee of the University of Verona (Prot. No. 33979) and registered on ClinicalTrials.gov (NCT07042724). Findings will be disseminated through peer-reviewed journals, scientific meetings, public forums and guideline updates.
Clinicaltrial.gov: NCT07042724.
Creating a healthy work environment requires balancing organizational goals with ethical responsibilities, where head nurses' ethical leadership can shape staff outcomes by mitigating work–family conflicts and promoting nurses' well-being, retention, and patient safety. This study aims to analyze the mediating role of work–family between head nurses' ethical leadership and nurses' reported errors, turnover intention, and physical and mental health.
Nationwide Multicenter cross-sectional study.
Validated self-report scales were used to assess nurses' perceptions of head nurses' ethical leadership, work–family conflict, error, turnover intention, physical and mental health. Descriptive and inferential analyses were conducted. Structural equation modeling examined the relationships among these variables based on Della Bella's and Fiorini's framework.
Data from 409 nurses across seven Italian hospitals was analyzed. The structural equation model showed an excellent fit. Head nurses' Ethical leadership was negatively associated with work–family conflicts, turnover intention, and errors, and positively associated with nurses' health. Work–family conflicts were significantly linked to turnover intention, errors, and nurses' health. Work–family conflicts mediate the relation between ethical leadership and turnover intention, errors, and nurses' health.
Promoting healthy work environments is crucial for nurses', patients', and organizations' well-being. Ethical leadership helps achieve this condition by reducing work–family conflicts, fostering nurses' well-being, decreasing turnover intention, and improving care quality. Disseminating ethical leadership programs and integrating with work–life balance policies can therefore strengthen both staff retention and organizational outcomes.
Ethical leadership can foster patient care, reduce turnover intention and errors, and improve nurses' well-being. Therefore, maintaining employee performance and organizational results requires integrating work–life balance policies with ethical leadership development programs.
The study adhered to The Strengthening the Reporting of Observational Studies in Epidemiology checklist.
This study did not include patient or public involvement.
The study was preregistered on the Open Science Framework https://osf.io/8jk37/overview.
This study did not include patient or public involvement in its design, conduct, or reporting.
To predict nurses' turnover intention using machine learning techniques and identify the most influential psychosocial, organisational and demographic predictors across three countries.
A cross-sectional, multinational survey design.
Data were collected from 1625 nurses in the United States, Türkiye and Malta between June and September 2023 via an online survey. Twenty variables were assessed, including job satisfaction, psychological safety, depression, presenteeism, person-group fit and work engagement. Turnover intention was transformed into a binary variable using unsupervised machine learning (k-means clustering). Six supervised algorithms—logistic regression, random forest, XGBoost, decision tree, support vector machine and artificial neural networks—were employed. Model performance was evaluated using accuracy, precision, recall, F1 score and Area Under the Curve (AUC). Feature importance was examined using logistic regression (coefficients), XGBoost (gain) and random forest (mean decrease accuracy).
Logistic regression achieved the best predictive performance (accuracy = 0.829, f1 = 0.851, AUC = 0.890) followed closely by support vector machine (polynomial kernel) (accuracy = 0.805, f1 0.830, AUC = 0.864) and random forest (accuracy = 0.791, f1 = 0.820, AUC = 0.859). In the feature importance analysis, job satisfaction consistently emerged as the most influential predictor across all models. Other key predictors identified in the logistic regression model included country (USA), work experience (6–10 years), depression and psychological safety. XGBoost and random forest additionally emphasised the roles of work engagement, group-level authenticity and person–group fit. Job-stress-related presenteeism was uniquely significant in XGBoost, while depression ranked among the top predictors in both logistic regression and random forest models.
Machine learning can effectively predict turnover intention using multidimensional predictors. This methodology can support data-driven decision-making in clinical retention strategies.
This study provides a data-driven framework to identify nurses at risk of turnover. By integrating machine learning into workforce planning, healthcare leaders can develop targeted, evidence-based strategies to enhance retention and improve organisational stability.
This study adhered to STROBE reporting guideline.
This study did not include patient or public involvement in its design, conduct or reporting.
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