Introduction
The World Health Organization (WHO) emphasizes that “protecting the health and safety of healthcare workers contributes to improving their productivity, job satisfaction, and retention rates,” calling on all countries to “take necessary measures to safeguard and protect healthcare personnel at all levels“ [1]. The “Global Patient Safety Action Plan 2021–2030” also prioritizes healthcare worker safety actions as a key component of patient safety [2]. It is recognized that the hospital work environment can profoundly impact both nurses’ safety behaviors and patient safety [3]. Evidence showed that a favorable work environment enhances nursing safety and patient satisfaction while alleviating nurse stress and emotional fatigue [4‐6]. Conversely, suboptimal work environments can compromise nurses’ physical and mental well-being, decreasing job satisfaction, diminishing nursing quality, and increasing turnover rates [7‐9]. Given the unique demands of the ICU work environment, nurses are subjected to high-intensity workloads and extended shifts [10], resulting in adverse physical and mental health outcomes [11, 12], reduced work engagement [13, 14], and impaired clinical decision-making ability, and lead to the decline of nursing quality [15, 16]. Moreover, the rotating shift patterns in the ICU disrupt circadian rhythms, negatively impacting sleep quality and increasing nurses’ burnout during working time [17], particularly during night shifts, which escalates patient safety risks [18].
The job demands-resources (JD-R) model [19] is a theoretical framework that examines the relationship between job characteristics and occupational health, focusing on the impact of job demands and resources in the work environment on individuals [20]. According to the JD-R model, every occupation has specific factors that influence job performance, which can be categorized into two main components: job demands and resources [20]. It is believed that balancing job demands and resources is crucial for reducing work stress and fostering work motivation, thus enhancing job performance [21]. On the other hand, the JD-R model suggests that job resources can lead to higher levels of social support, which in turn positively influences the enhancement of individual resources among employees [22]; these individual resources can also empower individuals with the motivation and ability to control and influence their work environment, thereby producing better work outcomes [23, 24]. In studies focused on nurses’ job performance, two variables—self-resilience and self-efficacy—are commonly involved, as they are shown to alleviate symptoms of depression [25], reduce burnout and anxiety [26, 27], increase job engagement [28], and help achieve work goals [24]. When individuals enhance these personal resources, their well-being and job performance can improve [29]. Many studies have explored the relationship among job demands, job resources, and individual resources of nurses and their perceived workload or work stress [30, 31]; however, the impact of acute fatigue on alertness needs to be further explored.
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Currently, shift work schedules in global healthcare institutions vary, primarily consisting of 8-hour- and 12-hour shifts. The 8-hour shift pattern involves frequent personnel rotations, which can somewhat alleviate nurse shortages [32]. However, this scheduling pattern can exacerbate the difficulty for nurses in adapting to shift work and increase their experience of job burnout [33, 34]. ICU nurses in many Chinese hospitals work on a 12-hour night shift. Although this scheduling pattern reduces the frequency of shifts, it also increases nurses’ workload and continuous standby time [35, 36]. The study reported an even higher (68.3%) level of burnout among 1289 ICU nurses, where working in general ICU, more years of experience, working night shifts, and personal comorbidities were associated with higher burnout [37]. Thus, it is imperative to conduct research based on the specific work environment and demands, using a combination of subjective and objective measurements to thoroughly explore the impact of job demands and resources on nurses’ alertness. The Psychomotor Vigilance Task (PVT) is a commonly used tool to assess alertness levels by measuring reaction time and sustained attention [38], serving as the most widely used objective measure of alertness [39, 40]. Previous studies have utilized this tool to measure nurses’ alertness during shifts, with longer reaction times indicating lower alertness level [41, 42] and night-shift nurses exhibiting longer reaction times than day-shift nurses [41]. Furthermore, the likelihood of medication errors during night shifts was three times higher than during day shifts (AOR = 3.1) [43]. Hence, maintaining a high level of alertness during night shifts is crucial to ensuring patient safety and the quality of nursing.
This study describes the objective status of night-shift alertness among ICU shift nurses in China. Based on the JD-R model, it explores the effect of ICU job demands, job resources and personal resources on night-shift alertness. The result will enable organizations and managers to implement targeted interventions, form supportive work environments, decrease night-shift acute fatigue among ICU shift nurses, and improve nursing performance.
Theoretical basis
Based on the JD-R model proposed by Bakker and Demerouti in 2001 (Fig. 1) [44], job demands and resources are two major categories of job characteristics. Job demands (such as quantitative demands, emotional demands, work-family conflict, etc.) refer to the objective physical, psychological, social, or organizational requirements present in the job, requiring sustained physical and/or mental effort to accomplish tasks and meet specific standards [45]. These demands are objectively present in every workplace. They are not inherently negative, but if they exceed employees’ coping ability, they can become sources of strain, leading to excessive psychological burden and eventually resulting in employee exhaustion [46], triggering the process of health impairment [44].
Job resources (including colleague support, team collaboration, development opportunities, etc.) refer to factors in the workplace that support individuals in completing tasks, providing a sense of achievement and satisfaction [44]. These resources contribute to individuals effectively coping with job demands, enhancing job satisfaction and overall well-being [45], and promoting the process of health motivation [44]. Adequate job resources can buffer the impact of job demands on stress, particularly when facing high job demands, emphasizing the crucial role of job resources in individual motivation. Like job resources, personal resources are considered positive responses to job demands in the JD-R model, contributing to maintaining individuals’ workability and motivation, ultimately influencing job performance.
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Based on the above statements and previous studies, this study proposes the following hypotheses:
Hypothesis 1
There exists a correlation among the job demands, job resources, and personal resources of ICU shift nurses.
Hypothesis 2
Job demands, job resources, and personal resources can influence ICU shift nurses’ strain and/or motivation, thereby affecting their job performance (night-shift alertness).
Fig. 1
The Job demands-resources model designed by Bakker & Demerouti [44]
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Methods
Study design and participants
This study was a descriptive cross-sectional survey. Using the “semTools” package in R to calculate the required sample size for the Root Mean Square Error of Approximation (RMSEA) of the structural equation model, with the model’s degrees of freedom (df) set to 10, the expected RMSEA value at 0.05, a significance level (α) of 0.05, and a power of 0.80, the required sample size was determined to be 203. The study was conducted from July to September 2022, involving 291 ICU nurses from a hospital in Beijing, China. The duration of the shift was 12 h. Each nurse was responsible for 2 to 3 patients in the ICU where the study participants worked. These patients were primarily suffering from respiratory and circulatory disorders and required life support from external devices. The inclusion criterion was Registered Nurses (RN) providing direct patient care in the ICU and participation in clinical shifts, with at least 3-night shifts during the survey month. RNs with pregnancy and a history of mental illness were excluded. Institutional review board approval was obtained for the study (No. 2022030). Informed consent was obtained from all participants before their participation.
Measurements
Sociodemographic characteristics
Sociodemographic characteristics included participants’ age, gender, educational level, marital status, number of children, and whether they had sleep problems.
Job demands
The Copenhagen Psychosocial Questionnaire (COPSOQ) II-short version [47] was utilized in this study as a 40-item Likert-type scale to evaluate the psychosocial work environment and personal health. In this study, the job demands were measured using quantitative demands, emotional demands, and work-family conflict in the COPSOQ. The intensity or frequency of each question was measured on a score range of 0 to 100. Higher scores indicated higher levels of measured dimensions. The Cronbach’s α of the COPSOQ was 0.83, and the job demands dimension was 0.84.
Job resources
The job resources of ICU shift nurses were measured using six dimensions of the COPSOQ: support from supervisors, support from colleagues, commitment to the workplace, job recognition, trust, and justice of the COPSOQ. The Likert 5-level scoring method is adopted, and the score is the average score of the item, with a total score of 100. Higher scores indicated higher levels of measured dimensions; Cronbach’s α of this dimension is 0.78.
Motivation
The motivation of ICU shift nurses was measured using two dimensions of the COPSOQ: role clarity and job satisfaction. Role Clarity was assessed using a 5-point Likert scale, while Job Satisfaction was assessed using a 4-point Likert scale, with a total score of 100 points. Higher scores indicate higher levels of the dimensions being measured; Cronbach’s α coefficient of this dimension is 0.81.
Strain
The strain of ICU shift nurses was measured using two COPSOQ dimensions: burnout and stress. And the Likert 5-level score was used, with a total score of 100. Higher scores indicated higher levels of dimensions measured. Cronbach’s α coefficient of this dimension is 0.75.
Personal resources
The Self-resilience scale, developed by Block and Kremen [48] in 1996, was utilized to assess the self-resilience level of night-shift nurses. Comprising 14 items rated on a 4-point Likert scale, with total scores ranging from 14 to 56, higher scores indicate higher levels of self-resilience. The Cronbach’s α of this scale was 0.83.
Additionally, the General Self-Efficacy Scale (GSES), developed by Schwarzer et al. [49], was employed to measure the self-efficacy of night-shift nurses. Consisting of 10 items, each rated on a 4-point Likert scale ranging from “completely incorrect” to “completely correct” (scores 1 to 4), with total scores ranging from 10 to 40; higher scores indicate higher levels of self-efficacy. The Cronbach’s α of the GSES was 0.83.
Alertness
The objective alertness level of ICU night-shift nurses is represented using reaction time. Reaction time refers to the time interval from stimulus presentation to the physical response, indicating the gap between stimulus and reaction [50]. This study measured reaction time using the Psychomotor Vigilance Task (PVT-192), widely utilized as a behavioral alertness measure [40, 51]. The PVT task lasted 5 min, recorded in milliseconds (ms), ranging from 100 to 1000 ms. Data exceeding 600 ms, anticipation, and false touches (i.e., pressing the button without the screen displaying the number) were deemed erroneous. The participants were drawn from ICU units that follow a rotating shift pattern: day shift (day 1) − 12-hour night shift (day 2) - post-night shift (day 3) - rest day (day 4) - day shift (day 5) - day shift (day 6) - rest day (day 7). Reaction time was measured during the night shift on day 2, 30 min before the start of the shift, to facilitate the implementation of measures aimed at increasing the night-shift alertness level of ICU shift nurses.
Procedures
This study used electronic surveys and on-site measurements for data collection. Before the survey, eligible shift nurses within each department were provided with standardized instructions detailing the survey’s objectives, cooperation requirements, and relevant considerations. Voluntary informed consent was obtained from participants before their enrollment. Electronic questionnaire links were then disseminated via WeChat, a popular Chinese social media platform. Participants were required to complete all questionnaire items before submission. On-site PVT measurements were conducted within the departments, with two researchers assigned to provide face-to-face guidance. They addressed any questions participants encountered during the questionnaire completion process and offered hands-on assistance with the PVT tasks. Both researchers underwent standardized training before the survey to ensure consistency and reliability.
Data analysis
We conducted data analysis using SPSS 26.0 and Mplus 8.3. Descriptive statistics were used for all variables. Frequency and percentage were employed to describe categorical data. At the same time, mean ± standard deviation (SD) was used for normally distributed continuous data, and median (upper and lower quartiles) [M(P25, P75)] was used for non-normally distributed continuous data. Single-factor analysis utilized t-tests and analysis of variance (ANOVA). Correlation analysis employed the Spearman method.
In our model, job demands, job resources, personal resources, motivation, and strain were treated as latent variables, while reaction time served as the manifest variable. Due to the skewed distribution of reaction time, the generally weighted least squares (GWLS) method was used to estimate the model accurately [52]. Model fit was assessed using chi-square (χ2), degree of freedom (df), χ2/df, Comparative Fit Index (CFI), Tucker–Lewis Index (TLI), Standardized Root Mean Square Residual (SRMR), and Root Mean Square Error of Approximation (RMSEA). Criteria for good model fit were set as CFI and TLI > 0.90, χ2/df < 3.0, SRMR < 0.05, and RMSEA < 0.08.
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Results
Descriptive of the study participants and the variables
The study included 291 ICU shift nurses with an average age of 29.80 years (SD = 4.84). The majority were female (89.7%), married (56.0%), without children (56.7%), and held a bachelor’s degree or higher (73.5%). 52.6% had subjective sleep problems. The average length of work experience was 7.88 years (SD = 5.07). Results of the single-factor analysis indicated no statistically significant differences in reaction time among shift nurses of different personal characteristics (P > 0.05), as shown in Table 1.
Table 1
Characteristics and univariate analysis of the study participants (n = 291)
Variable | N(%) | RT [M(P25, P75), ms] | Z/χ2 | P |
|---|---|---|---|---|
Gender | -0.107 | 0.915 | ||
Male | 30(10.3) | 254.00(219.38,283.50) | ||
Female | 261(89.7) | 251.00(232.50,268.50) | ||
Age (years) | 0.8501) | 0.654 | ||
< 25 | 33(11.3) | 253.00(233.75,268.00) | ||
25 ~ 35 | 215(73.9) | 250.50(230.00,268.50) | ||
> 35 | 43(14.8) | 249.50(234.00,283.00) | ||
Marriage | -0.414 | 0.679 | ||
Married | 163(56.0) | 250.00(232.50,267.50) | ||
Single | 128(44.0) | 252.50(231.25,271.75) | ||
Number of children | 1.0591) | 0.589 | ||
0 | 165(56.7) | 252.00(232.50,269.50) | ||
1 | 105(36.1) | 249.00(228.50,267.00) | ||
2 | 21(7.2) | 255.50(233.75,284.00) | ||
Education | -1.670 | 0.095 | ||
Diploma | 77(26.5) | 255.00(232.25,282.50) | ||
Bachelor and above | 214(73.5) | 248.50(231.88,267.63) | ||
Work years | 1.1961) | 0.550 | ||
< 6 | 107(36.8) | 252.50(232.50,269.00) | ||
6 ~ 15 | 150(51.5) | 250.00(228.88,268.88) | ||
> 15 | 34(11.7) | 250.50(235.38,283.50) | ||
Sleep problem | -0.788 | 0.431 | ||
Yes | 153(52.6) | 249.50(228.50,270.00) | ||
No | 138(47.4) | 252.00(235.00,269.25) | ||
The median reaction time was 251.0 ms. Scores for job demands, job resources, and personal resources are shown in the table below. The level of quantitative demands (median = 25.00) was lower than that of emotional demands (median = 37.50) and work-family conflict (median = 33.30). Scores for job resources dimensions were generally high, with average scores of trust, justice, and support from colleagues exceeding 80. Detailed information is presented in Table 2.
Table 2
Characteristics of the measured variables in ICU shift nurse (n = 291)
Variable | Min ~ Max | Mean±SD/ Median(P25,P75) |
|---|---|---|
Job demands | ||
Quantitative demands | 0 ~ 75 | 25.00(12.50, 25.00) |
Emotional demands | 0 ~ 100 | 37.50(25.00, 50.00) |
Work-family conflict | 0 ~ 100 | 33.30(16.65, 49.95) |
Job resources | ||
Support from supervisors | 0 ~ 100 | 79.21 ± 21.51 |
Support from colleague | 25 ~ 100 | 81.92 ± 16.67 |
Commitment to the workplace | 12.50 ~ 100 | 73.63 ± 22.08 |
Job recognition | 0 ~ 100 | 75.00(62.50, 87.50) |
Trust | 12.5 ~ 100 | 84.62 ± 16.96 |
Justice | 0 ~ 100 | 83.20 ± 17.52 |
Personal resources | ||
Self-resilience | 21 ~ 56 | 39.89 ± 7.88 |
Self-efficacy | 12 ~ 40 | 27.43 ± 5.80 |
Motivation | ||
Role clarity | 25 ~ 100 | 81.66 ± 16.55 |
Job satisfaction | 33.3 ~ 100 | 72.23 ± 16.48 |
Strain | ||
Burnout | 0 ~ 100 | 50(25, 62.5) |
Stress | 0 ~ 100 | 50(37.5, 62.5) |
Reaction time (ms) | 193.5 ~ 515.0 | 251.0(232.0, 269.0) |
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Correlation analysis
The correlation analysis of job demands, job resources, personal resources, motivation, strain, and reaction time of ICU shift nurses are presented in Table 3. Job demands, job resources, personal resources, motivation, and strain dimensions were all correlated. However, reaction time was only negatively correlated with support from colleagues (r=-0.132, P = 0.025) and job recognition (r=-0.119, P = 0.043).
Table 3
Correlation analysis result (n = 291, r value)
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Job demands | ||||||||||||||||
1. Quantitative demands | 1 | |||||||||||||||
2. Emotional demands | 0.311** | 1 | ||||||||||||||
3. Work-family conflict | 0.218** | 0.503** | 1 | |||||||||||||
Job resources | ||||||||||||||||
4. Support from supervisors | − 0.192** | − 0.263* | − 0.270** | 1 | ||||||||||||
5. Support from colleague | − 0.166** | − 0.203** | − 0.260** | 0.604** | 1 | |||||||||||
6. Commitment to the workplace | − 0.292** | − 0.319** | − 0.372** | 0.493** | 0.411** | 1 | ||||||||||
7. Job recognition | − 0.229** | − 0.256** | − 0.218** | 0.632** | 0.484** | 0.545** | 1 | |||||||||
8. Trust | − 0.233** | − 0.346** | − 0.247** | 0.606** | 0.402** | 0.506** | 0.558** | 1 | ||||||||
9. Justice | − 0.263** | − 0.365** | − 0.293** | 0.590** | 0.502** | 0.520** | 0.583** | 0.735** | 1 | |||||||
Motivation | ||||||||||||||||
10. Role clarity | − 0.263** | − 0.217** | − 0.219** | 0.431** | 0.463** | 0.509** | 0.572** | 0.543** | 0.508** | 1 | ||||||
11. Job satisfaction | − 0.258** | − 0.333** | − 0.363** | 0.440** | 0.423** | 0.480** | 0.480** | 0.372** | 0.477** | 0.432** | 1 | |||||
strain | ||||||||||||||||
12. Burnout | 0.341** | 0.460** | 0.573** | − 0.212** | − 0.111 | − 0.335** | − 0.232** | − 0.230** | − 0.277** | − 0.193** | − 0.339** | 1 | ||||
13. Stress | 0.275** | 0.493** | 0.622** | − 0.253** | − 0.177** | − 0.328** | − 0.204** | − 0.253** | − 0.336** | − 0.159** | − 0.408** | 0.798** | 1 | |||
Personal resources | ||||||||||||||||
14. Self-resilience | − 0.323** | − 0.258** | − 0.247** | 0.292** | 0.326** | 0.277** | 0.393** | 0.372** | 0.389** | 0.348** | 0.278** | − 0.318** | − 0.246** | 1 | ||
15. Self-efficacy | − 0.328** | − 0.213** | − 0.199** | 0.311** | 0.312** | 0.311** | 0.371** | 0.307** | 0.315** | 0.314** | 0.278** | − 0.294** | − 0.255** | 0.647** | 1 | |
Reaction time | 0.050 | 0.106 | − 0.008 | 0.050 | − 0.132* | 0.068 | − 0.119* | 0.012 | 0.079 | 0.089 | 0.068 | 0.036 | 0.054 | − 0.043 | − 0.032 | |
The path model
Based on the JD-R model, a hypothetical model was constructed using Mplus 8.3, and the model was adjusted and fitted based on modification indices and specific circumstances, as shown in Table 4; Fig. 2.
The result indicated a negative correlation between job demands and job resources among ICU shift nurses (r=-0.570, P < 0.001), as well as a positive correlation between job resources and personal resources (r = 0.554, P < 0.001). Job demands were found to increase strain (β = 0.955, P < 0.001), while job resources can decrease ICU shift nurses’ strain (β=-0.477, P = 0.047). Furthermore, enhancing motivation (β = 0.874, P < 0.001) was observed to shorten reaction time (β=-0.148, P = 0.044) and increase night-shift alertness among ICU shift nurses. The model fitting indexes were χ2/df = 2.736, CFI = 0.923, TLI = 0.901, SRMR = 0.047, RMSEA = 0.077, indicating that this model fit well.
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Table 4
Model path relationship analysis results
Model | B | SE | CR | P | β | ||
|---|---|---|---|---|---|---|---|
Job demands | <---> | Job resources | -54.494 | 12.083 | -4.510 | 0.000 | -0.557 |
Job demands | <---> | Personal resources | -13.406 | 3.392 | -3.952 | 0.000 | -0.462 |
Job resources | <---> | Personal resources | 37.011 | 6.186 | 5.983 | 0.000 | 0.554 |
Strain | <--- | Job demands | 2.859 | 0.484 | 5.911 | 0.000 | 0.955 |
Strain | <--- | Job resources | -0.230 | 0.116 | 1.990 | 0.047 | -0.477 |
Motivation | <--- | Job resources | 0.658 | 0.092 | 7.177 | 0.000 | 0.874 |
Reaction Time | <--- | Motivation | -0.471 | 0.233 | 2.019 | 0.044 | -0.148 |
Fig. 2
Structural equation model with standardized path coefficients. Job demands can increase strain, and job resources can decrease strain and enhance motivation, which can shorten reaction time. **: P < 0.01; *:P < 0.05
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Discussion
This study aims to investigate the objective status of night-shift alertness among ICU shift nurses and develop a path model based on the JD-R model to explore the impact of job demands, job resources, and personal resources on night-shift alertness. The model demonstrates a negative relationship between job demands and both job resources and personal resources, while a positive relationship exists between job resources and personal resources (Hypothesis 1). Furthermore, it is concluded that job resources can reduce reaction time by enhancing motivation, thereby increasing night-shift alertness among ICU shift nurses (Hypothesis 2).
ICU shift nurses exhibited moderate night-shift alertness, with a relatively balanced alignment between job demands and resources
In this study, the nurse-patient ratio was 1:2 ~ 3. This ratio is slightly lower than the 1:2 ratio commonly found in the United States [53], but higher than the 1:1 ratio reported in Australia [54]. Under the condition of consistent staffing level, the median reaction time of ICU shift nurses before night shifts was 251.0 ms, which is consistent with the results of Ruggiero (participants were American female shift nurses) [27] but shorter than that reported by Liu (median = 288.44 ms) [41]. Liu’s study, also conducted in China, utilized PVT to assess the reaction time levels of 118 ICU nurses before and after day and night shifts and explored their influenced factors. Results indicated that factors influencing pre-night shift reaction time included gender, number of children, years of work experience, and caffeine intake. However, in our study, Table 1 demonstrates that demographic factors such as gender and number of children did not significantly impact night-shift reaction time. This discrepancy is primarily attributed to differences in work environments. Nurses’ performance is significantly influenced by the work environment [6], and in our study, the reaction time reflecting the alertness of ICU shift nurses was not influenced by individual characteristics like gender. This suggests that other factors in the work environment may play a role. Liu’s study did not explore factors of the ICU work environment, which our study aims to supplement. Furthermore, the existence of sleep problems among ICU shift nurses also had no statistical significance on the difference in night-shift alertness, which may be related to differences in the amount and/or timing of sleep before or between night shifts rather than circadian rhythm [55, 56], indicating that ICU nurses may have other adaptive mechanisms may be established to maintain the stability of night-shift alertness even if they have sleep problems.
In this study, the level of job demands and resources among ICU shift nurses was relatively balanced. Within job demands, emotional demands and work-family conflict scores were higher than quantitative demands. This suggested that the core issues within the ICU shift nurses may not lay solely within the job tasks themselves but rather focused more on emotional labor and work-family balance. This placed greater demands on nurses’ emotional investment, potentially leading to psychological burdens and fatigue [57]. The level of job resources among ICU shift nurses was generally high [42], with the colleague support score being the highest. This was consistent with the features of nursing work. Medical care tasks require close teamwork, mutual assistance, and support among colleagues, contributing to holistic patient care and enhancing nursing quality [56]. They are directly associated with reduced occupational burnout and the fostering of positive work relationships [58].
In this study, ICU shift nurses demonstrated higher scores in self-resilience and self-efficacy compared to the average scores of the scales, indicating their confidence in effectively coping with work tasks and their strong ability to recover and adapt when facing work pressure and challenges [59]. This is also related to the fact that the study subjects are ICU nurses who often need strong psychological adjustment and coping skills to handle high-intensity work environments and unexpected situations [60, 61].
The relationship between job demands, job resources, and personal resources is consistent with the JD-R model
The results (Table 4; Fig. 2) demonstrated a significant negative correlation between job demands and both job resources and personal resources, consistent with the JD-R model [46]. On the one hand, the limited availability of both job and personal resources can intensify the perceived pressure of job demands among nurses; on the other hand, it may lead to competition and conflict among nurses for resources, exacerbating the bad effects of job demands [31]. This calls for managerial intervention to improve the work environment, optimize job resources, and simultaneously enhance nurses’ personal resources, fostering a balanced work ecosystem to alleviate the adverse effects of job demands among ICU shift nurses.
In the framework of the JD-R model, there are multifaceted positive relationships between job and personal resources [62]. Firstly, by providing support and protective mechanisms, job resources can mitigate the negative impact of job demands faced by individuals [63]. Secondly, job resources can foster individual professional development and growth by offering training and developmental opportunities; they enhance individuals’ professional competence, thereby bolstering their confidence and capability to tackle various work challenges [24]. Moreover, job resources play a crucial role in establishing social support networks. Positive colleague relationships and support contribute to heightened perceived levels of social support, facilitating individuals’ resilience in coping with stress and adversity [22].
Furthermore, social support serves as a significant source of self-efficacy. Encouragement and support from colleagues instill greater belief in individuals’ ability to accomplish tasks [22, 64]. Additionally, a strong sense of job cognition and a fair, trusted work environment can cultivate a positive psychological atmosphere, enhancing individuals’ emotional and mental well-being and reducing emotional fatigue [65, 66]. These factors collectively create favorable conditions for the utilization of personal resources.
Effects on night-shift alertness
The model (Fig. 2) illustrated that adequate job resources positively impacted motivation, while a high level of motivation can increase the night-shift alertness of ICU shift nurses. As described above, sufficient job resources can support and assist nurses to engage more actively in their work. When nurses feel more motivated at work, they are inclined to focus on tasks, value work quality more, and thus maintain high alertness and attention [45]. Nursing managers should ensure ample job resources, emphasize the motivation level of ICU shift nurses, and foster a supportive team atmosphere. Regular evaluation of nurses’ job performance should also be conducted to identify and address issues promptly.
The model (Fig. 2) also indicated that the job demands of ICU shift nurses can increase their strain, while job resources can reduce strain. A complex and high-intensity work environment with elevated job demands can induce pressure on nurses. Yet, in the presence of adequate support, training, and resources, ICU shift nurses are better equipped to manage work pressure [31, 67]. Notably, we did not observe a significant impact of strain on night-shift reaction time. Possible reasons for this could be twofold: (1) Sample characteristics: Model outcomes are influenced by the characteristics of the study sample [68]. Due to their cultivated professional skills and experience in high-pressure work environments, ICU shift nurses may manage work stress effectively through adaptive strategies or self-regulation mechanisms [69]. Thus, even when experiencing some pressure, it may not significantly affect their alertness. (2) “Supernurse” Culture: Henshall et al. [70] found a “supernurse” phenomenon in the professional culture of nursing. This includes enduring hardship, being willing to sacrifice, having a strong sense of responsibility, and believing in self-sacrifice for the greater good. This culture compels nurses to overcome strain and maintain alertness in their work, even when facing significant stress. (3) Interventions by other factors: In this model, the strain may have been influenced by other unaccounted factors, resulting in its lack of impact on night-shift reaction time. Future research should explore the relationship between individual psychological characteristics and job performance in high-pressure work environments.
Our study did not observe a significant impact of personal resources on strain, motivation, and night-shift alertness among ICU shift nurses. This suggested that the role of personal resources in the ICU nurses may not be as significant as expected. The ICU work environment is exceptionally complex, involving high-intensity nursing tasks and unpredictable medical situations [10]. In such work environments, the effect of personal resources may be interfered with or weakened by other factors, such as the suddenness and urgency of job demands. Additionally, teamwork and organizational support are more critical in the ICU environment than personal resources [71]. Nurses rely more on teamwork and leadership support to cope with work pressure, while the role of personal resources is relatively minor. However, this may also be related to our study’s dimension selection limitations and sample size. Nonetheless, this does not imply that nurses’ personal resources are entirely ineffective. Previous studies have shown that high levels of personal resources lead nurses to take a more positive view of the work environment, proactively optimize job demands, adjust their perception levels of job resources [72, 73], alleviate fatigue, stress, and other adverse effects of work, and are associated with higher job satisfaction, work performance, and lower absenteeism rates [74].
Applicability of the JD-R model in ICU shift nurses
Based on the above results, it appeared that there are some discrepancies with the traditional JD-R model assumptions, which may impact its applicability within this specific cohort: (1) Insignificant influence of personal resources: In the JD-R model, personal resources are typically presumed to affect strain and motivation positively. However, within the ICU shift nurses, personal resources were not observed to affect strain, motivation, or night-shift alertness significantly. This suggests that the role of personal resources may not be as pronounced in this cohort as anticipated, or other factors may be at play. (2) Influence of other factors: Besides the factors considered in the JD-R model, such as job demands, job resources, personal resources, motivation, and strain, there may be additional factors influencing the job performance of ICU shift nurses. Factors such as specific work environment, teamwork atmosphere, and complexity of job tasks might have a greater impact on their job performance. (3) Necessity for model revision: Based on our findings, Hypotheses 1 and 2 are supported in the context of ICU shift nurses. There is a significant correlation among job demands, job resources, and personal resources. Additionally, these factors influence strain and motivation, subsequently affecting night-shift alertness. However, our study’s model diverges from the JD-R model. To enhance the model’s explanatory power and applicability, we recommend appropriate adjustments to the JD-R model to capture better ICU shift nurses’ unique work characteristics and influencing factors.
In summary, while the JD-R model provides a useful framework for understanding the relationship between work strain, motivation, and job performance, its applicability may be subject to certain limitations within specific groups. When applying the JD-R model to ICU shift nurses, careful consideration should be given to the validity of the model’s assumptions, and modifications and adjustments should be made based on the specific circumstances to accommodate this group’s characteristics better.
Limitations
While our research has made strides in uncovering key factors in ICU nursing work, there are still limitations to consider. For instance, our study focused solely on ICU shift nurses at a single location. In the selection and competence of ICU nurses, there is a certain degree of selection and survivorship bias. ICU nurses typically need to possess specific skills and qualities. This means that our study sample may not fully represent the entire nursing population, as the results are skewed toward those nurses who can endure the long-term pressures of ICU work. To mitigate these effects, we recommend that future research employ broader recruitment strategies, including different types of nursing personnel. This would enhance the diversity and representativeness of the sample, providing a more comprehensive perspective.
Furthermore, the job demands, resources, motivations, strains, and personal resources in nursing are multifaceted. Our study only classified them based on the JD-R model and the COPSOQ, which is not exhaustive. Future research could consider incorporating additional physiological and psychological measurement tools to assess nursing work factors from multiple perspectives, thereby providing a more comprehensive evaluation of the impact of the nursing work environment on nursing professionals. Additionally, future research and practice should focus on the effects of cultural factors on nurse performance and implement measures to change the work environment and culture. This would help alleviate nurse burnout and enhance job satisfaction and efficiency.
Conclusion
This study demonstrated that the JD-R model exhibits a certain degree of adaptability among ICU shift nurses. High job demands positively influence strain, while job resources buffer against strain, alleviating nurse strain with provided support. Job resources positively impact motivation, increasing alertness during night shifts. However, personal resources do not significantly influence strain, motivation, or night-shift alertness, nor does strain. This may be attributed to the specific and complex nature of the ICU work environment and individual differences among nurses, warranting further investigation. Job resources significantly reduce strain, enhance motivation, and improve night-shift alertness, highlighting their importance. Managers should reinforce job resources within the ICU environment to cultivate a supportive work environment and increase nurses’ job alertness.
Acknowledgements
Acknowledgment and sincere thanks to the nurses who participated in this study.
Declarations
Ethics approval and consent to participate
This study was approved by the Institutional Review Board of Peking Union Medical College (No. 2022030). It was conducted in accordance with the principles outlined in the Declaration of Helsinki. All participants were informed about the study details before participation, including its purpose, procedures, potential risks, benefits, confidentiality measures, and voluntary involvement. Informed consent was obtained from all participants, and the survey was conducted following relevant procedural guidelines.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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