Nurses’ Perception of a Healthy Work Environment —Psychometric Validation Study 

Nurses’ Perception of a Healthy Work Environment —Psychometric Validation Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Nurses’ Perception of a Healthy Work Environment —Psychometric Validation Study Anna Antoszewska, Beata Penar-Zadarko, Beata Dobrowolska, Adrianna Rożniecka, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9003556/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Aim To adapt culturally and validate the Polish version of the Healthy Work Environment Assessment Tool for use among hospital nurses working in inpatient wards, and to assess nurses’ perception of the work environment in medical and surgical wards. Design Two-phase cross-cultural adaptation and psychometric validation study. Methods A cross-sectional, multicenter validation study was conducted in eight hospitals in 2024–2025. A convenience sample of nurses providing adult inpatient care completed the Healthy Work Environment Assessment Tool and the measure assessing teamwork and safety climate. Cultural adaptation was conducted in accordance with established translation and expert review procedures. A psychometric evaluation included analyses of internal structure, internal consistency, temporal stability, and convergent validity. Results The tool demonstrated good measurement performance, including high internal consistency, satisfactory temporal stability, and convergent validity, as indicated by positive relationships with related constructs. Nurses reported a low-to-moderate level of a healthy work environment, with staffing rated as the weakest area, whereas decision-making and communication were rated higher. Conclusion The Polish version of Healthy Work Environment Assessment Tool is suitable for assessing key components of a healthy work environment among hospital nurses in medical and surgical wards and may support monitoring and improvement initiatives. Implications Routine assessment can help leaders identify priority gaps, particularly staffing, and guide organizational actions that support nursing retention, quality of care, and patient safety. Impact The validated Polish version of the tool enables systematic assessment of nurses’ perceptions of a healthy work environment in hospital wards. It can help hospitals identify gaps and guide improvement efforts, particularly in staffing, to support safe, high-quality nursing care. Reporting Method The study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology reporting checklist for cross-sectional studies. healthy work environment nursing work environment psychometric validation cross-cultural adaptation hospital nursing staffing communication leadership teamwork climate Introduction The healthcare system is facing increasing challenges that directly impact the daily work of medical personnel. The most important include the growing demand for healthcare services, the shortage of nursing staff [1] the aging patient population, and the dynamic development of technology, which, combined with heavy workloads, contribute to the increasing phenomenon of burnout [2] and highlight the importance of the quality of the work environment for staff well-being [3] and patient safety [4]. Background The work environment is a complex phenomenon that has been defined and conceptualized in the extensive literature on the subject. From an organizational perspective, it refers to the culture and climate of an institution, from a psychological perspective, it refers to perceived support, satisfaction, and interpersonal relationships and from a practical perspective, it refers to material conditions, workload, and available resources [ 5 ]. Researchers suggest that it can be defined in three ways: (a) by emphasizing structural and organizational factors; (b) by emphasizing the psychosocial and relational aspects of work; and (c) by combining both dimensions into a coherent multidimensional framework [ 6 ]. The work environment includes organizational elements [ 7 ] as well as interpersonal [ 8 ] and individual [ 9 ] factors that may facilitate or hinder the maintenance of high-quality care. Many researchers emphasize that the work environment of medical staff is crucial for the quality of care, patient safety and employee well-being [ 10 ]. The hospital care environment should provide healthcare workers with a safe, supportive work environment that promotes their professional well-being, enables effective task performance, and fosters high-quality patient care. Meta-analytic evidence suggests that negative work environments are associated with poorer patient outcomes [ 11 ]. Several studies have documented that hospitals with a better work environment have lower mortality rates [ 12 ] and fewer hospital readmissions [ 13 ]. Research indicates that investing in improving healthcare workers’ working conditions can significantly reduce patient mortality [ 14 ], improve patient outcomes, and enhance the quality of care [ 15 ]. A poor assessment of the work environment also contributes to the increased frequency of omissions in required nursing care. Research results show a negative correlation between the rationing of nursing care and the assessment of the work environment [ 16 ]. This means that the lower the standards are met, the more often nursing care is omitted, which is directly related to poorer quality of care, more frequent complications [ 11 ] and mortality [ 17 ]. A healthy work environment is also undoubtedly linked to nursing outcomes. The work environment is a key factor influencing nurses’ decisions to remain in the profession, and its quality directly determines the level of retention in this professional group [ 18 ], burnout [ 19 ], and job satisfaction [ 20 ]. Research results clearly indicate that investing in improving the work environment for nurses is fundamental to the stability and quality of the healthcare system, as creating such an environment not only attracts and retains competent healthcare workers [ 21 ], but also strengthens the loyalty and satisfaction of nursing staff [ 22 ]. Elements such as communication, collaboration, and appropriate staffing significantly determine the quality of care provided to patients and their families [ 23 ]. Clinical leaders emphasize that ensuring high-quality care requires a focus on team effectiveness [ 24 ] which, in turn, requires the use of reliable and valid tools for a comprehensive assessment of organizational climate. Due to the multidimensional nature of this concept, numerous tools have been developed to assess it. A systematic literature review [ 25 ] identified 37 instruments assessing the hospital work environment developed since the 1980s. These included both nursing-specific and multiprofessional instruments addressing organizational culture, psychological climate, teamwork, and socio-organizational conditions. Content analysis revealed a wide variety of approaches, encompassing 48 distinct components that contribute to the construct of a healthy work environment. A positive work environment in healthcare is understood as one that fosters excellence and sound practice, protects the health, safety, and well-being of staff, supports high-quality patient care, and enhances the motivation, productivity, and effectiveness of teams and organizations. Standards for a healthy work environment in intensive care units (Healthy Work Environments (HWE) as defined by the American Association of Critical-Care Nurses (AACN) [ 26 ] include six key elements: skilled communication, true collaboration, effective decision-making, appropriate staffing, meaningful recognition, and authentic leadership. To assess the degree of their implementation, AACN developed the online Work Environment Assessment Tool in 2009. The Healthy Work Environment Assessment Tool (HWEAT) was designed to both establish baseline status and monitor progress of hospital units in implementing and maintaining healthy work environment standards. This tool has been validated in the United States [ 26 ]. The Healthy Work Environment Assessment Tool was used to assess the work environment in intensive care units in five European countries, including Poland, as part of the Erasmus+ project (Strategic Partnerships, Key Action 2, sector KA202) entitled “Improving Working Environments for Nurses in the Critical-Care Unit (HWE4CCN)”, implemented between 2019 and 2022 [ 27 ]. However, the evaluation of the psychometric properties of the Polish version of HWEAT during the Erasmus project was partial and based on data obtained from nurses working in intensive care units. This justifies further evaluation of the psychometric properties of the Polish version of the HWEAT in other nurse groups. The study 3.1 Purpose The aim of this study was to validate the Polish version of the Healthy Work Environment Assessment Tool (HWEAT) questionnaire among nurses working in hospital in medical and surgical wards. The study had the following main objectives: (a) to assess the reliability and validity of the Polish version of HWEAT, (b) to assess the work environment of nurses in surgical and non-surgical wards. Methods 4.1 Study design A cross-sectional, multi-center validation study was conducted in 2024–2025. 4.2 Participants Convenience sampling was used in the study. Inclusion criteria included active employment as a nurse in a hospital, providing direct patient care in a surgical or non-surgical ward for adults, consenting to participate in the study, and not holding a management position. Exclusion from participation included employment in an intensive care unit and emergency department or a lack of consent to participate in the study. Of the 359 nurses invited, 73.6% agreed to participate. A total of 264 nurses participated in both phases – the test and retest. 4.3 Research tools The following tools were used in the study: Healthy Work Environment Assessment Tool questionnaire The HWEAT developed by the American Association of Critical-Care Nurses, is used to assess key elements of a healthy environment. The questionnaire contains 16 items assigned to six key elements (standards) of a healthy work environment: (1) skilled communication, (2) true collaboration, (3) effective decision-making, (4) appropriate staffing, (5) meaningful recognition, and (6) authentic leadership. Responses are provided on a four-point Likert scale, ranging from “strongly agree” (4 points) to “strongly disagree” (1 point). The results of the healthy work environment assessment were analyzed collectively and at the level of individual standards. As the overall score and the score for each specific standard increase, the work environment is perceived as being healthier. The HWEAT questionnaire has been used in numerous studies conducted in hospital settings, covering various units and nursing populations [ 27 ]. This tool has been formally validated in the United States, where high internal consistency was demonstrated (Cronbach’s α = 0.77; range 0.77–0.81), and its psychometric validity was confirmed [ 26 ]. The AACN granted permission to use the Polish version of the HWEAT questionnaire for research purposes. Safety Attitudes and Behaviors Questionnaire (BePoZa) The Teamwork and Safety Climate (KPZiB) version of the Safety Attitudes and Behaviors Questionnaire (BePoZa) [ 28 ] consists of 27 items. Questions 1–14 assess the teamwork climate, while questions 15–27 assess the safety climate. For statements with a positive construct, a five-point Likert scale was used: 1 – strongly disagree, 2 – somewhat disagree, 3 – neither agree nor disagree, 4 – somewhat agree, 5 – strongly agree. For negatively formulated statements (questions 2, 6, 18, 23, 24), the scoring was reversed: 1 and 2 were changed to 5 and 4, respectively. A higher final score indicates a higher assessment of the teamwork and safety climate. Hospital Ethical Climate Survey (HECS-Pol) questionnaire The Polish version of the Hospital Ethical Climate Survey (HECS-Pol) comprises 21 items across five subscales: relationships with colleagues, patients, management, hospital, and doctors. Responses are provided on a five-point Likert scale (1–5), with higher scores indicating a more positive assessment of the ethical climate. The instrument is characterized by high reliability (Cronbach’s α = 0.93) and satisfactory test-retest stability [ 29 ]. Sociodemographic information was collected, including age, gender, number of workplaces, number of working hours per month, and work system (single shift/equivalent). 4.4 Cultural adaptation procedure The cultural adaptation procedure of the HWEAT questionnaire was carried out in accordance with the guidelines of the International Testing Commission. Two English translators independently prepared the Polish version of the questionnaire items. The resulting translations were analyzed by a team of experts, including specialists in nursing and research methodology, and then a working Polish version of the tool was developed. In the next stage, a back-translation into English was performed by an independent translator. The analysis of the back-translation’s compliance with the original revealed no significant discrepancies, and none of the items required modification. The final Polish version of the questionnaire was administered to a pilot sample of 30 nurses. In order to assess the content validity of the scale (content validity), an Item-Level Content Validity Index (I-CVI) was determined, with values ranging from 0 to 1 (higher values indicate better content validity) [ 30 ]. The assessment was conducted in a group of 10 nurses, and the obtained I-CVI index value was 0.92. This value exceeds the generally accepted threshold of 0.78, confirming the tool’s high content validity and indicating a high degree of agreement among the experts. 4.5 Data collection procedures The study was conducted in eight general hospitals, after obtaining consent from the facility directors. Nurses meeting the inclusion criteria were given paper questionnaires in sealed envelopes. After completion, these were returned to their immediate supervisors. Before data collection began, participants were briefed on the study’s objectives and procedures and informed of the voluntary and anonymous nature of their participation. A statement at the beginning of the questionnaire indicated that completing the survey constituted informed consent to participate in the study. Participants were informed that they could withdraw at any stage without providing a reason and that their data would be kept confidential. Throughout the procedure, participants were given the opportunity to ask questions and obtain clarifications, and data collection was conducted without pressure in an environment conducive to free and reliable responses. Of the 359 nurses invited, 73.6% accepted the invitation to participate. A total of 264 nurses participated in both stages – the test and the retest. 4.6 Data analysis Statistical analyses were performed using the Statistica TIBCO 13.3 package and IBM SPSS Statistics 25 and IBM SPSS AMOS 25 software. Descriptive statistics were used to characterize the nurses’ work environment, including frequencies (N), percentages (%), means (x), standard deviations (SD), confidence intervals (CI 95%), and measures of skewness and kurtosis. Content validity was assessed by determining the Item-Level Content Validity Index (I-CVI). The acceptable I-CVI value was 0.78 or higher [ 30 ]. A two-stage approach was used to assess the internal structure of the HWEAT-PL. First, exploratory factor analysis (EFA) was conducted separately for the “hospital-level” and “ward-level” sections to verify whether the empirical data supported the assumed six-factor structure of the instrument. The adequacy of the data for factor analysis was assessed using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity. Next, confirmatory factor analysis (CFA) was performed for the six-factor model in both sections. Model fit was assessed using the χ² statistic and the χ²/df index, as well as the fit indices: RMSEA (with 90% confidence intervals and PCLOSE), CFI, and SRMR. Additionally, the GFI and AGFI indices were reported as auxiliary measures of model fit. Cronbach’s alpha coefficient and the item-total correlation matrix were analyzed to assess the consistency of the scale items with the overall score. The test-retest stability of the HWEAT-PL tool was assessed at a three-week interval. Convergent validity was verified by analyzing the correlations of HWEAT-PL scores with the scores on the Safety Attitudes and Behaviors Questionnaire (BePoZa) and discriminant validity was verified by analyzing correlations of HWEAT-PL and the Hospital Ethical Climate Scale (HECS-Pol). A p < 0.05 was considered statistically significant. Relationships between quantitative variables were assessed using the Pearson correlation coefficient (r). The strength of the relationship was interpreted based on the absolute value of the coefficient, according to Evans’s criteria: |r|<0.20 – very weak, 0.20–0.39 – weak, 0.40–0.59 – moderate, 0.60–0.79 – strong, ≥ 0.80 – very strong. Additionally, the relationship between sociodemographic variables and HWEAT dimensions was analyzed. 4.7 Ethical procedures The research protocol was approved by the Warmia and Mazury University’s Research Ethics Committee in Olsztyn (approval number: 19/2023). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was received from the nurses after they were given information about the purpose of the study. Participation in the study was entirely voluntary. Participants had the right to withdraw at any stage by refusing to complete or return the questionnaire. During data collection, participants were given the opportunity to ask questions and seek clarification regarding the research procedure. To ensure confidentiality and data protection, all responses were anonymized using coded questionnaires, and the data were securely stored in a manner accessible only to the research team. Results Participants Two hundred and sixty-four nurses participated in both phases of the study (test and retest). The mean age at testing was 40.52 ± 12.96 years (Me = 41). Most of the nurses worked 100–180 hours per month (71.97%) in 12-hour day, night shifts system (77.65%); the majority had higher education with a specialization (47.35%) and were employed in surgical wards (62.88%). Details are presented in Table 1 . Table 1 Characteristics of Participants Variables Test n = 264 n % Gender Female 253 95.83% Male 11 4.17% Age 40.52 ± 12.96, Me = 41 Number of workplaces 1.29 ± 0.54, Me = 1 Number of working hours per month Below 100 hours 2 0.76% 100–180 hours 190 71.97% 181–230 hours 60 22.73% 231–300 hours 11 4.17% Over 300 1 0.38% Number of working hours at the workplace Below 100 hours 4 1.52% 100–180 hours 247 93.56% 181–230 hours 12 4.55% 231–300 hours 1 0.38% Work system 0.00% Single-shift/ 8-hour day shift 51 19.32% 12-hour day, night shifts 205 77.65% 12-hour day shifts 8 3.03% Education Medium 24 9.09% Higher 110 41.67% Secondary school with specialization 5 1.89% Higher education with specialization 125 47.35% Seniority Below 6 months 1 0.38% 6–11 months 42 15.91% 1–2 years 34 12.88% 3–7 years 46 17.42% 8–12 years 31 11.74% 13–20 years 41 15.53% Over 20 years 69 26.14% Ward Medical ward 98 37.12% Surgical ward 166 62.88% Me – median Analysis of the internal structure of HWEAT Exploratory factor analysis (EFA) Exploratory factor analysis was performed on the collected data. The adequacy of the data for factor analysis was confirmed based on the Kaiser–Meyer–Olkin measure (KMO = 0.89) and Bartlett’s test of sphericity (χ²=2968.68; p < 0.001) for the “hospital-level” part, and KMO = 0.91 and Bartlett’s test (χ²=3215.36; p < 0.001), respectively for the “ward-level” part. Preliminary analysis of the correlation matrix revealed numerous statistically significant correlations (p < 0.05) between items, indicating the existence of common dimensions measured by the tool. For the ““hospital-level” section, correlations ranged from r = 0.17 to 0.74, while for the “ward-level” section, they ranged from r = 0.15 to 0.77. In accordance with the study’s objective, EFA was used to verify whether the six-factor structure of the tool described in the original study is comparable in the Polish nursing population. The factors were defined as: (1) skilled communication, (2) true collaboration, (3) effective decision-making, (4) appropriate staffing, (5) meaningful recognition, and (6) authentic leadership, with the designations MP (“hospital-level”) and O (“ward-level”). The analysis yielded factor loadings of at least 0.40 for the items within the assigned factors. Correlations between HWEAT factors in the in the “hospital-level” section were statistically significant and positive (p < 0.05) and mostly moderate (r = 0.33–0.64). Similarly, in the in the “ward-level” section, interfactor correlations were statistically significant and positive (p < 0.05) and mostly moderate (r = 0.33–0.70). Details are presented in Table 2 . Confirmatory factor analysis (CFA) A CFA was conducted to assess the fit of the six-factor theoretical model. For the “hospital-level” section, the chi-square test was statistically significant (χ²=345.02; p < 0.001), and the relative index χ²/df = 3.80 indicated an acceptable fit. For the “ward-level” section, the chi-square test was also significant (χ²=359.00; p < 0.001), and χ²/df = 4.03 also indicated an acceptable fit. It should be emphasized that the chi-square test is sensitive to sample size and model complexity. In the “hospital-level” section, RMSEA = 0.078 (90% CI: 0.070–0.087) and SRMR = 0.075 were obtained, which indicates an acceptable fit. The CFI = 0.912 suggests an acceptable fit. At the same time, the PCLOSE index value of 0.001 does not support the “close fit hypothesis” (RMSEA ≤ 0.05). The GFI = 0.650 and AGFI = 0.555 were low and indicate poorer fit in these measures. In the “ward-level” section, RMSEA = 0.081 (90% CI: 0.072–0.088) and SRMR = 0.062 were obtained, indicating acceptable fit. The CFI = 0.914 also suggests an acceptable fit. As above, PCLOSE = 0.001 does not support the “close fit hypothesis”. The GFI and AGFI indices were low (0.633 and 0.534, respectively). In summary, the six-factor model was partially confirmed, and the fit to the data was acceptable to moderate based on RMSEA, CFI, and SRMR, with low GFI/AGFI values and without confirmation of the “close fit hypothesis” in the PCLOSE test. Table 2 Correlation analysis between HWEAT factors Variable x SD MP1 MP2 MP3 MP4 MP5 MP6 O1 O2 O3 O4 O5 O6 MP1 2.86 0.57 1 0.56 0.55 0.33 0.45 0.46 MP2 2.58 0.59 0.56 1 0.54 0.41 0.45 0.47 MP3 2.88 0.48 0.55 0.54 1 0.44 0.54 0.55 MP4 2.37 0.62 0.33 0.41 0.44 1 0.53 0.52 MP5 2.67 0.55 0.45 0.45 0.54 0.53 1 0.64 MP6 2.8 0.53 0.46 0.47 0.55 0.52 0.64 1 O1 2.95 0.6 1 O2 2.63 0.62 0.57 1 O3 2.96 0.49 0.57 0.54 1 O4 2.43 0.64 0.33 0.39 0.43 1 O5 2.77 0.59 0.48 0.46 0.55 0.54 1 O6 2.84 0.57 0.52 0.5 0.57 0.49 0.7 1 MP - “hospital-level” O – “ward-level” Validity and reliability of the HWEAT test Factors were labeled according to the original version of the HWEAT instrument. Furthermore, internal consistency and a test-retest approach were used to assess the HWEAT reliability. Specifically, the retest approach aimed to assess the instrument’s stability and to determine the extent to which the results of the work environment tests were independent of participant-level random factors, such as negative personal experiences or data-collection procedures. Analysis of the internal structure of the item-total correlation matrix revealed moderate correlations between the items and the total. Internal reliability analysis Cronbach’s alpha was 0.895 for the “hospital-level” section and 0.900 for the “ward-level” section. In the retest, alpha values were even higher (0.915 and 0.913, respectively), confirming the instrument’s internal stability over time. Item-total correlations for individual statements ranged from 0.34 to 0.71, and the alpha values after item deletion were lower than the total alpha, indicating that none of the questions compromised the instrument’s reliability. All items contribute significantly to the measurement of the construct under study. Detailed results are presented in Tables 3 and 4 . Table 3 Validity and reliability of HWEAT factors for the test Test Hospital-level x SD Item-total correlation Post-item alpha Ward-level x SD Item-total correlation Post-item p.1 2.86 0.69 0.477 0.890 p.1 2.96 0.71 0.500 0.895 p.2 2.88 0.71 0.594 0.886 p.2 2.94 0.75 0.618 0.891 p.3 2.78 0.67 0.609 0.886 p.3 2.92 0.70 0.631 0.890 p.4 2.44 0.78 0.512 0.890 p.4 2.47 0.80 0.523 0.894 p.5 2.44 0.74 0.540 0.888 p.5 2.46 0.76 0.535 0.894 p.6 2.88 0.70 0.603 0.886 p.6 2.96 0.70 0.658 0.889 p.7 2.86 0.61 0.615 0.886 p.7 2.89 0.63 0.591 0.892 p.8 2.77 0.69 0.556 0.888 p.8 2.85 0.68 0.528 0.894 p.9 2.94 0.64 0.503 0.889 p.9 3.08 0.65 0.519 0.894 p.10 2.21 0.75 0.375 0.895 p.10 2.28 0.79 0.344 0.901 p.11 2.41 0.69 0.521 0.889 p.11 2.42 0.68 0.519 0.894 p.12 2.42 0.76 0.604 0.886 p.12 2.55 0.83 0.641 0.890 p.13 2.86 0.59 0.530 0.889 p.13 2.97 0.58 0.568 0.893 p.14 2.76 0.68 0.655 0.884 p.14 2.82 0.72 0.684 0.888 p.15 2.73 0.66 0.647 0.884 p.15 2.80 0.73 0.655 0.889 p.16 2.84 0.65 0.569 0.887 p.16 2.86 0.69 0.575 0.892 Cronbach’s alpha 0.895 Cronbach’s alpha 0.900 x — mean; SD — standard deviation; −95% / +95% lower/upper limit of the 95% confidence interval for the mean. Table 4 Test-retest validity and reliability of HWEAT factors Retest Hospital-level x SD Item-total correlation Post-item alpha Ward-level x SD Item-total correlation Post-item alpha p.1 2.88 0.65 0.553 0.910 p.1 3.04 0.67 0.593 0.909 p.2 2.89 0.70 0.643 0.907 p.2 2.93 0.72 0.665 0.907 p.3 2.86 0.62 0.641 0.908 p.3 3.01 0.68 0.644 0.907 p.4 2.52 0.75 0.578 0.910 p.4 2.57 0.76 0.600 0.909 p.5 2.51 0.74 0.568 0.910 p.5 2.54 0.76 0.591 0.909 p.6 2.89 0.62 0.603 0.909 p.6 2.96 0.64 0.652 0.907 p.7 2.86 0.63 0.629 0.908 p.7 2.89 0.66 0.612 0.908 p.8 2.78 0.67 0.701 0.906 p.8 2.83 0.69 0.677 0.906 p.9 2.94 0.64 0.625 0.908 p.9 3.03 0.65 0.622 0.908 p.10 2.32 0.78 0.486 0.913 p.10 2.37 0.85 0.437 0.915 p.11 2.49 0.66 0.561 0.910 p.11 2.51 0.68 0.567 0.910 p.12 2.52 0.71 0.612 0.909 p.12 2.64 0.75 0.599 0.909 p.13 2.91 0.56 0.536 0.911 p.13 3.00 0.59 0.505 0.911 p.14 2.80 0.62 0.657 0.907 p.14 2.87 0.66 0.620 0.908 p.15 2.73 0.65 0.708 0.906 p.15 2.83 0.69 0.693 0.906 p.16 2.85 0.64 0.599 0.909 p16 2.92 0.69 0.620 0.908 Cronbach’s alpha 0.915 Cronbach’s alpha 0.913 x — mean; SD — standard deviation; −95% / +95% lower/upper limit of the 95% confidence interval for the mean. HWEAT test stability analysis After 3 weeks (retest), the instrument was re-administered to assess temporal stability. Pearson correlation coefficients and Cronbach’s alpha coefficients values for the “hospital-level” (MP) and “ward level” (O) question obtained at test and retest are presented in Table 5 . Pearson correlation coefficients for the “hospital-level” (MP) questions and for each factor were statistically significant, ranging from r = 0.657 (MP. Effective decision-making) to r = 0.481 (MP. Authentic leadership). Pearson correlation coefficients for the “ward-level” (O) for each factor were statistically significant, ranging from r = 0.648 (O. Effective decision-making) to r = 0.491 (O. Appropriate staffing). Detailed results are presented in Table 6 . Table 5 HWEAT Stability analysis Stability analysis Test Retest r α r α MP. Skilled communication 0.404 0.575 0.529 0.692 MP. True collaboration 0.515 0.740 0.540 0.761 MP. Effective decision-making 0.458 0.771 0.539 0.822 MP Appropriate staffing 0.417 0.588 0.526 0.689 MP. Meaningful recognition 0.479 0.647 0.563 0.720 MP. Authentic leadership 0.603 0.807 0.576 0.792 O. Skilled communication 0.481 0.649 0.551 0.711 O. True collaboration 0.529 0.754 0.530 0.754 O. Effective decision-making 0.465 0.776 0.544 0.826 O. Appropriate staffing 0.423 0.594 0.485 0.653 O. Meaningful recognition 0.491 0.658 0.473 0.642 O. Authentic leadership 0.589 0.799 0.596 0.802 MP - “hospital-level” O – “ward-level”; α – Cronbach’s alpha; r - Pearson correlation Table 6 Test-retest results of the stability analysis of the HWEAT questionnaire subscales Test-retest 1 Skilled communication 2 True collaboration 3 Effective decision-making 4 Appropriate staffing 5 Meaningful recognition 6 Authentic leadership MP. Skilled communication 0.551 MP. True collaboration 0.606 MP. Effective decision-making 0.657 MP Appropriate staffing 0.485 MP. Meaningful recognition 0.519 MP. Authentic leadership 0.481 O. Skilled communication 0.545 O. True collaboration 0.637 O. Effective decision-making 0.648 O. Appropriate staffing 0.491 O. Meaningful recognition 0.562 O. Authentic leadership 0.524 MP - “hospital-level” O – “ward-level” The construct validity of the Polish version of the HWEAT was assessed using Pearson correlations (r) between HWEAT factor scores and scores on two instruments: Safety Attitudes and Behaviors Questionnaire (BePoZa) and the Hospital Ethical Climate Scale (HECS-Pol). In the case of BePoZa, all correlations were positive and statistically significant (p < 0.001), and their strength was mostly moderate (r = 0.297–0.584), indicating consistency between the HWEAT and a measure addressing related aspects of the work environment. Detailed results are presented in Table 7 . In the case of HECS-Pol, all correlations were positive and significant (p < 0.001), but their strength was mostly moderate (r = 0.221–0.481). Detailed results are presented in Table 8 . Table 7 Pearson r correlation of HWEAT with BePoZa MP. Skilled communication Teamwork climate Safety climate BePoZa 0.339 0.348 0.368 MP. True collaboration 0.298 0.330 0.339 MP. Effective decision-making 0.442 0.505 0.511 MP Appropriate staffing 0.297 0.500 0.431 MP. Meaningful recognition 0.396 0.456 0.461 MP. Authentic leadership 0.514 0.560 0.584 O. Skilled communication 0.434 0.390 0.445 O. True collaboration 0.362 0.364 0.393 O. Effective decision-making 0.509 0.555 0.576 O. Appropriate staffing 0.307 0.499 0.435 O. Meaningful recognition 0.472 0.522 0.539 O. Authentic leadership 0.534 0.553 0.593 MP - “hospital-level”; O – “ward-level”; p < 0.0001 Table 8 Pearson r correlation of HWEAT with HECS-Pol MP. Skilled communication Relationships with colleagues Relationships with patients Relations with management Relations with the hospital Relationships with doctors HECS-Pol 0.227 0.256 0.285 0.313 0.206 0.295 MP. True collaboration 0.250 0.231 0.264 0.350 0.246 0.311 MP. Effective decision-making 0.345 0.321 0.345 0.393 0.309 0.394 MP Appropriate staffing 0.234 0.221 0.319 0.301 0.224 0.305 MP. Meaningful recognition 0.311 0.301 0.276 0.356 0.305 0.356 MP. Authentic leadership 0.388 0.337 0.408 0.438 0.323 0.437 O. Skilled communication 0.280 0.272 0.338 0.387 0.229 0.345 O. True collaboration 0.321 0.287 0.308 0.410 0.270 0.365 O. Effective decision-making 0.390 0.348 0.402 0.458 0.318 0.439 O. Appropriate staffing 0.238 0.226 0.322 0.316 0.254 0.320 O. Meaningful recognition 0.389 0.369 0.353 0.417 0.331 0.423 O. Authentic leadership 0.412 0.368 0.431 0.481 0.326 0.462 MP - “hospital-level”; O – “ward-level”; p < 0.0001 Descriptive statistics and factors influencing HWEAT levels The aim of the analysis was to present descriptive statistics for individual HWEAT dimensions and to identify factors differentiating the results. Across the entire sample (n = 264), mean scores ranged from 2.31 to 2.95 (scale 1–4), and medians ranged from 2.50–3.00, indicating a low-to-moderate level of a healthy work environment. The lowest scores were recorded for the “appropriate staffing” dimensions (MP: M = 2.31; O: M = 2.35), while the relatively highest scores were recorded for “effective decision-making” (MP: M = 2.87; O: M = 2.95) and “skilled communication” (MP: M = 2.87; O: M = 2.95). The remaining dimensions were in the middle of the distribution (e.g., “meaningful recognition”: MP: 2.64; O: 2.76; “authentic leadership”: MP: 2.78; O: 2.83; “true collaboration”: MP: 2.55; O: 2.62). The variability of the scores was moderate (SD approximately 0.51–0.63), and the 95% confidence intervals for the means were narrow (approximately ± 0.05–0.06), indicating satisfactory precision of the estimates. The distributions were close to normal, with weak skewness (from approximately − 0.22 to 0.40) and kurtosis close to zero (from approximately − 0.05 to 1.35). In some dimensions, such as “effective decision-making”, slightly higher kurtosis was observed, suggesting a more “peaky” distribution around the central values. A comparison of perspectives indicates slightly higher ratings for “ward-level” than “hospital-level”, although these differences remain small. Analyses of differentiating factors revealed no influence of gender, age, total monthly work hours, or shift pattern on the levels of individual HWEAT dimensions. However, significant associations were found for characteristics related to career progression and workload. Employment duration (in months) was associated with the “appropriate staffing” dimension in both the “hospital-level” and “ward-level” perspectives. The number of hours spent in the workplace differentiated scores on “true collaboration” from the “hospital-level” perspective. Education was associated with the level of “skilled communication” in both perspectives. Seniority differentiated “effective decision-making” in the “hospital-level” perspective. Detailed results are presented in Table 9 . Table 9 Descriptive statistics of the HWEAT questionnaire HWEAT dimensions/ standards N x ME Min Max Q1 Q3 SD -95% + 95% Skewness Kurtosis MP. Skilled communication 264 2.87 3.00 1.00 4.00 2.50 3.00 0.59 0.54 0.64 0.04 0.43 MP. True collaboration 264 2.55 2.33 1.00 4.00 2.00 3.00 0.60 0.55 0.65 0.40 0.73 MP. Effective decision-making 264 2.87 3.00 1.00 4.00 2.75 3.00 0.51 0.47 0.56 -0.17 1.34 MP Appropriate staffing 264 2.31 2.50 1.00 4.00 2.00 2.50 0.60 0.56 0.66 -0.17 -0.02 MP. Meaningful recognition 264 2.64 2.50 1.00 4.00 2.00 3.00 0.58 0.54 0.64 0.10 0.13 MP. Authentic leadership 264 2.78 3.00 1.00 4.00 2.33 3.00 0.56 0.52 0.61 -0.07 0.57 O. Skilled communication 264 2.95 3.00 1.00 4.00 2.50 3.50 0.63 0.58 0.69 -0.08 0.15 O. True collaboration 264 2.62 2.67 1.00 4.00 2.33 3.00 0.62 0.57 0.68 0.24 0.34 O. Effective decision-making 264 2.95 3.00 1.00 4.00 2.75 3.25 0.52 0.47 0.56 -0.22 1.35 O. the appropriate staffing 264 2.35 2.50 1.00 4.00 2.00 3.00 0.62 0.57 0.68 -0.15 -0.05 O. Meaningful recognition 264 2.76 3.00 1.00 4.00 2.50 3.00 0.61 0.56 0.67 0.07 0.18 O. Authentic leadership 264 2.83 3.00 1.00 4.00 2.33 3.00 0.60 0.56 0.66 -0.01 0.24 N — number; x — mean; ME — median; Min/Max — minimum/maximum values; Q1/Q3 — first/third quartile; SD — standard deviation; −95% / +95% lower/upper limit of the 95% confidence interval for the mean; MP — Hospital-level; O — Ward-level. Scale 1–4 (higher = more favorable). Discussion The aim of this study was to assess the psychometric properties of the Polish version of the HWEAT and to measure the level of key elements of a healthy work environment among nurses. Although tools assessing related dimensions of organizational climate are available in Poland, including BePoZa (teamwork and safety climate components) [ 28 ] and the Polish version of Practice Environment Scale of the Nursing Work Index (PES-NWI) [ 31 ], they do not directly relate to the full set of HWE standards defined by the AACN. Therefore, adaptation and validation of the HWEAT and verification of its reliability and validity in a sample of Polish nurses are important for further research and international comparisons. Results of the validation process The Polish version of the HWEAT demonstrated very good psychometric properties. Internal consistency of the entire scale was high: at baseline, α = 0.895 (hospital-level perspective) and α = 0.900 (ward-level perspective), and at retests, α = 0.915 and α = 0.913, respectively. Item-total correlations for all items ranged from moderate to high, and the “post-item alpha” values remained lower than the total α, indicating that no item reduced the scale’s reliability. Test-to-retest stability after three weeks was satisfactory for all dimensions and both assessment perspectives. When assessing sample size adequacy, commonly cited item-to-respondent ratios were also considered. Although there is no clear consensus in the literature regarding the minimum required sample size in validation studies, a ratio of at least 1:10 is often recommended [ 32 ]. In the current study, 16 questionnaire items were completed by 264 participants, a proportion that significantly exceeded the threshold, thereby confirming that the sample was sufficiently large for reliable psychometric analyses [ 32 ]. In the “hospital-level” category, Pearson r coefficients ranged from r = 0.481 (authentic leadership) to r = 0.657 (effective decision-making), and in the “ward-level” category, from r = 0.491 (appropriate staffing) to r = 0.648 (effective decision-making). All correlations were statistically significant. Convergent validity was confirmed by positive, mostly moderate correlations of HWEAT scores with the BePoZa questionnaire (p < 0.001), ranging from 0.297 to 0.584, with the strongest associations observed for dimensions related to leadership and decision-making. Furthermore, descriptive statistics suggest low-to-moderate levels of healthy work environment ratings in the study sample, with relatively low scores for “appropriate staffing” and higher scores for “effective decision-making” and “skilled communication,” which is consistent with the correlation profile and further supports the scale’s theoretical validity. Cronbach’s alpha was 0.895 for the entire scale in the “hospital-level” perspective and 0.900 in the “ward-level” perspective. For the subscales (test), the highest α was recorded for “authentic leadership” (0.799) and the lowest for “appropriate staffing” (0.594). For the interpretation of reliability, Cronbach’s alpha values ≥ 0.70 were assumed to be acceptable (preferably 0.70–0.90), and values < 0.6 were unacceptable [ 32 ]. The results for the entire scale and most subscales met these criteria, confirming the tool’s good internal consistency. In the original validation of the HWEAT by Connor et al. (2018), internal consistency was α = 0.77 for the total scale (standard range 0.77–0.81, and 3-week test–retest stability was in the range of 0.50–0.68. In the Japanese adaptation, α = 0.607–0.811 for the domains and ICC = 0.618–0.903 were reported after approximately two weeks, with an acceptable CFA model fit (CFI = 0.918; RMSEA = 0.082) [ 33 ]. The GFI and AGFI indices served as supplementary indicators, and their low values suggest a poorer fit in these measures. However, the overall assessment using RMSEA, CFI, and SRMR indicates an acceptable or moderate fit. To assess the construct validity of the Polish version of HWEAT, two external tools available in Polish that measure related dimensions of the work environment was used, i.e., the Safety Attitudes and Behaviors Questionnaire (BePoZa) and the Hospital Ethical Climate Scale (HECS-Pol). Positive, statistically significant correlations were obtained between all HWEAT dimensions and subscales. BePoZa, mostly of moderate strength, confirming the convergent validity of the instrument. The strongest relationships were found for the standards “authentic leadership” and “effective decision-making”, which were clearly associated with both teamwork and safety climate. In the case of HECS-Pol, all correlations were positive, but their strength was mostly weak to moderate, suggesting that the Hospital Ethical Climate Scale measure construct related to the healthy work environment, but not the same. Taken together, these results suggest that healthy work environment standards, as measured by the HWEAT, are consistently related to the concept of the healthy work environment, which supports the good construct validity of the Polish version of the questionnaire. Healthy Work Environment Assessment In the current study, the level of a healthy work environment, assessed using the Polish version of the HWEAT, was low to moderate from both the “hospital-level” and “ward-level” perspectives. The mean values of individual standards ranged from 2.31 to 2.95 points on a scale of 1 to 4, indicating that healthy work environment standards are only partially implemented in the units studied. The lowest-rated area was “appropriate staffing” (M = 2.31 from the “hospital-level” perspective and M = 2.35 from the “ward-level” perspective), while the relatively highest values were obtained in “effective decision-making” (MP: M = 2.87; O: M = 2.95) and “skilled communication” (MP: M = 2.87; O: M = 2.95). This profile of results indicates that nurses should more closely assess the functioning of communication processes and the possibility of participating in decision-making, while also clearly indicating insufficient organizational conditions of work, primarily related to staff shortages and workload. The results obtained in the study are consistent with the AACN framework, which identifies “appropriate staffing” as one of six key standards for a healthy work environment, and is also directly dependent on systemic and organizational decisions. International studies consistently link staffing shortages and poorer work environments to negative consequences for staff (including burnout and intention to leave) and care outcomes [ 35 ]. Relatively higher scores in the areas of “skilled communication” and “effective decision-making” can be interpreted as indicators of stronger team functioning. At the same time, persistently low scores for “appropriate staffing” indicate that staffing shortages may limit the transfer of these resources into daily practice and contribute to the workload [ 36 ]. Consequently, actions aimed at organizing and planning resources (including appropriate staffing and adapting the workload to the severity of the patient’s condition) are justified [ 37 ], while simultaneously strengthening solutions supporting communication and involving staff in decision-making processes [ 38 ]. It is noteworthy that the scores obtained in the “ward-level” perspective were slightly higher than those in the “hospital-level” perspective, which may reflect a stronger sense of team belonging and better interpersonal relationships within the immediate work environment. This phenomenon has also been observed in other studies, where the local nursing teamwork climate was assessed more favorably than the broader hospital organizational context. This may indicate that nurses compensate for systemic deficiencies through informal team support and intra-ward collaboration [ 39 ]. The results indicate that general demographic and organizational characteristics (gender, age, number of working hours per month, work system) did not differentiate the evaluations of the work environment, and similar observations are found in other studies [ 40 ]. However, variables reflecting the career path and actual workload were significant [ 41 ]. These relationships suggest that the perception of a healthy work environment is shaped to a greater extent by work experience, level of competence (education) [ 42 ] and work intensity in the workplace, which is particularly evident in staffing, collaboration, communication, and decision-making. In summary, the results confirm that a healthy work environment for nurses in Polish hospital wards remains a priority that requires systemic intervention. Strengthening structural standards, such as appropriate staffing and meaningful recognition of nurses’ work, seems particularly important. These standards, as demonstrated in international studies, are key determinants of staff well-being, quality of care, and patient safety. Using HWEAT not only enables a reliable diagnosis of these areas but also provides a foundation for monitoring the effects of future corrective actions. Limitations This study has several limitations that should be considered when interpreting the results. First, convenience sampling was used, which may limit the sample’s representativeness and the generalizability of the results to the entire population of nurses in Poland. The demographic and professional structure of the study group—though typical of the nursing community—may have further influenced the responses obtained. Second, the geographic scope of the study was limited, which may reflect specific regional organizational and staffing conditions and limit the possibility of extrapolating the results to centers in other regions and facilities with different profiles. Third, the cross-sectional nature of the study does not allow for inferences about cause-and-effect relationships or the assessment of changes over time. The results reflect respondents’ perceptions at a specific point in time and may have been influenced by ongoing organizational or individual factors that were not accounted for. Conclusions In Poland, the Healthy Work Environment Assessment Tool (HWEAT) was tested among medical and surgical nursing wards and demonstrated good psychometric properties, including high internal consistency, satisfactory measurement stability, and evidence of convergent validity. The validated Polish version of the HWEAT may be a useful tool for monitoring the quality of nurses’ work environments across various types of units and facilities, and for designing studies on the relationships between working conditions and care rationing, burnout, job satisfaction, and patient health outcomes. Moreover, the use of HWEAT in national and international studies enables comparison of the effects of organizational interventions and the formulation of practical recommendations and health policies based on empirical data. Abbreviations AACN the American Association of Critical-Care Nurses BePoZa Safety Attitudes and Behaviors Questionnaire CFA Confirmatory factor analysis EFA Exploratory factor analysis HECS Pol-the Hospital Ethical Climate Survey questionnaire HWE Healthy Work Environments as defined by the American Association of Critical-Care Nurses HWEAT the Healthy Work Environment Assessment Tool I CVI-Item-Level Content Validity Index KMO Kaiser-Meyer-Olkin KPZiB the Teamwork and Safety Climate version of the Safety Attitudes and Behaviors Questionnaire Declarations Ethics approval and consent to participate The research protocol was approved by the Warmia and Mazury University’s Research Ethics Committee in Olsztyn (approval number: 19/2023). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was received from the nurses after they were given information about the purpose of the study. Participation in the study was entirely voluntary. Participants had the right to withdraw at any stage by refusing to complete or return the questionnaire. During data collection, participants were given the opportunity to ask questions and seek clarification regarding the research procedure. To ensure confidentiality and data protection, all responses were anonymized using coded questionnaires, and the data were securely stored in a manner accessible only to the research team. Consent for publication - Not applicable. This study did not include patient or public involvement in its design, conduct, or reporting. Availability of data and materials - The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests - The authors declare that they have no competing interests Funding - The authors declare no conflicts of interest. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions - All authors meet the criteria for authorship and have made substantial contributions to the conception and design of the study, critical revision of the manuscript for important intellectual content, and final approval of the version submitted. AA: Conceptualization, Data Curation, Formal Analysis, Methodology, Investigation, Project Administration, Visualization, Writing – original draft. BP-Z: Conceptualization, Formal Analysis, Methodology, Investigation. BD: Conceptualization, Formal Analysis, Methodology, Investigation, Supervision, Validation. AR: Conceptualization, Methodology, Investigation. DAO: Conceptualization, Methodology, Investigation. ASZ: Conceptualization, Methodology, Investigation. 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Medina-Córdoba M, Cadavid S, Espinosa-Aranzales A-F, Aguía-Rojas K, Bermúdez-Hernández PA, Quiroga-Torres D-A, Rodríguez-Dueñas WR. The effect of interprofessional education on the work environment of health professionals: a scoping review. Adv Health Sci Educ. 2024;29(4):1463–80. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 23 Apr, 2026 Reviewers agreed at journal 19 Apr, 2026 Reviewers agreed at journal 14 Apr, 2026 Reviewers invited by journal 14 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Editor invited by journal 20 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 19 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9003556","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":626748242,"identity":"157b9aa1-deb5-404d-9802-4a5a084ec37b","order_by":0,"name":"Anna Antoszewska","email":"","orcid":"","institution":"University of Warmia and Mazury in Olsztyn","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Antoszewska","suffix":""},{"id":626748248,"identity":"65ca02bd-62dc-4c49-ab0f-dfc0514e631b","order_by":1,"name":"Beata Penar-Zadarko","email":"","orcid":"","institution":"University of Rzeszów","correspondingAuthor":false,"prefix":"","firstName":"Beata","middleName":"","lastName":"Penar-Zadarko","suffix":""},{"id":626748249,"identity":"dee869f0-c814-45f7-8ac9-0faeff8dc846","order_by":2,"name":"Beata Dobrowolska","email":"","orcid":"","institution":"Medical University of Lublin","correspondingAuthor":false,"prefix":"","firstName":"Beata","middleName":"","lastName":"Dobrowolska","suffix":""},{"id":626748250,"identity":"99872d54-77a3-44f3-8fab-39b8341ddc05","order_by":3,"name":"Adrianna Rożniecka","email":"","orcid":"","institution":"University of Warmia and Mazury in Olsztyn","correspondingAuthor":false,"prefix":"","firstName":"Adrianna","middleName":"","lastName":"Rożniecka","suffix":""},{"id":626748255,"identity":"16209a77-6fc8-4d75-8995-09772542b830","order_by":4,"name":"Dorota Agnieszka Ozga","email":"","orcid":"","institution":"University of Rzeszów","correspondingAuthor":false,"prefix":"","firstName":"Dorota","middleName":"Agnieszka","lastName":"Ozga","suffix":""},{"id":626748257,"identity":"03cd7582-253f-4dbb-9fc2-f364daa77944","order_by":5,"name":"Anna Szypulska","email":"","orcid":"","institution":"University of Warmia and Mazury in Olsztyn","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Szypulska","suffix":""},{"id":626748261,"identity":"fbbd5867-5c6f-42f5-abe4-7c9b8c29fb6e","order_by":6,"name":"Iwona Wołosewicz","email":"","orcid":"","institution":"University of Warmia and Mazury in Olsztyn","correspondingAuthor":false,"prefix":"","firstName":"Iwona","middleName":"","lastName":"Wołosewicz","suffix":""},{"id":626748265,"identity":"f146786d-2ff9-4981-8391-9367c92664f3","order_by":7,"name":"Aleksandra Gutysz-Wojnicka","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABA0lEQVRIiWNgGAWjYDADxgYQZLCB8HiAmA+f8gMILWkILWyEtEBsYjhMWAt/A/s16Q8Mh+WYZzc3fpxRcz5xw7UDjA/etjHk4dIicYCnTOIAw2FjxjkHmyU3HLuduOF2ArPh3DaGYpwOO8CTBtRyO7FxRmIb4wO224nbbiewSfO2MSS24dAhj6rl3zmQFvbf+LQYHGA/htCyse0A2BZmfFoMD/MwW5wx+G/MOCOxWXJmX7Lx/ttAxpxzEjj9Ine8/eGNioo0OcMZ6Q8/9nyzk505O/nghzdlNnn8uLzPzGMAdB7Quga4ECOIKZGASwcDA/sDSDigi+PRMgpGwSgYBSMMAABDj2CS9VmDzgAAAABJRU5ErkJggg==","orcid":"","institution":"University of Warmia and Mazury in Olsztyn","correspondingAuthor":true,"prefix":"","firstName":"Aleksandra","middleName":"","lastName":"Gutysz-Wojnicka","suffix":""}],"badges":[],"createdAt":"2026-03-01 19:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9003556/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9003556/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107705364,"identity":"43a9a80a-c5f5-4776-9811-faed817690b4","added_by":"auto","created_at":"2026-04-24 09:11:54","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":935317,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9003556/v1/49fab64f-bf8d-4659-8d66-f5b168dcca16.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Nurses’ Perception of a Healthy Work Environment —Psychometric Validation Study ","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe healthcare system is facing increasing challenges that directly impact the daily work of medical personnel. The most important include the growing demand for healthcare services, the shortage of nursing staff [1] the aging patient population, and the dynamic development of technology, which, combined with heavy workloads, contribute to the increasing phenomenon of burnout [2] and highlight the importance of the quality of the work environment for staff well-being [3] and patient safety [4].\u003c/p\u003e\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eThe work environment is a complex phenomenon that has been defined and conceptualized in the extensive literature on the subject. From an organizational perspective, it refers to the culture and climate of an institution, from a psychological perspective, it refers to perceived support, satisfaction, and interpersonal relationships and from a practical perspective, it refers to material conditions, workload, and available resources [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Researchers suggest that it can be defined in three ways: (a) by emphasizing structural and organizational factors; (b) by emphasizing the psychosocial and relational aspects of work; and (c) by combining both dimensions into a coherent multidimensional framework [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The work environment includes organizational elements [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] as well as interpersonal [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and individual [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] factors that may facilitate or hinder the maintenance of high-quality care. Many researchers emphasize that the work environment of medical staff is crucial for the quality of care, patient safety and employee well-being [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe hospital care environment should provide healthcare workers with a safe, supportive work environment that promotes their professional well-being, enables effective task performance, and fosters high-quality patient care. Meta-analytic evidence suggests that negative work environments are associated with poorer patient outcomes [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Several studies have documented that hospitals with a better work environment have lower mortality rates [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and fewer hospital readmissions [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Research indicates that investing in improving healthcare workers\u0026rsquo; working conditions can significantly reduce patient mortality [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], improve patient outcomes, and enhance the quality of care [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A poor assessment of the work environment also contributes to the increased frequency of omissions in required nursing care. Research results show a negative correlation between the rationing of nursing care and the assessment of the work environment [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This means that the lower the standards are met, the more often nursing care is omitted, which is directly related to poorer quality of care, more frequent complications [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and mortality [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA healthy work environment is also undoubtedly linked to nursing outcomes. The work environment is a key factor influencing nurses\u0026rsquo; decisions to remain in the profession, and its quality directly determines the level of retention in this professional group [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], burnout [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and job satisfaction [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Research results clearly indicate that investing in improving the work environment for nurses is fundamental to the stability and quality of the healthcare system, as creating such an environment not only attracts and retains competent healthcare workers [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], but also strengthens the loyalty and satisfaction of nursing staff [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Elements such as communication, collaboration, and appropriate staffing significantly determine the quality of care provided to patients and their families [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eClinical leaders emphasize that ensuring high-quality care requires a focus on team effectiveness [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] which, in turn, requires the use of reliable and valid tools for a comprehensive assessment of organizational climate. Due to the multidimensional nature of this concept, numerous tools have been developed to assess it. A systematic literature review [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] identified 37 instruments assessing the hospital work environment developed since the 1980s. These included both nursing-specific and multiprofessional instruments addressing organizational culture, psychological climate, teamwork, and socio-organizational conditions. Content analysis revealed a wide variety of approaches, encompassing 48 distinct components that contribute to the construct of a healthy work environment. A positive work environment in healthcare is understood as one that fosters excellence and sound practice, protects the health, safety, and well-being of staff, supports high-quality patient care, and enhances the motivation, productivity, and effectiveness of teams and organizations.\u003c/p\u003e \u003cp\u003eStandards for a healthy work environment in intensive care units (Healthy Work Environments (HWE) as defined by the American Association of Critical-Care Nurses (AACN) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] include six key elements: skilled communication, true collaboration, effective decision-making, appropriate staffing, meaningful recognition, and authentic leadership. To assess the degree of their implementation, AACN developed the online Work Environment Assessment Tool in 2009. The Healthy Work Environment Assessment Tool (HWEAT) was designed to both establish baseline status and monitor progress of hospital units in implementing and maintaining healthy work environment standards. This tool has been validated in the United States [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The Healthy Work Environment Assessment Tool was used to assess the work environment in intensive care units in five European countries, including Poland, as part of the Erasmus+ project (Strategic Partnerships, Key Action 2, sector KA202) entitled \u0026ldquo;Improving Working Environments for Nurses in the Critical-Care Unit (HWE4CCN)\u0026rdquo;, implemented between 2019 and 2022 [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, the evaluation of the psychometric properties of the Polish version of HWEAT during the Erasmus project was partial and based on data obtained from nurses working in intensive care units. This justifies further evaluation of the psychometric properties of the Polish version of the HWEAT in other nurse groups.\u003c/p\u003e\n\u003ch3\u003eThe study\u003c/h3\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Purpose\u003c/h2\u003e \u003cp\u003eThe aim of this study was to validate the Polish version of the Healthy Work Environment Assessment Tool (HWEAT) questionnaire among nurses working in hospital in medical and surgical wards. The study had the following main objectives: (a) to assess the reliability and validity of the Polish version of HWEAT, (b) to assess the work environment of nurses in surgical and non-surgical wards.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Study design\u003c/h2\u003e \u003cp\u003eA cross-sectional, multi-center validation study was conducted in 2024\u0026ndash;2025.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Participants\u003c/h2\u003e \u003cp\u003eConvenience sampling was used in the study. Inclusion criteria included active employment as a nurse in a hospital, providing direct patient care in a surgical or non-surgical ward for adults, consenting to participate in the study, and not holding a management position. Exclusion from participation included employment in an intensive care unit and emergency department or a lack of consent to participate in the study. Of the 359 nurses invited, 73.6% agreed to participate. A total of 264 nurses participated in both phases \u0026ndash; the test and retest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Research tools\u003c/h2\u003e \u003cp\u003eThe following tools were used in the study:\u003c/p\u003e \u003cp\u003e \u003cb\u003eHealthy Work Environment Assessment Tool questionnaire\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe HWEAT developed by the American Association of Critical-Care Nurses, is used to assess key elements of a healthy environment. The questionnaire contains 16 items assigned to six key elements (standards) of a healthy work environment: (1) skilled communication, (2) true collaboration, (3) effective decision-making, (4) appropriate staffing, (5) meaningful recognition, and (6) authentic leadership. Responses are provided on a four-point Likert scale, ranging from \u0026ldquo;strongly agree\u0026rdquo; (4 points) to \u0026ldquo;strongly disagree\u0026rdquo; (1 point). The results of the healthy work environment assessment were analyzed collectively and at the level of individual standards. As the overall score and the score for each specific standard increase, the work environment is perceived as being healthier. The HWEAT questionnaire has been used in numerous studies conducted in hospital settings, covering various units and nursing populations [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This tool has been formally validated in the United States, where high internal consistency was demonstrated (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.77; range 0.77\u0026ndash;0.81), and its psychometric validity was confirmed [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The AACN granted permission to use the Polish version of the HWEAT questionnaire for research purposes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSafety Attitudes and Behaviors Questionnaire (BePoZa)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Teamwork and Safety Climate (KPZiB) version of the Safety Attitudes and Behaviors Questionnaire (BePoZa) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] consists of 27 items. Questions 1\u0026ndash;14 assess the teamwork climate, while questions 15\u0026ndash;27 assess the safety climate. For statements with a positive construct, a five-point Likert scale was used: 1 \u0026ndash; strongly disagree, 2 \u0026ndash; somewhat disagree, 3 \u0026ndash; neither agree nor disagree, 4 \u0026ndash; somewhat agree, 5 \u0026ndash; strongly agree. For negatively formulated statements (questions 2, 6, 18, 23, 24), the scoring was reversed: 1 and 2 were changed to 5 and 4, respectively. A higher final score indicates a higher assessment of the teamwork and safety climate.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHospital Ethical Climate Survey (HECS-Pol) questionnaire\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Polish version of the Hospital Ethical Climate Survey (HECS-Pol) comprises 21 items across five subscales: relationships with colleagues, patients, management, hospital, and doctors. Responses are provided on a five-point Likert scale (1\u0026ndash;5), with higher scores indicating a more positive assessment of the ethical climate. The instrument is characterized by high reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.93) and satisfactory test-retest stability [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSociodemographic information was collected, including age, gender,\u003c/p\u003e \u003cp\u003enumber of workplaces, number of working hours per month, and work system (single shift/equivalent).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Cultural adaptation procedure\u003c/h2\u003e \u003cp\u003e The cultural adaptation procedure of the HWEAT questionnaire was carried out in accordance with the guidelines of the International Testing Commission. Two English translators independently prepared the Polish version of the questionnaire items. The resulting translations were analyzed by a team of experts, including specialists in nursing and research methodology, and then a working Polish version of the tool was developed. In the next stage, a back-translation into English was performed by an independent translator. The analysis of the back-translation\u0026rsquo;s compliance with the original revealed no significant discrepancies, and none of the items required modification. The final Polish version of the questionnaire was administered to a pilot sample of 30 nurses. In order to assess the content validity of the scale (content validity), an Item-Level Content Validity Index (I-CVI) was determined, with values ranging from 0 to 1 (higher values indicate better content validity) [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The assessment was conducted in a group of 10 nurses, and the obtained I-CVI index value was 0.92. This value exceeds the generally accepted threshold of 0.78, confirming the tool\u0026rsquo;s high content validity and indicating a high degree of agreement among the experts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Data collection procedures\u003c/h2\u003e \u003cp\u003eThe study was conducted in eight general hospitals, after obtaining consent from the facility directors. Nurses meeting the inclusion criteria were given paper questionnaires in sealed envelopes. After completion, these were returned to their immediate supervisors. Before data collection began, participants were briefed on the study\u0026rsquo;s objectives and procedures and informed of the voluntary and anonymous nature of their participation. A statement at the beginning of the questionnaire indicated that completing the survey constituted informed consent to participate in the study. Participants were informed that they could withdraw at any stage without providing a reason and that their data would be kept confidential. Throughout the procedure, participants were given the opportunity to ask questions and obtain clarifications, and data collection was conducted without pressure in an environment conducive to free and reliable responses. Of the 359 nurses invited, 73.6% accepted the invitation to participate. A total of 264 nurses participated in both stages \u0026ndash; the test and the retest.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Data analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using the Statistica TIBCO 13.3 package and IBM SPSS Statistics 25 and IBM SPSS AMOS 25 software. Descriptive statistics were used to characterize the nurses\u0026rsquo; work environment, including frequencies (N), percentages (%), means (x), standard deviations (SD), confidence intervals (CI 95%), and measures of skewness and kurtosis. Content validity was assessed by determining the Item-Level Content Validity Index (I-CVI). The acceptable I-CVI value was 0.78 or higher [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A two-stage approach was used to assess the internal structure of the HWEAT-PL. First, exploratory factor analysis (EFA) was conducted separately for the \u0026ldquo;hospital-level\u0026rdquo; and \u0026ldquo;ward-level\u0026rdquo; sections to verify whether the empirical data supported the assumed six-factor structure of the instrument. The adequacy of the data for factor analysis was assessed using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett\u0026rsquo;s test of sphericity. Next, confirmatory factor analysis (CFA) was performed for the six-factor model in both sections. Model fit was assessed using the χ\u0026sup2; statistic and the χ\u0026sup2;/df index, as well as the fit indices: RMSEA (with 90% confidence intervals and PCLOSE), CFI, and SRMR. Additionally, the GFI and AGFI indices were reported as auxiliary measures of model fit. Cronbach\u0026rsquo;s alpha coefficient and the item-total correlation matrix were analyzed to assess the consistency of the scale items with the overall score. The test-retest stability of the HWEAT-PL tool was assessed at a three-week interval. Convergent validity was verified by analyzing the correlations of HWEAT-PL scores with the scores on the Safety Attitudes and Behaviors Questionnaire (BePoZa) and discriminant validity was verified by analyzing correlations of HWEAT-PL and the Hospital Ethical Climate Scale (HECS-Pol). A p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. Relationships between quantitative variables were assessed using the Pearson correlation coefficient (r). The strength of the relationship was interpreted based on the absolute value of the coefficient, according to Evans\u0026rsquo;s criteria: |r|\u0026lt;0.20 \u0026ndash; very weak, 0.20\u0026ndash;0.39 \u0026ndash; weak, 0.40\u0026ndash;0.59 \u0026ndash; moderate, 0.60\u0026ndash;0.79 \u0026ndash; strong, \u0026ge;\u0026thinsp;0.80 \u0026ndash; very strong. Additionally, the relationship between sociodemographic variables and HWEAT dimensions was analyzed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e4.7 Ethical procedures\u003c/h2\u003e \u003cp\u003e The research protocol was approved by the Warmia and Mazury University\u0026rsquo;s Research Ethics Committee in Olsztyn (approval number: 19/2023). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was received from the nurses after they were given information about the purpose of the study. Participation in the study was entirely voluntary. Participants had the right to withdraw at any stage by refusing to complete or return the questionnaire. During data collection, participants were given the opportunity to ask questions and seek clarification regarding the research procedure. To ensure confidentiality and data protection, all responses were anonymized using coded questionnaires, and the data were securely stored in a manner accessible only to the research team.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eParticipants\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTwo hundred and sixty-four nurses participated in both phases of the study (test and retest). The mean age at testing was 40.52\u0026thinsp;\u0026plusmn;\u0026thinsp;12.96 years (Me\u0026thinsp;=\u0026thinsp;41). Most of the nurses worked 100\u0026ndash;180 hours per month (71.97%) in 12-hour day, night shifts system (77.65%); the majority had higher education with a specialization (47.35%) and were employed in surgical wards (62.88%). Details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of Participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTest n\u0026thinsp;=\u0026thinsp;264\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95.83%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e40.52\u0026thinsp;\u0026plusmn;\u0026thinsp;12.96, Me\u0026thinsp;=\u0026thinsp;41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of workplaces\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e1.29\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54, Me\u0026thinsp;=\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of working hours per month\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 100 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u0026ndash;180 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.97%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e181\u0026ndash;230 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.73%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e231\u0026ndash;300 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.17%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of working hours at the workplace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 100 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.52%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u0026ndash;180 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93.56%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e181\u0026ndash;230 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e231\u0026ndash;300 hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWork system\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle-shift/ 8-hour day shift\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12-hour day, night shifts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.65%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12-hour day shifts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.03%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.09%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.67%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary school with specialization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.89%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher education with specialization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSeniority\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow 6 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;11 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.91%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u0026ndash;2 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u0026ndash;7 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u0026ndash;12 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.74%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u0026ndash;20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver 20 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.14%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWard\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.12%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurgical ward\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62.88%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cem\u003eMe \u0026ndash; median\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eAnalysis of the internal structure of HWEAT\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e\u003cb\u003eExploratory factor analysis (EFA)\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eExploratory factor analysis was performed on the collected data. The adequacy of the data for factor analysis was confirmed based on the Kaiser\u0026ndash;Meyer\u0026ndash;Olkin measure (KMO\u0026thinsp;=\u0026thinsp;0.89) and Bartlett\u0026rsquo;s test of sphericity (χ\u0026sup2;=2968.68; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) for the \u0026ldquo;hospital-level\u0026rdquo; part, and KMO\u0026thinsp;=\u0026thinsp;0.91 and Bartlett\u0026rsquo;s test (χ\u0026sup2;=3215.36; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respectively for the \u0026ldquo;ward-level\u0026rdquo; part.\u003c/p\u003e \u003cp\u003ePreliminary analysis of the correlation matrix revealed numerous statistically significant correlations (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) between items, indicating the existence of common dimensions measured by the tool. For the \u0026ldquo;\u0026ldquo;hospital-level\u0026rdquo; section, correlations ranged from r\u0026thinsp;=\u0026thinsp;0.17 to 0.74, while for the \u0026ldquo;ward-level\u0026rdquo; section, they ranged from r\u0026thinsp;=\u0026thinsp;0.15 to 0.77. In accordance with the study\u0026rsquo;s objective, EFA was used to verify whether the six-factor structure of the tool described in the original study is comparable in the Polish nursing population. The factors were defined as: (1) skilled communication, (2) true collaboration, (3) effective decision-making, (4) appropriate staffing, (5) meaningful recognition, and (6) authentic leadership, with the designations MP (\u0026ldquo;hospital-level\u0026rdquo;) and O (\u0026ldquo;ward-level\u0026rdquo;). The analysis yielded factor loadings of at least 0.40 for the items within the assigned factors.\u003c/p\u003e \u003cp\u003eCorrelations between HWEAT factors in the in the \u0026ldquo;hospital-level\u0026rdquo; section were statistically significant and positive (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and mostly moderate (r\u0026thinsp;=\u0026thinsp;0.33\u0026ndash;0.64). Similarly, in the in the \u0026ldquo;ward-level\u0026rdquo; section, interfactor correlations were statistically significant and positive (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and mostly moderate (r\u0026thinsp;=\u0026thinsp;0.33\u0026ndash;0.70). Details are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConfirmatory factor analysis (CFA)\u003c/b\u003e \u003c/p\u003e \u003cp\u003eA CFA was conducted to assess the fit of the six-factor theoretical model. For the \u0026ldquo;hospital-level\u0026rdquo; section, the chi-square test was statistically significant (χ\u0026sup2;=345.02; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and the relative index χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;3.80 indicated an acceptable fit. For the \u0026ldquo;ward-level\u0026rdquo; section, the chi-square test was also significant (χ\u0026sup2;=359.00; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and χ\u0026sup2;/df\u0026thinsp;=\u0026thinsp;4.03 also indicated an acceptable fit. It should be emphasized that the chi-square test is sensitive to sample size and model complexity.\u003c/p\u003e \u003cp\u003eIn the \u0026ldquo;hospital-level\u0026rdquo; section, RMSEA\u0026thinsp;=\u0026thinsp;0.078 (90% CI: 0.070\u0026ndash;0.087) and SRMR\u0026thinsp;=\u0026thinsp;0.075 were obtained, which indicates an acceptable fit. The CFI\u0026thinsp;=\u0026thinsp;0.912 suggests an acceptable fit. At the same time, the PCLOSE index value of 0.001 does not support the \u0026ldquo;close fit hypothesis\u0026rdquo; (RMSEA\u0026thinsp;\u0026le;\u0026thinsp;0.05). The GFI\u0026thinsp;=\u0026thinsp;0.650 and AGFI\u0026thinsp;=\u0026thinsp;0.555 were low and indicate poorer fit in these measures. In the \u0026ldquo;ward-level\u0026rdquo; section, RMSEA\u0026thinsp;=\u0026thinsp;0.081 (90% CI: 0.072\u0026ndash;0.088) and SRMR\u0026thinsp;=\u0026thinsp;0.062 were obtained, indicating acceptable fit. The CFI\u0026thinsp;=\u0026thinsp;0.914 also suggests an acceptable fit. As above, PCLOSE\u0026thinsp;=\u0026thinsp;0.001 does not support the \u0026ldquo;close fit hypothesis\u0026rdquo;. The GFI and AGFI indices were low (0.633 and 0.534, respectively). In summary, the six-factor model was partially confirmed, and the fit to the data was acceptable to moderate based on RMSEA, CFI, and SRMR, with low GFI/AGFI values and without confirmation of the \u0026ldquo;close fit hypothesis\u0026rdquo; in the PCLOSE test.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation analysis between HWEAT factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"15\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" 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colname=\"c1\"\u003e \u003cp\u003eMP2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e 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colname=\"c1\"\u003e \u003cp\u003eMP5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c15\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003e\u003cem\u003eMP - \u0026ldquo;hospital-level\u0026rdquo; O \u0026ndash; \u0026ldquo;ward-level\u0026rdquo;\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"15\"\u003e\u003cb\u003eValidity and reliability of the HWEAT test\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFactors were labeled according to the original version of the HWEAT instrument. Furthermore, internal consistency and a test-retest approach were used to assess the HWEAT reliability. Specifically, the retest approach aimed to assess the instrument\u0026rsquo;s stability and to determine the extent to which the results of the work environment tests were independent of participant-level random factors, such as negative personal experiences or data-collection procedures. Analysis of the internal structure of the item-total correlation matrix revealed moderate correlations between the items and the total.\u003c/p\u003e \u003cp\u003e \u003cb\u003eInternal reliability analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha was 0.895 for the \u0026ldquo;hospital-level\u0026rdquo; section and 0.900 for the \u0026ldquo;ward-level\u0026rdquo; section. In the retest, alpha values were even higher (0.915 and 0.913, respectively), confirming the instrument\u0026rsquo;s internal stability over time. Item-total correlations for individual statements ranged from 0.34 to 0.71, and the alpha values after item deletion were lower than the total alpha, indicating that none of the questions compromised the instrument\u0026rsquo;s reliability. All items contribute significantly to the measurement of the construct under study. Detailed results are presented in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eValidity and reliability of HWEAT factors for the test\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eItem-total correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost-item alpha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWard-level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eItem-total correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePost-item\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.891\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e 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align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.886\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.890\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.893\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.888\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.884\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.887\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.892\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha 0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha 0.900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ex \u0026mdash; mean; SD \u0026mdash; standard deviation; \u0026minus;95% / +95% lower/upper limit of the 95% confidence interval for the mean.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest-retest validity and reliability of HWEAT factors\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eRetest\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital-level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eItem-total correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost-item alpha\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWard-level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eItem-total correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003ePost-item alpha\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.665\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.652\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.677\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.915\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.567\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.911\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.907\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ep.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.909\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.908\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha 0.915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eCronbach\u0026rsquo;s alpha 0.913\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ex \u0026mdash; mean; SD \u0026mdash; standard deviation; \u0026minus;95% / +95% lower/upper limit of the 95% confidence interval for the mean.\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eHWEAT test stability analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAfter 3 weeks (retest), the instrument was re-administered to assess temporal stability. Pearson correlation coefficients and Cronbach\u0026rsquo;s alpha coefficients values for the \u0026ldquo;hospital-level\u0026rdquo; (MP) and \u0026ldquo;ward level\u0026rdquo; (O) question obtained at test and retest are presented in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. Pearson correlation coefficients for the \u0026ldquo;hospital-level\u0026rdquo; (MP) questions and for each factor were statistically significant, ranging from r\u0026thinsp;=\u0026thinsp;0.657 (MP. Effective decision-making) to r\u0026thinsp;=\u0026thinsp;0.481 (MP. Authentic leadership). Pearson correlation coefficients for the \u0026ldquo;ward-level\u0026rdquo; (O) for each factor were statistically significant, ranging from r\u0026thinsp;=\u0026thinsp;0.648 (O. Effective decision-making) to r\u0026thinsp;=\u0026thinsp;0.491 (O. Appropriate staffing). Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHWEAT Stability analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStability analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eTest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRetest\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003er\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eα\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.692\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.526\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.689\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.720\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.649\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.711\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.529\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.465\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.544\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.826\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.653\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.802\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eMP - \u0026ldquo;hospital-level\u0026rdquo; O \u0026ndash; \u0026ldquo;ward-level\u0026rdquo;; α \u0026ndash; Cronbach\u0026rsquo;s alpha; r - Pearson correlation\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTest-retest results of the stability analysis of the HWEAT questionnaire subscales\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTest-retest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003cp\u003eSkilled communication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003cp\u003eTrue collaboration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003cp\u003eEffective decision-making\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003cp\u003eAppropriate staffing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003cp\u003eMeaningful recognition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e6\u003c/p\u003e \u003cp\u003eAuthentic leadership\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.551\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.657\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eMP - \u0026ldquo;hospital-level\u0026rdquo; O \u0026ndash; \u0026ldquo;ward-level\u0026rdquo;\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e The construct validity of the Polish version of the HWEAT was assessed using Pearson correlations (r) between HWEAT factor scores and scores on two instruments: Safety Attitudes and Behaviors Questionnaire (BePoZa) and the Hospital Ethical Climate Scale (HECS-Pol). In the case of BePoZa, all correlations were positive and statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and their strength was mostly moderate (r\u0026thinsp;=\u0026thinsp;0.297\u0026ndash;0.584), indicating consistency between the HWEAT and a measure addressing related aspects of the work environment. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e. In the case of HECS-Pol, all correlations were positive and significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but their strength was mostly moderate (r\u0026thinsp;=\u0026thinsp;0.221\u0026ndash;0.481). Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson r correlation of HWEAT with BePoZa\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMP. Skilled communication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTeamwork climate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSafety climate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBePoZa\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.330\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.505\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.461\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.584\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.445\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.509\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.555\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.576\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.472\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.522\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.534\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eMP - \u0026ldquo;hospital-level\u0026rdquo;; O \u0026ndash; \u0026ldquo;ward-level\u0026rdquo;; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePearson r correlation of HWEAT with HECS-Pol\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMP. Skilled communication\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelationships with colleagues\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRelationships with patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelations with management\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRelations with the hospital\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRelationships with doctors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eHECS-Pol\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.313\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.350\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.393\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.408\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.280\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.272\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.387\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.345\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.390\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.458\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.238\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.320\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.412\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.326\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMP - \u0026ldquo;hospital-level\u0026rdquo;; O \u0026ndash; \u0026ldquo;ward-level\u0026rdquo;; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003eDescriptive statistics and factors influencing HWEAT levels\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe aim of the analysis was to present descriptive statistics for individual HWEAT dimensions and to identify factors differentiating the results. Across the entire sample (n\u0026thinsp;=\u0026thinsp;264), mean scores ranged from 2.31 to 2.95 (scale 1\u0026ndash;4), and medians ranged from 2.50\u0026ndash;3.00, indicating a low-to-moderate level of a healthy work environment. The lowest scores were recorded for the \u0026ldquo;appropriate staffing\u0026rdquo; dimensions (MP: M\u0026thinsp;=\u0026thinsp;2.31; O: M\u0026thinsp;=\u0026thinsp;2.35), while the relatively highest scores were recorded for \u0026ldquo;effective decision-making\u0026rdquo; (MP: M\u0026thinsp;=\u0026thinsp;2.87; O: M\u0026thinsp;=\u0026thinsp;2.95) and \u0026ldquo;skilled communication\u0026rdquo; (MP: M\u0026thinsp;=\u0026thinsp;2.87; O: M\u0026thinsp;=\u0026thinsp;2.95). The remaining dimensions were in the middle of the distribution (e.g., \u0026ldquo;meaningful recognition\u0026rdquo;: MP: 2.64; O: 2.76; \u0026ldquo;authentic leadership\u0026rdquo;: MP: 2.78; O: 2.83; \u0026ldquo;true collaboration\u0026rdquo;: MP: 2.55; O: 2.62). The variability of the scores was moderate (SD approximately 0.51\u0026ndash;0.63), and the 95% confidence intervals for the means were narrow (approximately\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u0026ndash;0.06), indicating satisfactory precision of the estimates. The distributions were close to normal, with weak skewness (from approximately\u0026thinsp;\u0026minus;\u0026thinsp;0.22 to 0.40) and kurtosis close to zero (from approximately\u0026thinsp;\u0026minus;\u0026thinsp;0.05 to 1.35). In some dimensions, such as \u0026ldquo;effective decision-making\u0026rdquo;, slightly higher kurtosis was observed, suggesting a more \u0026ldquo;peaky\u0026rdquo; distribution around the central values. A comparison of perspectives indicates slightly higher ratings for \u0026ldquo;ward-level\u0026rdquo; than \u0026ldquo;hospital-level\u0026rdquo;, although these differences remain small.\u003c/p\u003e \u003cp\u003eAnalyses of differentiating factors revealed no influence of gender, age, total monthly work hours, or shift pattern on the levels of individual HWEAT dimensions. However, significant associations were found for characteristics related to career progression and workload. Employment duration (in months) was associated with the \u0026ldquo;appropriate staffing\u0026rdquo; dimension in both the \u0026ldquo;hospital-level\u0026rdquo; and \u0026ldquo;ward-level\u0026rdquo; perspectives. The number of hours spent in the workplace differentiated scores on \u0026ldquo;true collaboration\u0026rdquo; from the \u0026ldquo;hospital-level\u0026rdquo; perspective. Education was associated with the level of \u0026ldquo;skilled communication\u0026rdquo; in both perspectives. Seniority differentiated \u0026ldquo;effective decision-making\u0026rdquo; in the \u0026ldquo;hospital-level\u0026rdquo; perspective. Detailed results are presented in Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive statistics of the HWEAT questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"13\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHWEAT dimensions/ standards\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ex\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eME\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eQ1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eQ3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e+\u0026thinsp;95%\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eSkewness\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003eKurtosis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP Appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMP. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Skilled communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. True collaboration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Effective decision-making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. the appropriate staffing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e-0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Meaningful recognition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eO. Authentic leadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e264\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eN \u0026mdash; number; x \u0026mdash; mean; ME \u0026mdash; median; Min/Max \u0026mdash; minimum/maximum values; Q1/Q3 \u0026mdash; first/third quartile; SD \u0026mdash; standard deviation; \u0026minus;95% / +95% lower/upper limit of the 95% confidence interval for the mean; MP \u0026mdash; Hospital-level; O \u0026mdash; Ward-level. Scale 1\u0026ndash;4 (higher\u0026thinsp;=\u0026thinsp;more favorable).\u003c/em\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe aim of this study was to assess the psychometric properties of the Polish version of the HWEAT and to measure the level of key elements of a healthy work environment among nurses. Although tools assessing related dimensions of organizational climate are available in Poland, including BePoZa (teamwork and safety climate components) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and the Polish version of Practice Environment Scale of the Nursing Work Index (PES-NWI) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], they do not directly relate to the full set of HWE standards defined by the AACN. Therefore, adaptation and validation of the HWEAT and verification of its reliability and validity in a sample of Polish nurses are important for further research and international comparisons.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults of the validation process\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Polish version of the HWEAT demonstrated very good psychometric properties. Internal consistency of the entire scale was high: at baseline, α\u0026thinsp;=\u0026thinsp;0.895 (hospital-level perspective) and α\u0026thinsp;=\u0026thinsp;0.900 (ward-level perspective), and at retests, α\u0026thinsp;=\u0026thinsp;0.915 and α\u0026thinsp;=\u0026thinsp;0.913, respectively. Item-total correlations for all items ranged from moderate to high, and the \u0026ldquo;post-item alpha\u0026rdquo; values remained lower than the total α, indicating that no item reduced the scale\u0026rsquo;s reliability. Test-to-retest stability after three weeks was satisfactory for all dimensions and both assessment perspectives. When assessing sample size adequacy, commonly cited item-to-respondent ratios were also considered. Although there is no clear consensus in the literature regarding the minimum required sample size in validation studies, a ratio of at least 1:10 is often recommended [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the current study, 16 questionnaire items were completed by 264 participants, a proportion that significantly exceeded the threshold, thereby confirming that the sample was sufficiently large for reliable psychometric analyses [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. In the \u0026ldquo;hospital-level\u0026rdquo; category, Pearson r coefficients ranged from r\u0026thinsp;=\u0026thinsp;0.481 (authentic leadership) to r\u0026thinsp;=\u0026thinsp;0.657 (effective decision-making), and in the \u0026ldquo;ward-level\u0026rdquo; category, from r\u0026thinsp;=\u0026thinsp;0.491 (appropriate staffing) to r\u0026thinsp;=\u0026thinsp;0.648 (effective decision-making). All correlations were statistically significant. Convergent validity was confirmed by positive, mostly moderate correlations of HWEAT scores with the BePoZa questionnaire (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), ranging from 0.297 to 0.584, with the strongest associations observed for dimensions related to leadership and decision-making. Furthermore, descriptive statistics suggest low-to-moderate levels of healthy work environment ratings in the study sample, with relatively low scores for \u0026ldquo;appropriate staffing\u0026rdquo; and higher scores for \u0026ldquo;effective decision-making\u0026rdquo; and \u0026ldquo;skilled communication,\u0026rdquo; which is consistent with the correlation profile and further supports the scale\u0026rsquo;s theoretical validity. Cronbach\u0026rsquo;s alpha was 0.895 for the entire scale in the \u0026ldquo;hospital-level\u0026rdquo; perspective and 0.900 in the \u0026ldquo;ward-level\u0026rdquo; perspective. For the subscales (test), the highest α was recorded for \u0026ldquo;authentic leadership\u0026rdquo; (0.799) and the lowest for \u0026ldquo;appropriate staffing\u0026rdquo; (0.594). For the interpretation of reliability, Cronbach\u0026rsquo;s alpha values\u0026thinsp;\u0026ge;\u0026thinsp;0.70 were assumed to be acceptable (preferably 0.70\u0026ndash;0.90), and values\u0026thinsp;\u0026lt;\u0026thinsp;0.6 were unacceptable [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. The results for the entire scale and most subscales met these criteria, confirming the tool\u0026rsquo;s good internal consistency. In the original validation of the HWEAT by Connor et al. (2018), internal consistency was α\u0026thinsp;=\u0026thinsp;0.77 for the total scale (standard range 0.77\u0026ndash;0.81, and 3-week test\u0026ndash;retest stability was in the range of 0.50\u0026ndash;0.68. In the Japanese adaptation, α\u0026thinsp;=\u0026thinsp;0.607\u0026ndash;0.811 for the domains and ICC\u0026thinsp;=\u0026thinsp;0.618\u0026ndash;0.903 were reported after approximately two weeks, with an acceptable CFA model fit (CFI\u0026thinsp;=\u0026thinsp;0.918; RMSEA\u0026thinsp;=\u0026thinsp;0.082) [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The GFI and AGFI indices served as supplementary indicators, and their low values suggest a poorer fit in these measures. However, the overall assessment using RMSEA, CFI, and SRMR indicates an acceptable or moderate fit.\u003c/p\u003e \u003cp\u003eTo assess the construct validity of the Polish version of HWEAT, two external tools available in Polish that measure related dimensions of the work environment was used, i.e., the Safety Attitudes and Behaviors Questionnaire (BePoZa) and the Hospital Ethical Climate Scale (HECS-Pol). Positive, statistically significant correlations were obtained between all HWEAT dimensions and subscales. BePoZa, mostly of moderate strength, confirming the convergent validity of the instrument. The strongest relationships were found for the standards \u0026ldquo;authentic leadership\u0026rdquo; and \u0026ldquo;effective decision-making\u0026rdquo;, which were clearly associated with both teamwork and safety climate. In the case of HECS-Pol, all correlations were positive, but their strength was mostly weak to moderate, suggesting that the Hospital Ethical Climate Scale measure construct related to the healthy work environment, but not the same. Taken together, these results suggest that healthy work environment standards, as measured by the HWEAT, are consistently related to the concept of the healthy work environment, which supports the good construct validity of the Polish version of the questionnaire.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHealthy Work Environment Assessment\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the current study, the level of a healthy work environment, assessed using the Polish version of the HWEAT, was low to moderate from both the \u0026ldquo;hospital-level\u0026rdquo; and \u0026ldquo;ward-level\u0026rdquo; perspectives. The mean values of individual standards ranged from 2.31 to 2.95 points on a scale of 1 to 4, indicating that healthy work environment standards are only partially implemented in the units studied. The lowest-rated area was \u0026ldquo;appropriate staffing\u0026rdquo; (M\u0026thinsp;=\u0026thinsp;2.31 from the \u0026ldquo;hospital-level\u0026rdquo; perspective and M\u0026thinsp;=\u0026thinsp;2.35 from the \u0026ldquo;ward-level\u0026rdquo; perspective), while the relatively highest values were obtained in \u0026ldquo;effective decision-making\u0026rdquo; (MP: M\u0026thinsp;=\u0026thinsp;2.87; O: M\u0026thinsp;=\u0026thinsp;2.95) and \u0026ldquo;skilled communication\u0026rdquo; (MP: M\u0026thinsp;=\u0026thinsp;2.87; O: M\u0026thinsp;=\u0026thinsp;2.95). This profile of results indicates that nurses should more closely assess the functioning of communication processes and the possibility of participating in decision-making, while also clearly indicating insufficient organizational conditions of work, primarily related to staff shortages and workload.\u003c/p\u003e \u003cp\u003eThe results obtained in the study are consistent with the AACN framework, which identifies \u0026ldquo;appropriate staffing\u0026rdquo; as one of six key standards for a healthy work environment, and is also directly dependent on systemic and organizational decisions. International studies consistently link staffing shortages and poorer work environments to negative consequences for staff (including burnout and intention to leave) and care outcomes [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Relatively higher scores in the areas of \u0026ldquo;skilled communication\u0026rdquo; and \u0026ldquo;effective decision-making\u0026rdquo; can be interpreted as indicators of stronger team functioning. At the same time, persistently low scores for \u0026ldquo;appropriate staffing\u0026rdquo; indicate that staffing shortages may limit the transfer of these resources into daily practice and contribute to the workload [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Consequently, actions aimed at organizing and planning resources (including appropriate staffing and adapting the workload to the severity of the patient\u0026rsquo;s condition) are justified [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], while simultaneously strengthening solutions supporting communication and involving staff in decision-making processes [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIt is noteworthy that the scores obtained in the \u0026ldquo;ward-level\u0026rdquo; perspective were slightly higher than those in the \u0026ldquo;hospital-level\u0026rdquo; perspective, which may reflect a stronger sense of team belonging and better interpersonal relationships within the immediate work environment. This phenomenon has also been observed in other studies, where the local nursing teamwork climate was assessed more favorably than the broader hospital organizational context. This may indicate that nurses compensate for systemic deficiencies through informal team support and intra-ward collaboration [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe results indicate that general demographic and organizational characteristics (gender, age, number of working hours per month, work system) did not differentiate the evaluations of the work environment, and similar observations are found in other studies [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, variables reflecting the career path and actual workload were significant [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These relationships suggest that the perception of a healthy work environment is shaped to a greater extent by work experience, level of competence (education) [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and work intensity in the workplace, which is particularly evident in staffing, collaboration, communication, and decision-making.\u003c/p\u003e \u003cp\u003eIn summary, the results confirm that a healthy work environment for nurses in Polish hospital wards remains a priority that requires systemic intervention. Strengthening structural standards, such as appropriate staffing and meaningful recognition of nurses\u0026rsquo; work, seems particularly important. These standards, as demonstrated in international studies, are key determinants of staff well-being, quality of care, and patient safety. Using HWEAT not only enables a reliable diagnosis of these areas but also provides a foundation for monitoring the effects of future corrective actions.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered when interpreting the results. First, convenience sampling was used, which may limit the sample\u0026rsquo;s representativeness and the generalizability of the results to the entire population of nurses in Poland. The demographic and professional structure of the study group\u0026mdash;though typical of the nursing community\u0026mdash;may have further influenced the responses obtained. Second, the geographic scope of the study was limited, which may reflect specific regional organizational and staffing conditions and limit the possibility of extrapolating the results to centers in other regions and facilities with different profiles. Third, the cross-sectional nature of the study does not allow for inferences about cause-and-effect relationships or the assessment of changes over time. The results reflect respondents\u0026rsquo; perceptions at a specific point in time and may have been influenced by ongoing organizational or individual factors that were not accounted for.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn Poland, the Healthy Work Environment Assessment Tool (HWEAT) was tested among medical and surgical nursing wards and demonstrated good psychometric properties, including high internal consistency, satisfactory measurement stability, and evidence of convergent validity. The validated Polish version of the HWEAT may be a useful tool for monitoring the quality of nurses\u0026rsquo; work environments across various types of units and facilities, and for designing studies on the relationships between working conditions and care rationing, burnout, job satisfaction, and patient health outcomes. Moreover, the use of HWEAT in national and international studies enables comparison of the effects of organizational interventions and the formulation of practical recommendations and health policies based on empirical data.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAACN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe American Association of Critical-Care Nurses\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBePoZa\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSafety Attitudes and Behaviors Questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfirmatory factor analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExploratory factor analysis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHECS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePol-the Hospital Ethical Climate Survey questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHWE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHealthy Work Environments as defined by the American Association of Critical-Care Nurses\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHWEAT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe Healthy Work Environment Assessment Tool\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCVI-Item-Level Content Validity Index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKMO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKaiser-Meyer-Olkin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKPZiB\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ethe Teamwork and Safety Climate version of the Safety Attitudes and Behaviors Questionnaire\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe research protocol was approved by the Warmia and Mazury University\u0026rsquo;s Research Ethics Committee in Olsztyn (approval number: 19/2023). The study was conducted in accordance with the principles of the Declaration of Helsinki. Written informed consent was received from the nurses after they were given information about the purpose of the study. Participation in the study was entirely voluntary. Participants had the right to withdraw at any stage by refusing to complete or return the questionnaire. During data collection, participants were given the opportunity to ask questions and seek clarification regarding the research procedure. To ensure confidentiality and data protection, all responses were anonymized using coded questionnaires, and the data were securely stored in a manner accessible only to the research team.\u003c/p\u003e\n\u003cp\u003eConsent for publication - Not applicable. This study did not include patient or public involvement in its design, conduct, or reporting.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials - The datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting interests - The authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003eFunding - The authors declare no conflicts of interest. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions - All authors meet the criteria for authorship and have made substantial contributions to the conception and design of the study, critical revision of the manuscript for important intellectual content, and final approval of the version submitted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAA: Conceptualization, Data Curation, Formal Analysis, Methodology, Investigation, Project Administration, Visualization, Writing \u0026ndash; original draft.\u003c/p\u003e\n\u003cp\u003eBP-Z: Conceptualization, Formal Analysis, Methodology, Investigation.\u003c/p\u003e\n\u003cp\u003eBD: Conceptualization, Formal Analysis, Methodology, Investigation, Supervision, Validation.\u003c/p\u003e\n\u003cp\u003eAR: Conceptualization, Methodology, Investigation.\u003c/p\u003e\n\u003cp\u003eDAO: Conceptualization, Methodology, Investigation.\u003c/p\u003e\n\u003cp\u003eASZ: Conceptualization, Methodology, Investigation.\u003c/p\u003e\n\u003cp\u003eIW: Conceptualization, Methodology, Investigation.\u003c/p\u003e\n\u003cp\u003eAG-W: Conceptualization, Formal Analysis, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003eAcknowledgements - Not applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTamata AT, Mohammadnezhad M. 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Adv Health Sci Educ. 2024;29(4):1463\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"healthy work environment, nursing work environment, psychometric validation, cross-cultural adaptation, hospital nursing, staffing, communication, leadership, teamwork climate","lastPublishedDoi":"10.21203/rs.3.rs-9003556/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9003556/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAim\u003c/p\u003e\n\u003cp\u003eTo adapt culturally and validate the Polish version of the Healthy Work Environment Assessment Tool for use among hospital nurses working in inpatient wards, and to assess nurses’ perception of the work environment in medical and surgical wards.\u003c/p\u003e\n\u003cp\u003eDesign\u003c/p\u003e\n\u003cp\u003eTwo-phase cross-cultural adaptation and psychometric validation study.\u003c/p\u003e\n\u003cp\u003eMethods\u003c/p\u003e\n\u003cp\u003eA cross-sectional, multicenter validation study was conducted in eight hospitals in 2024–2025. A convenience sample of nurses providing adult inpatient care completed the Healthy Work Environment Assessment Tool and the measure assessing teamwork and safety climate. Cultural adaptation was conducted in accordance with established translation and expert review procedures. A psychometric evaluation included analyses of internal structure, internal consistency, temporal stability, and convergent validity.\u003c/p\u003e\n\u003cp\u003eResults\u003c/p\u003e\n\u003cp\u003eThe tool demonstrated good measurement performance, including high internal consistency, satisfactory temporal stability, and convergent validity, as indicated by positive relationships with related constructs. Nurses reported a low-to-moderate level of a healthy work environment, with staffing rated as the weakest area, whereas decision-making and communication were rated higher.\u003c/p\u003e\n\u003cp\u003eConclusion\u003c/p\u003e\n\u003cp\u003eThe Polish version of Healthy Work Environment Assessment Tool is suitable for assessing key components of a healthy work environment among hospital nurses in medical and surgical wards and may support monitoring and improvement initiatives.\u003c/p\u003e\n\u003cp\u003eImplications\u003c/p\u003e\n\u003cp\u003eRoutine assessment can help leaders identify priority gaps, particularly staffing, and guide organizational actions that support nursing retention, quality of care, and patient safety.\u003c/p\u003e\n\u003cp\u003eImpact\u003c/p\u003e\n\u003cp\u003eThe validated Polish version of the tool enables systematic assessment of nurses’ perceptions of a healthy work environment in hospital wards. It can help hospitals identify gaps and guide improvement efforts, particularly in staffing, to support safe, high-quality nursing care.\u003c/p\u003e\n\u003cp\u003eReporting Method\u003c/p\u003e\n\u003cp\u003eThe study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology reporting checklist for cross-sectional studies.\u003c/p\u003e","manuscriptTitle":"Nurses’ Perception of a Healthy Work Environment —Psychometric Validation Study ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-22 07:58:07","doi":"10.21203/rs.3.rs-9003556/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-23T21:44:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"187594988390141290216191213955587269561","date":"2026-04-20T00:15:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268647144937689903861517745614954494250","date":"2026-04-14T17:08:25+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-14T16:19:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T10:26:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-20T14:21:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-20T00:03:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2026-03-19T23:58:16+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f6c2112c-0883-45c5-a77b-5e900a59ff05","owner":[],"postedDate":"April 22nd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T07:58:07+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-22 07:58:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9003556","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9003556","identity":"rs-9003556","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}