Factors related to job burnout among older nurses in Guizhou province, China

Design and participants

This study was a descriptive survey study. We built an electronic questionnaire on a special questionnaire survey website. We distributed the questionnaire through the mobile WeChat application. Nurses aged over 40 years were the target population. The nurses could complete and directly submit the questionnaire after completing the questionnaire.

The inclusion criteria were as follows: (1) working as a nurse for more than 1 year, (2) provided informed consent and were willing to participate in this study. The exclusion criteria were as follows: (1) stopped working as a nurse at 6 or more months before the survey (e.g., studying abroad, transferring nursing jobs), (2) diagnosed with a psychological disorder, or (3) diagnosed with a physical disorder, such as visceral function failure, malignant tumors.

Instruments

The general information questionnaire was designed by the researchers and included items concerning gender, age, marital status, academic degree, working years, job title, income, employment method, number of children, number of night shifts, hospital level, etc.

The Maslach Burnout Inventory (MBI), which was developed by American psychologists Maslach & Jackson (1981), was used to evaluate the respondents’ emotional reaction to work pressure and attitudes and perceptions of personal work. A Chinese MBI scale, which was revised by Chen, Liu & Meng (2018), was used to measure the job burnout of older nurses. This scale includes 22 items, and the Cronbach’s α is 0.763. There are three dimensions in the scale, i.e., emotional exhaustion (Cronbach’s α is 0.863), personification (Cronbach’s α is 0.718), and personal accomplishment (Cronbach’s α is 0.812), and the scores of the three dimensions are calculated independently. Job burnout is divided into 4 levels: zero burnout (job burnout scores on all 3 dimensions are below the severe threshold), mild burnout (scores equal to or above the severe threshold on one factor in the job burnout scale), moderate burnout (scores on one of the two dimensions are equal to or higher than the severe threshold), and severe burnout (scores on both dimensions are equal to or above the severe burnout threshold).

Job stressors was designed according to China’s national conditions by Li & Liu (2000). The job stressors scale includes 35 items, and the Cronbach’s α is 0.98. The scale includes the following five dimensions: nursing profession and work problems (Cronbach’s α is 0.95), time allocation and workload (Cronbach’s α is 0.83), working environment and equipment problems (Cronbach’s α is 0.92), patient care issues (Cronbach’s α is 0.94), and management and interpersonal problems (Cronbach’s α is 0.90). The responses were provided on a 4-point Likert scale. The higher the score, the higher the nursing work stress level.

The professional identity scale was developed by Liu, Hao & Liu (2011). The professional identity scale includes a total of 30 items. The questionnaire has good reliability and validity, with a Cronbach’s α of 0.938, and can be used to measure nurses’ professional identity. The scale is divided into the following five dimensions: professional identity evaluation (Cronbach’s α is 0.911), professional social support (Cronbach’s α is 0.824), social skills (Cronbach’s α is 0.763), coping with professional frustration (Cronbach’s α is 0.830) and professional self-reflection (Cronbach’s α is 0.720). The scale uses a 5-point Likert scale. The questions are positively worded, and the total possible score is 150 points, with higher scores indicating higher professional identity levels. Scores of 30–60, 61–90, 91–120, and 121–150 were used to create the lower-, low-, medium-, and high-scoring groups, respectively.

Procedures

The questionnaire was administered via Questionnaire Star. After obtaining written informed consent from the study subjects, the researchers presented unified instructions for completing the questionnaire and indicated matters needing attention to the respondents. The respondents could access the questionnaire online using the provided links or by scanning the provided QR code and submit it by clicking “submit” after completion. From July to August 2019, nurses aged over 40 years in Guizhou Province, China assessed their job burnout, professional identity and job stressors through the Questionnaire Star platform.

Ethical considerations

This study was approved by the Ethics Committee of the First People’s Hospital of Zunyi (2019-061), and permission for the data collection was obtained from the participants. All participants received a written notification before participating in the study. The online questionnaire explained that the privacy of the participants would be fully protected and that all submitted information would only be used for research purposes.

Statistical analysis

In this study, 521 questionnaires were collected through the Questionnaire Star platform; of these questionnaires, 520 were valid, yielding an effective recovery rate of 99.8%. One questionnaire was excluded because of a logical error in the information. Excel 2010 was used to build the database, however the SPSS 18.0 software package was used for the data analysis. The measurement data were presented as the mean ± standard deviation ($\overline{x}$ ±s). A Pearson correlation analysis was used to analyze the correlations among job burnout, job identity and job stress, and a one-way ANOVA, independent-samples t- test and multiple stepwise linear regression analysis were used to analyze the factors influencing job burnout. The effect size and 95% confidence intervals were calculated by one-way ANOVA and independent-samples t- test. The effect size was used to measure the magnitude of the difference. In the t- test, Cohen’s d value was used to indicate the effect size, and we considered d = 0.20 small, d = 0.50 medium, and d = 0.80 large effect sizes. Cohen’s f value was used to indicate the effect size of the ANOVA, and we considered d = 0.10 small, d = 0.25 medium, and d = 0.40 large effect sizes. The critical points of the effect size are 0.20, 0.50, and 0.80. Comparisons between the groups were performed by analyzing the data using the least significant difference (LSD) post hoc method. P < 0.05 was considered indicative of statistical significance.

Basic information of the respondents

The basic information of the respondents is shown in Table 1. In total, 520 respondents aged 40–60 (45.89 ± 4.64) years, including 9 males (1.7%) and 511 females (98.3%), participated in this study; the average number of working years was 25.16 ± 5.35 years. In total, 84.3% of the nurses had intermediate or above professional titles. In total, 79.2% of the nurses had one child, 17.3% of the nurses had two or more children, and 73.1% of the nurses did not work night shifts. In total, 4.2% of the nurses were from primary hospitals, 49% of the nurses were from secondary hospitals and 46.7% of the nurses were from tertiary hospitals.

Single-factor analysis of the job burnout of older nurses

The single-factor analysis and effect size are shown in Table 1. The ANOVA of job burnout revealed a significant difference among the older nurses by age (F = 4.211, P = 0.006). The LSD post hoc analysis showed that older nurses aged 51–55 years had a lower level of job burnout than those aged 40–45 years (P = 0.001) and 46-50 years (P = 0.030). The independent-samples t- tests showed a significant difference between the genders (t = 5.464, P = 0.020), males had a higher level of job burnout. The ANOVA of job burnout revealed a significant difference among the older nurses by job title (F = 7.948, P = 0.000). The LSD post hoc analysis showed that older nurses with a nurse job title had higher job burnout than those with a job title of senior nurse (P = 0.017), supervisor nurse (P = 0.000), cochief superintendent nurse (P = 0.000), and chief superintendent nurse (P = 0.046). The ANOVA showed a significant difference among the older nurses by department (F = 2.368, P = 0.013). The ANOVA showed that job burnout significantly varies by the length of work years (F = 10.069, P = 0.000). The LSD post hoc analysis showed that the nurses who worked for 16–20 years had higher job burnout than those who worked for 21–25 years (P = 0.000), 26–30 years (P = 0.000), 31–35 years (P = 0.000), and ≥36 years (P = 0.000). There was a significant difference among the different income groups (F = 6.141, P = 0.000). The LSD post hoc analysis showed that the lower income groups had higher job burnout, especially between the 3000–5999 group and the 6000–8999 group (P = 0.007) and 9000-11999 group (P = 0.000). The ANOVA showed that job burnout significantly varied by the number of children (F = 12.399, P = 0.000), and the LSD post hoc analysis showed that older nurses with one child had lower job burnout than those who had no children (P = 0.000) and 2 children (P = 0.000). Our results showed that nurses’ job burnout differed by hospital grade (F = 3.112, P = 0.045), and the LSD post hoc analysis revealed that secondary hospitals had more serious burnout than tertiary hospitals (P = 0.016).

Job burnout, job stressors and professional identity scores

The results showed that the job burnout scores of the respondents were as follows: the average emotional exhaustion dimension score was 26.58 ± 11.54, with an average item score of 2.95 ± 1.28; the average personification dimension score was 10.42 ± 6.13, with an average item score of 2.08 ± 1.23; and the average personal accomplishment dimension score was 18.44 ± 8.45, with an average item score of 2.30 ± 1.06. The job stressor and professional identity scores of the nurses are shown in Table 2.

Pearson correlation analysis of job burnout, job stressors and professional identity

The Pearson correlation analysis results showed that the job stressor scores were positively correlated with the total job burnout score (r = 0.477) and that the job stressor scores were positively correlated with the emotional exhaustion (r = 0.527) and personification (r = 0.443) scores. Nursing profession and work problems were positively correlated with emotional exhaustion (r = 0.371) and the total job burnout score (r = 0.341). Time allocation and workload were positively correlated with emotional exhaustion (r = 0.463), personification (r = 0.326), and the total job burnout score (r = 0.380). The working environment and equipment problems were positively correlated with emotional exhaustion (r = 0.437), personification (r = 0.374), and the total job burnout score (r = 0.398). Patient care issues were positively correlated with emotional exhaustion (r = 0.476), personification (r = 0.438), and the total job burnout score (r = 0.419). Management and interpersonal problems were positively correlated with emotional exhaustion (r = 0.487), personification (r = 0.423), and the total job burnout score (r = 0.471). However, these five dimensions were not correlated with personal accomplishment.

The total professional identity scores were negatively correlated with personal accomplishment (r =  − 0.564) and the total job burnout score (r =  − 0.398). Professional identity evaluation was negatively correlated with personal accomplishment (r =  − 0.506) and the total job burnout score (r =  − 0.410). Professional social support was negatively correlated with personal accomplishment (r =  − 0.501) and the total job burnout score (r =  − 0.337). Social skills were negatively correlated with personal accomplishment (r =  − 0.509). Professional frustration was negatively correlated with personal accomplishment (r =  − 0.563) and the total job burnout score (r =  − 0.397). Professional self-reflection was negatively correlated with personal accomplishment (r =  − 0.479) and the total job burnout score (r =  − 0.354). No dimension of professional identity was correlated with emotional exhaustion and personification. The results are shown in Table 3.

Multiple linear regression analysis of job burnout

Personal characteristics, job stressors, and professional identity were used as independent variables, and job burnout was used as a dependent variable in the multiple linear regression analysis. The goodness of fit of the model was 0.447, indicating that the degree of interpretation of the data information by this equation reached 44.7%. The corresponding P-value was 0.000, which is less than 0.05, indicating that the model was reasonable. The results showed that working years, number of children, hospital grade, nursing profession and work problems, time allocation and workload, patient care issues, management and interpersonal problems, professional identity evaluation, and professional frustration were significantly related to job burnout (P < 0.05). The results are shown in Table 4.