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Latent profile analysis of operating room nurses’ occupational fatigue and its relationship with attentional control

BMC Nursing volume 24, Article number: 310 (2025) Cite this article

Abstract

Background

Occupational fatigue in operating room nurses may influence their attentional control. However, few previous studies have explored the correlation between occupational fatigue and attentional control in operating room nurses. To better understand operating room nurses’ occupational fatigue and its relationship with attentional control, this study aimed to identify the latent profiles and their factors that influence operating room nurses’ occupational fatigue as well as differences in attentional control across each latent profile.

Methods

A cross-sectional study was conducted from May 2024 to July 2024, and a total of 386 operating room nurses were recruited from 6 hospitals in Chengdu. The participants completed the Occupational Fatigue Scale and the Attentional Control Scale. Latent profile analysis (LPA) was employed to identify latent profiles of occupational fatigue among operating room nurses. The predictors of occupational fatigue in different latent profiles were assessed via multinomial logistic regression analysis. One-way ANOVA and the Kruskal–Wallis test were used to compare the scores on the attentional control scale for each latent profile of nurses’ occupational fatigue.

Results

This study identified three latent profiles of operating room nurses’. occupational fatigue: the “low-fatigue/high-recovery group” (n = 80, 21.2%), the “high-fatigue/low-recovery group” (n = 113,29.3%) and the “moderate-fatigue/mod-erate-recovery group” (n = 193, 49.4%). The results of the multinomial logistic regression analysis suggested that age, work experience, educational level and monthly income were predictors of operating room nurses’ occupational fatigue. There were significant differences in attentional control among the different pr-ofiles of occupational fatigue (P < 0.001). The scores for attentional focus were. Significantly different across each profile (P < 0.001), whereas the scores for at-tentional shift were not different across profiles (P = 0.342).

Conclusions

Operating room nurses’ occupational fatigue can be divided into three latent profiles. Reducing chronic and acute fatigue while enhancing intershift recovery can improve nurses’ attentional control and improve the overall service quality of the hospital. Nursing managers should identify operating room nurses who are at risk and implement targeted interventions to reduce occupational fatigue.

Trial registration

This study does not involve clinical trials or interventional procedures and therefore does not meet the criteria for clinical trial registration.

Peer Review reports

Introduction

Occupational fatigue refers to a state in which individuals are exposed to high work demands and stresses over a long period of time. It manifests as a decline in physical activity, mental cognition, and the ability to work normally [1]. In the 21st century, occupational fatigue has increasingly become a prevalent issue in contemporary society particularly among healthcare professionals, driven by intense competition, high pressure, and a rapid pace [2, 3]. As the core department of the hospital, the operating room is the site of the important tasks of surgical treatment [4] and the rescue of critically ill patients. The tasks performed by operating room nurses are characterized by a high degree of professionalism, precision, collaboration, and the ability to respond to emergencies [5]. These tasks primarily focus on the care of surgical patients and the smooth progression of surgical procedures [6]. Operating room nurses are at high risk of occupational fatigue, with an incidence of 71–94.8% [7,8,9]. Long-term occupational fatigue can affect operating room nurses’ physical and mental health and work performance, reduce work efficiency, increase medical errors, and affect the quality of nursing services and patient safety [7, 10, 11].

Occupational fatigue among operating room nurses has not been thoroughly and comprehensively investigated [12]. To date, most studies have adopted a variable-centric approach and evaluated each dimension as a discrete variable. This approach is appropriate when the aim is to analyze how the components of different dimensions change in a population or the relationships between variables in a group of individuals [13]. However, this approach overlooks the dynamic relationships among the dimensions of occupational fatigue and whether the behavioral impact of any one component depends on the relative strength and combination of the other components. Individual-centered analysis (e.g., latent profiling) can address the interactions among the dimensions of occupational fatigue and allow for the holistic assessment of the experience of fatigue, which facilitates precise understanding of the nuances and complexity of individual differences in variable systems [13].

Attentional control is a topic of increasing interest in both scientific and clinical fields [14, 15]. Attentional control is a cognitive ability that focuses consciousness on a specific stimulus or location and maintains attention; it plays a key role in a variety of operations and is critical for higher-order cognitive and functional activities [16]. Attentional deficits can affect individual physiology and mental health and have adverse effects on quality of life, such as poor professional performance, interpersonal difficulties, and emotional disorders [17, 18]. Occupational fatigue is a significant factor affecting workplace safety, and it has been shown to have a notable impact on human errors and unsafe behaviors across various industries and environments. Previous studies on firefighters [19], construction workers [20], and gas industry workers [21] have consistently demonstrated a strong correlation between occupational fatigue and human errors as well as unsafe behaviors. It significantly reduces the level of safe behaviors, impairs safety behavior intentions, and leads to decreased attention, prolonged reaction times, and weakened judgment. Particularly in complex tasks requiring high levels of concentration, occupational fatigue further increases the likelihood of human errors, thereby threatening the safety of both the workplace and the tasks at hand. Surgical coordination is a task that requires a high level of concentration. The ability to maintain prolonged stability and focus is crucial for the safety and efficiency of surgical procedures [22]. Any unsafe behaviors resulting from fatigue, such as contamination of the sterile field or dropping surgical instruments, can adversely affect the surgical process and patient safety. Previous research has confirmed that attentional control is related to fatigue [23]. Although significant associations between fatigue and attentional control have been demonstrated in previous studies [24, 25], few studies have explored the correlation between occupational fatigue and attentional control in operating room nurses. Therefore, it is unknown whether the degree of occupational fatigue experienced by operating room nurses influences their attentional control during surgical cooperation and affects surgical efficiency and results. Moreover, no research has examined whether attentional control varies across each latent profile of occupational fatigue.

Individual-centered analysis can be used to identify and compare subgroups with similar composition [26]. Latent profile analysis (LPA) is an individual-centered method that identifies distinct groups based on varying characteristics and differences in indicators, aiding in the detection of high-risk populations and enabling targeted interventions [27]. Using maximum likelihood estimation, LPA minimizes within-group variability while maximizing between-group variability, with statistical indicators ensuring classification accuracy and validity [28].

In this context, the purpose of this study was to investigate the level of occupational fatigue and attentional control among nurses in operating rooms, and identify categories of occupational fatigue. Meanwhile explore the latent profiles and its.

influencing factors of operating room nurses’ occupational fatigue, as well as differences in attentional control across each latent profile. To provide a theoretical foundation for nursing managers to design targeted and personalized interventions aimed at alleviating the occupational fatigue experienced by operating room nurses.

Methods

Participants

This cross-sectional study was approved by the medical ethics committee. From May 2024 to July 2024, participants were selected from nine administrative areas in Chengdu via convenience sampling. The inclusion criteria were (a) registered nurses who worked in the operating room, (b) provided informed consent regarding their willingness to participate in the study and (c) had worked in this position for at least 1 year. The exclusion criteria were (a) nurses on shifts who were currently not in a hospital nursing position, (b) newly graduated registered nurses with standardized training, and (c) nurses who were not on duty for various reasons (such as further training, maternity leave or vacation, and health problems). In addition, questionnaires with incorrect entries, those with consecutive identical responses exhibiting a certain pattern, and those with more than 10% of items left unanswered will be excluded. Paper questionnaires were distributed both offline and online, and 386 operating room nurses from 6 tertiary hospitals in Chengdu were included.

Sample

For descriptive cross-sectional studies of quantitative variables, the sample size was calculated as follows [29] : \(N = {{{Z^2}\alpha /2p\left( {1 - p} \right)} \over {{\delta ^2}}}\)

At the 95% confidence interval, Zα/2=1.96, δ represents the absolute error or precision, which was 0.05 in this study, and p is the incidence of severe occupational fatigue among nurses in the operating room that can be based on the data from previous research [30, 31], which was 26.3% here. According to the formula, the the oretical sample size was 298. Considering an invalid response rate of 20% during the study, it was concluded that at least 358 operating room nurses need to be investigated.

Data collection

This study used a combination of offline and online methods to collect questionnaires. For nearby hospitals, onsite surveys were used to gather data. For distant hospitals, data collection was conducted using an online questionnaire administered via the Questionnaire Star platform (Wenjuanxing, http://www.wjx.cn). Regardless of whether an offline or online survey was conducted, the researchers submitted ethical review approval documents and obtained the permission of the person in charge of the hospital before the investigation began. The investigators for this study comprised the research team, nursing departments in various hospitals and administrators of the hospital’s operating room department. All investigators received unified training and were responsible for selecting participants who met the inclusion criteria and informing the participants of the aim, significance, and content of the research. The research was anonymous. For offline questionnaires, after informed consent was obtained from the participants, the investigators introduced the requirements for completing the questionnaire to participants and then collected and reviewed the questionnaire on the spot. If any missing items were found, the respondent was invited to complete them in a timely manner. For the online questionnaires, the investigators sent the questionnaire link to the nursing WeChat group of each hospital and explained the purpose and completion requirements of the questionnaire survey to the participants through the WeChat group. After the participants provided informed consent, they could click the link to complete the questionnaire and submit it independently. To improve the quality of the online data collection, each IP address could be used only once to complete the questionnaire, and participants could submit the questionnaire when all options were completed. When the answers provided in a questionnaire were the same or the completion time for the online questionnaire was less than 300 s, the completed questionnaire was rejected.

Measurements

Participants’ general characteristics

Demographic data (age, gender, marital status, educational level) and work-related information (i.e., professional title, monthly salary income, average number of hours worked per week, monthly average number of night shifts, employment status, years of operating room work experience) were collected.

Occupational fatigue for operating room nurses

Nurses’ occupational fatigue recovery was measured via the Occupational Fatigue Exhaustion Recovery scale (OFER) for operating room nurses, which was developed by WINWOOD et al. [31].and Fang et al. [32].translated the Chinese version of the Scale in 2009. The scale consists of 15 items in 3 subscales: chronic fatigue(items 1–5), acute fatigue(items 6–10) and intershift recovery(items 11–15) and a cumulative variance contribution of 70.367%. The instrument measures chronic fatigue, acute fatigue and intershift recovery with a 7-point Likert response scale ranging from 0 (never) to 6 (always). The scores of each subscale were converted to a percentage scale, calculated as the total score of the items divided by 30, multiplied by 100. The total score ranges from 0 to 100 points, and acute and chronic fatigue are divided into 3 levels (0 ~ 33.3 points indicates mild fatigue, 33.4 ~ 66.6 points indicates moderate fatigue, and 66.7 ~ 100.0 points indicates severe fatigue). The higher the scores of the acute and chronic fatigue subscales, the greater the degree of fatigue. The lower the score is for the intershift recovery subscale, the lower the degree of recovery between shifts. The scale in our study showed good internal consistency and reliability with a Cronbach’s alpha of 0.783. The Cronbach’s alpha coefficients for each of the three dimensions were 0.902 (chronic fatigue), 0.876 (acute fatigue), and 0.827 (intershift recovery).

Attentional control for operating room nurses

The Attentional Control Scale (ACS) developed by Derryberry and Reed et al. [17].was originally developed in the form of a self-report survey. Yang et al. [33].translated the Chinese version of the Scale in 2014 and named it ACS-C. It measures the ability to control attention and contains 20 items on two subscales (i.e., 9 items on attentional focus and 11 items on attentional shift). This instrument measures attentional control on a 4-point Likert response scale ranging from 1 (never) to 4 (always). The higher the score, the better the individual’s attentional control ability is. The Cronbach’s alpha for attentional control was 0.801, and the Cronbach’s alpha coefficients for the dimensions of attentional focus and attentional shift were 0.874 and 0.776, respectively.

Ethical considerations

This research was approved by the medical ethics committee of Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China (approval no. 2024 − 197). All participants were informed of the purpose of the study before recruitment, and all participants were asked to voluntarily sign a written consent form. To protect the participants’ privacy, all collected data were preserved anonymously and confidentially.

Data analysis

Mplus version 8.0 was used to explore the latent profiles of operating room nurses’ occupational fatigue. Data for each item in the three dimensions were entered into the LPA. In this study, one to five potential profile models were explored sequentially from the initial model (1 profile) to the determination of the most appropriate model with a log-likelihood test. The LPA model fit test indices included the Akaike information criterion (AIC), the Bayesian information criterion (BIC), and the adjusted Bayesian information criterion (aBIC), with a lower value indicating a better-fitting model. The classification accuracy was evaluated with entropy values (from 0 to 1, with better values close to 1). The Lo–Mendell–Rubin Test (LMR) and bootstrap likelihood ratio test (BLRT) were used to assess the P values in the comparisons among models with different numbers of classes [34]. A low P value indicated that the k-class model fit better than the k-1-class model [35]. To explore the differences between demographic characteristics and work-related information for the subtypes based on LPA, IBM SPSS Statistics version 25.0 was used (IBM Corp., Armonk, NY, USA). Nurses’ demographic characteristics and work-related information, including the mean, standard deviation, frequency, and percentage, were analyzed via descriptive statistics. Differences between categorical variables of the different subtypes of operating room nurses’ occupational fatigue were analyzed via the chi-square test (χ2) or Fisher’s exact probability. Furthermore, multinomial logistic regression analysis was performed to investigate the predictive factors in the groups. One-way ANOVA, the Student–Newman–Keuls (SNK) test, and the Kruskal–Wallis test were conducted to determine differences in the ACS scores in each latent profile. Statistical significance was identified at a two-tailed P value < 0.05.

Results

Characteristics of participants

A total of 422 operating room nurses participated in the study. After 36 ineligible questionnaires (e.g.,14 the same response to all questions and more than 10% of the items in 22 questionnaires were not completed), 386 valid questionnaires were analyzed with an effective recovery rate of 91.4%. Most of the participants were female (84.2%), 53.1% were younger than 31 ~ 40 years, and 77.2% of the participants were married. The majority of the participants (82.1%) held a university degree, 53.1% of nurses had intermediate titles, and 33.9% had more than 13 years of experience in the operating room. More details can be found in Table 1.

Table 1 Comparison of demographic and work-related characteristics between the three profiles by latent profile membership (n = 386)
Full size table

Latent profiles of occupational fatigue

To identify the best model, five models were estimated separately in this study. Table 2 displays the fit statistics of each model. As shown in Table 1, the entropy value of the 3-profile model was highest (0.934), and the AIC, BIC, and aBIC values continued to decrease and tended to stabilize after the 3-profile model. The LMR P values in the 4- and 5-profile models were not significant. Therefore, considering the proportion of each model and the practical significance of the results, we determined that the 3-profile model was the most appropriate model.

Table 2 Fit statistics of the latent profile analysis (n = 386)
Full size table

Table 3 shows the distribution of the three dimensions of occupational fatigue in the three-profile model, and Fig. 1 shows the scores of the three-profile model for the 15 items. Class 1 was the smallest group and accounted for 20.7% (n = 80) of all nurses. Operating room nurses in this class reported the lowest scores for chronic and acute fatigue but the highest score for intershift recovery. Therefore, this subgroup was labeled the “low-fatigue/high-recovery” group to indicate that operating room nurses in this group had a high tolerance for occupational fatigue and were able to recover from fatigue quickly, so their occupational fatigue was actually at a low level. Class 3 was the largest group and accounted for 50.0% (n = 193) of the participants. It was named the “moderate-fatigue/moderate-recovery” group to indicate that the nurses in this group had an average level of occupational fatigue. Finally, class 2 was the second largest group and accounted for 29.3% (n = 113) of the participants. Nurses in this group reported the highest scores for occupational fatigue. Moreover, the mean scores for the intershift recovery subdimension were lower than those in class 1 and class 3. Therefore, class 2 was named the “high-fatigue/low-recovery” group to indicate that operating room nurses in this group perceived severe fatigue and experienced a high level of occupational fatigue.

Table 3 Distribution of the three-profile model (n = 386)
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Fig. 1
figure 1

Latent profiles of occupational fatigue among operating room nurses. Note items (PL1-PL5) for the chronic fatigue dimension, items (PL6-PL10) for the acute fatigue dimension, and items (PL11-PL15) for the intershift recovery dimension

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Relationship between occupational fatigue and attentional control

Pearson correlation analysis was used to analyze the relationships among the three dimensions of occupational fatigue and attentional control. Table 4 presents the results of the Pearson correlation analysis, which revealed that chronic fatigue and acute fatigue were negatively associated with attentional control, whereas intershift recovery had a positive association with attentional control.

Table 4 Correlation analysis of 3 dimensions of occupational fatigue and attentional control
Full size table

Comparison of demographic and work-related variables across the three profiles

Table 1 presents the results of the comparison of demographic and work-related characteristics across the three profiles. Significant differences were found between the groups in terms of age, work experience, education level, professional title, employment status, marital status, monthly income and average monthly number of night shifts (all P < 0.05).

Predictor of latent profile membership

To identify the demographic and work-related variables that affect occupational fatigue in operating room nurses across different profiles, a multinomial logistic regression analysis was used with the class 1 group as the reference. Profile membership was the outcome variable, and the predictor variables included age, education level, professional title, employment status, marital status, monthly income, and monthly average number of night shifts.

Table 5 presents the results of the factors that influenced latent profile membership. All predictors are highlighted in bold. Age, work experience, educational level and monthly income affected profile membership. In terms of age and monthly income, nurses aged 31–40 years were more likely to be placed in class 2 than nurses aged ≥ 41 years. Nurses whose monthly income was ≤ 5000 or 5000–10,000 were more likely to belong to class 2 than those whose income was >10,000. In terms of work experience, nurses with < 13 years of operating room work experience tended to be placed in class 2 more than nurses with ≥ 13 years of work experience. Nurses who had more than 13 years of work experience were more likely to belong to class 1. Furthermore, operating room nurses with master’s degrees were more likely to be in class 2 than those with college- and university-level education. Nurses who had less than 3 years of work experience were more likely to be in class 3. However, there were no major differences between class 1 and class 2 or class 3 in terms of professional title, employment status, marital status, and monthly average number of night shifts.

Table 5 Multinomial logistic regression analysis of predictor of latent profile membership (n = 386)
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Attentional control and latent profile membership

Table 6 shows the results of differences in the two dimensions of attentional control for the three profiles. The mean attentional focus scores of operating room nurses in classes 1, 2, and 3 were 35.9 (SD = 4.07), 28.8 (SD = 5.51), and 32.01 (SD = 3.86), respectively. The mean attentional shift scores of operating room nurses in classes 1, 2, and 3 were 21.27 (SD = 5.45), 20.92 (SD = 4.44), and 21.40 (SD = 3.60), respectively. The scores for attentional focus differed significantly across the three subgroups (P < 0.001), but the scores for attentional shift across the three subgroups did not differ significantly (P = 0.623). In addition, the SNK test results showed that the mean score for class 1 was significantly higher than the mean scores for class 2 and class 3.

Table 6 Attentional control difference of three profiles (n = 386)
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Discussion

Total occupational fatigue status of operating room nurses

The findings revealed that operating room nurses exhibited a significantly higher level of occupational fatigue compared to their counterparts in general wards, with a mean total score of (61.04 ± 9.97). Based on the established scoring criteria, this score indicates a moderately high level of occupational fatigue severity within this professional group. The elevated occupational fatigue among operating room nurses may be associated with multiple contributing factors, including but not limited to the specialized nature of surgical procedures, the high-pressure work environment, and the substantial psychological demands inherent in their professional responsibilities. Firstly, Operating room nurses have irregular working hours [36]. Surgeries are complex and require high levels of concentration and adaptability. The frequency of surgeries is high, resulting in significant work intensity, prolonged standing, and little to no breaks [10]. Secondly, the operating room environment is enclosed, and nurses frequently face challenges such as noise and chemical exposure; in contrast, ward nurses encounter different issues [8, 9]. Thirdly, Operating room nurses have limited contact with patients and their families, leading to simple communication and a tendency for their work value to be overlooked, resulting in a low sense of job value [37]. In contrast, ward nurses spend more time with patients, which facilitates the establishment of trust [38], allows for a more intuitive appreciation of their work value, and garners greater understanding and support. Therefore, the occupational fatigue of operating room nurses deserves greater attention.

Potential profile of occupational fatigue in operating room nurses

This research aimed to analyze the differences in occupational fatigue among operating room nurses according to latent profiles. The findings of this research identified three distinct potential profiles of occupational fatigue for operating room nurses according to the score responses for each item, namely, “low-fatigue/high- recovery”, “high-fatigue/low-recovery” and “moderate-fatigue/moderate-recovery”. The findings suggest that occupational fatigue symptoms are heterogeneous among operating room nurses, similar to the findings of existing studies [39]. This categorization reflects the heterogeneity of occupational fatigue among operating room nurses in each latent profile. It complements previous studies that treat operating room nurses as a homogeneous whole and provides guidance for the development of targeted intervention measures to reduce nurses’ occupational fatigue.

The “low-fatigue/high-recovery” group consisted of 20.7% (n = 80) of the sample. The total mean score for occupational fatigue in this group was (48.66 ± 6.36). This population represents a small proportion of the study sample. Although occupational fatigue in this population is relatively low, it is present and should not be overlooked. Measures must be taken to prevent the escalation of fatigue levels in this group to more severe conditions. The low fatigue levels observed in this population may be attributed to their advanced age, robust family support, and strong self-regulation capabilities [40]. Understanding the reasons for these nurses’ rapid recovery from fatigue and the mechanisms involved (such as the effects of family support and self-regulation) can assist nurses in the other two groups who experience higher levels of fatigue. The “high-fatigue/low-recovery” group represented 29.3% (n = 113) of the sample. The total mean score for occupational fatigue in this group was (71.05 ± 6.54). The conditional probabilities of this group were greater for each factor, especially for the chronic and acute fatigue dimensions. Compared with the general population, this group of individuals exhibits significantly greater fatigue in relation to work, and their enthusiasm for work is nearly absent. Furthermore, nurses in the class 2 group exhibited significantly lower recovery rates from fatigue compared to the other two groups. It is advisable for nurses in this group to undergo timely psychological intervention to prevent the accumulation of negative emotions that could lead to the development of fatigue [41]. The “moderate-fatigue/moderate-recovery” group accounted for 50.0% (n = 193) of the sample with a total mean occupational fatigue score of (60.31 ± 5.86). This population exhibited moderate levels of both acute and chronic fatigue as well as a moderate capacity for recovery from fatigue. Their ability to recover from fatigue was well balanced with their occupational demands. More than three-quarters of the nurses fell into the class 2 and class 3 categories, suggesting that occupational fatigue among most operating room nurses in Chengdu is moderate to high with substantial potential for enhancement. To safeguard the stability of the nursing workforce, special attention should be given to these groups.

Analysis of factors that influence the latent profile of operating room nurses’ occupational fatigue

The demographic and work-related factors that influence profile membership include age, work experience, educational level and monthly income. In this study, nurses aged 31–40 were more likely to be assigned to the class 2 “high-fatigue/low-recovery” group than those older than 41 years, similar to the results of previous studies [32, 42]. This phenomenon may be attributed to the fact that operating room nurses within this age bracket constitute the optimal demographic for the workforce due to the demanding nature of their responsibilities and the physically taxing tasks they undertake. In terms of work experience, nurses with less than 13 years of work experience in the operating room also tended to be in the “high-fatigue and low- recovery” group. First, work experience significantly influenced the occupational fatigue of operating room nurses, consistent with the findings of previous research [32, 43]. Nurses with limited work experience predominantly serve as scrub nurses and expend more energy during surgical procedures than itinerant nurses do. Additionally, nurses with less experience often work longer hours and have shorter recovery periods between shifts. Due to their lack of experience, these nurses exhibit lower theoretical knowledge and emergency response capabilities, which may raise concerns about errors in intraoperative coordination. Consequently, they are likely to experience higher levels of occupational fatigue and to be classified as class 2. Moreover, nurses with a college education or below were more frequently observed in the “low- fatigue/high-recovery” group. Research has indicated that educational attainment is a significant predictor of occupational fatigue [44]. Operating room nurses with master’s degrees had lower scores for acute fatigue but higher scores for chronic fatigue [45]. Operating room nurses with master’s degrees, who often engage in management, research, and teaching, may experience heightened negative emotions and reduced work motivation due to their multifaceted responsibilities and stress, which may exacerbate chronic fatigue [22]. Hospitals typically regard master’s degree nurses as the core strength and future leaders of the nursing team. They are often assigned greater management and supervisory responsibilities, such as serving as nursing team leaders [46] or specialized nurses in management positions [47]. In these roles, they are responsible for overseeing and guiding the work of nurses within their teams, coordinating nursing resources, and ensuring the efficient and orderly execution of nursing tasks [48, 49]. Therefore, nurses with a master’s degree were more likely to be in the “high-fatigue/low-recovery” group. This study revealed that operating room nurses with lower monthly income were more likely to be classified into class 2, the “high-fatigue/low-recovery” group. The rationale for this phenomenon may be that as income increases, there is greater acknowledgement from the organization of the high level of effort exerted by these nurses. A fair income enables nurses to perceive that their contributions are recognized and rewarded [50], and the sense of satisfaction based on compensation and professional recognition also serves as a factor in alleviating occupational fatigue. Previous studies have demonstrated that addressing processing inefficiencies and enhancing personnel performance are effective strategies for mitigating fatigue [51].

Our study also revealed that the latent profile of operating room nurses’ occupational fatigue significantly influenced the attentional focus component of attentional control. This finding aligns with the results of previous research [23]. Operating room nurses who exhibit “low-fatigue/high-recovery” demonstrate superior attentional focus, whereas those in the “moderate-fatigue/moderate-recovery” and “high-fatigue/low- recovery” groups exhibit diminished attentional focus. This may be because operating room nurses who experience “low-fatigue/high-recovery” have more energy to consider the importance and meticulousness of surgical procedures. Research has demonstrated that individuals who experience chronic occupational fatigue frequently report challenges with concentration [52]. When operating room nurses experience fatigue, they might perceive their job as a series of tasks to be accomplished rather than carefully considering individual patients’ unique situations and their non-task needs during an operation [53]. Fatigued operating room nurses may encounter challenges in maintaining professional communication and may exhibit negative emotional responses. They may struggle to maintain a focus on their tasks. The unique demands of operating room work require nurses to invest significant energy to meet the requirements of surgical procedures. Given the rapid advancements in surgical techniques, nursing managers should prioritize addressing the issue of high occupational fatigue. Efforts should be made to mitigate fatigue in the context of consistently high-tension and high-intensity work environments to foster a shift toward a future in which nurses experience low fatigue and high recovery.

Limitations

This research has several limitations. First, we used convenience sampling; thus, the representativeness of the sample and the generalizability of the study findings may have some limitations. Varied and stratified samples should be provided in further studies. An online questionnaire was used to recruit some of the participants and collect part of the data. The number of questionnaires distributed and the differences between nurses who participated and those who refused to participate are unknown. However, our research team conducted offline data collection as much as possible and collected online data as a supplement, and quality control was strictly maintained to maximize the scientific validity and credibility of the data. Second, the use of self-reported measures to assess occupational fatigue might have led to possible bias. Furthermore, we used attentional control to assess operating room nurses’ gathering and shifting of control. Although the ACS-C has been verified with other samples, it requires further verification in relation to the language and environment of hospital nurses. Third, this was a cross-sectional study, so the results of this research cannot be used to identify causality. Therefore, a causal relationship between operating room nurses’ occupational fatigue and attentional control cannot be determined. Further longitudinal studies are needed to track the trajectory of operating room nurses’ occupational fatigue over time.

Conclusion

This research used LPA to innovatively identify the subgroup characteristics and predictors of operating room nurses’ occupational fatigue. We identified three obvious profiles of occupational fatigue among nurses with occupational fatigue: “low-fatigue/high-recovery”, “high-fatigue/low-recovery”, and “moderate- fatigue/moderate-recovery”. Furthermore, we discussed the role advantages of nurses in the “low-fatigue/high-recovery” group and revealed potential predictors of profile membership, including age, work experience, educational level and monthly income. This study contributes to the literature by suggesting that nursing administrators can design targeted interventions and specific training programs in relation to the heterogeneity of operating room nurses’ occupational fatigue. For example, nursing administrators can select nurses who are suitable for operating room positions on the basis of demographic and work-related characteristics. Furthermore, administrators can provide targeted incentives and psychological empowerment, such as peer support, and increase salaries for operating room nurses on the basis of the characteristics and needs of each subgroup, which may reduce nurses’ occupational fatigue. Reducing occupational fatigue can also affect the attentional focus aspect of nurses’ attentional control. In other words, reducing occupational fatigue is crucial to allow nurses to meet the demands of the hospital operating room and to improve their attentional focus. These approaches can improve the overall service quality of the hospital.

Data availability

The data supporting the conclusions of this research will be made available from the corresponding authors upon reasonable request.

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Acknowledgements

The authors gratefully thank everyone on the research team and all the nurses who took part in the study.

Funding

Supported by Sichuan Science and Technology Program Number 2023YFS0067.

Author information

Author notes

  1. Jiao Zhai and Shuangying Gong contributed equally to this work.

Authors and Affiliations

  1. Department of Pediatric Surgery, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Jiao Zhai

  2. School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Shuangying Gong

  3. Department of Cancer Center, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Feng Chen

  4. Department of Nursing, PengZhou People’s Hospital, Chengdu, Sichuan Province, China

    Ping Zheng

  5. Department of Anesthesia Surgery Center, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Wanlin Liu

  6. Nursing Department, The Second People’s Hospital of Yibin, Yibin, Sichuan Province, China

    Xiaoxia Dai

  7. Department of Nursing, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China

    Caixia Xie

Authors
  1. Jiao Zhai
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  2. Shuangying Gong
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  3. Feng Chen
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  5. Wanlin Liu
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  7. Caixia Xie
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Contributions

J.Z and S.G designed the study. S.G, X.D, W.L collected the data. J.Z, F.C and P.Z contributed to data analysis. J.Z and S.G produced the original draft. C.X took responsibility for revising the manuscript. All authors contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Caixia Xie.

Ethics declarations

Ethics approval and consent to participate

This research was approved by the Medical Ethics Committee of Sichuan Provincial People’s Hospital (approval no. 2024 − 197). All methods were carried out in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants. To protect the participants’ privacy, all the collected data were preserved anonymously and confidentially.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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Zhai, J., Gong, S., Chen, F. et al. Latent profile analysis of operating room nurses’ occupational fatigue and its relationship with attentional control. BMC Nurs 24, 310 (2025). https://doi.org/10.1186/s12912-025-02931-2

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BMC Nursing

ISSN: 1472-6955

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