Prevalence and factors associated with job burnout among nurses in China: A cross-sectional study
Lei Li and Jing Fan contributed equally to this work.
Abstract
Aim
Many people see nursing as a high-pressure, high-risk profession. Therefore, job burnout among nursing staff has become an important topic of study and has received widespread attention worldwide. This research intended to evaluate the frequency of and variables related with work burnout among nurses in public hospitals in China.
Design
Using a multistage random sample procedure, a cross-sectional survey was carried out in the eastern, central and western areas of China.
Methods
The Maslach Inventory-Human Service Survey and demographic information made up the two sections of the questionnaire. Of the 5250 questionnaires sent, 4865 were deemed legitimate, yielding an effective response rate of 92.67%. A linear regression analysis was performed to investigate the variables linked to nursing work burnout.
Results
Among the 4865 nurses, women accounted for 97.4% of the survey respondents, most of whom were aged 26–35 years. Results showed that the total scores of emotional exhaustion (EE), depersonalization (DP) and reduced personal accomplishment (PA) were 20.02 ± 12.04, 4.78 ± 5.54 and 34.42 ± 10.32 respectively. 50.7% of subjects obtained high or moderated scores on EE, 32.8% of subjects obtained high or moderated scores on DP and 80.4% of subjects obtained low or moderated scores on PA. Age, department, position, post-establishment, work shift type in recent months, overtime times in recent months and night shift frequency in recent months were negatively correlated with EE, and child status, monthly income, working days per week and sleep quality in recent 1 month were positively correlated with it (F = 141.827, P < 0.01, R2 = 0.243). Age, gender, department, post-establishment, overtime hours in recent months and night shift frequency in recent months were negatively correlated with DP, and child status and sleep quality in the last 1 month were positively correlated with it (F = 78.794, p < 0.01, R2 = 0.115). Child status, years of nursing work and sleep quality in the last 1 month were negatively correlated with PA, whereas age, position, work shift type in recent months and night shift frequency in recent months were positively correlated with it (F = 67.981, p < 0.01, R2 = 0.089).
1 INTRODUCTION
Although the COVID-19 pandemic is extremely serious, some organizations have noted the emergence of a parallel pandemic related to mental health (Dzau et al., 2020). COVID-19 broke out suddenly, intensifying the nurse workload, causing strong work pressure and pushing the nurse job burnout situation intensively, resulting in a decline in job satisfaction and job performance. Thus, it is necessary to examine the frequency of work burnout among nurses and the variables that contribute to it (Mo et al., 2020). Before the COVID-19 pandemic, the shortage of human resources in nursing teams has attracted extensive attention worldwide. The common reasons for the shortage of nurses' human resources are low salaries, few promotion opportunities and so on (Mo et al., 2020). Moreover, Job burnout is thought to be an important contributing factor in nurses' desire to quit, and it is a global concern for nurses with broad implications for the health of nurses and patients (Mo et al., 2020).
A negative condition of physical and mental tiredness, emotional depletion, less work enthusiasm and a diminished feeling of work success brought on by excessive working hours, an excessive workload and high work intensity is referred to as job burnout, also known as professional burnout (Maslach et al., 2001). Job burnout usually manifests as emotional exhaustion (EE), depersonalization (DP) and reduced personal accomplishment (PA) (Maslach et al., 2001).
EE represents the basic personal stress dimension of job burnout, which refers to an excessive sense of dedication and the depletion of physical and emotional resources (Maslach & Jackson, 1981). DP represents the dimension of interpersonal relationships, which refers to negative indifference and excessive isolation from others (Maslach & Jackson, 1981). PA represents the dimension of self-evaluation, which refers to the feeling of incompetence and the lack of management and productivity at work. This is the reduction in self-ability and the tendency to make negative evaluations of oneself (Maslach & Jackson, 1981).
Job burnout was first proposed to describe a group of negative symptoms experienced by individuals in the service industry (Freudenberger, 1974). Since then, the research on job burnout began to be carried out widely, and the research object expanded from the service industry to other populations, such as teachers (Agyapong et al., 2022), police officers (Queirós et al., 2020), miners, journalists (Bustamante-Granda et al., 2021) and so on. Chapman DM's study has confirmed that job burnout exists in almost all occupations (Chapman, 1997), especially in those who deal with heavy workloads for a long time and cannot find any meaning in their work (Ling et al., 2020). Thus, the harm caused by job burnout cannot be ignored. People's physical and mental health are negatively impacted, and stress-related illnesses including depression and anxiety, insomnia, hypertension, heart disease, headaches, dyspepsia and other symptoms are also brought on by it (Al-Ruzzieh & Ayaad, 2021; Azemi et al., 2022; Lin et al., 2020). It also leads to a reduction in their work enthusiasm, negative work attitudes and a decline in output to the objects they serve and their organizations.
Nursing is a profession that provides high-quality medical services to patients in stressful work environments. They often face great negative emotions and interpersonal pressure at work, so they are seen to be a high-risk and vulnerable population for burnout from their jobs (Wu et al., 2011). For nurses, job burnout often leads to psychological fatigue and physiological obstacles. It reduces their work efficiency and quality, which affects the embodiment of patients' medical treatment and even poses a threat to the nursing system (Teo et al., 2021; Xu et al., 2020). Job burnout in nurses is a hot topic in occupational health psychology (Li et al., 2020). To prevent increasingly serious job burnout among nurses, clinical psychologists have conducted investigations and research on the symptoms of job burnout. The findings indicated that the likelihood of people developing chronic illnesses rises in direct proportion to the level of work burnout, such as hypertension, headache and chronic fatigue (Beckstead, 2002). China has paid increasing attention to the study of nurses' job burnout (Ge et al., 2023), but the related studies are obviously insufficient compared with European and American countries. In addition, the majority of studies on work burnout among Chinese nurses have focused on clinical departments (Xie et al., 2021) such as emergency departments, paediatrics, ICU and mental health in one province (Li et al., 2020).
In order to investigate the general state of work burnout among nurses during the COVID-19 epidemic, a cross-sectional research involving 4865 nurses in 21 public hospitals in China was conducted, further exploring the factors that positively or negatively affect job burnout, proposing corresponding intervention measures and suggestions to reduce the level of job burnout and providing theoretical reference and implementation suggestions for managers to formulate measures for nurses' job burnout.
The novelty of this study is as follows: first, it is a large sample size of nurses in public hospitals at different levels, and was conducted in China's eastern, central and western areas to measure job burnout using a multistage random sampling method during the COVID-19 pandemic which is more representative.
2 METHODS
2.1 Study design and participants
Using a multistage random sample process, based on the country's geographic location and rate of economic development, one province (municipality) was selected from each of the three regions: eastern (Zhejiang), central (Heilongjiang) and western (Chongqing). The sample is representative since these three provinces have varying capacities for economic, cultural and medical services. The National Health Commission of China provided data indicating that, taking into account variations in percentage among provinces, the ratio of nurses at the tertiary, secondary and primary hospital levels is around 12:8:1. Finally, we selected 21 public hospitals (16:4:1) and seven hospitals from each province. A random number table was used to randomly select 250 nursing staff members from each hospital. Before beginning the inquiry, each investigator had standardized training, and they were all eligible to function as investigators when the time came. The management, medical conflict resolution and human resources departments of the participating institutions granted permission for the study to be carried out.
This study was approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (approval number: KY2020-197). The Ethics Committee authorized every research technique. Participants gave their free and informed permission to take part in the investigation. Online and private paper-and-pencil survey-gathering techniques often provide respondents with the confidentiality they want and are unaffected by recurrent or inconsequential responses (Gosling et al., 2004).
Respondents who did not correctly complete the questionnaire, nurses with mental or psychological disorders, part-time nurses, interns or nurses on leave during the survey were excluded.
2.2 Measurement instruments
The questionnaire consisted of the following two parts: (1) General demographic characteristics such as gender, age, marital status, child status, unit grade, unit type, department, years engaged in nursing work, educational background, current technical title, position, post-staffing type, monthly income level, work shift type, daily working hours in recent months, working days per week, overtime times, night shift times and sleep quality. (2) The occupational burnout of nurses was measured using the Maslach Burnout Inventory-Human Service Survey (MBI-HSS) (Li et al., 2003). This scale is widely used by scholars in various professional service groups, including nurses, managers, teachers, students, doctors, etc (Liu et al., 2018). There are 22 items on the scale composed of three dimensions: EE, DP and PA. The scale is scored according to 0–6 points, with a total of seven levels. The participant's overall score for each dimension is represented by the composite score on each scale. On the emotional fatigue measure, participants with scores of 0–18, 19–26 and ≥27 showed mild, moderate and severe degrees of emotional weariness respectively. On the depersonalization dimension, those who scored 0–5, 6–9 and >9, respectively, showed low, moderate and high degrees of depersonalization. In the facet of lack of achievement, those scoring ≥40, 34–39 and 0–33, respectively, had a high, moderate and low degree of lack of personal success. The items in this dimension were reverse coded. In this investigation, the Cronbach's alpha scale was 0.737. The subscales of EE, DP and PA have Cronbach's alphas of 0.898, 0.753 and 0.842, in that order.
2.3 Data collection
From March to July 2021, data were gathered using the “wen juan xing” online survey app. Nurses working in hospitals were required to provide their unit names, which allowed us to aggregate data from hospitals and analyse nurses' burnout levels. Respondents completed an anonymous questionnaire and distributed 5250 questionnaires. A total of 4865 valid questionnaires – or an effective rate of 92.67% – were kept after removing those with missing data, partial completion, repetitive omissions and multiple choice questions. Participants had to meet three requirements in order to be considered for inclusion: (1) they had to be Registered nurses; (2) they had to work at a hospital for a minimum of 1 year and (3) they had to provide their informed permission and volunteer to fill out the questionnaires. Hospital-based nursing students were not included.
2.4 Data analysis
Statistical analyses were performed using IBM SPSS statistics software (version 24.0). K–S tests were used to confirm that the continuous variables had normal distributions. For the demographic data, descriptive statistics were computed, such as numbers (n), percentages (%), medians and interquartile ranges (IQR). The Kruskal–Wallis H test and Kolmogorov–Smirnov Z test were used to examine group differences in continuous variable measurements. The least significant difference post-comparison method was used for multiple comparisons between groups. Multicollinearity was investigated for every research variable. Linear logistic regression was used to analyse the factors influencing nurses' job burnout. The level of statistical significance was set at p < 0.05.
3 RESULTS
3.1 Demographic characteristics of respondents
Table 1 lists the demographic characteristics of the respondents. A total of 4865 nurses participated in the survey. Among them, 2.6% were men, and 97.4% were women; aged 26–35 made up the majority of them (n = 2371, 48.7%), most of the respondents were unmarried (n = 3476, 71.4%) and 65.1% of the nurses (n = 3168) had no children.
Variables | Number | Percentage (%) |
---|---|---|
Gender | ||
Female | 4738 | 97.4 |
Male | 127 | 2.6 |
Age | ||
≤25 years old | 629 | 12.9 |
26–35 years old | 2371 | 48.7 |
36–45 years old | 1132 | 23.3 |
46–55 years old | 707 | 14.5 |
≧56 years old | 26 | 0.6 |
Marital status | ||
Unmarried | 3476 | 71.4 |
Married | 1223 | 25.2 |
Divorced/Widowed | 166 | 3.4 |
Child status | ||
Yes | 3168 | 65.1 |
No | 1697 | 34.9 |
Unit level | ||
Tertiary hospital | 3769 | 77.5 |
Secondary hospital | 903 | 18.6 |
Primary hospital | 114 | 2.3 |
Others (unrated hospitals) | 79 | 1.6 |
Type of unit | ||
General hospital | 3974 | 81.7 |
Specialized hospital | 772 | 15.9 |
Community Health Centre | 119 | 2.4 |
Department | ||
Mobile post/in rotation | 94 | 1.9 |
Internal medicine | 1254 | 25.8 |
Surgery | 1218 | 25.0 |
Emergency treatment | 166 | 3.4 |
Gynaecology | 193 | 4.0 |
Medical Technology Department | 112 | 2.3 |
Paediatrics | 358 | 7.4 |
Traditional Chinese Medicine Department | 19 | 0.4 |
ICU | 302 | 6.2 |
Operation room | 265 | 5.4 |
Others | 884 | 18.2 |
Years of nursing work | ||
≤5 years | 1002 | 20.6 |
6–10 years | 1467 | 30.2 |
11–20 years | 1237 | 25.4 |
21–30 years | 822 | 16.9 |
≥31 years | 337 | 6.9 |
Educational level | ||
Technical Secondary School and below | 222 | 4.6 |
Junior college | 1199 | 24.6 |
Undergraduate | 3353 | 68.9 |
Graduate and above | 91 | 1.9 |
Technical title | ||
Nurse | 1076 | 22.1 |
Nurse practitioner | 1751 | 36.0 |
Nurse in charge | 1498 | 30.8 |
Deputy chief nurse | 436 | 9.0 |
Chief nurse | 104 | 2.1 |
Position | ||
Nurse | 4059 | 83.4 |
Deputy head nurse | 114 | 2.3 |
Head Nurse of Department | 636 | 13.2 |
Head nurse | 41 | 0.8 |
Director of Nursing Department | 15 | 0.3 |
Post-establishment | ||
Career establishment | 1631 | 33.5 |
Contract system | 2846 | 58.5 |
Equal pay for equal work | 321 | 6.6 |
Temporary worker | 67 | 1.4 |
Monthly income | ||
≤3000 yuan | 694 | 14.3 |
3001–5000 yuan | 2038 | 41.9 |
5001–7000 yuan | 1265 | 26.0 |
7001–9000 yuan | 465 | 9.6 |
≥9001 yuan | 403 | 8.2 |
Work shift type in recent month | ||
Day shift only | 2506 | 51.5 |
Split shift | 2296 | 47.2 |
Swing shift | 8 | 0.2 |
Night shift | 55 | 1.1 |
The usual daily working hours in the past month | ||
≤6 h | 124 | 2.5 |
7–8 h | 2929 | 60.2 |
9–10 h | 1276 | 26.2 |
11–12 h | 303 | 6.3 |
≥13 h | 233 | 4.8 |
Overtime times in recent months | ||
0–5 times | 1133 | 23.3 |
6–10 times | 726 | 14.9 |
11–15 times | 1944 | 40.0 |
≥16 times | 1062 | 21.8 |
Night shift frequency in recent months | ||
0–2 times | 376 | 7.7 |
3–4 times | 801 | 16.5 |
5–6 times | 1270 | 26.1 |
≥6 times | 2418 | 49.7 |
Sleep quality in recent 1 month | ||
Very satisfied | 187 | 3.8 |
Quite satisfied | 797 | 16.4 |
General satisfaction | 2250 | 46.2 |
Quite dissatisfied | 1127 | 23.2 |
Very dissatisfied | 504 | 10.4 |
In terms of working conditions, 77.5% of the nurses worked in public hospitals (n = 3769), and 81.7% (n = 3974) of nurses worked in general hospitals. Among the 4865 respondents, 25.8% (n = 1254) came from internal medicine, 30.2% (n = 1467) had been engaged in nursing for 6–10 years and most had a bachelor's degree (n = 3353, 68.9%) and were nurses (n = 1751, 36.0%). More than half of the nurses were on contract (n = 2846, 58.5%) and only worked day shifts (n = 2506, 51.5%). The proportion of nurses with a monthly income ranging from 3001 to 5000 yuan was the highest, accounting for 41.9% (n = 2038). Most nurses work 7–8 h in the past month (n = 2929, 60.2%). A total of 46.2% (n = 2250) said that their sleep quality in the past month had only reached the general level.
3.2 The overall situation of job burnout among nurses
The nurses exhibited low PA, moderate DP and moderate EE, as Table 2 demonstrates. In addition, the total burnout level average score was 2.69 ± 0.70, the score of DP dimension was the lowest, which was 0.96 ± 1.11, followed by EE and personal achievement, which were 2.22 ± 1.34 and 4.30 ± 1.29 respectively.
Variables | n | % | Item total score | Item average | Norm | t | p |
---|---|---|---|---|---|---|---|
EE | |||||||
Low level | 2399 | 49.3 | 20.02 ± 12.04 | 2.22 ± 1.34 | 22.19 ± 9.53 | −12.581 | <0.001 |
Medium level | 1100 | 22.6 | |||||
High level | 1366 | 28.1 | |||||
DP | |||||||
Low level | 3269 | 67.2 | 4.78 ± 5.54 | 0.96 ± 1.11 | 7.12 ± 5.22 | −29.428 | <0.001 |
Medium level | 777 | 16.0 | |||||
High level | 819 | 16.8 | |||||
PA | |||||||
Low level | 2932 | 60.3 | 34.42 ± 10.32 | 4.30 ± 1.29 | 36.54 ± 7.34 | −14.329 | <0.001 |
Medium level | 980 | 20.1 | |||||
High level | 953 | 19.6 |
Of the respondents, 50.7% had moderate or high EE, 32.8% had moderate or high DP and emotional alienation, and 80.4% had moderate or low personal achievement. The results also showed that the scores of EE and DP of nurses in this study were lower than the norm (Maslach et al., 1993), and the scores of low sense of achievement were higher than the norm (p < 0.05).
3.3 Characteristics of participants in relation to job burnout
3.3.1 Characteristics of participants in relation to EE
The results showed statistically significant differences in EE score levels among different gender, age, marital status, child status, unit level, type of unit, department, years of nursing work, educational level, technical title, position, post-establishment, monthly income, working shifts type, working hours, overtime times, night shift frequency and sleep quality (Table 3; p < 0.05). There was a substantial association seen between the number of working days per week in the last month and the existence of EE (r = 0.067, p < 0.01).
Variables | Median | IQR | Z/H |
---|---|---|---|
Gender | |||
Female | 19 | 14;29 | 1.669Z** |
Male | 19 | 10;28 | |
Age | |||
≤25 years old | 21 | 13;30 | 206.673H** |
26–35 years old | 20 | 12;29 | |
36–45 years old | 17 | 9;26 | |
46–55 years old | 12 | 7;22 | |
≧56 years old | 16 | 8;18 | |
Marital status | |||
Unmarried | 18 | 9;26 | 108.218H** |
Married | 22 | 14;31 | |
Divorced/Widowed | 18 | 9;27 | |
Child status | |||
Yes | 17 | 9;26 | 4.713Z** |
No | 21 | 13;31 | |
Unit level | |||
Tertiary hospital | 19 | 10;28 | 8.439H* |
Secondary hospital | 18 | 10;27 | |
Primary hospital | 17 | 10;23 | |
Others (unrated hospitals) | 24 | 12;30 | |
Type of unit | |||
General hospital | 19 | 10;28 | 6.155H* |
Specialized hospital | 19 | 11;29 | |
Community Health Centre | 17 | 10;23 | |
Department | |||
Mobile post/in rotation | 22 | 14;30 | 102.879H** |
Internal medicine | 20 | 11;29 | |
Surgery | 21 | 12;30 | |
Emergency treatment | 16.5 | 10;28 | |
Gynaecology | 14 | 8;24 | |
Medical Technology Department | 19 | 10;29 | |
Paediatrics | 15 | 8.25;22 | |
Traditional Chinese Medicine Department | 20 | 11;28 | |
ICU | 12 | 10;16 | |
Operation room | 20 | 14;28 | |
Others | 17 | 9;24 | |
Years of nursing work | |||
≤5 years | 21 | 13;30 | 150.661H** |
6–10 years | 20 | 12;30 | |
11–20 years | 18 | 10;27 | |
21–30 years | 16 | 9;24 | |
≥31 years | 13 | 6;21.5 | |
Educational level | |||
Technical Secondary School and below | 20.5 | 11;33 | 9.444H* |
Junior college | 19 | 11;28 | |
Undergraduate | 18 | 10;27 | |
Graduate and above | 19 | 12;30 | |
Technical title | |||
Nurse | 20 | 12;30 | 147.598H** |
Nurse Practitioner | 20 | 11;29 | |
Nurse in charge | 18 | 11;27 | |
Deputy chief nurse | 13 | 8;22 | |
Chief nurse | 8.5 | 4.25;21 | |
Position | |||
Nurse | 19 | 11;29 | 96.673H** |
Deputy head nurse | 14 | 8;26 | |
Head Nurse of Department | 15 | 8;23 | |
Head nurse | 10 | 5.5;24 | |
Director of Nursing Department | 8 | 4;21 | |
Post-establishment | |||
Career establishment | 17 | 9;26 | 65.008H** |
Contract system | 20 | 12;29 | |
Equal pay for equal work | 16 | 8;26.5 | |
Temporary worker | 16 | 13;29 | |
Monthly income | |||
≤3000 yuan | 19 | 11;31 | 18.889H** |
3001–5000 yuan | 19 | 11;28 | |
5001–7000 yuan | 18 | 9;27 | |
7001–9000 yuan | 18 | 10;26 | |
≥9001 yuan | 18 | 10;27 | |
Work shift type in recent month | |||
Day shift only | 16 | 9;25 | 128.211H** |
Split shift | 21 | 12;29 | |
Swing shift | 23.5 | 20.75;29.25 | |
Night shift | 23 | 15;39 | |
The usual daily working hours in the past month | |||
≤6 h | 14.5 | 8;26 | 160.855H** |
7–8 h | 17 | 9;26 | |
9–10 h | 22 | 13;30 | |
11–12 h | 23 | 15;32 | |
≥13 h | 21 | 13;30.5 | |
Overtime times in recent months | |||
0–5 times | 29 | 18;38 | 379.868H** |
6–10 times | 23 | 15;32 | |
11–15 times | 19 | 11;27 | |
≥16 times | 15 | 8;24 | |
Night shift frequency in recent months | |||
0–2 times | 29 | 21;40 | 355.499H** |
3–4 times | 22 | 13;31 | |
5–6 times | 19 | 11;27 | |
≥6 times | 16 | 8;25 | |
Sleep quality in recent 1 month | |||
Very satisfied | 10 | 4;18 | 807.339H** |
Quite satisfied | 12 | 7;20 | |
General satisfaction | 18 | 10;25 | |
Quite dissatisfied | 23 | 15;32 | |
Very dissatisfied | 31 | 22;42 |
- Abbreviations: H, Kruskal–Wallis H test; Z, Kolmogorov–Smirnov Z test.
- * p < 0.05;
- ** p < 0.01.
3.3.2 Characteristics of participants in relation to DP
The results showed that there were notable variations in DP score levels according to gender, age, marital status, child status, unit level, type of unit, department, years of nursing work, technical title, position, post-establishment, working shifts type, working hours, overtime time, night shift frequency and sleep quality (Table 4; p < 0.05). Working days per week in the most recent month were not related to DP (r = 0.024, p = 0.099).
Variables | Median | IQR | Z/H |
---|---|---|---|
Gender | |||
Female | 4 | 1;12 | 1.674Z** |
Male | 3 | 1;7 | |
Age | |||
≤ 25 years old | 4 | 1;10 | 210.793H** |
26–35 years old | 4 | 1;8 | |
36–45 years old | 2 | 0;6 | |
46–55 years old | 1 | 0;4 | |
≧56 years old | 4 | 0;6 | |
Marital status | |||
Unmarried | 3 | 0;6 | 99.901H** |
Married | 4 | 1;10 | |
Divorced/Widowed | 2 | 1;6 | |
Child status | |||
Yes | 2 | 0;6 | 4.463Z** |
No | 4 | 1;9 | |
Unit level | |||
Tertiary hospital | 3 | 1;7 | 13.028H** |
Secondary hospital | 3 | 0;6 | |
Primary hospital | 2 | 0;6 | |
Others (unrated hospitals) | 4 | 1;7 | |
Type of unit | |||
General hospital | 3 | 1;7 | 6.921H* |
Specialized hospital | 3 | 1;7 | |
Community Health Centre | 1 | 0;5 | |
Department | |||
Mobile post/in rotation | 5.5 | 1.75;10.25 | 106.663H** |
Internal medicine | 4 | 1;8 | |
Surgery | 3 | 1;7 | |
Emergency treatment | 3 | 1;7.25 | |
Gynaecology | 1 | 0;5 | |
Medical Technology Department | 3 | 0;6 | |
Paediatrics | 1 | 0;5 | |
Traditional Chinese Medicine Department | 3 | 0;8 | |
ICU | 1 | 0;4 | |
Operation room | 3 | 1;8 | |
Others | 2 | 0;6 | |
Years of nursing work | |||
≤5 years | 4 | 1;9 | 162.989H** |
6–10 years | 4 | 1;8 | |
11–20 years | 3 | 1;6 | |
21–30 years | 1 | 0;5 | |
≥31 years | 1 | 0;4 | |
Educational level | |||
Technical Secondary School and below | 3 | 0;8 | 0.675H |
Junior college | 3 | 0;7 | |
Undergraduate | 3 | 1;7 | |
Graduate and above | 3 | 1;7 | |
Technical title | |||
Nurse | 4 | 1;8.75 | 98.54H** |
Nurse Practitioner | 3 | 1;8 | |
Nurse in charge | 2 | 1;6 | |
Deputy chief nurse | 1 | 0;5 | |
Chief nurse | 1 | 0;4 | |
Position | |||
Nurse | 3 | 1;7 | 56.685H** |
Deputy head nurse | 2 | 0;6 | |
Head Nurse of Department | 2 | 0;5 | |
Head nurse | 1 | 0;5 | |
Director of Nursing Department | 1 | 1;4 | |
Post-establishment | |||
Career establishment | 2 | 0;6 | 39.043H** |
Contract system | 3 | 1;7 | |
Equal pay for equal work | 3 | 0;8.5 | |
Temporary worker | 3 | 0;10 | |
Monthly income | |||
≤3000 yuan | 3 | 0;7 | 5.649H |
3001–5000 yuan | 3 | 1;7 | |
5001–7000 yuan | 3 | 1;6 | |
7001–9000 yuan | 3 | 1;7 | |
≥9001 yuan | 3 | 1;6 | |
Work shift type in recent month | |||
Day shift only | 2 | 0;6 | 124.648H** |
Split shift | 4 | 1;9 | |
Swing shift | 3 | 2.25;11.25 | |
Night shift | 5 | 2;12 | |
The usual daily working hours in the past month | |||
≤6 h | 1.5 | 0;6 | 70.409H** |
7–8 h | 2 | 0;6 | |
9–10 h | 4 | 1;8 | |
11–12 h | 4 | 1;9 | |
≥13 h | 4 | 1;8 | |
Overtime times in recent months | |||
0–5 times | 5 | 1;12 | 118.58H** |
6–10 times | 4 | 1;9 | |
11–15 times | 3 | 1;7 | |
≥16 times | 2 | 0;6 | |
Night shift frequency in recent months | |||
0–2 times | 6 | 2;14 | 228.366H** |
3–4 times | 4 | 1;9 | |
5–6 times | 3 | 0;7 | |
≥6 times | 2 | 0;6 | |
Sleep quality in recent 1 month | |||
Very satisfied | 1 | 0;4 | 277.891H** |
Quite satisfied | 1 | 0;5 | |
General satisfaction | 3 | 0;6 | |
Quite dissatisfied | 4 | 1;9 | |
Very dissatisfied | 6 | 1;13 |
- Abbreviations: H, Kruskal–Wallis H test; Z, Kolmogorov–Smirnov Z test.
- * p < 0.05;
- ** p < 0.01.
3.3.3 Characteristics of participants in relation to PA
The outcomes demonstrated that there were notable variations in PA score levels among the different age groups, marital status, child status, unit type, department, years of nursing work, educational level, technical title, position, post-establishment, monthly income, working shifts type, working hours, overtime times, night shift frequency and sleep quality (Table 5; p < 0.05). There was a connection between the total amount of working days per week in the most recent month and the existence of PA (r = 0.032, p = 0.028).
Variables | Median | IQR | Z/H |
---|---|---|---|
Gender | |||
Female | 39 | 26;42 | 0.928Z |
Male | 36 | 27;43 | |
Age | |||
≤ 25 years old | 34 | 25;41 | 238.375H** |
26–35 years old | 34 | 25;42 | |
36–45 years old | 38 | 30;44 | |
46–55 years old | 41 | 33;46 | |
≧56 years old | 42 | 40;47 | |
Marital status | |||
Unmarried | 37 | 28;44 | 96.815H** |
Married | 32 | 24;41 | |
Divorced/Widowed | 39 | 34;43.25 | |
Child status | |||
Yes | 38 | 29;44 | 5.065Z** |
No | 33 | 24;41 | |
Unit level | |||
Tertiary hospital | 36 | 27;43 | 5.355H |
Secondary hospital | 36 | 26;43 | |
Primary hospital | 38 | 29;43 | |
Others (unrated hospitals) | 33 | 25;39 | |
Type of unit | |||
General hospital | 36 | 26;43 | 9.317H* |
Specialized hospital | 36 | 26;43 | |
Community Health Centre | 40 | 31;44 | |
Department | |||
Mobile post/in rotation | 33 | 25;40 | 58.048H** |
Internal medicine | 36 | 26;42 | |
Surgery | 36 | 27;43 | |
Emergency treatment | 39 | 30;45 | |
Gynaecology | 39 | 29;45 | |
Medical Technology Department | 36 | 27;44 | |
Paediatrics | 33.5 | 38.25;42 | |
Traditional Chinese Medicine Department | 35 | 25;42 | |
ICU | 47 | 39;48 | |
Operation room | 35 | 24;41 | |
Others | 37 | 27;44 | |
Years of nursing work | |||
≤5 years | 34 | 25;42 | 187.267H** |
6–10 years | 34 | 24;41 | |
11–20 years | 36 | 27;43 | |
21–30 years | 39 | 31;45 | |
≥31 years | 41 | 34;46 | |
Educational level | |||
Technical Secondary School and below | 36 | 25.75;42 | 22.09H** |
Junior college | 35 | 26;42 | |
Undergraduate | 37 | 27;43 | |
Graduate and above | 41 | 33;44 | |
Technical title | |||
Nurse | 33 | 25;42 | 226.905H** |
Nurse practitioner | 34 | 25;42 | |
Nurse in charge | 37 | 28;43 | |
Deputy chief nurse | 41 | 35;46 | |
Chief nurse | 44 | 39.25;48 | |
Position | |||
Nurse | 36 | 26;42 | 125.563H** |
Deputy head nurse | 38.5 | 26;46 | |
Head Nurse of Department | 40 | 33;46 | |
Head nurse | 41 | 35;47 | |
Director of Nursing Department | 42 | 26;48 | |
Post-establishment | |||
Career establishment | 39 | 29;44 | 84.725H** |
Contract system | 35 | 26;42 | |
Equal pay for equal work | 37 | 29;43 | |
Temporary worker | 37 | 24;45 | |
Monthly income | |||
≤3000 yuan | 35 | 25;43 | 48.908H** |
3001–5000 yuan | 35 | 26;42 | |
5001–7000 yuan | 37 | 28;44 | |
7001–9000 yuan | 38 | 29;44 | |
≥9001 yuan | 39 | 29;44 | |
Work shift type in recent month | |||
Day shift only | 38 | 29;44 | 131.131H** |
Split shift | 34 | 25;42 | |
Swing shift | 34 | 17.5;37.75 | |
Night shift | 34 | 25;40 | |
The usual daily working hours in the past month | |||
≤6 h | 38 | 32;44 | 30.591H** |
7–8 h | 37 | 27;43 | |
9–10 h | 36 | 26;43 | |
11–12 h | 32 | 24;41 | |
≥13 h | 35 | 24.5;42 | |
Overtime times in recent month | |||
0–5 times | 33 | 24;42 | 14.517H** |
6–10 times | 37 | 26;42 | |
11–15 times | 36 | 26;43 | |
≥16 times | 37 | 27.5;43 | |
Night shift frequency in recent month | |||
0–2 times | 27 | 22;36.75 | 226.828H** |
3–4 times | 34 | 25;41 | |
5–6 times | 36 | 26;42 | |
≥6 times | 39 | 30;44 | |
Sleep quality in recent 1 month | |||
Very satisfied | 42 | 33;48 | 249.176H** |
Quite satisfied | 40 | 32;46 | |
General satisfaction | 37 | 27;43 | |
Quite dissatisfied | 33 | 25;41 | |
Very dissatisfied | 31 | 23;40 |
- Abbreviations: H, Kruskal–Wallis H test; Z, Kolmogorov–Smirnov Z test.
- * p < 0.05;
- ** p < 0.01.
3.3.4 Linear regression analysis of factors related to nurse job burnout
Table 6 displays the outcomes of the linear regression analysis. The following are the regression analysis's findings: first, age, department, position, post-establishment, work shift type in recent months, overtime times in recent months and night shift frequency in recent months were negatively correlated with EE, while child status, monthly income, working days per week in recent months and sleep quality in recent 1 month were positively correlated with EE (F = 141.827, p < 0.01, R2 = 0.243). Second, age, gender, department, post-establishment, overtime times in recent months and night shift frequency in recent months were negatively correlated with DP, and child status and sleep quality in recent 1 month were positively correlated with it (F = 78.794, p < 0.01, R2 = 0.115). Third, child status, years of nursing work and sleep quality in recent 1 month were negatively correlated with PA, while age, position, work shift type in recent months and night shift frequency in recent months were positively correlated with it (F = 67.981, p < 0.01, R2 = 0.089).
Dependent variable | Variables | B | SE | Beta | t | p | 95%CI |
---|---|---|---|---|---|---|---|
EE | (Constant) | 20.512 | 2.276 | 9.014 | 0 < 0.01 | 16.051 to 24.973 | |
Age | −1.385 | 0.226 | −0.104 | −6.114 | 0 < 0.01 | −1.829 to −0.941 | |
Child status | 1.573 | 0.382 | 0.062 | 4.117 | 0 < 0.01 | 0.824 to 2.322 | |
Department | −0.223 | 0.041 | −0.068 | −5.453 | 0 < 0.01 | −0.304 to −0.143 | |
Position | −1.109 | 0.227 | −0.069 | −4.89 | 0 < 0.01 | −1.554 to −0.664 | |
Post-establishment | −1.148 | 0.271 | −0.06 | −4.229 | 0 < 0.01 | −1.68 to −0.616 | |
Monthly income | 0.407 | 0.145 | 0.037 | 2.799 | 0.005 | 0.122 to 0.692 | |
Working days per week in recent month | 0.729 | 0.177 | 0.054 | 4.118 | 0 < 0.01 | 0.382 to 1.076 | |
Work shift type in recent month. | −1.421 | 0.419 | −0.067 | −3.388 | 0.001 | −2.243 to −0.599 | |
Overtime times in recent months | −2.442 | 0.178 | −0.184 | −13.688 | 0 < 0.01 | −2.792 to −2.092 | |
Night shift frequency in recent months | −0.94 | 0.252 | −0.076 | −3.732 | 0 < 0.01 | −1.433 to −0.446 | |
Sleep quality in recent 1 month | 4.169 | 0.178 | 0.333 | 23.476 | 0 < 0.01 | 3.821 to 4.518 | |
F | 141.827** | ||||||
R 2 | 0.243 | ||||||
DP | (Constant) | 9.058 | 1.18 | 7.678 | 0 < 0.01 | 6.745 to 11.371 | |
Age | −0.701 | 0.109 | −0.115 | −6.422 | 0 < 0.01 | −0.915 to −0.487 | |
Gender | −1.401 | 0.476 | −0.04 | −2.942 | 0.003 | −2.335 to −0.468 | |
Child status | 0.697 | 0.189 | 0.06 | 3.679 | 0 < 0.01 | 0.325 to 1.068 | |
Department | −0.12 | 0.02 | −0.08 | −5.85 | 0 < 0.01 | −0.16 to −0.08 | |
Post-establishment | −0.271 | 0.132 | −0.031 | −2.054 | 0.04 | −0.53 to −0.012 | |
Overtime times in recent months | −0.648 | 0.085 | −0.106 | −7.579 | 0 < 0.01 | −0.816 to −0.48 | |
Night shift frequency in recent months | −0.299 | 0.093 | −0.052 | −3.203 | 0.001 | −0.482 to −0.116 | |
Sleep quality in recent 1 month | 1.049 | 0.086 | 0.182 | 12.137 | 0 | 0.88 to 1.219 | |
F | 78.794** | ||||||
R 2 | 0.115 | ||||||
PA | (Constant) | 32.45 | 1.663 | 19.512 | 0 | 29.189 to 35.71 | |
Age | 1.739 | 0.325 | 0.153 | 5.348 | 0 | 1.102 to 2.377 | |
Child status | −1.347 | 0.367 | −0.062 | −3.671 | 0 | −2.067 to −0.628 | |
Position | 0.955 | 0.209 | 0.07 | 4.563 | 0 | 0.545 to 1.365 | |
Years of nursing work | −0.593 | 0.256 | −0.068 | −2.316 | 0.021 | −1.095 to −0.091 | |
Work shift type in recent months. | 1.039 | 0.388 | 0.057 | 2.678 | 0.007 | 0.278 to 1.8 | |
Night shift frequency in recent months | 1.184 | 0.231 | 0.111 | 5.117 | 0 | 0.731 to 1.638 | |
Sleep quality in recent 1 month | −1.708 | 0.162 | −0.159 | −10.569 | 0 | −2.025 to −1.391 | |
F | 67.981** | ||||||
R 2 | 0.089 |
- Abbreviations: B, unstandardized coefficients; Beta, standardized coefficients; SE, standard error.
4 DISCUSSION
4.1 Current situation of each dimension of job burnout among nurses
A previous study confirmed that nurses' job burnout not only affects the quality of nursing but also leads to an increase in nurses' turnover intention (Liu et al., 2018). Lower patient satisfaction is correlated with high levels of burnout and job unhappiness among nurses, which suggests issues with the quality of treatment. The present state of nurse work burnout and strategies for lowering its incidence have emerged as major areas of interest for the organizational behaviour and human resource management study (Aiken et al., 2002). Therefore, it is important to take measures to reduce nurses' EE and DP and improve PA.
4.2 Differences of different demographic characteristics of nurses in various dimensions of job burnout
In terms of age, through pairwise comparison, it can be seen that the EE and DP factor scores of nurses in the age group under the age of 25 are greater than those in the age group over the age of 36, and the PA is lower than those in the age group over the age of 36. It was also found that the lower the working years, technical titles and positions of nurses, the easier it was for them to experience lower levels of EE, DP and PA. This may be because nurses under the age of 25 years who have fewer working years are in the early stages of career development and cannot skilfully cope with changes in the working environment and stress factors, and a stable colleague relationship has not been established; therefore, they have received relatively little social support. In addition, the sense of a gap caused by the conflict between ideal work goals and reality produces helplessness, which leads to a loss of personal achievement.
Married nurses with children scored relatively high in EE and DP. In addition to undertaking work tasks, married nurses with children must also play a variety of roles in the family, such as supporting the older people and raising children. To master the balance between work and family conflicts, they make use of more physical strength and energy. This irregular shift caused them to spend less time with their families and receive less emotional support. In addition, nurses who have experienced divorce or widowhood may suffer more severe emotional trauma, lack support from their families and be prone to negative self-evaluations. Additionally, the data indicated that compared to single nurses, married nurses had a higher risk of experiencing occupational burnout. This is consistent with Sabbah's research results (Sabbah et al., 2012). Based on a comprehensive analysis of existing research on the subject, work–family conflict emerges when the demands of one role impede the fulfilment of those of another, or when the demands of one role necessitate particular behaviours that complicate the accomplishment of the demands of another; or when one role's requirements cause strain from participation in another role. Owing to busy work and limited personal energy, role conflicts between family and work often make it difficult for nurses to achieve a balance. Therefore, nurses should avoid bringing negative emotions such as fatigue and anxiety to their families because of long-term exposure to high-pressure environments.
In terms of unit types, the research discovered that although the DP level was lower in general and speciality hospitals, the EE and PA levels of nurses at community health care centres were higher. The development of grassroots medical and health services may be mostly carried out collectively, and their work effect is a long process that needs to be gradually highlighted. However, community nursing work that needs to go deeply into the family requires greater patient compliance. The difficulty of work and the non-cooperation of residents lead to the gradual loss of professional values and professional beliefs and doubt the significance of their work. It is noteworthy that this research discovered a greater degree of job burnout among ICU nurses, which might be attributed to the following factors. First, ICU patients' condition was critical and changed rapidly; they not only faced basic nursing work but also carried out various special treatments because the work content was more complex and the workload was greater. Second, ICU nurse staffing did not keep up with patient volume, and the nursing human resources were seriously insufficient, which has become a common problem in the medical field. Third, compared to other departments, ICU patients are in critical condition. Nurses often perform many nursing operations, but patients do not improve or die more frequently, which makes them feel frustrated. Fourth, there are many types of medical equipment in the ICU wards, and the environment is relatively closed and narrow. Working in this environment for a long time makes it easy to feel irritable and unable to concentrate (Hu et al., 2021).
In terms of monthly income, nurses officially employed in public hospitals (public institutions) are treated as civil servants who are more stable and provide better welfare benefits than contract nurses. The burnout level of nurses working day and night shifts was higher than that of nurses working day shifts only. The worse the sleep quality, the more likely it was to experience burnout. Some scholars have pointed out that factors leading to fatigue include the quantity and quality of sleep and rest, working time processes and work intensity, which is consistent with our result (Krueger, 1989). Compared with full-time day-shift nurses, shift nurses have a higher probability of poor sleep, irregular work and rest, sleeping during work and physical fatigue, while night shift work focuses on condition observation, operation and treatment, so their personal sense of achievement cannot be improved. The longer the usual daily working hours in recent months and the more overtime work, the higher the corresponding rest and sleep time cannot be adequately guaranteed, and sleep quality is the premise to ensuring good mood, improving personal sense of achievement and good social behaviour. Lack of sleep can lead to changes in psychological functions, such as irritability, anxiety, depression, other negative emotions and loss of interest in work. Some studies have found that the sleep problems of nursing students are higher than those of the general population (Hu et al., 2021; Mulyadi et al., 2021), which reminds us to some extent that attention should be paid to the rationality of nurse scheduling, avoiding long-term continuous work, and doing a good job in the psychological debugging of nurses to improve their sleep quality.
4.3 Effective measures and countermeasures to prevent and alleviate job burnout
The survey's findings indicated that nurses are more vulnerable to burnout from their jobs. To preserve the physical and mental well-being of the nursing group, guarantee the standard of nursing care and sustain the advancement of nursing professions, proactive and efficacious interventions against EE, depersonalization and decreased personal accomplishment should be implemented. Therefore, this study proposes the following measures and suggestions to prevent job burnout among nurses:
First, previous studies have pointed out that the employment process is an interactive process between professionals and occupations (Safari et al., 2022), so we should not only consider the influence of external factors but also the problem of job burnout from the cognitive aspect of professionals (Rasmussen et al., 2016). Therefore, in order to firmly establish a positive concept of employment, this study recommends that nurses learn stress management techniques, monitor their own emotional changes over time, pay attention to the quality of their sleep and seek out professional or social support when juggling work and personal obligations.
Second, owing to the continuous improvement in nursing in China (Zhao et al., 2021), professional requirements for nurses are also increasing. According to Maslow's demand theory, medical and health institutions should not only improve the professional requirements of nurses but also provide them with corresponding care (Giuffrida & Davila, 2024; Zhan et al., 2021). For example, paying attention to the physiological and psychological needs of nurses to reduce their stressors, arranging shifts scientifically, ensuring that nurses have sufficient rest time and regular work and rest, attaching great importance to the interest needs of nurses and actively striving for policy support to safeguard and protect their professional rights and interests. In addition, it should be ensured that the career promotion channel for nurses is unblocked, provide social support for nurses to a certain extent and implement necessary psychological interventions and organizational adjustments to reduce and prevent nurses' job burnout. Those nurses who are new to the field and have little experience should get special care. They should receive salaries and benefits or help in making career plans, provide more psychological attention to married nurses who work in the operating room and provide psychological guidance when necessary to help them eliminate negative emotions. The training provided should focus on the multidimensional development of basic nursing knowledge, nursing skills and nurse–patient interpersonal relationships to improve nurses' job efficiency, quality of life and work quality.
Third, the competent medical and health departments and hospital managers should strengthen the publicity of nursing through policy-making and other ways (Chiu et al., 2021; Salvage & White, 2019) and advocate for the whole society, including the families of patients and nurses, to understand and respect the nursing profession to improve their social status and social support and maintain family harmony. Improving the working environment of nurses (Blau et al., 2023), building a harmonious nurse–patient relationship, creating a healthy working atmosphere and reducing the employment pressure on nurses from the perspective of professional social cognition (White et al., 2019).
4.4 Limitations
There are several restrictions on our investigation. Initially, a cross-sectional design was used in this research to examine the variables influencing work burnout in nurses at this point in their careers. Without a longitudinal survey, the causal relationships between variables cannot be explained. Therefore, further longitudinal studies are required to address this issue. Second, the sample size of male nurses was small, and male nurses were fewer than female nurses in hospitals. It is suggested that future research can start from effective means to alleviate nurses' job burnout, deeply study the internal mechanism and intervention path of job burnout, put forward practical methods to prevent or alleviate nurses' job burnout and find means to include more male nurses.
5 CONCLUSIONS
China's state hospitals have high overall work burnout ratings among its nursing staff. Unit type, daily working hours in recent months, sleep quality, technical title, position, monthly income and department are the key factors affecting job burnout. Therefore, it is imperative that nursing managers give more consideration to these crucial aspects and implement proactive strategies to mitigate job burnout and maintain the stability of the nursing staff.
AUTHOR CONTRIBUTIONS
All authors have read and approved the manuscript. LL, JF, YW and ML wrote the first draft of the manuscript. LL, JF, LQ, CL, YW, SZ and ML revised the manuscript. LL, JF, LQ, CL, YW, XH and ML analysed the research data. YW, SZ and ML edited the paper.
ACKNOWLEDGEMENTS
We are extremely grateful to all the members who took part in this study.
FUNDING INFORMATION
This work was supported by the Innovative Science Research Foundation of Harbin Medical University (2022-KYYWF-0326) and Higher Education Foundation of HeiLongjiang Association of Higher Education (23GJYBI022).
CONFLICT OF INTEREST STATEMENT
The authors declare that they have no competing interests.
ETHICS STATEMENT
All study procedures were approved by the Ethics Committee of the Second Affiliated Hospital of Harbin Medical University (approval number: KY2020-197).
Open Research
DATA AVAILABILITY STATEMENT
The data that support the findings of this study are available from the corresponding author upon reasonable request.