Nurses' Organization of Work and Its Relation to Workload in Medical Surgical Units: A Cross-Sectional Observational Multi-Center Study

Exploring Nurses' Quit Intentions: A Structural Equation Modelling and Mediation Analysis Based on the JD-R and Social Exchange Theories

BACKGROUND/OBJECTIVES

Understanding how work environments affect nurses' turnover intentions is crucial for improving retention and organizational stability. Research on factors influencing nursing turnover intentions in Italy is limited despite its significant impact on healthcare sustainability today.

AIM

This study aims to identify the individual, interpersonal, and job-related factors influencing quit intentions among nurses, examining the mediating role of job satisfaction.

METHODS

Guided by the Job Demands-Resources (JD-R) theory and Social Exchange Theory (SET), this cross-sectional study applied structural equation modelling (SEM) to analyse theoretical relationships. Researchers collected data between August 2022 and December 2023 via an online survey sent to nurses in different settings across Italy. This study tested a hypothesised mediation model using SEM analysis, demonstrating good fit indices.

RESULTS

A total of 1745 nurses responded. The findings reveal that high job demands-physical, mental, and emotional workloads-were significantly associated with increased dissatisfaction and quit intentions. Conversely, job resources, including decision-making autonomy, inspiring leadership, and positive leader-member exchanges, were linked to greater job satisfaction and retention. Contrary to expectations, work satisfaction did not mediate the relationship between job demands/resources and turnover intentions. This could be explained by the strong direct effect of job satisfaction on turnover intentions. Additionally, younger nurses were more likely to report higher turnover intentions.

CONCLUSIONS

Identifying potential quitters at an early stage is essential for the sustainability of healthcare organizations. Understanding the factors contributing to nurse turnover is crucial for developing effective retention strategies. This study emphasizes the need for healthcare organizations to prioritize supportive work environments to enhance nurse job resources, well-being, and retention.

The Relationship Between Nursing Work Environment and Breastfeeding Prevalence During Child Hospitalization: A Multicenter Study

Background/Objectives: Breastfeeding during pediatric hospitalization is often challenging, especially in a setting where nursing work environments can affect breastfeeding support. This study examines the relationship between nursing work environments and the prevalence of breastfeeding during child hospitalization, focusing on aspects such as nursing workload, stress levels, and quality of work life (QoWL). Methods: A cross-sectional multicenter study was conducted in Italian pediatric hospitals from October 2023 to January 2024. Each ward head nurse completed a form daily for 30 consecutive days to record the number of children breastfed. Nurses' workload, stress, and QoWL were measured using validated self-report questionnaires. Multivariate regression was employed to examine the associations between organizational variables and breastfeeding prevalence. Results: A total of 256 nurses from low- and medium-intensity pediatric wards completed the survey (86.7% female, mean age = 39.2, SD = 9.96). Nurses reported low stress levels (M = 2.74; SD = 0.54) and a good QoWL (M = 3.03; SD = 0.50) despite high workloads (M = 3.34; SD = 0.95). The breastfeeding prevalence mean was 1.12 (SD = 1.38), which was highest in surgical units. Regression analysis revealed that higher breastfeeding prevalence was associated with nurses' female gender (β = 0.17), clinical setting, and higher levels of nurses' QoWL (β = 0.14) (R2 = 0.23; p < 0.001). Conclusions: To enhance breastfeeding support during child hospitalizations, healthcare policies should address workload management, stress reduction, and work-life balance. Future longitudinal research should expand to other clinical settings and include detailed patient data to understand these relationships.

Predicting nursing workload in digestive wards based on machine learning: A prospective study

BACKGROUND

The process of assessing and allocating nursing staff, as well as evaluating performance, relies heavily on nursing workload, which is strongly associated with patient safety outcomes. Nevertheless, most previous studies have utilized cross-sectional data collection methods, which limit the precision of workload prediction. Static workload models do not incorporate longitudinal changes in influential factors, potentially resulting in delayed or erroneous nursing management decisions and ultimately causing imbalances in nurses' workload.

AIM

To employ machine learning algorithms to facilitate the dynamic prediction of nursing workload on the basis of patient characteristics.

METHODS

This prospective cohort quantitative study was conducted between March 2019 and August 2021 in two general hospitals located in China. Data on the characteristics of 133 patients over the course of 1339 hospital days, as well as direct nursing time, were collected. A longitudinal investigation of nursing workload was carried out, applying multiple linear regression to identify measurable factors that significantly impact nursing workload. Additionally, machine learning methods were applied to dynamically predict the nursing time needed for each patient.

RESULTS

The mean direct nursing workload varied greatly across hospitalizations. Significant factors contributing to increased care needs included complications, comorbidities, body mass index (BMI), income, history of past illness, simple clinical score (SCS), and activities of daily living (ADL). The predictive performance improved through machine learning, with the random forest model demonstrated the best performance (root mean square error (RMSE): 1148.38; coefficient of determination (R2): 0.74; mean square error (MSE): 1318744.64).

CONCLUSIONS

The variability in nursing workload during hospitalization is influenced primarily by patient self-care capacity, complications, and comorbidities. The random forest algorithm, a machine learning algorithm, effectively handles a wide range of features, such as patient characteristics, complications, comorbidities, and other factors. This algorithm has demonstrated good performance in predicting workload.

IMPLICATIONS FOR NURSING MANAGEMENT

This study introduces a quantitative model designed to evaluate nursing workload throughout the duration of hospitalization. By employing the model, nursing managers can consider multiple factors that impact workload comprehensively, resulting in enhanced comprehension and interpretation of workload variations. Through the application of a random forest algorithm for workload prediction, nursing managers can anticipate and estimate workload in a proactive and precise manner, thereby facilitating more efficient human resource planning.

Exploring the Influencing Factors of Experienced Nurses' Retention Behaviour: A Qualitative Study Based on the COM-B Model

AIM

The aim of this study was to explore the factors influencing the retention behaviour of experienced nurses in China, using the capability, opportunity, motivation and behaviour (COM-B) model as a conceptual framework.

DESIGN

A qualitative descriptive study based on the COM-B model.

METHODS

In this qualitative descriptive study, semi-structured interviews were conducted with 22 nurses across 11 cities in the Guangdong-Hong Kong-Macao Great Bay Area of China between March and May 2024. The interviews followed a predefined topic guide derived from the COM-B model. The transcriptions of the interviews were then subjected to deductive thematic analysis.

RESULTS

Eleven key themes emerged, which were embedded in three categories of the COM-B model, including capability (physical and mental health, professional knowledge and skills), motivation (increasing income, sense of fulfilment in nursing work, positive colleague relationships and job stability) and opportunity (management, career development opportunities, work-life balance, prejudice against nursing and workload).

CONCLUSIONS

The study provides new perspectives on factors influencing the retention of experienced nurses in Mainland China, Hong Kong and Macao. The study identified 11 factors that influence nurse retention behaviour, emphasising three distinctive perceptions: the 'iron rice bowl', the concept of filial piety and public prejudice towards nursing in Chinese society, which are unique to China compared to other nations. Additionally, it revealed similarities in nurse retention factors across Mainland China, Hong Kong and Macao.

IMPLICATIONS FOR THE PROFESSION

To strengthen nurse retention, it is essential to develop tailored strategies for experienced nurses. Future research should also take social culture into account to enhance retention efforts.

REPORTING METHOD

This study's reporting adhered to the Consolidated Criteria for Reporting Qualitative Studies (COREQ) checklist.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

A prospective longitudinal cohort study of the association between nurses' subjective and objective workload

Critical care nurses have high workloads due to the severity of the disease and the complexity of the treatment and care. Understanding the factors that influence subjective workload as well as the association between subjective and objective workload could lead to new insights to reduce critical care nurses' workload. (1) To describe critical care nurses' subjective and objective workload per shift in a university-affiliated interdisciplinary adult intensive care unit in Switzerland and (2) to explore the association between objective and subjective workload. The study used a prospective longitudinal cohort design. Critical care nurses completed the adapted Questionnaire on the Experience and Evaluation of Work 2.0 (QEEW2.0) to assess the subjective workload after every shift for four weeks (0 = never loaded, 100 = always loaded). The objective workload was assessed with the Therapeutic Intervention Scoring System-28 (TISS-28), Nine Equivalents of Nursing Manpower Use Score (NEMS), Swiss Society for Intensive Care Medicine (SGI)-patients' categories and Patient-to-Nurse Ratio (PNR). Data was analysed using multilevel mixed models. The workload of 60 critical care nurses with a total of 765 shifts were analysed. The critical care nurses experienced a subjective high mental load (66 ± 26), moderate pace and amount of work (30 ± 25) and physical load (33 ± 25), and low emotional-moral load (26 ± 22). The one-time baseline subjective workload values were higher than the day-to-day values. The mean objective shift load using the TISS-28 was 43 ± 16 points, the NEMS 36 ± 14 points, the SGI-category 1.1 ± 0.5 nurses needed per patient and the PNR 1.2 ± 0.4. We found positive associations between day-to-day objective variables with subjective pace and amount of work, with physical and mental load but not with emotional-moral load and performance. Measured objective workload is associated with only certain subjective workload domains. To promote and retain critical care nurses in the profession, nursing management should give a high priority to understanding subjective workload and strategies for reducing it.

Effects of job demands, job resources, personal resources on night-shift alertness of ICU shift nurses: a cross‑sectional survey study based on the job demands-resources model

BACKGROUND

A positive work environment can enhance nursing safety and patient satisfaction while alleviating nurse stress. Conversely, a poor work environment can harm nurses' physical and mental health and compromise the quality of care, particularly in the high-intensity and shift-based setting of the ICU.

OBJECTIVES

Based on the Job demands-resources (JD-R) model, this study examined the effects of job demands and job resources in the work environment, as well as personal resources, on the night-shift alertness of ICU shift nurses.

METHODS

This cross-sectional correlational exploratory study, conducted from July to September 2022, recruited 291 ICU shift nurses from a hospital in Beijing, China. The Copenhagen Psychosocial Questionnaire (COPSOQ), the Self-resilience scale, the General Self-Efficacy Scale (GSES), and the Psychomotor Vigilance Task (PVT) were used to subjectively and objectively measure the job demands, job resources, personal resources, and night-shift alertness. SPSS 26.0 and Mplus 8.3 were used to analyze the data and construct the structural equation model.

RESULTS

The night-shift reaction time was 251.0 ms (Median), indicating a relatively high level of alertness. Job demands were negatively correlated with both job resources (r=-0.570, P < 0.001) and personal resources (r=-0.462, P < 0.001), while a positive correlation existed between job resources and personal resources (r = 0.554, P < 0.001). The results show that increased job demands can lead to higher levels of nurse strain (β = 0.955, P < 0.001), whereas job resources were found that it can decrease strain (β=-0.477, P = 0.047). Adequate job resources can enhance motivation directly (β = 0.874, P < 0.001), subsequently reducing reaction time (β=-0.148, P = 0.044) and improving night-shift alertness among ICU shift nurses.

CONCLUSION

Enhancing ICU shift nurses' work motivation through bolstering job resources can boost night-shift alertness. However, it is noteworthy that, in this study, neither strain nor individual resources significantly influenced nurses' night-shift alertness. This may be attributed to the complexity of the ICU environment and individual differences. Future research should explore the relationship between these factors and nurses' work alertness.

Relevant factors affecting nurse staffing: a qualitative study from the perspective of nursing managers

Objective

To understand the current situation of nursing manpower allocation, explore the factors affecting nurse staffing, improve nurse staffing level, and provide reference for better formulation of nursing human resources staffing standards.

Methods

A descriptive research method was used to conduct semi-structured interviews with 14 nursing managers. The data were analyzed and refined by content analysis. The sample size was subject to content saturation.

Results

Nine themes and twenty sub-themes of influencing factors for nursing staffing were identified across four levels: hospital level, department level, patient level, and nurse level.

Conclusion

Hospital and department managers need to comprehensively consider the factors of affecting nurse staffing. Adopting multidimensional optimization measures, improving relevant systems, optimizing nurse structure, and establishing flexible and mobile nurse database to cope with public emergencies, so as to effectively improve nurse staffing and nursing service quality.

Clinical nurses' work procrastination and smartphone addiction: a potential profile study

Background

In the medical field, effective time management by clinical nurses is crucial for enhancing the quality of patient care. However, in recent years, with increasing work pressure for clinical nurses, procrastination has become a prevalent issue. Many nurses use smartphones as a way to alleviate stress and manage emotions, but excessive smartphone use could exacerbate procrastination, thereby jeopardizing patient safety and healthcare quality. Therefore, understanding the current state of work procrastination among clinical nurses, its heterogeneity, and exploring the impact of smartphone addiction and demographic factors on different aspects of nurse procrastination hold significant importance for improving patient care quality.

Objective

This study aims to explore the current state of work procrastination among clinical nurses and identify potential profile categories. It further analyzes the impact of mobile phone addiction and demographic factors on work procrastination among clinical nurses.

Methods

Convenience sampling was employed to recruit participants from three tertiary hospitals in central China from October to November 2023. Surveys measuring nurses' work procrastination and smartphone addiction were distributed and collected through online platforms. A total of 1,536 nurses participated in this study. Mplus 8.3 statistical software was used for latent profile analysis of clinical nurses' work procrastination, and SPSS 26.0 software was utilized for chi-square tests, rank-sum tests, and multi-classification logistic regression analyses.

Results

The median total score for clinical nurses' work procrastination was 21.00 (17.00, 28.00), and three subgroups were identified: low procrastination (66.93%), medium-low procrastination (20.66%), and medium-high procrastination (12.41%). Additionally, logistic regression analysis revealed that smartphone addiction and department atmosphere were common influencing factors for medium-low and medium-high work procrastination. Hospitals with stricter management and nurses holding the position of head nurse were more likely to belong to the low work procrastination group. Nurses with higher incomes or those holding intermediate titles were more prone to medium-low work procrastination, while those experiencing career advancement difficulties were more likely to exhibit medium-high work procrastination (p < 0.05).

Conclusion

Clinical nurses' work procrastination is generally at a medium-to-low level, with three subgroups identified: low procrastination, medium-low procrastination, and medium-high procrastination. Additionally, clinical nurses in surgical departments or those with intermediate titles exhibit higher levels of procrastination. Factors such as smartphone addiction, higher monthly income, tense departmental atmosphere, and unsuccessful career advancement are more likely to lead to work procrastination. Conversely, nurses in hospitals with strict management or those holding the position of head nurse exhibit lower levels of work procrastination. Therefore, nursing managers should pay close attention to the work procrastination behaviors of clinical nurses, actively monitor predictive factors among different groups, and provide psychological counseling and relevant training based on individual nurse circumstances. Additionally, it is also essential to focus on and improve departmental atmosphere and nurse smartphone addiction to enhance clinical nurses' work efficiency and reduce work procrastination.

Trust in the Leader, Organizational Commitment, and Nurses' Intention to Leave-Insights from a Nationwide Study Using Structural Equation Modeling

Nursing retention is a major challenge globally. Ongoing workforce instability across countries underscores the need to understand the factors influencing turnover and nursing retention. Trust is a crucial element in managing workplace relationships between nurse managers and nurses. Existing studies have shown the direct impact of trust on employees' intention to leave their job but have not explored the effects of potential mediators such as organizational commitment. The aim of this study was to examine the impact of trust in the leader on nurses' intention to leave their job through the mediation of organizational commitment. A cross-sectional study was conducted in Italy. A convenience sample of 1853 nurses completed a self-report survey. The study tested a hypothesis-based mediation model using structural equation modeling, which showed good fit indices. The results indicated that trust in the leader had a significant impact on nurses' intention to leave, and this relationship was partially mediated by organizational commitment. Nurses who trust their leader are more likely to demonstrate higher levels of organizational commitment, resulting in a lower intention to leave their job. Furthermore, organizational commitment and trust emerge as critical factors in reducing nurses' intention to leave their current positions. Therefore, managers can reduce nurses' intention to leave by building trustful relationships that enhance organizational commitment.This study was not registered.

The influence of psychosocial work environment, personal perceived health and job crafting on nurses' well-being: a cross-sectional survey study

BACKGROUND

The World Health Organization urged governments to prioritize the health and work well-being of nursing staff by promoting a positive working environment. A safe and healthy physical and psychosocial work environment is a basic human right for nurses. Job crafting is a necessary skill when facing challenging working conditions.

OBJECTIVES

This cross-sectional correlational research based on the Job Demands-Resources Model aimed to explore the correlation between psychosocial work environment and work well-being among nurses working in the intensive care unit (ICU) and determine whether personal perceived health could mediate the relationship and whether job crafting can moderate the mediating effect. The study hypothesized that: 1. The psychosocial work environment would impact nurses' work well-being; 2. Personal perceived health would play a role as a mediator in the relationship between psychosocial work environment and work well-being; 3. Job crafting would moderate the relationship between personal perceived health and work well-being.

METHODS

A total of 655 registered nurses (RNs) from 7 ICUs in a teaching hospital in Beijing participated in this study. The RNs completed a battery questionnaire measuring their health, psychosocial work environment, well-being, and job crafting. PROCESS macros analysis was used to test mediating and moderating effects.

RESULTS

Personal perceived health mediated the relationship between psychosocial work environment and work well-being (b = 0.012, 95% CI [0.008, 0.016]). The moderated mediated analysis revealed that job crafting moderated perceived health's impact on work well-being (b = -0.007, 95% CI [- 0.010, - 0.003]).

CONCLUSION

A better psychosocial work environment with well-designed work organization and job content through job crafting could positively impact nurses' health and work well-being.

Repercussions of moving patients on the context of practice: perspectives of the nursing team

OBJECTIVE

to examine the nursing team's view of the repercussions of moving patients (admissions, transfers and discharges) on the organization of work and the delivery of care.

METHOD

this is a qualitative study using the focus group technique, conducted with 23 professionals - 12 nurses, eight nurse technicians and three nurse assistants working in three inpatient units at a teaching hospital in the countryside of Sao Paulo. Four meetings took place between November 2021 and March 2022. The reports were analyzed thematically using MAXQDA software.

RESULTS

two thematic categories emerged: the influence of structural factors and work organization on the intra-hospital moving of patients; it demands time, generates work overload and interferes with the delivery of care.

CONCLUSION

the volume of moving patient associated with unforeseen demands, care complexity and insufficient staff and resources have a negative impact on the delivery of care, with clinical risks and work overload. The findings make it possible to improve the regulation of patients entering and leaving the units, work organization and care management, avoiding clinical risks, delays, omissions and work overload.

BACKGROUND

(1) Moving patients around the hospital requires structure and work organization.

BACKGROUND

(2) Nursing estimates dedicating 10-15 minutes to 2-3 hours of work on these interventions.

BACKGROUND

(3) Frequency, unpredictability and complexity of care have a negative impact on care.

BACKGROUND

(4) Unfavorable conditions for moving generate care and occupational risks.

Decoding Nursing Job Demands: A Multicenter Cross-Sectional Descriptive Study Assessing Nursing Workload in Hospital Medical-Surgical Wards

Background

Nursing workload is largely studied but poorly explored under physical, mental, and emotional dimensions. Currently, only a limited number of variables have been linked to nursing workload and work contexts.

Purpose

The study aimed to investigate whether it is feasible to identify variables that consistently correlate with nursing workload and others that are specific to the context.

Methods

We employed a descriptive correlational analysis and a cross-sectional design. Data were collected through a survey distributed to registered nurses working across Italy, at the conclusion of randomly assigned morning or afternoon shifts.

Results

We received 456 surveys from 195 shifts, collected from nurses in four public and two private hospitals. Commonly associated variables with nursing workload dimensions included patient complexity of care, admission/discharge or transfer, informing patients/relatives, contacting physicians, and unscheduled activities. Variables categorized as setting-specific were patient isolation and specialties, nurse-to-patient ratio, adequacy of staff in the shift, peer collaboration, healthcare documentation, educating others, and medical urgency.

Conclusions

In summary, certain variables consistently correlate with nursing workload across settings, while others are specific to the context of care. It is imperative for nurses and nurse managers to measure the nursing workload in various dimensions, enabling the prompt implementation of improvement actions.

Nurses' motivations to leave the nursing profession: A qualitative meta-aggregation

AIM

To systematically provide an overview of the qualitative evidence available on the motivations for nurses to leave the nursing profession.

DESIGN

A qualitative systematic review using the meta-aggregation design of the Joanna Briggs Institute.

DATA SOURCES

Qualitative studies in English, dating from 2010 until January 2023, were obtained from CINAHL, PsycINFO and PubMed.

REVIEW METHODS

Studies were selected using predetermined inclusion and exclusion criteria. Quality assessment was done using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. The assessment of confidence in the review findings was done according to the ConQual approach.

RESULTS

Nine papers that investigated nurses' motivations to leave the profession were included. We developed four synthesized findings from 11 synthesized categories and 31 categories to reflect nurses' motivations to leave the profession, including (1) challenging work environment, (2) emotional distress, (3) disappointment about nursing reality, and (4) culture of hierarchy and discrimination.

CONCLUSION

This review provides an in-depth and meaningful understanding of motivations for nurses to leave the profession. Among others, poor working conditions, a lack of opportunities for career development, a lack of support from managers, work-related stress, a discrepancy between nursing education and practice and bullying behaviour were motivations to leave the profession, which calls for targeted action to retain nurses in the profession.

IMPACT

Findings of this study shine a light on reasons why nurses leave the profession, providing evidence to support nurse managers and policymakers to develop retention strategies to move out of current crisis into recovery of sustainable global healthcare.

PATIENT OR PUBLIC CONTRIBUTION

There was no direct patient or caregiver contribution to this study because this study originated from the process of a Master study. However, two of the authors are still involved in clinical nursing practice and provided the necessary link between research and practice.

Unintended consequences of the electronic health record and cognitive load in emergency department nurses

AIM

The study aimed to explore the relationship between the unintended consequences of the electronic health record and cognitive load in emergency department nurses.

METHODS

The study utilized a correlational quantitative design with a survey method approach. This study had a 30.4 % response rate for a total of 304 ED nurse participants who were members of a national ED nursing organization. Data analysis included descriptive and correlational measurements of two instruments.

RESULTS

In this study, there was a statistically significant, weak negative relationship between CL and UC-EHR in ED nurses, rs (264) = -0.154, p 0.002. Although a significant weak relationship was identified in this study, the study variables, subscales, and demographic data groupings presented moderate-to-strong positive, statistically significant correlations. Descriptive frequency data unveiled EHR stimulated patient safety threats occurring once a week to monthly.

CONCLUSIONS

The novelty of this research study provided profound implications for the future of nursing practice, policy, and nursing science. EHR optimization to minimize patient safety risks is recommended with the inclusion of end-users from this study's identified subgroups. The researchers propose a reduction of EHR burden in nursing practice.

Assessment of the Psychometric Characteristics of the Italian Version of the Nurse Manager Actions Scale

Nurse managers play a vital role in healthcare organizations, wielding the ability to substantially enhance work environments, foster nurses' autonomy, and bolster retention within workplaces. In this context, this study focuses on the Nurse Manager Actions scale, aiming to evaluate its items' scalability as well as the scale's validity and reliability among nurses and nurse managers operating within the Italian healthcare context. The study protocol was not registered. To ensure linguistic and cultural alignment, an iterative and collaborative translation process was undertaken. Subsequently, a multi-center cross-sectional design was adopted. Using a web-survey approach, data were collected among 683 nurses and 188 nurse managers between August 2022 and January 2023. The Nurse Manager Actions scale was found to be a valid and reliable instrument in Italian after a Mokken Scale Analysis. For nurses (HT= 0.630, Molenaar-Sijtsma rho = 0.890), the scale included 6 items, while 11 items were confirmed for nurse managers (HT= 0.620, Molenaar-Sijtsma rho = 0.830). Nurse Manager Actions scale scores were correlated with increased satisfaction and decreased intention to leave for both nurses and nurse managers. The employed validation process enhanced the scale validity for use in Italy and provided a model for other researchers to follow when assessing similar measures in different populations. Measuring and empowering nurse manager actions in work contexts is essential to improve the general well-being and retention of nurses, especially in the current nursing shortage.

Psychometric Properties of the Italian Version of the Leader Member Exchange Scale (LMX-7): A Validation Study

For decades, scholars have studied leader-member exchange (LMX) relationships to understand and explain the effects of leadership on follower attitudes and performance outcomes within work settings. One available instrument to measure these aspects is the LMX-7 scale. This measurement has been widely used in empirical studies, but its psychometric properties have been poorly explored. The aim of this study was to test the psychometric characteristics (content, structural and construct validity, and reliability) of the Italian version of the LMX-7 scale and to support its cultural adaptation. We used a cross-sectional multi-center design. The forward-backward translation process was used to develop the Italian version of the scale. The scale was administered through an online survey to 837 nurses and nurse managers working in different settings. The factorial structure was tested using both exploratory and confirmatory factor analyses (EFA and CFA), and reliability was evaluated using Cronbach's alpha. For the construct validity, we used hypothesis testing and differentiation by known groups. The Italian version of the LMX-7 scale presented one dimension. All the psychometric tests performed confirmed its validity and suggested its usefulness for future research.