The mediating effect of job satisfaction and occupational fatigue on the relationship between Nursing practice environment and missed nursing Care among Critical Care Nurses in Saudi Arabia

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Alkubati, Awatif Alrasheeday, Farhan Alshammari This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7041225/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background: Missed nursing care (MNC)—defined as any required patient care that is omitted or delayed—poses significant risks to patient safety, especially in critical care units (CCUs) where patient acuity is high. The nursing practice environment is increasingly recognized as a key organizational determinant of care quality. However, the pathways through which it influences MNC, particularly the mediating roles of occupational fatigue and job satisfaction, remain underexplored. Aim This study aimed to examine the direct and indirect effects of the nursing practice environment on MNC among critical care nurses in governmental hospitals in Hail City, Saudi Arabia, with job satisfaction and occupational fatigue as mediating variables. Methods A cross-sectional correlational design was employed. Data were collected from 211 registered critical care nurses using validated instruments: the Practice Environment Scale of the Nursing Work Index (PES-NWI), the Minnesota Satisfaction Questionnaire (MSQ), the Occupational Fatigue Exhaustion Recovery (OFER-15) scale, and the MISSCARE Survey. Structural equation modeling (SEM) was conducted using AMOS 24.0 to test hypothesized relationships, and bootstrapping was used to assess mediation. Results The nursing practice environment was significantly associated with increased job satisfaction (β = 0.305, p < 0.001) and decreased occupational fatigue (β = -0.541, p < 0.001). Both job satisfaction (β = -0.289, p < 0.001) and occupational fatigue (β = 0.230, p = 0.004) were significantly associated with MNC. The practice environment had a significant direct negative effect on MNC (β = -0.160, p < 0.001) and also exerted significant indirect effects via job satisfaction (β = -0.090, p = 0.003) and fatigue (β = -0.124, p < 0.001), confirming their mediating roles. The total effect of the practice environment on MNC was substantial (β = -0.374, p < 0.001). Model fit indices indicated excellent fit (CFI = 0.997, TLI = 0.984, RMSEA = 0.044). Conclusion A supportive nursing practice environment significantly reduces MNC in critical care settings, both directly and indirectly through increased job satisfaction and reduced occupational fatigue. These findings support the integration of the Job Demands–Resources model and Kalisch’s Missed Nursing Care model, underscoring the importance of organizational strategies that improve the work environment to enhance nurse well-being and patient care quality. Interventions targeting staffing adequacy, managerial support, and fatigue mitigation are recommended to minimize MNC and ensure safe, complete care delivery in high-acuity units. Clinical trial number : Not applicable. Missed nursing care nursing practice environment job satisfaction occupational fatigue critical care Nurses structural equation modeling Saudi Arabia. Figures Figure 1 Introduction Missed nursing care (MNC)—defined as any required patient care that is omitted (either partially or entirely) or delayed—is a growing concern in healthcare systems, particularly in critical care units where the stakes of timely and complete care delivery are extremely high [1]. The increasing attention to MNC stems from its direct association with adverse patient outcomes such as medication errors, infections, longer hospital stays, and even increased mortality [2]. In Saudi Arabia, like in many healthcare systems worldwide, addressing missed care has become an urgent priority, especially in the high-intensity environment of critical care units (CCUs), where patient acuity and the pace of work elevate the risk of care omissions [3]. The nursing practice environment, conceptualized by Lake (2002)[4], includes the structural and organizational elements that support or hinder nursing practice, such as leadership, staffing adequacy, nurse involvement in governance, and nurse–physician collaboration. A positive practice environment has been consistently associated with better nurse and patient outcomes [5], while an unfavorable environment can contribute to excessive workloads, role ambiguity, and reduced performance—conditions ripe for MNC [6]. Critical care units are particularly vulnerable, as the complexity of care and high patient turnover demand a robust infrastructure and supportive culture for nurses to deliver complete care. Occupational fatigue, encompassing both acute and chronic components, emerges when job demands chronically exceed available resources and recovery time. Nurses in CCUs are especially susceptible to fatigue due to extended shifts, inadequate staffing, and emotional labor associated with high-acuity patients [7]. Fatigued nurses may experience impaired concentration and motivation, which can result in inadvertent errors or skipped care activities. This pathway is supported by several studies that have found a significant positive association between nursing fatigue and MNC [8-10]. Job satisfaction, which represents the extent to which nurses feel fulfilled and valued in their roles, also plays a critical role in determining care quality [11]. The Minnesota Satisfaction Questionnaire [12] has frequently been used to assess this construct. However, higher job satisfaction has been correlated with reduced intent to leave, increased organizational commitment, and better patient care [13]. Dissatisfied nurses, by contrast, may become disengaged, leading to reduced diligence and higher rates of missed care [9]. The practice environment significantly influences job satisfaction; supportive leadership, adequate staffing, and professional autonomy contribute to higher morale and job satisfaction among nurses [14]. Theoretical Framework This study is guided by an integration of the Job Demands–Resources (JD-R) model [15] and Kalisch’s Missed Nursing Care model [1] to examine how the nursing practice environment influences missed nursing MNC are in critical care settings. The JD-R model posits that workplace factors can trigger two parallel processes: a health impairment pathway, where excessive job demands (e.g., time pressure, workload) lead to fatigue and burnout, and a motivational pathway, where sufficient job resources (e.g., supportive leadership, staffing adequacy) foster job satisfaction and engagement [15]. In the context of critical care, where demands are inherently high, the presence or absence of resources becomes particularly influential in shaping nurses’ well-being and performance [16]. Complementing this, Kalisch’s MNC model [1] conceptualizes MNC as a system-level failure resulting from organizational constraints rather than individual negligence. According to Kalisch et al. (2009)[1], care tasks may be delayed or omitted due to resource limitations, communication failures, or workflow disruptions. In high-acuity environments such as ICUs, these systemic issues are frequently cited as causes of incomplete care. Evidence shows that inadequate staffing and unanticipated workload surges often force nurses to prioritize tasks, leading to the omission of non-urgent yet essential interventions [2, 17]. By integrating these frameworks, the current study hypothesizes that a supportive nursing practice environment reduces MNC both directly and indirectly—through decreased occupational fatigue (health impairment pathway) and increased job satisfaction (motivational pathway). A well-resourced environment is expected to reduce emotional exhaustion, enhance job morale, and ultimately enable nurses to deliver more comprehensive care. Empirical research supports these links: higher burnout has been associated with increased missed care, while greater job satisfaction correlates with lower rates of care omissions [18, 19]. Thus, this dual-theoretical lens provides a structured understanding of how organizational conditions affect both nurse outcomes and patient care quality. In critical care settings, where timely and complete nursing care is crucial, enhancing the practice environment may be a key strategy to reduce care omissions and support nursing workforce sustainability. Aim This study, therefore, aims to investigate the direct and indirect relationships between the nursing practice environment and MNC among critical care nurses in Hail governmental hospitals, with occupational fatigue and job satisfaction serving as potential mediators. Hypothesis The hypotheses of the study are as follows: H1: There is a positive relationship between the nursing practice environment and job satisfaction. H2: There is a negative relationship between the nursing practice environment and occupational fatigue. H3: There is a negative relationship between the nursing practice environment and MNC. H4: There is a negative relationship between job satisfaction and MNC. H5: There is a positive relationship between occupational fatigue and MNC. H6: Occupational fatigue mediates the relationship between the nursing practice environment and MNC. H7: Job satisfaction mediates the relationship between the nursing practice environment and MNC. Study Design and Setting This study employed a cross-sectional, correlational survey design to investigate the proposed relationships among variables. The research was conducted in governmental hospitals located in Hail City, Saudi Arabia. Specifically, data were collected from critical care nurses working in three major public hospitals in Hail: King Salman Specialist Hospital, King Khaled Hospital, and the Maternity and Children Hospital. These hospitals collectively provide a range of critical care services (adult intensive care, cardiac care, pediatric and neonatal intensive care, etc.) and were chosen to represent the governmental healthcare sector in the region. By focusing on multiple hospitals, the study captures a broad view of the nursing practice environment and missed care in Hail’s critical care settings. All data were gathered between February and June 2025. Sample and Inclusion Criteria The target population was registered nurses working in the critical care units of the above hospitals. A convenience sampling approach was used, whereby all eligible critical care nurses available during the study period were invited to participate. Inclusion criteria were: (1) being a licensed registered nurse employed in one of the critical care units (e.g., ICU, CCU, NICU) at the study hospitals, and (2) having at least one year of work experience in nursing (to ensure participants had sufficient exposure to the work environment and routines of patient care). We excluded nursing interns, students, or newly hired nurses with less than one year of experience, as well as any temporary agency nurses, because these individuals might not be fully integrated into the unit’s practice environment or might have limited experience that could skew their perceptions of missed care and fatigue. Sample Size Calculation The required sample size was estimated using G*Power 3.1, targeting a medium effect size (f² = 0.15), an alpha level of 0.05, a statistical power of 0.80, and seven predictors reflecting the hypothesized paths in the structural model. The minimum calculated sample was 103. However, considering the model’s complexity and to ensure stable parameter estimation in structural equation modeling, a larger sample was targeted. A total of 211 valid responses were ultimately included in the analysis, exceeding the minimum requirement for robust testing. Data Collection Procedure Data were collected using an online self-administered questionnaire delivered via Google Forms. After obtaining the necessary institutional permissions, the researchers coordinated with the head nurses or unit managers of each critical care department. The head nurses assisted by distributing the Google Forms survey link to all eligible nurses in their units, typically through email or a secure messaging platform used in the hospital. The survey introduction informed participants about the study’s purpose, assured them of confidentiality, and included an informed consent statement. Nurses willing to participate proceeded to complete the questionnaire anonymously online at their convenience. To improve response rates, a reminder notice was sent out approximately two weeks after the initial distribution, again through the unit heads, encouraging those who had not yet responded to complete the survey. The online form was kept open for responses over a period of several months (from February to June 2025) to allow ample time for busy critical care staff to participate. All responses were automatically recorded in a secure Google spreadsheet accessible only to the research team. No identifying personal information was collected in the survey to preserve anonymity. Instruments and Measures The survey questionnaire consisted of several standardized instruments and items to measure the key variables of interest, along with basic demographic questions. Five main measures were utilized in this study: Demographic and Work-Related Questionnaire : This section gathered information on participants’ background and professional characteristics. Items included age, gender, highest educational qualification, total years of nursing experience, years of experience in the current critical care unit, job title/position, and shift type (e.g., rotating or fixed shifts). Additional work-related data such as typical working hours per week and nurse-to-patient ratio in their unit were also surveyed. Missed Nursing Care Scale (MISSCARE Survey): MNC was measured using the MISSCARE Survey, originally developed and validated by Kalisch and Williams [20] in a two-part survey assessing the phenomena of care omissions. Part A of the MISSCARE Survey contains 25 items representing common nursing care activities (such as patient assessments, medication administration, turning patients, providing hygiene, etc.). Nurses were asked to indicate the frequency with which each of these care activities was missed (i.e., not completed or significantly delayed) in their unit. Responses were recorded on a Likert-type frequency scale (for example: 0 = Never missed, 1 = Rarely missed, 2 = Sometimes missed, 3 = Often missed, 4 = Always missed). Part B of the survey lists 22 potential reasons for missed care, including factors like inadequate staffing, lack of supplies, poor communication, or urgent patient situations. Participants identified which reasons were contributors to missed care on their unit (e.g., by rating the significance of each reason or marking all that apply). The MISSCARE Survey has established content validity and reliability; in the original development studies, Part A demonstrated good test–retest reliability (r = 0.87) and internal consistency (Cronbach’s α reported up to 0.86 for certain subscales) [20]. MNC frequency was scored by averaging the item responses from Part A (higher scores indicating a greater frequency of missed care). Although Part B (reasons) data were collected to contextualize the causes of missed care, our analysis of hypotheses focused primarily on the frequency of missed care (Part A) as the outcome variable. Minnesota Satisfaction Questionnaire (MSQ) – Short Form : Nurse job satisfaction was assessed using the short form of the Minnesota Satisfaction Questionnaire developed by Weiss et al. [12]. The MSQ short form consists of 20 items that measure an individual’s satisfaction with various facets of their job. Each item describes an aspect of work (e.g., “The freedom to use my own judgment” or “Recognition for a job well done”), and nurses indicate their level of satisfaction with that aspect on a 5-point Likert scale (ranging from 1 = Very dissatisfied to 5 = Very satisfied). The MSQ yields an overall satisfaction score, as well as subscale scores for intrinsic and extrinsic satisfaction (though in this study we primarily considered the overall job satisfaction score). The MSQ is a widely used instrument in organizational psychology and has been validated across many occupations, including nursing. It has high internal consistency (typically α > 0.90 for the total score) and has shown good construct validity in measuring job satisfaction. In our survey, minor wording adjustments were made to fit nursing context where necessary (for example, referring to “supervisor” as “nurse manager”). A sample item from the MSQ is: “I am satisfied with my chance to do something that makes use of my abilities.” Respondents’ scores were computed by summing or averaging the item responses, with higher scores reflecting greater job satisfaction. Practice Environment Scale of the Nursing Work Index (PES-NWI): The quality of the nursing practice environment was measured by the PES-NWI, originally developed by Lake (2002)[4] to assess organizational attributes of nursing work settings. The PES-NWI contains 31 items which are rated on a Likert scale (typically 1 = Strongly disagree to 4 = Strongly agree) indicating the extent to which certain organizational features are present in the nurse’s work environment. These 31 items are grouped into five subscales representing key dimensions of the practice environment: (a) Nurse Participation in Hospital Affairs (involvement in policy and governance), (b) Nursing Foundations for Quality of Care (support for evidence-based practice and continuing education), (c) Nurse Manager Ability, Leadership, and Support (competency of nursing leadership and managerial support), (d) Staffing and Resource Adequacy (sufficient staffing and resources to provide care), and (e) Collegial Nurse–Physician Relations (positive working relationships and communication with physicians). The PES-NWI has been used extensively and is endorsed by the National Quality Forum as a nursing-sensitive measure of work environment. Lake (2002) [4] reported that the PES-NWI subscales have good reliability (Cronbach’s α for subscales typically in the 0.80s) and that higher PES-NWI scores are associated with better nurse and patient outcomes [4]. In this study, we asked participants to reflect on their current workplace (unit/hospital) and indicate their agreement with each statement (e.g., “Nurses have opportunities to participate in hospital decision-making” or “There are enough staff to get the work done”). Scores for each subscale were calculated as the mean of component items, and an overall practice environment score was derived by averaging all item responses (with higher scores denoting a more favorable environment). This provided a quantitative assessment of how supportive each nurse perceived their work setting to be. Occupational Fatigue Exhaustion Recovery (OFER - 15) Scale : Occupational fatigue was measured using the OFER-15 scale developed by Winwood et al. (2005, 2006)[21, 22], which is a specialized instrument for work-related fatigue in shift-working populations. The OFER-15 is a 15-item self-report scale designed to capture three dimensions of fatigue: acute fatigue (fatigue experienced at the end of a work period or shift), chronic fatigue (persistent fatigue and tiredness accumulated over time), and inter-shift recovery (the degree of recovery experienced between shifts) [23]. Each item is a statement such as “By the end of my workday, I feel really worn out” (acute fatigue) or “I often feel emotionally drained from my work” (chronic fatigue) or “I have enough time to recover between shifts” (recovery). Nurses indicated their agreement with each statement on a 7-point Likert scale from 0 = Strongly Disagree to 6 = Strongly Agree. Notably, higher scores on the fatigue subscales (acute and chronic) represent greater fatigue, whereas a higher score on the recovery subscale represents better recuperation between shifts. In scoring the OFER-15, we followed the standard approach: computing separate mean scores for acute fatigue, chronic fatigue, and inter-shift recovery, as well as an overall fatigue score if appropriate (sometimes a combined “persistent fatigue” score is calculated by averaging acute and chronic fatigue or other methods, as suggested by Winwood et al.). The OFER has undergone extensive validation; the refined OFER-15 version has demonstrated robust psychometric properties, with each subscale showing high internal reliability (α > 0.84) and clear discrimination between fatigue states [22]. For example, Winwood et al. (2006) [22] reported that the OFER-15 could effectively distinguish between workers with high acute fatigue versus high chronic fatigue, and that the inter-shift recovery subscale is a unique indicator not captured by other fatigue measures. In this study, the OFER-15 allowed us to quantify each nurse’s level of work-related exhaustion and recovery. A higher acute/chronic fatigue score indicates the nurse is more fatigued (physically and mentally), while a lower inter-shift recovery score indicates insufficient recovery time. All instruments above were used in their English versions, as English is the primary language of documentation and communication in most Saudi Arabian hospitals and the nurses in the sample were generally proficient in English. Ethical Considerations Ethical approval for this study was obtained from the Institutional Review Board (IRB) of the University of Hail prior to data collection (Approval No. H-2025-625, dated 17/02/2025). Written informed consent was obtained from all participants prior to their participation in the study. Official permission was also secured from the administration of each participating hospital. All participants were provided with information about the study’s aims, procedures, and their rights as research subjects. Participation was entirely voluntary: nurses were under no obligation to complete the survey and could choose to withdraw at any time by not submitting the form. Completion of the online questionnaire was regarded as implied informed consent. The survey introduction clearly stated that responses would be kept confidential and used only for research purposes. To protect privacy, no names or personal identifiers were collected, and results are reported only in aggregate form. The Google Form was set to not collect email addresses or any identifying meta-data. Data security was ensured by storing the downloaded response data on a password-protected computer accessible only to the research team. Data analysis Data were analyzed using IBM SPSS Statistics version 28 for descriptive and preliminary inferential statistics, and Analysis of Moment Structures (AMOS) version 24 for structural equation modeling (SEM). The dataset was first screened for completeness, normality, and outliers. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were calculated to summarize demographic characteristics and study variables. Pearson’s correlation analysis was conducted to examine the bivariate associations among the main study variables: nursing practice environment, occupational fatigue, job satisfaction, and MNC. Path analysis was performed using AMOS 23.0 software to ascertain the mediating effect of job satisfaction and occupational fatigue on the relationship between nursing practice environment and MNC, using the bootstrap method (2000 replicates, 95% bias-corrected confidence interval). The adequacy of the measurement model is strongly supported by its goodness-of-fit indices. X2=1.414, TLI=.984, CFI=.997, NFI=.991, GFI=.997, RESMA=.044. Similarly, the model fit values for the mediation models were acceptable. The robustness of the mediation model was supported by the statistical significance of the direct, indirect, and total effects (p < 0.05). A p-value of ˂0.05 was used as the threshold for significance. Results As described in Table 1 , most of the nurses were females, Saudi, married, and aged more than 30 years old (55.9%, 70.6%, 54.5%, and 59.2%, respectively). In addition, the majority held bachelor's degrees, had experience of more than 5 years, and were working in the day shift (58.3%, 54.5%, and 56.4%, respectively) Table 1 Sociodemographic characteristics of participants (N = 211) Variables Categories n % Age (years) 32.72 ± 4.51 ≤ 30 86 40.8 > 30 125 59.2 Sex Male 93 44.1 Female 118 55.9 Nationality Saudi 149 70.6 Non-Saudi 62 29.4 Marital status Single 77 36.5 Married 115 54.5 Divorced/Widowed 19 9.0 Level of education Diploma 57 27.0 Bachelor 123 58.3 Postgraduate 31 14.7 Experience (years) ≤ 5 Years 96 45.5 > 5 Years 115 54.5 Shift type Day shift 119 56.4 Night shift 13 6.2 Rotating shifts 79 37.4 Table 2 illustrates that the mean of the nursing practice environment scores was 81.10 ± 23.57, with a range of 93 (31.00 ± 124.00). In addition, the means of job satisfaction, occupational fatigue, and MNC were 59.04 ± 18.71, 44.72 ± 14.26, and 56.30 ± 27.61, respectively. Table 2 Descriptive statistics of study variables Variables Range Minimum Maximum Mean ± SD Nursing practice environment 93.00 31.00 124.00 81.10 ± 23.57 Job satisfaction 80.00 20.00 100.00 59.04 ± 18.71 Occupational fatigue 58.00 20.00 78.00 44.72 ± 14.26 Missed nursing care 100.00 25.00 125.00 56.30 ± 27.61 SD: standard deviation There was a significant positive correlation between the nursing practice environment and job satisfaction (r = .305, p < .001). By contrast, a negative correlation was found between the nursing practice environment and occupational fatigue (r=-.541, p < .001) and MNC (r=-.372, p < .001). In addition, a significant negative correlation was found between job satisfaction and occupational fatigue (r=-.231, p < .001) and MNC (r=-.389, p < .001). Finally, a significant positive correlation was found between occupational fatigue and MNC (r = .381, p < .001), Table 3 . Table 3 Correlation between study variables (N = 211) Variables Nursing practice environment Job satisfaction Occupational fatigue Missed nursing care Nursing practice environment r 1 p Job satisfaction r .305** 1 p < .001 Occupational fatigue r − .541** − .231** 1 p < .001 < .001 Missed nursing care r − .372** − .389** .381** 1 p < .001 < .001 < .001 **Correlation is significant at the 0.01 level (2-tailed). The mediating effect of job satisfaction and occupational fatigue on the relationship between nursing practice environment and missed nursing care A structural equation model was established using AMOS 24.0, with the nursing practice environment as the independent variable, MNC as the dependent variable, and job satisfaction and occupational fatigue as mediating variables. Figure 1 represents the model of how job satisfaction and occupational fatigue mediate the relationship between the nursing practice environment and MNC. According to the model, the nursing practice environment had an indirect negative impact on MNC through job satisfaction and occupational fatigue (β=-.090, p = .003 and β=-.124, p < .001, respectively). Furthermore, the nursing practice environment had a significant negative direct effect on MNC (β=-160, p < .001), with a total effect of (β=-.374, p < .001). nursing practice environment also had a significant positive direct effect on job satisfaction (β = .305, p < .001) and a significant negative direct effect on occupational fatigue (β=-.541, pp < .001). Finally, job satisfaction had significant negative direct effects on MNC (β=-.289, p < .001) and occupational fatigue had significant positive direct effects on MNC (β = .230, p = .004) (Table 4 ). The adequacy of the measurement model is strongly supported by its goodness-of-fit indices. X2 = 1.414, TLI = .984, CFI = .997, NFI = .991, GFI = .997, RESMA = .044 see Table 4 . Table 4 Path analysis of occupational fatigue and job satisfaction on the relationship between nursing practice environment and missed nursing care Path Effect size CI (95%) P-value Indirect Effect Nursing practice environment → Job satisfaction → Missed nursing care − .090 − .165–.045 .003 Nursing practice environment → Occupational fatigue → Missed nursing care − .124 − .186–.020 < .001 Direct effect Nursing practice environment → Job satisfaction .305 .168-.430 < .001 Nursing practice environment → Occupational fatigue − .541 − .618–.455 < .001 Job satisfaction → Missed nursing care − .289 − .389–.188 < .001 Occupational fatigue → Missed nursing care .230 .101-.353 .004 Nursing practice environment → Missed nursing care − .160 − .477–.258 < .001 Total Effect Nursing practice environment → Missed nursing care − .374 − .409–.184 < .001 CI, confidence interval Discussion This study provides empirical support for the hypothesized model linking the nursing practice environment to MNC in critical care settings. All proposed relationships (H1–H7) were confirmed by the data. A more favorable nursing practice environment was significantly associated with higher job satisfaction among critical care nurses and lower occupational fatigue, which in turn corresponded to a lower frequency of MNC. Even after accounting for these mediators, the practice environment maintained a direct negative effect on missed care. These findings underscore that a supportive work environment not only directly reduces care omissions but also does so indirectly by bolstering nurses’ well-being (increasing satisfaction and reducing fatigue), which translates into more consistent and complete patient care. Our results reinforce the well-established link between a supportive practice environment and positive nurse outcomes. Critical care nurses who perceived their work environment as more favorable (e.g. adequate staffing, strong leadership support, good interdisciplinary relations) reported significantly higher job satisfaction, aligning with numerous prior studies [ 11 , 24 ]. This is consistent with the idea that when nurses have sufficient resources, autonomy, and managerial support, they feel more valued and fulfilled in their roles [ 25 ]. Conversely, we found that a poor practice environment was associated with greater occupational fatigue. This finding accords with evidence that suboptimal work conditions – such as chronic understaffing, high workload, and lack of support – contribute to nurse burnout and exhaustion [ 26 , 27 ]. In fact, Abraham et al. (2021)[ 26 ] noted that unfavorable practice settings drive higher burnout rates, whereas favorable environments with adequate resources, autonomy, and collegial support can protect against fatigue and burnout. Our study extends these insights to the critical care context in Saudi Arabia, suggesting that improving the work environment can simultaneously enhance nurses’ job morale and reduce their fatigue levels. Practice Environment and Missed Nursing Care Crucially, a better nursing practice environment was linked to lower incidences of MNC in our critical care units, supporting hypothesis H3. This result is highly consistent with prior research from other settings. For example, Park et al. (2018)[ 28 ] found that hospital units characterized as having “good” nursing environments had significantly lower odds of nurses missing required care tasks compared to units with poor environments [ 28 ]. In their large U.S. sample, adequate staffing and resource availability, competent management, and positive nurse–physician collaboration were key environmental features that reduced the likelihood of missed care [ 28 ]. Similarly, a recent study in Iran observed that hospitals with unfavorable practice conditions suffered a higher frequency of missed care, whereas stronger “nursing foundations for quality care” in the environment predicted fewer care omissions [ 29 ]. Our findings mirror these patterns in the context of Saudi Arabian critical care units, reinforcing that the practice environment is a pivotal system-level determinant of care quality. When the work environment supports nurses – through sufficient staffing, good teamwork, and supportive leadership – nurses are more able to complete necessary interventions and avoid omitting critical patient care. This study also sheds light on how individual nurse states, namely job satisfaction and fatigue, relate to missed care. As hypothesized (H4), we found that higher job satisfaction was associated with a lower frequency of MNC. In other words, nurses who felt more satisfied and content in their jobs tended to report fewer care activities left undone. This relationship is coherent with previous evidence that when nurses are satisfied with their jobs, they are more engaged and conscientious in delivering care [ 11 , 30 ]. A recent literature review confirms that missed or unfinished nursing care is closely tied to heightened job dissatisfaction, which can erode nurses’ motivation and attention to detail. In fact, a systematic review by Stemmer et al. (2022)[ 31 ] found that in 5 out of 7 studies analyzed, nurses who experienced more missed care also reported significantly lower job satisfaction. Our results reinforce this negative correlation between missed care and morale: failing to complete required care tasks may leave nurses feeling unaccomplished and frustrated, whereas a satisfying work experience likely energizes nurses to ensure patients’ needs are fully met. Conversely, greater occupational fatigue was associated with more frequent missed care (supporting H5). Nurses suffering high levels of work-related exhaustion and burnout were more prone to report care omissions. This link can be explained by the well-documented impact of fatigue on cognitive functioning and performance. Exhausted nurses often experience impaired concentration, slower reaction times, and memory lapses [ 32 ]. As a result, errors of omission become more likely – fatigued staff may unintentionally forget, overlook, or delay nursing interventions. Qualitative evidence highlights that nurses recognize how working while overly tired can “impair our ability to provide safe, competent care” and lead to mistakes that could harm patients [ 33 ]. Our findings align with these insights, suggesting that occupational fatigue is not just a personal wellness issue but directly compromises nurses’ capacity to deliver all necessary care. Stimpfel and colleagues’ work further supports this, showing that nurses working longer shifts (over 10–12 hours) – a contributor to fatigue – were significantly more likely to experience burnout and report declines in care quality [ 10 ]. Taken together, the evidence is clear that nurse fatigue poses a risk to patient care, increasing the chances that critical nursing tasks will be missed or delayed. Mediating Effects and Theoretical Implications One of the central contributions of this study is demonstrating that job satisfaction and occupational fatigue mediate the relationship between the practice environment and MNC (H6 and H7). We found that a supportive practice environment leads to higher satisfaction, which in turn reduces missed care, and likewise leads to lower fatigue, which also reduces missed care. These indirect pathways are firmly in line with the dual processes outlined by the JD-R model. In JD-R theory, plentiful job resources (such as strong managerial support, adequate staff, and collegial work culture – all elements of a good practice environment) spark a motivational process that boosts work engagement and job satisfaction [ 29 ]. Our data validate this, showing that better environments were associated with significantly improved nurse satisfaction, which was associated with fewer missed tasks. Simultaneously, an unsupportive or resource-poor environment can create excessive job demands and stress, fueling a health-impairment process of fatigue and burnout. This too was borne out: poorer environments were linked to higher nurse fatigue, which in turn was linked to more missed care. The mediation analysis thus empirically illustrates how the practice environment’s impact on care quality is channeled through these two distinct nurse-focused mechanisms – one positive (via satisfaction) and one negative (via exhaustion) – as predicted by JD-R theory. Notably, even after accounting for these mediating factors, the practice environment retained a significant direct effect on MNC. This suggests that organizational context influences missed care above and beyond its influence on individual nurses’ satisfaction or fatigue levels. In other words, some aspects of a healthy practice environment likely reduce missed care through structural or team processes that were not fully captured by the two mediators. This observation resonates with Kalisch’s Missed Nursing Care model, which frames missed care largely as a system-level failure rather than an individual lapse. Kalisch and colleagues emphasize that adequate staffing, effective teamwork, and good communication are fundamental prerequisites for all required care to be delivered [ 1 ]. A positive practice environment inherently facilitates better coordination, prioritization, and problem-solving on the unit, thereby directly enabling nurses to complete their work [ 5 ]. Our finding of a remaining direct effect supports this view: for instance, units with strong nurse–physician collaboration and efficient workflows may prevent omissions by allowing nurses to address issues proactively, independent of any one nurse’s personal fatigue or satisfaction. Overall, the combination of direct and indirect effects underscores that the practice environment is paramount – it shapes nurses’ internal states and the external conditions in which care is delivered, both of which are critical for ensuring that necessary care is not missed. This integrated perspective reinforces arguments in the literature that organizational factors often outweigh individual-level factors in precipitating missed care. Improving the practice environment, therefore, strikes at the root of the missed care problem by simultaneously improving nurse well-being and the systemic supports for care delivery. Implications for Practice and Management Our findings carry important implications for hospital administrators and nursing leadership, particularly in critical care settings. First and foremost, efforts to enhance the nursing practice environment should be a strategic priority for reducing missed care and improving patient outcomes. This entails investing in the known attributes of healthy work environments: ensuring adequate nurse staffing and manageable workloads, fostering a culture of teamwork and respectful nurse–physician collaboration, providing strong managerial support and leadership, and involving nurses in unit decision-making. By strengthening these environmental factors, hospitals can indirectly reduce nurse fatigue and boost morale, creating a more resilient workforce that is capable of delivering complete, high-quality care even in high-pressure situations. For example, our results concur with Park et al. [ 28 ] in highlighting staffing and resource adequacy as a particularly influential aspect of the environment – better staffing was associated with significantly lower odds of MNC [ 28 ]. Managers should thus assess nurse-to-patient ratios and workload distribution in their critical care units, adjusting staffing levels or support resources to prevent excessive strain on nurses. Likewise, improving interdisciplinary communication and support can pay dividends; units with stronger nurse–physician relations saw fewer care tasks left undone [ 14 ]. Hospital leaders in Saudi Arabia (and beyond) should strive to cultivate open communication channels and mutual respect between nurses and physicians, as this collaborative climate helps nurses address patient needs without delay or omission. Another practical implication is the need to address occupational fatigue among nurses as a patient safety concern. Our data show that fatigue is not merely a health issue for staff but has tangible consequences for care delivery. Administrators should implement policies that mitigate nurse fatigue – for instance, regulating shift lengths and overtime, allowing sufficient rest breaks, and rotating nurses off high-acuity assignments periodically to recuperate. Training programs can also educate nurses and managers about fatigue recognition and safe staffing practices. As one article vividly pointed out, fatigue can lead to slowed reactions, errors of omission, and other mistakes that endanger patients [ 32 ]. Thus, preventing nurse burnout through employee wellness initiatives and supportive scheduling is directly linked to reducing MNC. Similarly, maintaining high job satisfaction among nursing staff should be viewed as more than just an HR goal; it is intertwined with care quality. Nurse managers can improve satisfaction by recognizing and rewarding good performance, offering opportunities for professional development, and involving nurses in quality improvement decisions. Satisfied nurses are more engaged and willing to “go the extra mile” for their patients [ 30 ], which means they are less likely to neglect or delay essential care tasks. In summary, healthcare organizations should treat nurse work environment improvements not as an added cost but as an investment in patient safety. By creating conditions that keep nurses happy, energized, and supported in their practice, hospitals enable nurses to provide comprehensive care with minimal omissions. Limitations and Future Directions Despite its contributions, this study has several limitations that should be acknowledged. First, the cross-sectional design limits the ability to establish causality. While the relationships proposed align with established theoretical frameworks, longitudinal or experimental studies are needed to confirm the directionality of these associations—particularly whether changes in the practice environment lead to corresponding changes in job satisfaction, fatigue, and missed care over time. Second, the study relied exclusively on self-reported data collected through standardized questionnaires. Although validated instruments were employed, self-reporting may introduce biases such as social desirability or common method variance. Incorporating objective measures in future research—such as direct care observations, administrative data, or multi-source reporting—would strengthen the validity of the findings. Third, the sample was geographically and institutionally limited to critical care nurses working in three governmental hospitals in Hail City, Saudi Arabia. As such, the results may not be generalizable to private sector hospitals, other regions of the Kingdom, or international contexts with different organizational structures and staffing models. Lastly, while the study focused on job satisfaction and occupational fatigue as mediators, other relevant psychosocial and organizational factors—such as teamwork quality, burnout, leadership style, or turnover intention—were not included in the model and should be explored in future research to provide a more comprehensive understanding of what influences MNC. Conclusion This study highlights the critical role of the nursing practice environment in influencing both nurse-related outcomes and the quality of patient care in critical care settings. The findings provide robust empirical support for the hypothesized model, demonstrating that a supportive practice environment is significantly associated with reduced MNC—both directly and indirectly—through enhanced job satisfaction and reduced occupational fatigue. These results reinforce the relevance of the Job Demands–Resources and MNC models in explaining how organizational conditions affect care delivery, especially in high-acuity environments. Importantly, the dual mediating roles of job satisfaction and fatigue underscore the need for healthcare administrators to adopt a holistic approach to workforce management—one that addresses both structural factors (e.g., staffing levels, managerial support) and the psychological well-being of nursing staff. Interventions aimed at improving the practice environment may not only reduce nurse fatigue and improve morale but also enhance care completeness, thereby improving patient safety and outcomes. Given the cross-sectional nature of the study, future longitudinal and interventional research is recommended to confirm causality and evaluate the impact of specific organizational strategies on reducing MNC. Nevertheless, this study contributes valuable evidence to the global discourse on nursing quality and provides practical guidance for improving critical care services in Saudi Arabia and similar healthcare contexts. Abbreviations Abbreviation Full Term MNC Missed Nursing Care CCU Critical Care Unit PES-NWI Practice Environment Scale of the Nursing Work Index MSQ Minnesota Satisfaction Questionnaire OFER-15 Occupational Fatigue Exhaustion Recovery – 15 item scale JD-R Job Demands–Resources SEM Structural Equation Modeling AMOS Analysis of Moment Structures CI Confidence Interval SD Standard Deviation GFI Goodness-of-Fit Index CFI Comparative Fit Index TLI Tucker–Lewis Index NFI Normed Fit Index RMSEA Root Mean Square Error of Approximation Declarations Ethics Approval and Consent to Participate Ethical approval for this study was obtained from the Institutional Review Board (IRB) of the University of Hail (Approval No. H-2025-625, dated 17/02/2025). Administrative permissions were also granted by King Salman Specialist Hospital, King Khaled Hospital, and the Maternity and Children Hospital in Hail City. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. All participants were informed about the study’s objectives and procedures. Written informed consent was obtained from all participants prior to their participation in the study. Participation was voluntary, and completion of the anonymous online questionnaire was considered as implied consent. Consent for Publication Not applicable. Availability of Data and Materials All data generated or analyzed during this study are included in this published article. Competing Interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ Contributions BA contributed to the study design, literature review, data collection coordination, and manuscript drafting. SAA conceptualized the study, supervised data analysis, conducted the statistical analysis, and critically revised the manuscript for intellectual content. AA participated in data interpretation, assisted with manuscript preparation, and contributed to reviewing and editing the final version. FA facilitated access to study sites, supported participant recruitment, and participated in reviewing and editing the final version. All authors (BA, SAA, AA, and FA) reviewed and approved the final manuscript. References Kalisch BJ, Landstrom GL, Hinshaw AS. Missed nursing care: a concept analysis. J Adv Nurs. 2009;65(7):1509–17. Tsegaye TG, Tadesse H, Yesera GE, Bezie HE, Oyato BT, Kena SS, Debela DE, Andarge RB. Missed nursing care and associated factors among nurses and midwives in maternity wards of Sidama region public hospitals, Ethiopia. BMC Nurs. 2024;23(1):686. Al Muharraq EH, Alallah SM, Alkhayrat SA, Jahlan AG. An Overview of Missed Nursing Care and Its Predictors in Saudi Arabia: A Cross-Sectional Study. Nurs Res Pract. 2022;2022:4971890. Lake ET. Development of the practice environment scale of the Nursing Work Index. Res Nurs Health. 2002;25(3):176–88. Alharbi A, Alkubati SA, Albaqawi H, Ali AZ, Hamed LA, Mohammed S, Cornejo LTO. Pasay-an E: Relationship between nursing work environment and clinical decision-making among Saudi nurses: psychological empowerment as mediator. BMC Nurs. 2025;24(1):682. Alshammari B, Alanazi NF, Kreedi F, Alshammari F, Alkubati SA, Alrasheeday A, Madkhali N, Alshara A, Bakthavatchaalam V, Al-Masaeed M, et al. Exposure to secondary traumatic stress and its related factors among emergency nurses in Saudi Arabia: a mixed method study. BMC Nurs. 2024;23(1):337. Alkubati SA, Alsaqri SH, Alrubaiee GG, Almoliky MA, Al-Qalah T, Pasay-an E, Almeaibed H, Elsayed SM. The influence of anxiety and depression on critical care nurses’ performance: A multicenter correlational study. Australian Crit Care. 2025;38(1):101064. Bell T, Sprajcer M, Flenady T, Sahay A. Fatigue in nurses and medication administration errors: A scoping review. J Clin Nurs. 2023;32(17–18):5445–60. White EM, Aiken LH, McHugh MD. Registered Nurse Burnout, Job Dissatisfaction, and Missed Care in Nursing Homes. J Am Geriatr Soc. 2019;67(10):2065–71. Stimpfel AW, Sloane DM, Aiken LH. The longer the shifts for hospital nurses, the higher the levels of burnout and patient dissatisfaction. Health Aff (Millwood). 2012;31(11):2501–9. Alkubati SA, Alrashidi OA, Albaqawi H, Alharbi A, Laradhi AO, Albani GF, Alsaqri S, Pasay-an E, Ali AZ. The mediating effect of resilience and job satisfaction on the relationship between critical care nurses’ stress-and task performance: findings to improve nursing care. BMC Nurs. 2025;24(1):579. Weiss DJ, Dawis RV, England GW. Manual for the Minnesota Satisfaction Questionnaire. Minn Stud Vocat Rehabilitation. 1967;22:120–120. Gregoriou I, Papastavrou E, Charalambous A, Economidou E, Soteriades ES, Merkouris A. Organisational commitment, job satisfaction and intention to leave among physicians in the public health sector of Cyprus: a cross-sectional survey. BMJ Open. 2023;13(5):e067527. Daheshi N, Alkubati SA, Villagracia H, Pasay-an E, Alharbi G, Alshammari F, Madkhali N, Alshammari B. Nurses’ Perception Regarding the Quality of Communication between Nurses and Physicians in Emergency Departments in Saudi Arabia: A Cross Sectional Study. Healthcare. 2023;11(5):645. Bakker AB, Demerouti E. The Job Demands-Resources model: State of the art. J Managerial Psychol. 2007;22(3):309–28. Nantsupawat A, Srisuphan W, Kunaviktikul W, Wichaikhum OA, Aungsuroch Y, Aiken LH. Impact of nurse work environment and staffing on hospital nurse and quality of care in Thailand. J Nurs Scholarsh. 2011;43(4):426–32. Hessels AJ, Flynn L, Cimiotti JP, Cadmus E, Gershon RR. The Impact of the Nursing Practice Environment on Missed Nursing Care. Clin Nurs Stud. 2015;3(4):60–5. Algin A, Yesilbas H, Kantek F. The Relationship Between Missed Nursing Care and Nurse Job Satisfaction: A Systematic Review and Meta-Analysis. West J Nurs Res. 2024;46(12):980–8. Nantsupawat A, Wichaikhum OA, Abhicharttibutra K, Sadarangani T, Poghosyan L. The relationship between nurse burnout, missed nursing care, and care quality following COVID-19 pandemic. J Clin Nurs. 2023;32(15–16):5076–83. Kalisch BJ, Williams RA. Development and psychometric testing of a tool to measure missed nursing care. J Nurs Adm. 2009;39(5):211–9. Winwood PC, Winefield AH, Dawson D, Lushington K. Development and validation of a scale to measure work-related fatigue and recovery: the Occupational Fatigue Exhaustion/Recovery Scale (OFER). J Occup Environ Med. 2005;47(6):594–606. Winwood PC, Lushington K, Winefield AH. Further development and validation of the Occupational Fatigue Exhaustion Recovery (OFER) scale. J Occup Environ Med. 2006;48(4):381–9. Di Fabio A, Svicher A, Gori A. Occupational Fatigue: Relationship With Personality Traits and Decent Work. Front Psychol 2021, Volume 12–2021. Choi J, Flynn L, Aiken LH. Nursing practice environment and registered nurses' job satisfaction in nursing homes. Gerontologist. 2012;52(4):484–92. El-Gazar HE, Shawer M, Alkubati SA, Zoromba MA. The role of psychological ownership in linking decent work to nurses' vigor at work: A two-wave study. J Nurs Scholarsh. 2024;56(6):780–9. Abraham CM, Zheng K, Norful AA, Ghaffari A, Liu J, Poghosyan L. Primary care Practice Environment and Burnout among Nurse Practitioners. J Nurse Pract. 2021;17(2):157–62. Alshammari B, Pangket P, Alrasheeday A, Baghdadi N, Alkubati SA, Cabansag D, Gugoy N, Alshammari SM, Alanazi A, Alanezi MD, et al. The Mediating Role of Burnout in the Relationship Between Emotional Intelligence and Work Engagement Among Hospital Nurses: A Structural Equation Modeling Approach. Nurs Rep. 2025;15(6):208. Park SH, Hanchett M, Ma C. Practice Environment Characteristics Associated With Missed Nursing Care. J Nurs Scholarsh. 2018;50(6):722–30. Babaei S, Amini K, Ramezani-Badr F. Unveiling missed nursing care: a comprehensive examination of neglected responsibilities and practice environment challenges. BMC Health Serv Res. 2024;24(1):977. Azzellino G, Dante A, Petrucci C, Caponnetto V, Aitella E, Lancia L, Ginaldi L, De Martinis M. Intention to leave and missed nursing care: A scoping review. Int J Nurs Stud Adv. 2025;8:100312. Stemmer R, Bassi E, Ezra S, Harvey C, Jojo N, Meyer G, Özsaban A, Paterson C, Shifaza F, Turner MB, Bail K. A systematic review: Unfinished nursing care and the impact on the nurse outcomes of job satisfaction, burnout, intention-to-leave and turnover. J Adv Nurs. 2022;78(8):2290–303. Kelton D, Kingsley E, Davis C, Miller D. Running on empty? The facts about nursing fatigue. Nurs made Incredibly Easy. 2014;12(2):45–9. Steege LM, Rainbow JG. Fatigue in hospital nurses - 'Supernurse' culture is a barrier to addressing problems: A qualitative interview study. Int J Nurs Stud. 2017;67:20–8. Additional Declarations No competing interests reported. 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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-7041225","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":497826688,"identity":"6f150363-b4d0-41da-9c0b-f28cf6537112","order_by":0,"name":"Bushra Alshammari","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCUlEQVRIiWNgGAWjYBACexDxgOEAhJdQwcBgAKQl8GkxbACphGs5Q4QWgwPIWhjbiLFlRgLjh4Q/d+R1px1+9uHhvMNy5gzMB2/zMNTJ4/SLRAKzRGLbM8Ntt9OMZyRuO2xs2cCWbM3DcBjsZBy2MEgkNhxm3HY7wZgBqCVxwwEeM2kehgOMuLQY3Ehg/pHw57D9ttvpnxkS54C08H8Daqmzx6OFTSKB7XDitts5QFsawLawAbUwJ+J0WM/DNovEtsPJQC3FDAnH0o0NDrMZW84xOJyMS4s9e/LhGx/+HLYFOmwz448aazmD480Pb7ypqLPFpQUYF+hSzGAH41Q/CkbBKBgFo4AIAABFe17CD1c1FAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Hail","correspondingAuthor":true,"prefix":"","firstName":"Bushra","middleName":"","lastName":"Alshammari","suffix":""},{"id":497826689,"identity":"c5298640-6cf4-45de-9d9f-0fb654b5bb06","order_by":1,"name":"Sameer A. 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The increasing attention to MNC stems from its direct association with adverse patient outcomes such as medication errors, infections, longer hospital stays, and even increased mortality [2]. In Saudi Arabia, like in many healthcare systems worldwide, addressing missed care has become an urgent priority, especially in the high-intensity environment of critical care units (CCUs), where patient acuity and the pace of work elevate the risk of care omissions [3].\u003c/p\u003e\n\u003cp\u003eThe nursing practice environment, conceptualized by Lake (2002)[4], includes the structural and organizational elements that support or hinder nursing practice, such as leadership, staffing adequacy, nurse involvement in governance, and nurse–physician collaboration. A positive practice environment has been consistently associated with better nurse and patient outcomes [5], while an unfavorable environment can contribute to excessive workloads, role ambiguity, and reduced performance—conditions ripe for MNC [6]. Critical care units are particularly vulnerable, as the complexity of care and high patient turnover demand a robust infrastructure and supportive culture for nurses to deliver complete care.\u003c/p\u003e\n\u003cp\u003eOccupational fatigue, encompassing both acute and chronic components, emerges when job demands chronically exceed available resources and recovery time. Nurses in CCUs are especially susceptible to fatigue due to extended shifts, inadequate staffing, and emotional labor associated with high-acuity patients [7]. Fatigued nurses may experience impaired concentration and motivation, which can result in inadvertent errors or skipped care activities. This pathway is supported by several studies that have found a significant positive association between nursing fatigue and MNC [8-10].\u003c/p\u003e\n\u003cp\u003eJob satisfaction, which represents the extent to which nurses feel fulfilled and valued in their roles, also plays a critical role in determining care quality [11]. The Minnesota Satisfaction Questionnaire [12] has frequently been used to assess this construct. However, higher job satisfaction has been correlated with reduced intent to leave, increased organizational commitment, and better patient care [13]. Dissatisfied nurses, by contrast, may become disengaged, leading to reduced diligence and higher rates of missed care [9]. The practice environment significantly influences job satisfaction; supportive leadership, adequate staffing, and professional autonomy contribute to higher morale and job satisfaction among nurses [14].\u003c/p\u003e\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"},{"header":"Theoretical Framework","content":"\u003cp\u003eThis study is guided by an integration of the Job Demands–Resources (JD-R) model [15] and Kalisch’s Missed Nursing Care model [1] to examine how the nursing practice environment influences missed nursing MNC are in critical care settings. The JD-R model posits that workplace factors can trigger two parallel processes: a health impairment pathway, where excessive job demands (e.g., time pressure, workload) lead to fatigue and burnout, and a motivational pathway, where sufficient job resources (e.g., supportive leadership, staffing adequacy) foster job satisfaction and engagement [15]. In the context of critical care, where demands are inherently high, the presence or absence of resources becomes particularly influential in shaping nurses’ well-being and performance [16].\u003c/p\u003e\u003cp\u003eComplementing this, Kalisch’s MNC model [1] conceptualizes MNC as a system-level failure resulting from organizational constraints rather than individual negligence. According to Kalisch et al. (2009)[1], care tasks may be delayed or omitted due to resource limitations, communication failures, or workflow disruptions. In high-acuity environments such as ICUs, these systemic issues are frequently cited as causes of incomplete care. Evidence shows that inadequate staffing and unanticipated workload surges often force nurses to prioritize tasks, leading to the omission of non-urgent yet essential interventions [2, 17].\u003c/p\u003e\u003cp\u003eBy integrating these frameworks, the current study hypothesizes that a supportive nursing practice environment reduces MNC both directly and indirectly—through decreased occupational fatigue (health impairment pathway) and increased job satisfaction (motivational pathway). A well-resourced environment is expected to reduce emotional exhaustion, enhance job morale, and ultimately enable nurses to deliver more comprehensive care. Empirical research supports these links: higher burnout has been associated with increased missed care, while greater job satisfaction correlates with lower rates of care omissions [18, 19]. Thus, this dual-theoretical lens provides a structured understanding of how organizational conditions affect both nurse outcomes and patient care quality. In critical care settings, where timely and complete nursing care is crucial, enhancing the practice environment may be a key strategy to reduce care omissions and support nursing workforce sustainability.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study, therefore, aims to investigate the direct and indirect relationships between the nursing practice environment and MNC among critical care nurses in Hail governmental hospitals, with occupational fatigue and job satisfaction serving as potential mediators.\u003cbr\u003e\u003cstrong\u003eHypothesis\u003c/strong\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;The hypotheses of the study are as follows:\u003c/p\u003e\u003cp\u003eH1: There is a positive relationship between the nursing practice environment and job satisfaction.\u003cbr\u003e\u0026nbsp;H2: There is a negative relationship between the nursing practice environment and occupational fatigue.\u003c/p\u003e\u003cp\u003eH3: There is a negative relationship between the nursing practice environment and MNC.\u003c/p\u003e\u003cp\u003eH4: There is a negative relationship between job satisfaction and MNC.\u003cbr\u003e\u0026nbsp;H5: There is a positive relationship between occupational fatigue and MNC.\u003cbr\u003e\u0026nbsp;H6: Occupational fatigue mediates the relationship between the nursing practice environment and MNC.\u003c/p\u003e\u003cp\u003eH7: Job satisfaction mediates the relationship between the nursing practice environment and MNC.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eStudy Design and Setting\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThis study employed a cross-sectional, correlational survey design to investigate the proposed relationships among variables. The research was conducted in governmental hospitals located in Hail City, Saudi Arabia. Specifically, data were collected from critical care nurses working in three major public hospitals in Hail: King Salman Specialist Hospital, King Khaled Hospital, and the Maternity and Children Hospital. These hospitals collectively provide a range of critical care services (adult intensive care, cardiac care, pediatric and neonatal intensive care, etc.) and were chosen to represent the governmental healthcare sector in the region. By focusing on multiple hospitals, the study captures a broad view of the nursing practice environment and missed care in Hail’s critical care settings. All data were gathered between February and June 2025.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSample and Inclusion Criteria\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe target population was registered nurses working in the critical care units of the above hospitals. A convenience sampling approach was used, whereby all eligible critical care nurses available during the study period were invited to participate. Inclusion criteria were: (1) being a licensed registered nurse employed in one of the critical care units (e.g., ICU, CCU, NICU) at the study hospitals, and (2) having at least one year of work experience in nursing (to ensure participants had sufficient exposure to the work environment and routines of patient care). We excluded nursing interns, students, or newly hired nurses with less than one year of experience, as well as any temporary agency nurses, because these individuals might not be fully integrated into the unit’s practice environment or might have limited experience that could skew their perceptions of missed care and fatigue.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eSample Size Calculation\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe required sample size was estimated using G*Power 3.1, targeting a medium effect size (f² = 0.15), an alpha level of 0.05, a statistical power of 0.80, and seven predictors reflecting the hypothesized paths in the structural model. The minimum calculated sample was 103. However, considering the model’s complexity and to ensure stable parameter estimation in structural equation modeling, a larger sample was targeted. A total of 211 valid responses were ultimately included in the analysis, exceeding the minimum requirement for robust testing.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Collection Procedure\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eData were collected using an online self-administered questionnaire delivered via Google Forms. After obtaining the necessary institutional permissions, the researchers coordinated with the head nurses or unit managers of each critical care department. The head nurses assisted by distributing the Google Forms survey link to all eligible nurses in their units, typically through email or a secure messaging platform used in the hospital. The survey introduction informed participants about the study’s purpose, assured them of confidentiality, and included an informed consent statement. Nurses willing to participate proceeded to complete the questionnaire anonymously online at their convenience. To improve response rates, a reminder notice was sent out approximately two weeks after the initial distribution, again through the unit heads, encouraging those who had not yet responded to complete the survey. The online form was kept open for responses over a period of several months (from February to June 2025) to allow ample time for busy critical care staff to participate. All responses were automatically recorded in a secure Google spreadsheet accessible only to the research team. No identifying personal information was collected in the survey to preserve anonymity.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eInstruments and Measures\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eThe survey questionnaire consisted of several standardized instruments and items to measure the key variables of interest, along with basic demographic questions. Five main measures were utilized in this study:\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDemographic and Work-Related Questionnaire\u003c/strong\u003e: This section gathered information on participants’ background and professional characteristics. Items included age, gender, highest educational qualification, total years of nursing experience, years of experience in the current critical care unit, job title/position, and shift type (e.g., rotating or fixed shifts). Additional work-related data such as typical working hours per week and nurse-to-patient ratio in their unit were also surveyed.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMissed Nursing Care Scale (MISSCARE Survey):\u003c/strong\u003e MNC was measured using the MISSCARE Survey, originally developed and validated by Kalisch and Williams [20] in a two-part survey assessing the phenomena of care omissions. Part A of the MISSCARE Survey contains 25 items representing common nursing care activities (such as patient assessments, medication administration, turning patients, providing hygiene, etc.). Nurses were asked to indicate the frequency with which each of these care activities was missed (i.e., not completed or significantly delayed) in their unit. Responses were recorded on a Likert-type frequency scale (for example: 0 = Never missed, 1 = Rarely missed, 2 = Sometimes missed, 3 = Often missed, 4 = Always missed). Part B of the survey lists 22 potential reasons for missed care, including factors like inadequate staffing, lack of supplies, poor communication, or urgent patient situations. Participants identified which reasons were contributors to missed care on their unit (e.g., by rating the significance of each reason or marking all that apply). The MISSCARE Survey has established content validity and reliability; in the original development studies, Part A demonstrated good test–retest reliability (r = 0.87) and internal consistency (Cronbach’s α reported up to 0.86 for certain subscales) [20]. MNC frequency was scored by averaging the item responses from Part A (higher scores indicating a greater frequency of missed care). Although Part B (reasons) data were collected to contextualize the causes of missed care, our analysis of hypotheses focused primarily on the frequency of missed care (Part A) as the outcome variable.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMinnesota Satisfaction Questionnaire (MSQ) – Short Form\u003c/strong\u003e: Nurse job satisfaction was assessed using the short form of the Minnesota Satisfaction Questionnaire developed by Weiss et al. [12]. The MSQ short form consists of 20 items that measure an individual’s satisfaction with various facets of their job. Each item describes an aspect of work (e.g., “The freedom to use my own judgment” or “Recognition for a job well done”), and nurses indicate their level of satisfaction with that aspect on a 5-point Likert scale (ranging from 1 = Very dissatisfied to 5 = Very satisfied). The MSQ yields an overall satisfaction score, as well as subscale scores for intrinsic and extrinsic satisfaction (though in this study we primarily considered the overall job satisfaction score). The MSQ is a widely used instrument in organizational psychology and has been validated across many occupations, including nursing. It has high internal consistency (typically α \u0026gt; 0.90 for the total score) and has shown good construct validity in measuring job satisfaction. In our survey, minor wording adjustments were made to fit nursing context where necessary (for example, referring to “supervisor” as “nurse manager”). A sample item from the MSQ is: “I am satisfied with my chance to do something that makes use of my abilities.” Respondents’ scores were computed by summing or averaging the item responses, with higher scores reflecting greater job satisfaction.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePractice Environment Scale of the Nursing Work Index (PES-NWI):\u003c/strong\u003e The quality of the nursing practice environment was measured by the PES-NWI, originally developed by Lake (2002)[4] to assess organizational attributes of nursing work settings. The PES-NWI contains 31 items which are rated on a Likert scale (typically 1 = Strongly disagree to 4 = Strongly agree) indicating the extent to which certain organizational features are present in the nurse’s work environment. These 31 items are grouped into five subscales representing key dimensions of the practice environment: (a) Nurse Participation in Hospital Affairs (involvement in policy and governance), (b) Nursing Foundations for Quality of Care (support for evidence-based practice and continuing education), (c) Nurse Manager Ability, Leadership, and Support (competency of nursing leadership and managerial support), (d) Staffing and Resource Adequacy (sufficient staffing and resources to provide care), and (e) Collegial Nurse–Physician Relations (positive working relationships and communication with physicians). The PES-NWI has been used extensively and is endorsed by the National Quality Forum as a nursing-sensitive measure of work environment. Lake (2002) [4] reported that the PES-NWI subscales have good reliability (Cronbach’s α for subscales typically in the 0.80s) and that higher PES-NWI scores are associated with better nurse and patient outcomes [4]. In this study, we asked participants to reflect on their current workplace (unit/hospital) and indicate their agreement with each statement (e.g., “Nurses have opportunities to participate in hospital decision-making” or “There are enough staff to get the work done”). Scores for each subscale were calculated as the mean of component items, and an overall practice environment score was derived by averaging all item responses (with higher scores denoting a more favorable environment). This provided a quantitative assessment of how supportive each nurse perceived their work setting to be.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eOccupational Fatigue Exhaustion Recovery (OFER\u003c/strong\u003e-\u003cstrong\u003e15) Scale\u003c/strong\u003e: Occupational fatigue was measured using the OFER-15 scale developed by Winwood et al. (2005, 2006)[21, 22], which is a specialized instrument for work-related fatigue in shift-working populations. The OFER-15 is a 15-item self-report scale designed to capture three dimensions of fatigue: acute fatigue (fatigue experienced at the end of a work period or shift), chronic fatigue (persistent fatigue and tiredness accumulated over time), and inter-shift recovery (the degree of recovery experienced between shifts) [23]. Each item is a statement such as “By the end of my workday, I feel really worn out” (acute fatigue) or “I often feel emotionally drained from my work” (chronic fatigue) or “I have enough time to recover between shifts” (recovery). Nurses indicated their agreement with each statement on a 7-point Likert scale from 0 = Strongly Disagree to 6 = Strongly Agree. Notably, higher scores on the fatigue subscales (acute and chronic) represent greater fatigue, whereas a higher score on the recovery subscale represents better recuperation between shifts. In scoring the OFER-15, we followed the standard approach: computing separate mean scores for acute fatigue, chronic fatigue, and inter-shift recovery, as well as an overall fatigue score if appropriate (sometimes a combined “persistent fatigue” score is calculated by averaging acute and chronic fatigue or other methods, as suggested by Winwood et al.). The OFER has undergone extensive validation; the refined OFER-15 version has demonstrated robust psychometric properties, with each subscale showing high internal reliability (α \u0026gt; 0.84) and clear discrimination between fatigue states [22]. For example, Winwood et al. (2006) [22] reported that the OFER-15 could effectively distinguish between workers with high acute fatigue versus high chronic fatigue, and that the inter-shift recovery subscale is a unique indicator not captured by other fatigue measures. In this study, the OFER-15 allowed us to quantify each nurse’s level of work-related exhaustion and recovery. A higher acute/chronic fatigue score indicates the nurse is more fatigued (physically and mentally), while a lower inter-shift recovery score indicates insufficient recovery time.\u003c/p\u003e\u003cp\u003eAll instruments above were used in their English versions, as English is the primary language of documentation and communication in most Saudi Arabian hospitals and the nurses in the sample were generally proficient in English.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eEthical approval for this study was obtained from the Institutional Review Board (IRB) of the University of Hail prior to data collection (Approval No. H-2025-625, dated 17/02/2025). Written informed consent was obtained from all participants prior to their participation in the study. Official permission was also secured from the administration of each participating hospital. All participants were provided with information about the study’s aims, procedures, and their rights as research subjects. Participation was entirely voluntary: nurses were under no obligation to complete the survey and could choose to withdraw at any time by not submitting the form. Completion of the online questionnaire was regarded as implied informed consent. The survey introduction clearly stated that responses would be kept confidential and used only for research purposes. To protect privacy, no names or personal identifiers were collected, and results are reported only in aggregate form. The Google Form was set to not collect email addresses or any identifying meta-data. Data security was ensured by storing the downloaded response data on a password-protected computer accessible only to the research team.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eData were analyzed using IBM SPSS Statistics version 28 for descriptive and preliminary inferential statistics, and Analysis of Moment Structures (AMOS) version 24 for structural equation modeling (SEM). The dataset was first screened for completeness, normality, and outliers. Descriptive statistics, including means, standard deviations, frequencies, and percentages, were calculated to summarize demographic characteristics and study variables. Pearson’s correlation analysis was conducted to examine the bivariate associations among the main study variables: nursing practice environment, occupational fatigue, job satisfaction, and MNC. Path analysis was performed using AMOS 23.0 software to ascertain the mediating effect of job satisfaction and occupational fatigue on the relationship between nursing practice environment and MNC, using the bootstrap method (2000 replicates, 95% bias-corrected confidence interval). The adequacy of the measurement model is strongly supported by its goodness-of-fit indices. X2=1.414, TLI=.984, CFI=.997, NFI=.991, GFI=.997, RESMA=.044. Similarly, the model fit values for the mediation models were acceptable. The robustness of the mediation model was supported by the statistical significance of the direct, indirect, and total effects (p \u0026lt; 0.05). A p-value of ˂0.05 was used as the threshold for significance.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAs described in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, most of the nurses were females, Saudi, married, and aged more than 30 years old (55.9%, 70.6%, 54.5%, and 59.2%, respectively). In addition, the majority held bachelor's degrees, had experience of more than 5 years, and were working in the day shift (58.3%, 54.5%, and 56.4%, respectively)\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\u003eSociodemographic characteristics of participants (N\u0026thinsp;=\u0026thinsp;211)\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\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\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32.72\u0026thinsp;\u0026plusmn;\u0026thinsp;4.51\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e40.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e125\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e59.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSex\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e55.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNationality\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSaudi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e70.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-Saudi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e29.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e36.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced/Widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e9.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLevel of education\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDiploma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e27.0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBachelor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e58.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExperience (years)\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;5 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;5 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e54.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eShift type\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDay shift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e56.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNight shift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRotating shifts\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e37.4\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrates that the mean of the nursing practice environment scores was 81.10\u0026thinsp;\u0026plusmn;\u0026thinsp;23.57, with a range of 93 (31.00\u0026thinsp;\u0026plusmn;\u0026thinsp;124.00). In addition, the means of job satisfaction, occupational fatigue, and MNC were 59.04\u0026thinsp;\u0026plusmn;\u0026thinsp;18.71, 44.72\u0026thinsp;\u0026plusmn;\u0026thinsp;14.26, and 56.30\u0026thinsp;\u0026plusmn;\u0026thinsp;27.61, respectively.\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\u003eDescriptive statistics of study variables\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=\"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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMinimum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMaximum\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e31.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e124.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e81.10\u0026thinsp;\u0026plusmn;\u0026thinsp;23.57\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e80.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e59.04\u0026thinsp;\u0026plusmn;\u0026thinsp;18.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e58.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e20.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e78.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e44.72\u0026thinsp;\u0026plusmn;\u0026thinsp;14.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e100.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e25.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e125.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c5\"\u003e\u003cp\u003e56.30\u0026thinsp;\u0026plusmn;\u0026thinsp;27.61\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003eSD: standard deviation\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThere was a significant positive correlation between the nursing practice environment and job satisfaction (r\u0026thinsp;=\u0026thinsp;.305, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). By contrast, a negative correlation was found between the nursing practice environment and occupational fatigue (r=-.541, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and MNC (r=-.372, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). In addition, a significant negative correlation was found between job satisfaction and occupational fatigue (r=-.231, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and MNC (r=-.389, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). Finally, a significant positive correlation was found between occupational fatigue and MNC (r\u0026thinsp;=\u0026thinsp;.381, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\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\u003eCorrelation between study variables (N\u0026thinsp;=\u0026thinsp;211)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNursing practice environment\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eJob satisfaction\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOccupational fatigue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMissed nursing care\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.305**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.541**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.231**\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\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\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\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMissed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.372**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.389**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e.381**\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e**Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe mediating effect of job satisfaction and occupational fatigue on the relationship between nursing practice environment and missed nursing care\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA structural equation model was established using AMOS 24.0, with the nursing practice environment as the independent variable, MNC as the dependent variable, and job satisfaction and occupational fatigue as mediating variables. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e represents the model of how job satisfaction and occupational fatigue mediate the relationship between the nursing practice environment and MNC.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAccording to the model, the nursing practice environment had an indirect negative impact on MNC through job satisfaction and occupational fatigue (β=-.090, p\u0026thinsp;=\u0026thinsp;.003 and β=-.124, p\u0026thinsp;\u0026lt;\u0026thinsp;.001, respectively). Furthermore, the nursing practice environment had a significant negative direct effect on MNC (β=-160, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), with a total effect of (β=-.374, p\u0026thinsp;\u0026lt;\u0026thinsp;.001). nursing practice environment also had a significant positive direct effect on job satisfaction (β\u0026thinsp;=\u0026thinsp;.305, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and a significant negative direct effect on occupational fatigue (β=-.541, pp\u0026thinsp;\u0026lt;\u0026thinsp;.001). Finally, job satisfaction had significant negative direct effects on MNC (β=-.289, p\u0026thinsp;\u0026lt;\u0026thinsp;.001) and occupational fatigue had significant positive direct effects on MNC (β\u0026thinsp;=\u0026thinsp;.230, p\u0026thinsp;=\u0026thinsp;.004) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The adequacy of the measurement model is strongly supported by its goodness-of-fit indices. X2\u0026thinsp;=\u0026thinsp;1.414, TLI\u0026thinsp;=\u0026thinsp;.984, CFI\u0026thinsp;=\u0026thinsp;.997, NFI\u0026thinsp;=\u0026thinsp;.991, GFI\u0026thinsp;=\u0026thinsp;.997, RESMA\u0026thinsp;=\u0026thinsp;.044 see Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\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\u003ePath analysis of occupational fatigue and job satisfaction on the relationship between nursing practice environment and missed nursing care\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\"\u003e\u003cp\u003ePath\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEffect size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCI (95%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndirect Effect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Job satisfaction \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.165\u0026ndash;.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Occupational fatigue \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.124\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.186\u0026ndash;.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDirect effect\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Job satisfaction\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.305\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.168-.430\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Occupational fatigue\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.541\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.618\u0026ndash;.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob satisfaction \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.289\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.389\u0026ndash;.188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupational fatigue \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e.230\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e.101-.353\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.477\u0026ndash;.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal Effect\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\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing practice environment \u0026rarr; Missed nursing care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.374\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026minus;\u0026thinsp;.409\u0026ndash;.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eCI, confidence interval\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e This study provides empirical support for the hypothesized model linking the nursing practice environment to MNC in critical care settings. All proposed relationships (H1\u0026ndash;H7) were confirmed by the data. A more favorable nursing practice environment was significantly associated with higher job satisfaction among critical care nurses and lower occupational fatigue, which in turn corresponded to a lower frequency of MNC. Even after accounting for these mediators, the practice environment maintained a direct negative effect on missed care. These findings underscore that a supportive work environment not only directly reduces care omissions but also does so indirectly by bolstering nurses\u0026rsquo; well-being (increasing satisfaction and reducing fatigue), which translates into more consistent and complete patient care.\u003c/p\u003e\u003cp\u003eOur results reinforce the well-established link between a supportive practice environment and positive nurse outcomes. Critical care nurses who perceived their work environment as more favorable (e.g. adequate staffing, strong leadership support, good interdisciplinary relations) reported significantly higher job satisfaction, aligning with numerous prior studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This is consistent with the idea that when nurses have sufficient resources, autonomy, and managerial support, they feel more valued and fulfilled in their roles [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Conversely, we found that a poor practice environment was associated with greater occupational fatigue. This finding accords with evidence that suboptimal work conditions \u0026ndash; such as chronic understaffing, high workload, and lack of support \u0026ndash; contribute to nurse burnout and exhaustion [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In fact, Abraham et al. (2021)[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] noted that unfavorable practice settings drive higher burnout rates, whereas favorable environments with adequate resources, autonomy, and collegial support can protect against fatigue and burnout. Our study extends these insights to the critical care context in Saudi Arabia, suggesting that improving the work environment can simultaneously enhance nurses\u0026rsquo; job morale and reduce their fatigue levels.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePractice Environment and Missed Nursing Care\u003c/b\u003e\u003c/p\u003e\u003cp\u003e Crucially, a better nursing practice environment was linked to lower incidences of MNC in our critical care units, supporting hypothesis H3. This result is highly consistent with prior research from other settings. For example, Park et al. (2018)[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found that hospital units characterized as having \u0026ldquo;good\u0026rdquo; nursing environments had significantly lower odds of nurses missing required care tasks compared to units with poor environments [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. In their large U.S. sample, adequate staffing and resource availability, competent management, and positive nurse\u0026ndash;physician collaboration were key environmental features that reduced the likelihood of missed care [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Similarly, a recent study in Iran observed that hospitals with unfavorable practice conditions suffered a higher frequency of missed care, whereas stronger \u0026ldquo;nursing foundations for quality care\u0026rdquo; in the environment predicted fewer care omissions [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Our findings mirror these patterns in the context of Saudi Arabian critical care units, reinforcing that the practice environment is a pivotal system-level determinant of care quality. When the work environment supports nurses \u0026ndash; through sufficient staffing, good teamwork, and supportive leadership \u0026ndash; nurses are more able to complete necessary interventions and avoid omitting critical patient care.\u003c/p\u003e\u003cp\u003eThis study also sheds light on how individual nurse states, namely job satisfaction and fatigue, relate to missed care. As hypothesized (H4), we found that higher job satisfaction was associated with a lower frequency of MNC. In other words, nurses who felt more satisfied and content in their jobs tended to report fewer care activities left undone. This relationship is coherent with previous evidence that when nurses are satisfied with their jobs, they are more engaged and conscientious in delivering care [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A recent literature review confirms that missed or unfinished nursing care is closely tied to heightened job dissatisfaction, which can erode nurses\u0026rsquo; motivation and attention to detail. In fact, a systematic review by Stemmer et al. (2022)[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] found that in 5 out of 7 studies analyzed, nurses who experienced more missed care also reported significantly lower job satisfaction. Our results reinforce this negative correlation between missed care and morale: failing to complete required care tasks may leave nurses feeling unaccomplished and frustrated, whereas a satisfying work experience likely energizes nurses to ensure patients\u0026rsquo; needs are fully met.\u003c/p\u003e\u003cp\u003eConversely, greater occupational fatigue was associated with more frequent missed care (supporting H5). Nurses suffering high levels of work-related exhaustion and burnout were more prone to report care omissions. This link can be explained by the well-documented impact of fatigue on cognitive functioning and performance. Exhausted nurses often experience impaired concentration, slower reaction times, and memory lapses [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. As a result, errors of omission become more likely \u0026ndash; fatigued staff may unintentionally forget, overlook, or delay nursing interventions. Qualitative evidence highlights that nurses recognize how working while overly tired can \u0026ldquo;impair our ability to provide safe, competent care\u0026rdquo; and lead to mistakes that could harm patients [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Our findings align with these insights, suggesting that occupational fatigue is not just a personal wellness issue but directly compromises nurses\u0026rsquo; capacity to deliver all necessary care. Stimpfel and colleagues\u0026rsquo; work further supports this, showing that nurses working longer shifts (over 10\u0026ndash;12 hours) \u0026ndash; a contributor to fatigue \u0026ndash; were significantly more likely to experience burnout and report declines in care quality [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Taken together, the evidence is clear that nurse fatigue poses a risk to patient care, increasing the chances that critical nursing tasks will be missed or delayed.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMediating Effects and Theoretical Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOne of the central contributions of this study is demonstrating that job satisfaction and occupational fatigue mediate the relationship between the practice environment and MNC (H6 and H7). We found that a supportive practice environment leads to higher satisfaction, which in turn reduces missed care, and likewise leads to lower fatigue, which also reduces missed care. These indirect pathways are firmly in line with the dual processes outlined by the JD-R model. In JD-R theory, plentiful job resources (such as strong managerial support, adequate staff, and collegial work culture \u0026ndash; all elements of a good practice environment) spark a motivational process that boosts work engagement and job satisfaction [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Our data validate this, showing that better environments were associated with significantly improved nurse satisfaction, which was associated with fewer missed tasks. Simultaneously, an unsupportive or resource-poor environment can create excessive job demands and stress, fueling a health-impairment process of fatigue and burnout. This too was borne out: poorer environments were linked to higher nurse fatigue, which in turn was linked to more missed care. The mediation analysis thus empirically illustrates how the practice environment\u0026rsquo;s impact on care quality is channeled through these two distinct nurse-focused mechanisms \u0026ndash; one positive (via satisfaction) and one negative (via exhaustion) \u0026ndash; as predicted by JD-R theory.\u003c/p\u003e\u003cp\u003eNotably, even after accounting for these mediating factors, the practice environment retained a significant direct effect on MNC. This suggests that organizational context influences missed care above and beyond its influence on individual nurses\u0026rsquo; satisfaction or fatigue levels. In other words, some aspects of a healthy practice environment likely reduce missed care through structural or team processes that were not fully captured by the two mediators. This observation resonates with Kalisch\u0026rsquo;s Missed Nursing Care model, which frames missed care largely as a system-level failure rather than an individual lapse. Kalisch and colleagues emphasize that adequate staffing, effective teamwork, and good communication are fundamental prerequisites for all required care to be delivered [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. A positive practice environment inherently facilitates better coordination, prioritization, and problem-solving on the unit, thereby directly enabling nurses to complete their work [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Our finding of a remaining direct effect supports this view: for instance, units with strong nurse\u0026ndash;physician collaboration and efficient workflows may prevent omissions by allowing nurses to address issues proactively, independent of any one nurse\u0026rsquo;s personal fatigue or satisfaction. Overall, the combination of direct and indirect effects underscores that the practice environment is paramount \u0026ndash; it shapes nurses\u0026rsquo; internal states and the external conditions in which care is delivered, both of which are critical for ensuring that necessary care is not missed. This integrated perspective reinforces arguments in the literature that organizational factors often outweigh individual-level factors in precipitating missed care. Improving the practice environment, therefore, strikes at the root of the missed care problem by simultaneously improving nurse well-being and the systemic supports for care delivery.\u003c/p\u003e\u003cp\u003e\u003cb\u003eImplications for Practice and Management\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur findings carry important implications for hospital administrators and nursing leadership, particularly in critical care settings. First and foremost, efforts to enhance the nursing practice environment should be a strategic priority for reducing missed care and improving patient outcomes. This entails investing in the known attributes of healthy work environments: ensuring adequate nurse staffing and manageable workloads, fostering a culture of teamwork and respectful nurse\u0026ndash;physician collaboration, providing strong managerial support and leadership, and involving nurses in unit decision-making. By strengthening these environmental factors, hospitals can indirectly reduce nurse fatigue and boost morale, creating a more resilient workforce that is capable of delivering complete, high-quality care even in high-pressure situations. For example, our results concur with Park et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] in highlighting staffing and resource adequacy as a particularly influential aspect of the environment \u0026ndash; better staffing was associated with significantly lower odds of MNC [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Managers should thus assess nurse-to-patient ratios and workload distribution in their critical care units, adjusting staffing levels or support resources to prevent excessive strain on nurses. Likewise, improving interdisciplinary communication and support can pay dividends; units with stronger nurse\u0026ndash;physician relations saw fewer care tasks left undone [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHospital leaders in Saudi Arabia (and beyond) should strive to cultivate open communication channels and mutual respect between nurses and physicians, as this collaborative climate helps nurses address patient needs without delay or omission. Another practical implication is the need to address occupational fatigue among nurses as a patient safety concern. Our data show that fatigue is not merely a health issue for staff but has tangible consequences for care delivery. Administrators should implement policies that mitigate nurse fatigue \u0026ndash; for instance, regulating shift lengths and overtime, allowing sufficient rest breaks, and rotating nurses off high-acuity assignments periodically to recuperate. Training programs can also educate nurses and managers about fatigue recognition and safe staffing practices. As one article vividly pointed out, fatigue can lead to slowed reactions, errors of omission, and other mistakes that endanger patients [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Thus, preventing nurse burnout through employee wellness initiatives and supportive scheduling is directly linked to reducing MNC. Similarly, maintaining high job satisfaction among nursing staff should be viewed as more than just an HR goal; it is intertwined with care quality. Nurse managers can improve satisfaction by recognizing and rewarding good performance, offering opportunities for professional development, and involving nurses in quality improvement decisions. Satisfied nurses are more engaged and willing to \u0026ldquo;go the extra mile\u0026rdquo; for their patients [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], which means they are less likely to neglect or delay essential care tasks. In summary, healthcare organizations should treat nurse work environment improvements not as an added cost but as an investment in patient safety. By creating conditions that keep nurses happy, energized, and supported in their practice, hospitals enable nurses to provide comprehensive care with minimal omissions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations and Future Directions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDespite its contributions, this study has several limitations that should be acknowledged. First, the cross-sectional design limits the ability to establish causality. While the relationships proposed align with established theoretical frameworks, longitudinal or experimental studies are needed to confirm the directionality of these associations\u0026mdash;particularly whether changes in the practice environment lead to corresponding changes in job satisfaction, fatigue, and missed care over time. Second, the study relied exclusively on self-reported data collected through standardized questionnaires. Although validated instruments were employed, self-reporting may introduce biases such as social desirability or common method variance. Incorporating objective measures in future research\u0026mdash;such as direct care observations, administrative data, or multi-source reporting\u0026mdash;would strengthen the validity of the findings. Third, the sample was geographically and institutionally limited to critical care nurses working in three governmental hospitals in Hail City, Saudi Arabia. As such, the results may not be generalizable to private sector hospitals, other regions of the Kingdom, or international contexts with different organizational structures and staffing models. Lastly, while the study focused on job satisfaction and occupational fatigue as mediators, other relevant psychosocial and organizational factors\u0026mdash;such as teamwork quality, burnout, leadership style, or turnover intention\u0026mdash;were not included in the model and should be explored in future research to provide a more comprehensive understanding of what influences MNC.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights the critical role of the nursing practice environment in influencing both nurse-related outcomes and the quality of patient care in critical care settings. The findings provide robust empirical support for the hypothesized model, demonstrating that a supportive practice environment is significantly associated with reduced MNC\u0026mdash;both directly and indirectly\u0026mdash;through enhanced job satisfaction and reduced occupational fatigue. These results reinforce the relevance of the Job Demands\u0026ndash;Resources and MNC models in explaining how organizational conditions affect care delivery, especially in high-acuity environments.\u003c/p\u003e\u003cp\u003eImportantly, the dual mediating roles of job satisfaction and fatigue underscore the need for healthcare administrators to adopt a holistic approach to workforce management\u0026mdash;one that addresses both structural factors (e.g., staffing levels, managerial support) and the psychological well-being of nursing staff. Interventions aimed at improving the practice environment may not only reduce nurse fatigue and improve morale but also enhance care completeness, thereby improving patient safety and outcomes.\u003c/p\u003e\u003cp\u003eGiven the cross-sectional nature of the study, future longitudinal and interventional research is recommended to confirm causality and evaluate the impact of specific organizational strategies on reducing MNC. Nevertheless, this study contributes valuable evidence to the global discourse on nursing quality and provides practical guidance for improving critical care services in Saudi Arabia and similar healthcare contexts.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eFull Term\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eMNC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eMissed Nursing Care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eCCU\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eCritical Care Unit\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003ePES-NWI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003ePractice Environment Scale of the Nursing Work Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eMSQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eMinnesota Satisfaction Questionnaire\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eOFER-15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eOccupational Fatigue Exhaustion Recovery \u0026ndash; 15 item scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eJD-R\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eJob Demands\u0026ndash;Resources\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eSEM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eStructural Equation Modeling\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eAMOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eAnalysis of Moment Structures\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eConfidence Interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eGFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eGoodness-of-Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eComparative Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eTucker\u0026ndash;Lewis Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eNormed Fit Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.9167%;\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 77.0833%;\"\u003e\n \u003cp\u003eRoot Mean Square Error of Approximation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the Institutional Review Board (IRB) of the University of Hail (Approval No. H-2025-625, dated 17/02/2025). Administrative permissions were also granted by King Salman Specialist Hospital, King Khaled Hospital, and the Maternity and Children Hospital in Hail City. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. All participants were informed about the study’s objectives and procedures. Written informed consent was obtained from all participants prior to their participation in the study. Participation was voluntary, and completion of the anonymous online questionnaire was considered as implied consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data generated or analyzed during this study are included in this published article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBA contributed to the study design, literature review, data collection coordination, and manuscript drafting. SAA conceptualized the study, supervised data analysis, conducted the statistical analysis, and critically revised the manuscript for intellectual content. AA participated in data interpretation, assisted with manuscript preparation, and contributed to reviewing and editing the final version. FA facilitated access to study sites, supported participant recruitment, and participated in reviewing and editing the final version. All authors (BA, SAA, AA, and FA) reviewed and approved the final manuscript.\u003c/p\u003e"},{"header":"References ","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKalisch BJ, Landstrom GL, Hinshaw AS. Missed nursing care: a concept analysis. J Adv Nurs. 2009;65(7):1509\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsegaye TG, Tadesse H, Yesera GE, Bezie HE, Oyato BT, Kena SS, Debela DE, Andarge RB. 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J Occup Environ Med. 2006;48(4):381\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDi Fabio A, Svicher A, Gori A. Occupational Fatigue: Relationship With Personality Traits and Decent Work. Front Psychol 2021, Volume 12\u0026ndash;2021.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChoi J, Flynn L, Aiken LH. Nursing practice environment and registered nurses' job satisfaction in nursing homes. Gerontologist. 2012;52(4):484\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEl-Gazar HE, Shawer M, Alkubati SA, Zoromba MA. The role of psychological ownership in linking decent work to nurses' vigor at work: A two-wave study. J Nurs Scholarsh. 2024;56(6):780\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAbraham CM, Zheng K, Norful AA, Ghaffari A, Liu J, Poghosyan L. Primary care Practice Environment and Burnout among Nurse Practitioners. J Nurse Pract. 2021;17(2):157\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAlshammari B, Pangket P, Alrasheeday A, Baghdadi N, Alkubati SA, Cabansag D, Gugoy N, Alshammari SM, Alanazi A, Alanezi MD, et al. The Mediating Role of Burnout in the Relationship Between Emotional Intelligence and Work Engagement Among Hospital Nurses: A Structural Equation Modeling Approach. Nurs Rep. 2025;15(6):208.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePark SH, Hanchett M, Ma C. Practice Environment Characteristics Associated With Missed Nursing Care. J Nurs Scholarsh. 2018;50(6):722\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBabaei S, Amini K, Ramezani-Badr F. Unveiling missed nursing care: a comprehensive examination of neglected responsibilities and practice environment challenges. BMC Health Serv Res. 2024;24(1):977.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAzzellino G, Dante A, Petrucci C, Caponnetto V, Aitella E, Lancia L, Ginaldi L, De Martinis M. Intention to leave and missed nursing care: A scoping review. Int J Nurs Stud Adv. 2025;8:100312.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStemmer R, Bassi E, Ezra S, Harvey C, Jojo N, Meyer G, \u0026Ouml;zsaban A, Paterson C, Shifaza F, Turner MB, Bail K. A systematic review: Unfinished nursing care and the impact on the nurse outcomes of job satisfaction, burnout, intention-to-leave and turnover. J Adv Nurs. 2022;78(8):2290\u0026ndash;303.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKelton D, Kingsley E, Davis C, Miller D. Running on empty? The facts about nursing fatigue. Nurs made Incredibly Easy. 2014;12(2):45\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSteege LM, Rainbow JG. Fatigue in hospital nurses - 'Supernurse' culture is a barrier to addressing problems: A qualitative interview study. Int J Nurs Stud. 2017;67:20\u0026ndash;8.\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":"Missed nursing care, nursing practice environment, job satisfaction, occupational fatigue, critical care, Nurses, structural equation modeling, Saudi Arabia.","lastPublishedDoi":"10.21203/rs.3.rs-7041225/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7041225/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMissed nursing care (MNC)—defined as any required patient care that is omitted or delayed—poses significant risks to patient safety, especially in critical care units (CCUs) where patient acuity is high. The nursing practice environment is increasingly recognized as a key organizational determinant of care quality. However, the pathways through which it influences MNC, particularly the mediating roles of occupational fatigue and job satisfaction, remain underexplored.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to examine the direct and indirect effects of the nursing practice environment on MNC among critical care nurses in governmental hospitals in Hail City, Saudi Arabia, with job satisfaction and occupational fatigue as mediating variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional correlational design was employed. Data were collected from 211 registered critical care nurses using validated instruments: the Practice Environment Scale of the Nursing Work Index (PES-NWI), the Minnesota Satisfaction Questionnaire (MSQ), the Occupational Fatigue Exhaustion Recovery (OFER-15) scale, and the MISSCARE Survey. Structural equation modeling (SEM) was conducted using AMOS 24.0 to test hypothesized relationships, and bootstrapping was used to assess mediation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe nursing practice environment was significantly associated with increased job satisfaction (β = 0.305, p \u0026lt; 0.001) and decreased occupational fatigue (β = -0.541, p \u0026lt; 0.001). Both job satisfaction (β = -0.289, p \u0026lt; 0.001) and occupational fatigue (β = 0.230, p = 0.004) were significantly associated with MNC. The practice environment had a significant direct negative effect on MNC (β = -0.160, p \u0026lt; 0.001) and also exerted significant indirect effects via job satisfaction (β = -0.090, p = 0.003) and fatigue (β = -0.124, p \u0026lt; 0.001), confirming their mediating roles. The total effect of the practice environment on MNC was substantial (β = -0.374, p \u0026lt; 0.001). Model fit indices indicated excellent fit (CFI = 0.997, TLI = 0.984, RMSEA = 0.044).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA supportive nursing practice environment significantly reduces MNC in critical care settings, both directly and indirectly through increased job satisfaction and reduced occupational fatigue. These findings support the integration of the Job Demands–Resources model and Kalisch’s Missed Nursing Care model, underscoring the importance of organizational strategies that improve the work environment to enhance nurse well-being and patient care quality. Interventions targeting staffing adequacy, managerial support, and fatigue mitigation are recommended to minimize MNC and ensure safe, complete care delivery in high-acuity units.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical\u003c/strong\u003e \u003cstrong\u003etrial number\u003c/strong\u003e: Not applicable.\u003c/p\u003e","manuscriptTitle":"The mediating effect of job satisfaction and occupational fatigue on the relationship between Nursing practice environment and missed nursing Care among Critical Care Nurses in Saudi Arabia","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-12 12:46:55","doi":"10.21203/rs.3.rs-7041225/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-28T11:35:17+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-11T08:58:27+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95922413065329513664315566927377214413","date":"2026-02-28T07:41:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259440115626251857991130443076573689443","date":"2026-02-26T08:22:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"258525863605920898596782604303334754248","date":"2026-02-25T23:04:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"19522680689375251895175081604695854781","date":"2026-01-10T05:52:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-06T15:35:19+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-24T23:36:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-16T09:40:10+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-11T00:32:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2025-07-11T00:29:37+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":"32d145e1-ad9d-42eb-8834-c1654ce51d1b","owner":[],"postedDate":"August 12th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-12T12:46:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-12 12:46:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7041225","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7041225","identity":"rs-7041225","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}