job satisfaction among nurses a literature review pdf

Job satisfaction among nurses: a literature review

Affiliation.

1 Florence Nightingale School of Nursing and Midwifery, King's College London, James Clerk Maxwell Building, 57 Waterloo Road, London SE1 8WA, England, UK. [email protected]
PMID: 15680619
DOI: 10.1016/j.ijnurstu.2004.09.003

The current nursing shortage and high turnover is of great concern in many countries because of its impact upon the efficiency and effectiveness of any health-care delivery system. Recruitment and retention of nurses are persistent problems associated with job satisfaction. This paper analyses the growing literature relating to job satisfaction among nurses and concludes that more research is required to understand the relative importance of the many identified factors to job satisfaction. It is argued that the absence of a robust causal model incorporating organizational, professional and personal variables is undermining the development of interventions to improve nurse retention.

Publication types

Absenteeism
Attitude of Health Personnel*
Burnout, Professional / etiology
Burnout, Professional / prevention & control
Burnout, Professional / psychology
Job Description
Job Satisfaction*
Models, Psychological
Nurse's Role
Nursing Administration Research
Nursing Methodology Research
Nursing Staff / organization & administration
Nursing Staff / psychology*
Organizational Culture
Personnel Selection
Personnel Turnover
Professional Autonomy

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Job satisfaction among nurses: a literature review

2005, International Journal of Nursing Studies

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"In this century, thousands of studies have been conducted on job satisfaction. Originally, much of the study seemed to be stimulated by a desire to show that job satisfaction is important because it affects productivity and performance. This approach to studying job satisfaction is congruous with the improved prominence of humanistic psychology. Raising nurse job satisfaction has been perceived as the basic way of reducing turnover. There is a considerable amount of investigation in the domain of the possible causes of nurses overall job satisfaction and, to a lesser degree, the possible outcomes of job satisfaction. However, due to the many studies conducted, some with conflicting consequences, it is difficult to clearly understand the factors correlated with job satisfaction. The recent nursing shortage and highest turnover are of huge concern in several countries as well as in Malaysia because of its effects upon the efficiency and effectiveness of any health-care delivery system. Recruitment and maintenance of nurses are persistent problems related to job satisfaction. This paper analyses the growing literature related to job satisfaction among nurses and determines that more investigation is required to understand the relation significance of the many identified factors to nurse’s job satisfaction. It argues that the absence of a robust causal model incorporating organizational, professional and individual variables is limiting the improvement of interventions to develop nurse retention. A review of the literature is demonstrated to provide a better understanding on nurse’s job satisfaction. In this paper, we review the past studies on dispositional effects on nurse’s job satisfaction, particularly in Malaysia and in other societies as well. Keywords: Job satisfaction; Nurse Retention; Nurse Turnover; Intention to leave"

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Background: Nursing is one of the stressful jobs in health sector. The level of job satisfaction in the profession remains a matter of concern. This study means to explore the job satisfaction among the nurses of Dhulikhel Hospital. Methods: A Descriptive cross sectional study design was conducted in Dhulikhel Hospital; a community based Hospital of Kathmandu University from January to December 2009. All the nursing staffs that consented to the study filled up a standard questionnaire. Results: A total of 85 nurses completed the study. The mean age of the respondents' was 23. 80.6% of the nursing staffs were satisfied. "Being considered a resource of health" provided highest sense of satisfaction, while "Lack of opportunities for further education and training" provided lowest sense of satisfaction. Conclusions: Majority of the nurses were satisfied with their present condition of work. Since job satisfaction is a dynamic process, the result may not be static or consistence. Working environment and employees expectations should receive attention. AUTHORS Shrestha GK, Singh B Department of Nursing, Kathmandu University School of Medical Sciences, Department of Nursing, Kathmandu University Dhulikhel Hospital, Dhulikhel.

Journal ijmr.net.in(UGC Approved)

Job satisfaction describes how content a person is with his or her job. There are a variety of factors that influence a person's job satisfaction including levels of pay and benefits, the perceived fairness of the promotion system, working conditions, social relationships and the job itself, the variety of tasks involved, the interest and challenge the job generates and the clarity of the job description. Satisfaction can have a profound influence on organizational success. It can contribute to productive output (for example a high quantity or quality of product or services) and to organizational maintenance, objectives (for example low absenteeism and labour turnover) 1. Turnover and productivity are the important aspects of hospital management, it is worldwide known and proved in several studies that whenever satisfaction of employee's decreases, the turnover rate automatically increases, which directly influences quality care 2. Patients are often heard complaining about doctors and nurses attitudes and service delivery. Cases of negligence against doctors and nurses have been cited in the newspapers and on television, according to various articles and reports; conditions have reached crisis level in public hospitals 3. It is clear that poor attitudes of healthcare professionals can be linked to the low morale and negative outlooks brought on by a lack of job satisfaction. Healthcare professionals complaining of heavier workloads brought about by staff cutbacks and exacerbated by absenteeism and staff losses evidence this dissatisfaction. Unlike traditional job satisfaction surveys, this study tried to explore the correlation between employee's personal profile and their satisfaction in their job. The personal profile determinants which were compared with overall job satisfaction were-age, gender, and marital status. The aim of the study is to determine the factors influencing job satisfaction among healthcare professionals in hospitals.

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Job satisfaction and its related factors: A questionnaire survey of hospital nurses in Mainland China

The widespread nursing shortage is of concern in Mainland China and globally. Factors underpinning the increased mobility of the nursing workforce and their contribution to nurses’ turnover thus merit attention. Understanding nurses’ job satisfaction is important, as this is a key factor in nurses’ turnover.

The study aimed to explore nurses’ views and experience regarding different components of their working lives in Mainland China.

A cross-sectional survey design was selected and 512 nurses working in the medical and surgical departments in two teaching hospitals in Beijing completed questionnaires yielding a response rate of 81%.

More than half of nurses (53.7%; n =275) were satisfied or very satisfied with their jobs and 15% ( n =77) felt moderate to extreme occupational stress. The majority of the sample reported a high level of organizational commitment (63.7%; n =326) and professional commitment (85.9%; n =440) and only 5.9% ( n =30) and 10.0% ( n =51), respectively reported role conflict and role ambiguity often or very often. Nurses with a diploma or associate degree reported greater professional commitment and a lower level of role conflict than those with a bachelor degree ( p <0.05), but there were no significant differences in job satisfaction, organizational commitment, occupational stress and role ambiguity by educational programme ( p >0.05).

Conclusions

Hospital nurses’ positive feelings regarding their working lives may be influenced by developments in the health care system and the nursing profession in Mainland China. Nurses’ educational level is an influencing factor on nurses’ views and experiences of their working lives with the findings suggesting the need to develop a clinical career ladder for nursing staff in Mainland China.

What is already known about the topic?

• The current worldwide shortage of nurses is of great concern and job satisfaction among nurses has been identified as a key factor in nurses’ recruitment and retention.
• Several major factors are associated with job satisfaction of nurses, such as organizational commitment, occupational stress, professional commitment, role conflict and role ambiguity.
• Much research has been conducted on nurses’ job satisfaction and related factors in western countries and some Asian countries.

What this paper adds

• The developments in the health care system and nursing profession could influence nurses’ feelings towards their working lives.
• National culture should be considered in understanding nurses’ views and experiences regarding different components of their working lives.

1. Introduction

The widespread nursing shortage and nurses’ high turnover has become a global issue ( Kingma, 2001 ). The nursing workforce in Mainland China also faces similar challenges in recruitment and retention as a consequence of China entering the World Trade Organization, which has opened their labour market. Job mobility has also been fuelled by more relaxed immigration policies which has meant an increase in the number of Chinese nurses being recruited to western countries where salaries and opportunities are better ( Ho, 1995 ). Recruitment and retention of nurses are persistent problems associated with job satisfaction. There is an urgent need for rigorous research regarding job satisfaction and related factors to inform the development of good nurse employment strategies in Mainland China.

2. Background and literature review

2.1. job satisfaction and its relating factors.

Job satisfaction is defined as all the feelings that an individual has about his/her job ( Spector, 1997 ). Researchers have attempted to identify the various components of job satisfaction, measure the relative importance of each component of job satisfaction and examine what effects these components have on workers’ productivity ( Lu et al., 2005 ).

A range of findings derived from quantitative as well as qualitative studies has been reported in the literature regarding sources of job satisfaction among nurses. These sources include working conditions ( Adamson et al., 1995 ; Nolan et al., 1995 ), interactions with patients/co-workers/managers ( Lee, 1998 ; Aiken et al., 2001 ), work itself ( Lundh, 1999 ; Adams and Bond, 2000 ), remuneration ( Price, 2002 ; Wang, 2002 ), self-growth and promotion ( Tzeng, 2002a , Tzeng, 2002b ), praise and recognition ( Nolan et al., 1995 ; Lundh, 1999 ), control and responsibility (Lee, 1998; Price, 2002 ), job security ( Nolan et al., 1995 , Nolan et al., 1998 ) and leadership styles and organizational policies (Lee, 1998; Tzeng, 2002a , Tzeng, 2002b ).

Job satisfaction among nurses has been identified as a key factor in nurses’ turnover with the empirical literature suggesting that it is related to a number of organizational, professional and personal variables ( Lu et al., 2005 ). Organizational commitment refers to identification with and loyalty to the organization and its goals ( Blau and Boal, 1987 ). Organizational commitment has been found to be positively related to job satisfaction of hospital nurses ( Blegen, 1993 ; Al-Aameri, 2000 ) and could explain 41% of the variance in job satisfaction ( Knoop, 1995 ).

Professional commitment is a person's involvement, pledge, promise or resolution towards his/her profession ( Fang, 2001 ). It has an incremental effect on a person's intention to leave the organization ( Blau and Lunz, 1998 ) and is positively associated with the job satisfaction of nurses ( Lu et al., 2000 ; Jones, 2000 ).

Occupational stress has also been found to be a major factor related to the job satisfaction of nurses ( Blegen, 1993 ) as well as role conflict and role ambiguity ( Tovey and Adams, 1999 ). Role conflict occurs as the nurse attempts to satisfy a number of incompatible demands arising from other people's expectations of his/her role ( Rosse and Rosse, 1981 ). Inadequate or confused information about what work the nurse should cover, the limits of the role and other people's expectations of how the nurse's role fits in with their expectations produce role ambiguity ( Hingley and Cooper, 1986 ).

2.2. Nursing in Mainland China

2.2.1. changes in health care policies.

With ongoing economic reform, China has made some major policy changes in health care. The government has liberalized the private ownership of health facilities and private clinical practices and public hospitals have been partially freed from strict governmental labour market controls ( Ho, 1995 ; Hsiao, 1995 ). Job mobility has become a reality and pressures are building for higher rewards for the country's health care professional workforce ( Ho, 1995 ).

Additionally, nursing model reforms have impacted on the delivery of health care. The patient-centred holistic nursing care model has gradually replaced the traditional disease-centred nursing care model. However, primary nursing has only been introduced in leading hospitals because of the nurse shortage and a lack of appropriate knowledge and skills in the nursing workforce ( Ministry of Health, China, 2003 ).

These developments have coincided with a growing recognition of the professional status of nurses. In the 1980s, the Government reaffirmed that like medicine nursing was an independent profession that required well-qualified personnel with nurses being awarded a protected title by the National Ministry of Health ( Li, 2001 ). At present, there are three levels of basic nursing education in Mainland China: diploma programmes delivered by health schools, associate degree programmes mainly provided by colleges of nursing and bachelor degrees through university-based education.

2.2.2. Nursing shortage and turnover

A nursing shortage has been reported in Mainland China for many years, but in recent years it has become greater. According to the Ministry of Health, China (2003) , the number of registered nurses was 10:10,000 of the population 1997–2002. Further, the turnover of nurses with an associate degree or a bachelor degree is more serious than that of nurses with a diploma ( Wu, 1999 ). It suggests that Mainland China needs to increase the number of nurses, especially well-educated nurses, however, the increased mobility of the nursing workforce is exacerbating the situation and highlights the need to identify factors which contribute to nurses’ turnover ( Lu et al., 2005 ).

While the literature indicates common issues across the world, it is possible that different issues have greater significance in different countries due to the social context of particular labour markets. The current shortage of nurses in Mainland China highlights the importance of understanding nurses’ job satisfaction and related factors so that health care organizations can implement effective interventions to improve the retention of their nursing workforce. The little available research has significant methodological limitations and no research which directly addresses the topic has been conducted in Mainland China ( Yang and Cheng, 2004 ). In consequence, this study addressed an important gap in the available literature.

3.1. Aim and objectives

The study aimed to explore nurses’ views and experiences regarding different components of their working lives in Mainland China. The following objectives were set:

• To describe job satisfaction, organizational commitment, professional commitment, occupational stress, role conflict and role ambiguity of nurses;
• To compare job satisfaction, organizational commitment, professional commitment, occupational stress, role conflict and role ambiguity of nurses across the three educational programmes (diploma, associate degree and bachelor degree programmes).

3.2. Research design and sample

A cross-sectional survey design utilizing questionnaires was selected to fulfil the research objectives. A total population of 632 nurses working in the medical and surgical departments in two teaching hospitals in Beijing were surveyed. Five hundred and twelve nurses completed and returned a self-completed questionnaire representing a response rate of 81% (diploma: n =230, a response rate of 77.4%; associate degree: n =232, a response rate of 82.6%; bachelor degree: n =50, a response rate of 92.6%).

3.3. Instruments

The following instruments were utilized:

Job Satisfaction Scale ( Warr et al., 1979 ): a five-point Likert type scale (1=very dissatisfied, 5=very satisfied) with 15 items. The coefficient alpha was 0.85–0.88 and test–retest correlation coefficient was 0.63 for 6-month period ( Warr et al., 1979 ). The Cronbach's alpha was 0.89 in this study.
Organisational Commitment Scale ( Mowday et al., 1979 ): a five-point Likert type scale (1=strongly disagree, 5=strongly agree) with 15 items. Coefficient alphas ranged from 0.82 to 0.93 with a median of 0.90 and test–retest reliability coefficients were 0.53, 0.63 and 0.75 for 2-, 3- and 4-month periods, respectively ( Mowday et al., 1979 ). The Cronbach's alpha was 0.85 in this study.
Nurses’ Occupational Stress Scale ( Hingley & Cooper, 1986 ): a five-point Likert type scale (1=no pressure, 5=extreme pressure) with 24 items. The Cronbach's alpha was 0.92 in this study.
Professional Identification Scale ( Brown et al., 1986 ): a five-point Likert type scale (1=never, 5=very often) with 10 items. Items analysis of the scale yielded a Cronbach's alpha of 0.71 and factor analysis yielded an oblique solution ( Brown et al., 1986 ). The Cronbach's alpha was 0.82 in this study.
Role Conflict and Ambiguity Scale ( Rizzo et al., 1970 ): a five-point Likert type scale (1=never, 5=very often) with 14 items. Cronbach's alphas were reported 0.816–0.82 for role conflict and 0.78–0.808 for role ambiguity ( Rizzo et al., 1970 ). In this study the Cronbach's alphas were 0.81 and 0.85 for role conflict and ambiguity, respectively.
Biographical details were collected regarding personal profile and included nursing qualifications, length of time working in current hospital and educational level.

3.3.1. Instrument translation

In order to avoid the problems inherent in translation, this study used a combination of Brislin (1970) model for translating and back-translating instruments and committee approach. One bilingual expert translated the instruments from English to Chinese and a second bilingual expert back-translated blindly. A panel of three experts in the area of health care workforce management measured the face validity of the translated questionnaire.

3.4. Ethical considerations and negotiation of access

Ethical approval was gained from the Peking University's Research Ethics Committee. The main ethical issues were respondents’ right to self-determination, anonymity and confidentiality. The questionnaires with a participant information sheet on the nature of the study and a separate envelope were distributed to staff nurses working in medical and surgical departments in two teaching hospitals of Peking University. Completed questionnaires were recruited in sealed envelopes via a collection box places in ward offices. The questionnaire data were kept confidential and respondents were assured of their right to withdraw at any time. The names of the respondents were not recorded on the questionnaire, thus rendering the data anonymous.

3.5. Analysis of data

Data were entered and processed using the Statistical Package for the Social Sciences (SPSS) software, the English version 11.5. This study used descriptive statistics, χ 2 -test and Kruskal–Wallis test to analyse the data.

4. Findings

4.1. characteristics of respondents.

All respondents were female and were predominately between 21 and 35 years old ( n =463, 90.4%), with half being married ( n =256, 50.0%). The majority of respondents had a diploma or associate degree ( n =230, 44.9%, n =232, 45.3%, respectively) while less than 10.0% held a bachelor degree ( n =50, 9.8%). Slightly more respondents worked in medical wards ( n =272, 53.1%) compared with surgical wards ( n =240, 46.9%). Half of respondents had worked in their current hospital for 5 years or more ( n =324, 63.3%). In addition, more than two-thirds of respondents expressed their intention to leave the current hospitals ( n =368, 71.9%), with half reporting that nursing was their first choice of career ( n =278, 54.3%).

More than half of respondents reported that a system of primary care delivery was conducted in their wards ( n =300, 58.6%) while about a quarter reported that team nursing was used ( n =127, 24.8%). The majority of respondents had individualized written nursing care plans for each patient ( n =471, 92.0%) and for common nursing care problems/nursing diagnoses ( n =438, 85.5%). Almost all respondents reported that their hospitals had clearly stated standards and policies for nursing practice ( n =506, 98.8%) while over three-quarters thought that the Ministry of Health also produced such standards and policies ( n =398, 77.7%) and had regulatory power over nurses ( n =389, 76.0%).

Regarding respondents’ characteristics across the three educational programmes, there was a significant difference in age ( p <0.001). Bachelor degree nurses were oldest (mean=32.2 years, SD=5.5), followed by associate degree nurses (mean=28.2 years, SD=5.1), with diploma nurses having the lowest mean age (mean=26.5 years, SD=5.6). Similarly, bachelor degree nurses (mean=11.2 years, SD=6.3) had worked longer in current hospitals ( p <0.001) than associate degree or diploma nurses (mean=8.0 years, SD=5.6; mean=7.0 years, SD=5.6, respectively). Furthermore, the proportion of married nurses in the bachelor degree group (72.0%) was significantly more than that in the associate degree or diploma groups ( p <0.001). More than half of diploma nurses (62.2%) considered nursing as their first career choice, which was significantly higher than that of associate degree (49.1%) or bachelor degree nurses (42.0%). There was no significant difference in nurses’ intention to leave across the three nursing educational programmes ( p >0.05) (see Table 1 ).

Comparisons of characteristics of respondents by educational programme

* p <0.01, ** p <0.001.

4.2. Respondents’ job satisfaction

Regarding overall job satisfaction, more than half of respondents were satisfied ( n =275, 53.7%). Most respondents were satisfied or very satisfied with their immediate manager ( n =416, 81.2%) and their fellow workers ( n =413, 80.7%). On the other hand, almost three quarters of the sample felt dissatisfied or very dissatisfied with the rate of pay for nurses ( n =373, 72.9%) (see Table 2 ).

Frequency and percentage of each item in the job satisfaction scale

Although nurses with a bachelor degree (mean rank=234.92) reported a lower level of job satisfaction compared to those with an associate degree (mean rank=259.98) or diploma (mean rank=257.68), there was no significant difference in total job satisfaction of respondents from the different educational programmes ( p >0.05). However, nurses with a diploma (mean rank=264.05) were more likely to be satisfied with their fellow workers ( χ 2 =10.005, p <0.01) than those with an associate degree (mean rank=259.73) or bachelor degree (mean rank=204.72). Regarding other items of job satisfaction, there were no significant differences across the three nursing programmes ( p >0.05).

4.3. Respondents’ organizational commitment

Almost two-thirds of respondents reported a high-level of organizational commitment ( n =326, 63.7%). More than two-thirds of the sample agreed or strongly agreed that they really cared about the fate of their current hospitals ( n =369, 72.1%) and reported that they were willing to put in a great deal of effort beyond that normally expected in order to help their hospitals be successful ( n =366, 71.5%). Although more than half of the respondents disagreed or strongly disagreed that it would take very little change in their present circumstances to cause them to leave their current hospitals ( n =301, 58.8%) or to decide that working for these hospitals was a definite mistake on their part ( n =297, 58.0%), more than half agreed or strongly agreed that they could just as well be working for a different hospital as long as the type of work was similar ( n =271, 52.9%) (see Table 3 ).

Frequency and percentage of each item in the organizational commitment scale

There were no significant differences in total organizational commitment ( p >0.05) although nurses with a bachelor degree reported a lower level (mean rank=242.46) compared to those with an associate degree (mean rank=260.51) or diploma (mean rank=255.51). However, diploma nurses (mean rank=272.87) were more likely to agree that they would accept almost any type of job assignment in order to keep working for their current hospitals ( χ 2 =6.378, p <0.05) than those with an associate degree (mean rank=246.13) or bachelor degree (mean rank=229.34). In addition, diploma nurses (mean rank=240.40) were more likely to report that it would take very little changes in their present circumstances to cause them to leave their current hospitals ( χ 2 =7.171, p <0.05) compared to associate degree (mean rank=273.23) or bachelor nurses (mean rank=252.91). There were no significant differences in other items of organizational commitment across the three educational programmes ( p >0.05).

4.4. Respondents’ occupational stress

Just under two-thirds of respondents reported experiencing light to moderate stress at work ( n =311, 60.8%) while one-quarter reported no to light stress ( n =124, 24.2%), followed by less than one-sixth reporting moderate to extreme stress ( n =77, 15.0%). Scores of moderate to extreme stress reported by respondents related to workload ( n =398, 77.8%), time pressures and deadlines ( n =335, 65.4%), difficult patients ( n =309, 60.4%), staff shortages ( n =308, 60.1%) and involvement with life and death situations ( n =276, 53.9%) (see Table 4 ).

Frequency and percentage of each item in the occupational stress scale

There were no significant differences in total occupational stress across the three educational programmes ( p >0.05), although nurses with an associate degree (mean rank=260.05) reported experiencing more stress than those with a bachelor degree (mean rank=253.52) or diploma (mean rank=253.57). However, bachelor degree nurses (mean rank=292.63) were more likely to report experiencing stress regarding time pressures and deadlines ( χ 2 =6.738, p <0.05) than diploma (mean rank=263.78) or associate degree nurses (mean rank=241.50). Similarly, bachelor degree nurses (mean rank=284.05) were more likely to report experiencing stress regarding uncertainty about the degree or area of their responsibilities ( χ 2 =10.259) than associate degree (mean rank=271.92) or diploma nurses (mean rank=234.95).

In addition, regarding poor quality of supporting staff bachelor degree nurses (mean rank=281.30) were also more likely to report experiencing stress ( χ 2 =6.522, p <0.05) than associate degree (mean rank=268.10) or diploma nurses (mean rank=239.41). However, bachelor degree nurses (mean rank=189.45) were less likely to report experiencing stress regarding security of employment ( χ 2 =17.889, p <0.001) than associate degree (mean rank=248.08) or diploma nurses (mean rank=279.57). Regarding other aspects of stress, there were no significant differences across the three programmes ( p >0.05).

4.5. Respondents’ professional commitment

Most respondents reported a high-level of professional commitment ( n =440, 85.9%). The majority of respondents reported that they never or seldom: tried to hide belonging to the nursing profession ( n =466, 91.0%), were annoyed to say that they were members of the nursing profession ( n =416, 81.3%) or criticized the nursing profession ( n =398, 77.8%). However, only one-third reported that they were glad to belong to the nursing profession often or very often ( n =167, 32.6%) (see Table 5 ).

Frequency and percentage of each item in the professional commitment scale

Nurses with a bachelor degree (mean rank=204.30) reported a lower level of professional commitment ( χ 2 =8.323, p <0.05) compared to those with an associate degree (mean rank=254.03) or diploma (mean rank=270.33). Bachelor degree nurses (mean rank=190.11) were more likely to criticize the nursing profession ( χ 2 =12.788, p <0.01) than associate degree (mean rank=262.76) or diploma nurses (mean rank=264.62). In contrast, diploma nurses (mean rank=268.27) were more likely to be glad to belong to the profession ( χ 2 =7.765, p <0.05) than associate degree (mean rank=255.57) or bachelor degree nurses (mean rank=206.69). There were no other significant differences relating to other items of professional commitment across the three programmes ( p >0.05).

4.6. Respondents’ role conflict and role ambiguity

The majority of respondents reported a low-level of role conflict and role ambiguity ( n =482, 94.1%; n =461, 90.0%, respectively). More than three-quarters of respondents never or seldom had to ‘buck’ a rule or policy in order to carry out an assignment ( n =439, 85.7%), had worked with two or more groups who operated quite differently ( n =391, 76.4%) or received incompatible requests from two or more people ( n =380, 74.2%). Almost four-fifths of respondents reported that they knew often or very often what their responsibilities were ( n =447, 87.3%). Around three-quarters of respondents reported feeling certain about how much authority they had and felt that they had clear, planned goals and objectives for their jobs ( n =391, 76.4%; n =374, 73.1%, respectively) (see Table 6 ).

Frequency and percentage of each item in the role conflict and role ambiguity scale

Nurses with a bachelor degree (mean rank=298.81) reported greater role conflict ( χ 2 =6.174, p <0.05) compared to those with an associate degree (mean rank=260.63) or diploma (mean rank=243.13). There were no significant differences in role ambiguity across the three programmes ( p >0.05). Bachelor degree nurses (mean rank=286.26) were more like to report receiving incompatible requests from two or more people ( χ 2 =6.568, p <0.05) than associate degree (mean rank=266.22) or diploma nurses (mean rank=240.22). Bachelor degree nurses (mean rank=294.57) were also more likely to report doing things that were likely to be accepted by one person and not accepted by others ( χ 2 =7.591, p <0.05) than associate degree (mean rank=263.82) or diploma nurses (mean rank=240.84).

In addition, bachelor nurses (mean rank=307.08) were more likely to report receiving an assignment without adequate resources and materials to execute it ( χ 2 =10.810, i <0.01) than associate degree (mean rank=263.41) or diploma nurses (mean rank=238.54). Regarding other items of role conflict and role ambiguity, there were no differences across the three programmes ( p >0.05).

5. Discussion

The sample in this local questionnaire survey was limited to nurses working in teaching hospitals in Beijing. Thus, the generalization of the findings needs to be treated with caution.

5.1. Hospital nurses’ job satisfaction

In contrast to Wang's (2002) survey of nurses working in a hospital in Beijing where nurses reported more dissatisfaction than satisfaction, the study found that more than half of respondents were satisfied with their jobs ( n =275, 53.7%). Interestingly, this study's findings are similar to those of other studies of the job satisfaction of nurses in the USA ( Blau and Lunz, 1998 ; Aiken et al., 2001 ), the UK ( Price, 2002 ), Singapore ( Fang, 2001 ), Hong Kong ( Siu, 2002 ) and Taiwan ( Lu et al., 2002 ; Tzeng, 2002a ) despite the health care systems being very different from that of Mainland China.

A possible explanation for such similarity may lie with changes in the labour market in Mainland China, which has become more open during the last 5 years and increasingly similar to that in western countries. An open labour market has brought new pressures and challenges for hospital managers. Nurses’ job satisfaction has received increasing attention and enhancing nurse job satisfaction has been emphasized as a major strategy to recruit and retain qualified nurses ( Sun et al., 2001 ; Bao et al., 2004 ).

It is also possible that the development of nursing, particularly the adoption of the patient-centred primary nursing care model has had an effect on nurses’ job satisfaction ( Bond et al., 1990 ; Thomas and Bond, 1991 ). In Mainland China primary nursing has experienced more than 10-years of development mainly in leading hospitals ( Ye et al., 1999 ), which include the data collection sites in the study.

5.2. Hospital nurses’ organizational commitment

The findings of nurses’ strong organizational commitment in the study is inconsistent with Knoop's (1995) survey in Canada, which found that nurses had a low level of organizational commitment. However, most of the study's respondents expressed their intention to leave their current hospitals. Such ambivalent findings might be explained by the influence of culture. Glazer et al. (2004) have suggested that people's understanding of organizational commitment could be affected by their national culture. Chang (1999) further pointed out that employees in Asian countries are more likely than employees in Western countries to expect job security from their employers as part of their psychological contract of employment. These employees, in turn, are more committed when they feel that their employers have fulfilled this commitment.

Therefore, nurses’ high level of commitment to their hospitals does not remove the potential of turnover. Indeed, organizational commitment due to the communal nature of a culture may not contribute to nurses’ retention, as nurses are encouraged to build up an equally strong commitment to their new organization following a job change.

5.3. Hospital nurses’ occupational stress

Two-thirds of respondents reported slight to moderate pressure relating to occupational stress ( n =311, 60.8%), which is similar to the findings in Dailey's (1990) study in the USA and Fang's (2001) study in Singapore. Cox (1987) suggested that stress resides in the person's perception of the balance or transaction between the demands on him/her and his/her ability to cope with these. Thus occupational stress exists in people's recognition of their inability to cope with demands relating to work ( Cox, 1985 ) and the findings suggest that the majority of the sample had the abilities to cope with the work demands placed upon them.

Hingley and Cooper (1986) pointed out that for all individuals competence is a primary need at work, with incompetence being a major source of job stress due to its thwarting the individual to perform effectively or to feel effective. Nurses’ improved professional competence might therefore be associated with their lower occupational stress. In this study, some characteristics of the respondents including age, length of working time and educational level may be a proxy of their higher professional competence. For example, half of respondents had worked in their current hospital for 5 years or more ( n =324, 63.3%). In general, they were proficient in nursing techniques and skills and were able to resolve problems independently at work. Further, most respondents were 35 years old or younger ( n =473, 92.4%) and half had an associate degree or bachelor degree ( n =282, 55.1%). Therefore, it is possible that they had abilities to cope with new situations and technology.

Another possible explanation lies with respondents’ good interpersonal relationships at work. For example, most respondents reported that they were satisfied or very satisfied with their fellow workers ( n =413, 80.7%) and immediate manager ( n =416, 81.2%). The nature and quality of relationships at work has been identified as a major source of occupational stress ( Greenburg, 1980 ). Hingley and Cooper (1986) also suggested that poor relationships with colleagues and superiors are an important source of stress for nurses. This was highlighted in Bradley and Cartwright (2002) study which found that nurses who perceived more support from managers were less likely to experience job stress ( r =−0.12, p <0.05) although the extent to which this applies to Mainland China is uncertain as no equivalent research has been published regarding Chinese nurses.

Regarding the main stressors, such as workload, time pressures and deadlines and staff shortages, the findings are consistent with previous studies in China ( He et al., 2001 ; Dai and Wang, 2002 ; Zhao et al., 2002 ). Furthermore, nurses’ workload has also been emphasized as a major work-related stressor in similar studies conducted in other countries ( Aiken et al., 2001 ; Lambert et al., 2004 ; Khowaja et al., 2005 ). It is possible that the current global nursing shortage might increase nurses’ workload and China is not an exemption from this challenge ( Gong, 1996 ).

5.4. Hospital nurses’ professional commitment

The finding of the respondents’ strong commitment to the nursing profession is consistent with that in Taiwan ( Lu et al., 2002 ). This is possibly associated with a number of factors, including: recognition of the value of the nursing profession, increasing professional status and increasing academic professional activities.

People can develop devotion to their profession if they think that the profession is valuable ( Altschul, 1979 ). Nurses, in some respects, embody the absolute moral worth of the person who gives unselfish and devoted care and in return receives a high regard in society. In Mainland China nurses are often referred to as ‘White Angels’ for their contributions to human health with nurses’ work during the period of the outbreak of Severe Acute Respiratory Syndrome (SARS) in 2003 reaffirming the value and importance of the nursing profession ( Liu et al., 2004 ).

Additionally, the Chinese government's recognition of nursing as an independent profession and the development of university degree nursing programmes have undoubtedly facilitated an increasing professional status ( Li, 2001 ). Increased academic activities such as seminars or workshops also enhance nurses’ engagement in their professional roles and influence their attitude towards the nursing profession, which in turn can promote a stronger professional commitment ( Lu and Chiou, 1998 ).

5.5. Hospital nurses’ role conflict and role ambiguity

The majority of the respondents reported a low level of role conflict and role ambiguity, which is similar to Seo et al.'s (2004) findings in South Korea, but contrasts with Dailey's (1990) study in the USA. Such findings in the study may reflect compatible demands from nurse educators, colleagues and nursing managers resulting in clear and sufficient information about working responsibilities. It is possible that the majority of respondents graduated from the same educational institution to which their hospitals were affiliated so that the nurse educators, colleagues and hospital managers of the respondents held similar values and principles regarding nurses’ roles, thus reducing the potential for role conflict ( Hingley and Cooper, 1986 ). In addition, in 1982, the Ministry of Health, China published ‘Working Responsibilities of Health Care Personnel in Hospitals’ which set out the working roles of staff nurses, health care assistants, doctors and other health care personnel. Although some reforms in nursing have occurred, this guide has not been modified and has been widely implemented in hospitals across Mainland China so that the opportunities for role overlap and conflict may been minimized in consequence.

5.6. The impact of nurses’ educational level upon their working lives

The findings of significant differences in nurses’ role conflict and professional commitment across the three educational programmes (diploma, associate degree and bachelor degree) suggest primary differences arising from the impact of education ( p <0.05). Such findings may be explained by the bachelor degree nurses’ higher role expectations. The knowledge enrichment of the university-educated nurses may yield a broader perspective and a higher expectation of their working roles compared to that of diploma and associate degree nurses ( Wetzel et al., 1989 ). However, the bachelor degree nurses’ role perception is not dominant in a nursing workforce as they only represent a minority with about 5% of registered nurses in 2002 having a bachelor degree in China ( Jiang et al., 2004 ). This study found even in the teaching hospitals in Beijing, as the highest health care institutes, less than 10% of nurses had a bachelor degree. Additionally, in hospitals, the bachelor degree staff nurses assume the same roles and tasks as those with a diploma or associate degree ( Yang and Cheng, 2004 ), which may increase the bachelor degree nurses’ role conflict arising from the different role expectations and task requirements from universities, hospitals, peers and themselves.

The bachelor degree nurses’ weaker professional commitment is similar to Lu and Chen's (1999) local survey. One possible explanation is that well-educated nurses are more likely to experience the conflict between their role expectations and actual working roles. Indeed, Jing (2000) has suggested that such a conflict could result in bachelor degree nurses not feeling that they belong to the nursing profession.

Another possible explanation is that the bachelor degree nurses may have a stronger intention to leave the nursing profession. Bartlett et al. (1999) found that graduates were less confident in their initial decision to enter the nursing profession compared with diplomats. Similarly, Lu and Chen (1999) found that half of nursing undergraduates disliked or strongly disliked the nursing profession with most of them reporting that they intended to change to another career.

The findings indicate that there were no significant differences in total job satisfaction of nurses across the three educational programmes ( p >0.05). This finding is inconsistent with previous studies, which found that nurses with a higher educational level were less likely to be satisfied with their job ( Lu et al., 2002 ; Chu et al., 2003 ).

Part of the explanation for this finding may rest with the interrelationships between age, working years, marital status and job satisfaction. For example, Blegen's (1993) meta-analysis found that nurses who were older and had longer working experiences were more likely to be satisfied with their job. Yin and Yang (2002) also found that married nurses were more satisfied with their job than those who were unmarried. In this study, nurses with a bachelor degree were significantly older and had more working experience than nurses with a diploma or associate degree ( p <0.001). Additionally, most of the nurses with a bachelor degree were married ( p <0.001). It is possible that these respondent characteristics had an impact on the relationship between job satisfaction and educational level.

The findings indicate that there were no significant differences in organizational commitment, occupational stress and role ambiguity across the three educational programmes ( p >0.05). This may be the result of the limited sample size of bachelor degree nurses ( n =50) so that further research with a larger sample with different educational background is needed to explore these issues. Another possibility is that regardless educational level, the staff nurses in the study assumed similar roles and responsibilities, which were clearly described in hospital guideline. In these circumstances a significant difference in nurses’ role ambiguity across the three educational programmes would not be expected.

6. Conclusion

The findings in the study indicate that the hospital nurses in this study had a positive feeling towards their working lives in Mainland China. This may be a reflection of the developments in the health care system and nursing profession. But it is worthwhile to note that nurses’ intention to leave is still a serious problem and warrants more attention. International migration of nurses has increased as nurses pursue opportunities for improved pay and opportunities in the wake of global liberalization of trade spurred on by developed countries increasing their international recruitment to meet their health care workforce needs and in doing so creating a ‘skills drain’ in many developing countries ( Kingma, 2001 ). One might expect to observe dissatisfaction with changes in education with the influence of American curricula and higher education and limited changes to the nurse's role in the guideline established by the Ministry of Health, China, but it is likely that those experiencing greatest dissonance between the expectations and reality of their role will have entered the global labour market and such individuals would not have been recruited to this study. Further research is needed to test the impact of educational level upon job satisfaction, occupational commitment, occupational stress and role ambiguity using other samples.

The study also indicates that the bachelor degree nurses had weaker professional commitment and a higher level of role conflict. It is suggested that nurses’ educational background should be considered an important factor in understanding nurses’ working lives and may indicate the need for a clinical career ladder for nursing staff in Mainland China. Such a ladder, which uses a grading structure to facilitate career progression by defining different levels of clinical and professional practice in nursing, has been successfully introduced in other countries such as the UK ( Buchan, 1999 ). Further, Krugman et al.'s (2000) work in the USA found that the use of a clinical ladder facilitated nurses’ professional development, strengthened their organizational commitment and increased their job satisfaction in a study evaluating 10 years of progressive change.

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ORIGINAL RESEARCH article

Effective analysis of job satisfaction among medical staff in chinese public hospitals: a random forest model.

Department of Health Service Management, Humanities and Management School, Zhejiang Chinese Medical University, Hangzhou, China

Objective: This study explored the factors and influence degree of job satisfaction among medical staff in Chinese public hospitals by constructing the optimal discriminant model.

Methods: The participant sample is based on the service volume of 12,405 officially appointed medical staff from different departments of 16 public hospitals for three consecutive years from 2017 to 2019. All medical staff (doctors, nurses, administrative personnel) invited to participate in the survey for the current year will no longer repeat their participation. The importance of all associated factors and the optimal evaluation model has been calculated.

Results: The overall job satisfaction of medical staff is 25.62%. The most important factors affecting medical staff satisfaction are: Value staff opinions (Q10), Get recognition for your work (Q11), Democracy (Q9), and Performance Evaluation Satisfaction (Q5). The random forest model is the best evaluation model for medical staff satisfaction, and its prediction accuracy is higher than other similar models.

Conclusion: The improvement of medical staff job satisfaction is significantly related to the improvement of democracy, recognition of work, and increased employee performance. It has shown that improving these five key variables can maximize the job satisfaction and motivation of medical staff. The random forest model can maximize the accuracy and effectiveness of similar research.

The loss and lack of medical staff is becoming a global problem ( 1 ). It is crucial to improve the quality of life and health of patients through a large and stable medical service team ( 2 ). The dense urban population has accelerated the spread of respiratory infectious diseases such as COVID-19, posing new challenges to the prevention and control of public health emergencies ( 3 , 4 ). Indeed, The rapid realization of urban–rural integration also requires more medical services and support in China ( 5 ). Due to the continuous prevalence of the virus and the unsafe medical environment, medical workforce continue to drain in the post-epidemic era ( 6 ). The aging of the population and the decline of the birth rate have to some extent exacerbated the shortage of medical labor force in China ( 7 ). Meanwhile, Rural and urban areas have gradually become a medical service community with the implementation of graded diagnosis and treatment in a certain geographical range in China ( 8 ). High-quality medical and health resources will sink and radiate to surrounding areas through central cities ( 9 ). Therefore, this is a priority to retain public medical staff, especially the urban medical workforce.

Since the reform of China’s medical and health system in 2009, which established and improved the basic healthcare system covering urban and rural residents. China has expanded the coverage of basic medical insurance, implemented the reform of Diagnosis Related Groups (DRG) payment method and implemented the centralized purchase of drugs ( 10 – 12 ). The coverage of medical services has been continuously improved and the difficulty of seek medical services and cost of personal medical treatment have been effectively alleviated. It is easier for people to obtain safe, effective, convenient and inexpensive medical and health services along with the informatization construction of the hospital. Some scholars have systematically evaluated the satisfaction of burn patients and further found that the quality of care of medical workers can significantly improve patient satisfaction ( 13 ). Zhou et al. explored the association between patient satisfaction and nursing compliance and trust of medical workers of Chinese hypertensive patients ( 14 ). Moreover, Li et al. confirmed that the medical service quality of medical staff is the main factor affecting patient satisfaction from the perspective of inpatients ( 15 ). Of course, the implementation of a series of health reform policies not only reduces the economic burden of patients, but also greatly affects the income level of medical staff ( 16 – 18 ). The diversification of individual medical service needs is also increasing the daily workload of medical staff. At the same time, the demand for high-quality medical services has also increased the work difficulty of medical workforce ( 19 , 20 ). Some studies have found that poor working environment and large workload will aggravate the job burnout of medical staff, and lead to resignation ( 21 , 22 ). On the contrary, medical staff with higher job satisfaction tend to provide higher quality medical services and can effectively avoid medical accidents ( 23 , 24 ). The current studies are more biased toward the patient’s medical experience and thus ignores the work experience of medical staff ( 25 ). Therefore, this is of great significance for improving the accessibility of medical services and maintaining social stability by exploring the current situation and associated factors of staff job satisfaction in public hospitals in China.

Building an optimal calculation model is the prerequisite for influencing factor analysis, which is crucial to ensure the robustness and accuracy of the analysis results. Multiple logistic regression models are widely used in related research due to their relatively simple theoretical assumptions ( 26 ). Regression models have greater advantages over OLS models in probability prediction ( 27 ). Li et al. analyzed the influencing factors of patient satisfaction through a multiple logistic regression model ( 28 ). Zhou et al. used a multi-level logistic regression method to test the associated factors of job satisfaction among medical personnel in 2018 ( 29 ). As one of the most widely used linear regression analysis models, the accuracy of the analysis results obtained by multiple regression models remains to be discussed due to the possible natural defects of collinearity sensitivity between independent variables. And then, logical regression models cannot properly handle massive multi-category variables. Hence, it is necessary to introduce discriminant analysis models into current research. The naive Bayesian algorithm is based on the posterior probability thinking of classical mathematical theory to establish models, greatly optimizing the complexity of traditional Bayesian algorithms in the calculation process ( 30 ). The discriminant algorithm logic assumes that the attributes of the dataset are independent of each other, which exhibits strong stability and consistency for different datasets. Bai et al. used naive Bayesian models to accurately classify different water sources subject to weather interference in the environmental field ( 31 ). Some scholars predicted that the physical behavior of patients with COVID-19 by using the naive Bayesian model ( 32 ). similarly, the random forest algorithm has gradually become a widely recognized classification algorithm by combining classification tree models. Random forest model have strong adaptability because of Strong adaptability ( 33 ). Random forest model reduce the risk of over fitting in the calculation process by improving the generalization ability. Some scholars have applied random forest models to studies on disease risk assessment, tumor diagnosis, and postoperative prognosis ( 34 – 36 ). Other scholars have explored disease risk prediction, diagnosis, and classification through random forest models ( 37 – 39 ). Compared to traditional methods, these two classification algorithms are praised as one of the best currently available algorithms, which are not susceptible to environmental noise and can well predict ample of explanatory variables.

In recent years, K-Nearest Neighbor (KNN) algorithms have gradually been widely used in different fields. Some scholars have conducted study on the prevention and control of agricultural diseases and insect pests through the KNN algorithm for disease identification ( 40 ). Other scholars have explored the use of KNN algorithms for disease prediction in the medical field ( 41 ). KNN algorithm, a Simple Classification Algorithm, does not need to estimate parameters, but the calculation amount is relatively large when the heterogeneity between samples is large. Meanwhile, the Gradient Boosting Decision Tree (GBDT) algorithm can optimize the model by using an additive model and a forward step algorithm ( 42 ). Some scholars have used GBDT algorithm to effectively predict the employability of graduates in the internship environment ( 43 ). A European study effectively predicted the impact of psychosocial factors on quality of life in older adults people through machine learning algorithms ( 44 ). Machine learning algorithms are being used by more and more scholars in the field of public health. Unfortunately, there are few studies exploring the optimal evaluation model for medical staff job satisfaction. Therefore, we attempt to incorporate the above algorithms into model comparisons in order to obtain more accurate analysis results.

This paper aims to explore the associated factors and best evaluation models of staff job satisfaction in Chinese public hospitals. And we attempt to identify strategies to improve job satisfaction among public medical staff based on empirical research results.

Sample and methods

Ethics statement.

This study was approved and supported by the Zhejiang Provincial Health Commission, and the investigation was conducted after obtaining the consent and support of the relevant heads of 16 hospitals. All participating medical staff signed an informed consent form before filling out the questionnaire. This job satisfaction survey is anonymous and the content filled in is completely confidential.

Study design and samples

The survey was conducted from December 12, 2017 to January 13, 2020, involving 16 provincial public hospitals in Zhejiang, including 7 general hospitals, 5 specialized hospitals, 2 traditional Chinese medicine hospitals, and 2 integrated traditional Chinese and western medicine hospitals. We conduct an annual survey and determine the sampling quantity based on the business volume of different departments in each public hospital. All medical staff who participated in the survey that year will no longer undergo repeated sampling. A total of 12,405 valid questionnaires were obtained for medical staff. A self-designed medical staff job satisfaction survey questionnaire was used, with a total of 31 related indicators, including 6 sociodemographic factors and 25 hospital factors. The reliability and effectiveness of the questionnaire content are determined through expert consistency evaluation, which can ensure the authority and scientificity of the questionnaire. The consistency test results of the questionnaire indicate that the Cronbach’s Alpha coefficient is 0.944, indicating high reliability of the questionnaire.

Method of investigation

The outcome variables (medical staff job satisfaction) and explanatory variables of this paper are based on the Likert five level scoring method, with scores of 1 being very dissatisfied, 2 being not very satisfied, 3 being average, 4 being relatively satisfied, and 5 being very satisfied. And further simplify it into two categorical variables: combine “very satisfied” and “relatively satisfied” to “satisfied” (with a value of 1); The other answer combination is ‘dissatisfied’ (value 0). Missing and abnormal values are assigned a value of 99 and removed in subsequent data analysis. The data analysis was completed using SPSS 22.0 and R3.6.1 software.

Sample quality control

The minimum sample size required first has to be determined before the statistical model is established. The sample size calculation is shown in Formula 1 :

Where n is the sample size, Z α / 2 value is 1.96 typically, p is the overall staff job satisfaction rate and δ is the desired level of precision. And then, we assumed 95% confidence and 5% precision. The overall staff job satisfaction in this study is 25.62%. Therefore, the minimum sample size was: n = 1.96 2 ∗ 0.2562 ∗ 1 − 0.2562 0.05 2 ≈ 293 . The number of effective simple in this paper is 12,405, which is far greater than the minimum sample size required.

Multiple logistic regression

Logistic regression model is one of the supervised algorithms, which adds a sigmoid function to classify based on linear regression and sets a threshold value to map the results to the (0, 1) interval.

Further, when the mapping value is greater than the threshold value, it is classified as 1, and when the mapping value is less than the threshold value, it is classified as 0. In this study, we first conducted a single factor analysis of the explanatory variables. Indeed, the influencing factors with statistical differences ( p < 0.05) were included in the multiple logistic regression model based on the single factor analysis results. The calculation is shown in Formula 2 :

The probability prediction formula for employee job satisfaction is shown in Formula 3 :

Where P and 1 − P are the probabilities of overall job satisfaction and dissatisfaction by medical staff; n is the number of independent variables; β i presents the regression coefficient of each associated factor; x i present different independent variables and ε is a random interference term.

Gradient boosting decision tree algorithm

GBDT is an efficient decision tree algorithm that combines weak prediction models to obtain stronger prediction models ( 45 ). Specifically, CART regression trees are used to generate weak models by defining loss functions, and then the defined loss function is optimized by pre ordering and adding regular terms to achieve algorithm improvement. The specific construction method of the model is as follows:

Firstly, we construct the medical staff job satisfaction dataset D. As shown in Formula 4 :

Where x i and y 1 are explanatory variables and outcome variables. Training set D and fit it a weak learner model f 1 x .

Secondly, calculating the negative gradient of the loss function for each sample and generate a new dataset D ′ . As shown in Formulas 5 and 6 :

Thirdly, we can obtain the regression tree f K x by using the new dataset D ′ . As shown in Formulas 7 and 8 :

Where M is the node of the leaf of the tree; Q present the total value range of M ; n represents the number of samples per leaf node.

Finally, the optimized model is obtained through K-round iteration. As shown in Formula 9 :

Naive Bayesian algorithm

Naive Bayesian algorithm is a relatively stable classification algorithm based on Bayesian theorem ( 46 ). Firstly, the joint probability distribution of the sample set is trained, and then the output model with the maximum posterior probability is obtained based on the training results. The naive Bayesian algorithm combines a priori and a posteriori probability, which avoids the subjective bias of using only a priori probability and avoids the over fitting phenomenon of using sample information alone ( 47 ). Especially when the data set is large, it shows a high accuracy rate. We define staff job satisfaction data training sets X Y , where each sample X = x 1 , x 2 , x 3 , … , x n and K categories Y = y 1 y 2 y 3 … y k . The calculation process is shown in Formula 10 :

Formula 12 is the final form of Formula 10 .

Specially, the number of parameters ( k ∏ i = 1 n S i ) can be reduced to ∑ i = 1 n S i k through Formula (11) . Where P y k | x is optimal posterior probability, P x | y k means conditional probability, k is the number of categories and S i means the number of x i .

The final classification model is shown in Formula 13 :

K-nearest neighbor algorithm

KNN algorithm is also a classification algorithm in supervised learning ( 48 ). This algorithm classifies the closest samples in the feature space into one category. At present, Euclidean distance is the most commonly ranging method. The calculation progress of Euclidean distance is as Formula 14 :

Generally, a suitable k value is selected through cross validation based on the distribution of samples. Then return to the category with the highest frequency of occurrence of the first k points as the optimal prediction classification.

Random forest algorithm

Random forest model is an excellent bagging ensemble algorithm that fits the optimal multi-classification combination model through comprehensive comparison of random features based on a decision tree. The formula for calculation is as follows:

Firstly, we divide the data set D ( Formula 15 ) into a training set A (70% of the data is used to build the model) and a test set B (30% of the data is used to fit the optimal model).

Secondly, we use training set data A to construct the basic learning algorithm h . As shown in Formula 16 . Then, the out-of-bag estimate ( oob ) of was calculated by B through Formula (17) .

Finally, a classification model with the best fit degree is calculated through Formula (18) :

Where T is number of base learning algorithms, A b s is sample distribution of training set data, H o o b x is the combined classifier model and I ∗ is an indicator function.

In order to further explore the degree of influence between explanatory variables, we calculated the importance of different independent variables through Gini coefficient in the model. As shown in Formula 19 :

Finally, all calculated importance scores are normalized through Formula (22) :

Where K is the number of categories, p m k is the proportion of category k in node m . G I l and G I r represent the Gine coefficient of the two new nodes after branching. And V I M j is the importance score of the j th characteristic was caculated through Formulas (20 , 21) .

Building an optimal evaluation model

This paper incorporates as many mainstream classification and discrimination models as possible. We attempt to ensure the accuracy of the results and calculate the best evaluation model by comparing five models: Multiple logistic regression model, GBDT algorithm, Naive Bayes algorithm, KNN algorithm, and Random forest algorithm.

Generally speaking, the effectiveness of models are comprehensively judged by five indicators: Accuracy, Classification, Precision, Recall, and F1_Score. Indeed, we visualize the classification effects of different machine learning algorithms by drawing receiver operating characteristic (ROC) curves. And we use AUC (Area Under Curve) to determine the accuracy of the model through Formula (23) :

Where M is the number of positive samples; N is the number of sub samples.

Overall description of the analysis

The results showed that the overall job satisfaction rate of staff in large public hospitals was low (25.62%), while the job satisfaction rate of male staff was significantly higher than that of female staff. In particular, the proportion of female staff among all staff is 72.04%. The reason may be that the daily medical work of public hospitals requires a large number of female nursing staff. At the same time, the proportion of staff with bachelor’s degree or above in this study is 99.61%, with the highest proportion of master’s degree students (42.36%). As a result, medical staff are over 30 years old. Interestingly, almost all medical staff have been assessed with relevant professional titles (95.98%), with primary and lower professional titles accounting for 40.9%. The proportion of years of service between 10 and 15 years is the largest (25.32%). And the compliers accounts for 92%.

Single factor analysis of medical staff job satisfaction

The analysis results showed that there were significant differences in the job satisfaction of medical staff among sociodemographic factors such as gender, age, educational background, professional title, years of service, Compilers, and almost all hospital factors ( p < 0.05). As shown in Table 1 . Specially, Age, Professional title, Years of service, Interested in work, Time Freedom, and competence for this job are all protective factors for medical staff job satisfaction. Meanwhile, most other variables are associated factors.

Table 1 . Results of the multivariate analysis.

Multiple logistic regression analysis of medical staff job satisfaction

We included independent variables with significant statistical differences in univariate analysis into a multiple logistic regression model. The results showed that the multiple logistic regression results of medical staff job satisfaction are basically consistent with the results of random forest. There is a wide gap between Gender and Educational background. The results showed that almost all hospital factors were closely related to the improvement of medical staff job satisfaction ( p < 0.05) and were consistent with the results of random forest analysis. In particular, low levels of education are significantly related to medical staff job satisfaction, without the need to achieve the highest level of education, such as Doctors. As shown in Table 2 .

Table 2 . the results of multivariate logistic regression.

Optimal evaluation model

We calculated the accuracy and ROC curves of different models to compare the robustness of different models. The results show that random forests rank first in Accuracy and AUC, with the most accurate prediction effect. Figure 1 shows the ROC curves of the five models, with the results ranked in the order of Random forest (0.9713), KNN (0.9579), GBDT (0.9520), logical regression (0.9478) and Naive Bayesian (0.9378), with the Random forest model performing best.

Figure 1 . Receiver operating characteristic curves of five classification models.

Table 3 shows that all models have achieved good results. The random forest model is superior to KNN, GBDT, logistic regression model, and naive Bayesian model in accuracy index. The random forest model has the highest evaluation effect and the best performance effect in this study. With good practicality and flexibility, random forest models can not only make high-precision classification decisions, but also calculate the importance of each variable.

Table 3 . Comparison of evaluation effects of different evaluation models.

Importance of different explanatory variables

We plotted the importance ranking diagram of all explanatory variables through a random forest algorithm. As shown in Figure 2 . Value staff opinions (Q10), Get recognition for your work (Q11), Democracy (Q9) and Performance evaluation satisfaction (Q5) rank in the top 4 among all variables.

Figure 2 . Importance ranking chart of influencing factors.

Conclusion and discussion

In this study, we evaluated the effectiveness of five widely used models, including logistic regression, Random forest, Naive Bayesian, GBDT, and KNN. The results showed that the random forest model ranked first in accuracy and roc curve in this study. Therefore, we constructed an optimal evaluation model and explored the key variables that affect medical staff job satisfaction in Chinese public hospitals. Further, we can adopt the most appropriate strategies to improve the challenges faced by medical staff. This study shows a weak association between sociodemographic factors such as gender, age, educational background, and medical staff job satisfaction, which is consistent with previous studies ( 49 ). This further confirms that although factors such as age and educational background are the key to entering a hospital job, the key to ensuring high job satisfaction among medical staff lies more in the job itself. Interestingly, Compilers is not a key variable in staff job satisfaction in large public hospitals. Value staff opinions (Q10), Get recognition for your work (Q11), Democracy(Q9) and Performance evaluation satisfaction(Q5) are the four most important key factors that affect the satisfaction of medical staff, which provide a neglected perspective for improving the enthusiasm of medical staff in past research. This may be an effective way to improve medical staff satisfaction by weakening the direct authority of organizational leaders and paying more attention to the medical services provided to patients.

The evaluation and prediction of staff in Chinese public hospitals is very important due to undertaking major diagnostic treatment and the promotion and application of the most advanced medical technology ( 50 ). Furthermore, large public hospitals are the leaders of medical service complexes within a certain geographical range ( 51 ). This paper make some contribution from the following aspects. Firstly, the rapid changes in the disease spectrum and the rapidly increasing demand for individual medical services not only directly increase the difficulty of medical services, but indirectly increasing the challenges faced by medical staff. Few studies have explored the key factors from the perspective of medical staff, and we have conducted in-depth analysis of this. A large number of studies have confirmed the positive indirect role played by medical workers inpatient rehabilitation. Meanwhile, job satisfaction, occupational well-being and harmonious doctor-patient relationships all positively affect the work quality of medical staff ( 52 ). In addition, this is an effective measure to promote medical staff to actively provide high-quality services to effectively identify key variables that affect medical staff job satisfaction through the optimal evaluation model.

Although few studies have explored the best evaluation model for medical staff job satisfaction, some studies do emphasize that appropriate analytical models can increase the accuracy of research results ( 53 ). Therefore, understanding the actual needs of public medical staff will significantly improve the doctor-patient ecological environment and maximize medical staff job satisfaction with minimal resources.

First of all, value staff opinions is the most important influencing factor of staff job satisfaction. Ample studies believed that strengthening the importance attached by hospital leaders to staff is beneficial to improving the job satisfaction of medical staff ( 54 – 56 ). According to social exchange theory, when employees or individuals feel support from their organizations, they have a strong sense of obligation and belonging ( 57 ). This sense of obligation and belonging can be externalized into corresponding social behaviors, including actively providing assistance and consciously promoting work enthusiasm ( 58 ). Medical staff more need the care and support of organizational leaders due to the more severe work pressure in the post epidemic era ( 59 ). Only staff with high job satisfaction can meet the needs of patients to the maximum extent, and all patient-centered service concepts can be realized ( 60 , 61 ).

Secondly, get recognition for your work ranks second among all variables that affect staff job satisfaction. Obtaining recognition from others allows individuals to feel their own value in team work. Goal setting theory believes that people will work harder and engage in achieving their goals, as a positive feedback that can promote better development of personnel ( 62 ). Especially in the field of health, the work of medical staff requires more recognition and attention from the organization.

The leadership of public hospitals often ignores the positive affirmation of medical staff and unilaterally emphasizes the economic benefits of hospitals. And medical staff often have a reduced sense of self-worth and are discouraged from working due to a lack of leadership attention. Therefore, multi-point practice policy of China for doctors can not only improve their economic income and reputation, but also maximize their self-worth ( 63 ). In addition, it is recommended that informal democratic life meetings be held frequently to strengthen the relationship between hospital employees and their co organizational leaders. Increasing recognition of self-work and achieving self-worth through praise and self-praise are potentially effective strategies.

Thirdly, democracy is the third key variable that affects medical staff job satisfaction. Self-determination theory believes that individuals pursue autonomy and control after meeting their basic needs ( 64 ). Equity and democracy can effectively promote the sustainable development of public health ( 65 ). China has implemented a large number of health policy reforms, including centralized drug procurement policies and DRG(s) payment policies, which have effectively curbed the bureaucracy and corruption in public hospitals over the past decade. Medical staff have played a key role in epidemic prevention and control, benefiting from a high degree of democracy in public hospitals. Trust in institutions and democracy has also been further validated in vaccination ( 66 ). Therefore, effective strategies should continue to be adopted to maintain the democratization of public hospitals, including empowering medical staff to make decisions in the face of major decisions regarding hospital development and the interests of employee groups. The top three satisfaction influencing factors in this study are significantly related to hospital organizational leadership. Hence, democratic centralism is an effective measure that can not only ensure the rationality of decision-making but also effectively avoid the personal style of leaders in hospital organization and management ( 67 ).

Fourth, performance evaluation satisfaction is also crucial for hospital staff job satisfaction. The reform of the personnel and salary distribution system in public hospitals has been one of the core elements of health care reform over the past 10 years. Relevant research has confirmed that income distribution is one of the most important aspects of hospital performance evaluation for medical staff ( 68 ). At present, there are still problems in the performance evaluation of public hospitals in China, such as emphasizing economic benefits, unreasonable indicator settings, and imperfect allocation methods ( 69 ). A series of health policies have significantly reduced hospital income while reducing the economic burden on patients, resulting in a decrease in the income of medical staff ( 70 ). The reason may be that different departments of the hospital use unified assessment indicators ( 71 ).

In addition, the current staff incentive in public hospitals in China mainly focuses on simple and convenient salary incentives, which are also prone to problems such as generalization of incentive effects and excessive utilitarian orientation. Specifically, the large income gap among different staff is due to the large difference in the distribution coefficient of professional titles ( 72 , 73 ). Therefore, the performance evaluation of public hospitals should focus on improving medical quality, promoting hospital development, and enhancing social benefits. This is an effective measure to promote the development of conscience in public hospitals to improve a more scientific performance and evaluation indicator system.

Finally, machine learning algorithms provide a new research direction for research on hospital staff job satisfaction. Meanwhile, a good working environment can create a better working atmosphere and stimulate the work creativity of medical staff. This study attempts to fit the best discriminant model for medical staff job satisfaction from the perspective of health human resources. Compared with traditional linear algorithms and other machine learning algorithms, random forests have the highest accuracy and best prediction results. Therefore, we suggest using random forest algorithm to explore relevant studies on the factors affecting job satisfaction in future.

Strengths and limitations of this study

The strengths are the cross-sectional survey of a large sample for three consecutive years, the department service volume based sample, the most appropriate discriminant model and potential applicability of our findings to many settings, since high-quality healthcare human resources have long been scarce, especially in the post pandemic era. The unique aspect of this study lies in its design, which includes panel data for almost all types of medical staff in public hospitals and optimal Discriminant Model for Similar Studies. The main limitation is that the investigation was forced to be interrupted after 3 years. Our investigation after 2020 has to stop because of the global epidemic of COVID-19, and it is difficult to recover to the pre epidemic level. In addition, China’s healthcare reform has affected the personnel structure and internal management of public hospitals to varying degrees, which may make precise measurements difficult. Moreover, the same strategy may not apply to medical personnel in all regions due to differences in economic levels and educational resources in different regions of China.

Data availability statement

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding authors.

Author contributions

CL: Conceptualization, Methodology, Writing – original draft. XM: Conceptualization, Data curation, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Acknowledgments

The authors would like to thank all the students who volunteered to participate in this study.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

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Keywords: medical staff, job satisfaction, large public hospitals, random forest model, key associated factors

Citation: Li C and Meng X (2024) Effective analysis of job satisfaction among medical staff in Chinese public hospitals: a random forest model. Front. Public Health . 12:1357709. doi: 10.3389/fpubh.2024.1357709

Received: 18 December 2023; Accepted: 05 April 2024; Published: 18 April 2024.

Reviewed by:

Copyright © 2024 Li and Meng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Xuehui Meng, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Job satisfaction among hospital nurses: A literature review
Job satisfaction of hospital nurses is closely related to work environment, structural empowerment, organizational commitment, professional commitment, job stress, patient satisfaction, patient-nurse ratios, social capital, evidence-based practice and ethnic background. Various mediating or moderating pathways have been identified with nurses ...
Job satisfaction among hospital nurses: A literature review
Job performance. Hou et al. (2013) investigated the influence of nurses' job satisfaction on the job performance of staff nurses. They found that, after controlling for demographic variables, nurses' job satisfaction independently explained 11.8% of the total variance of job performance. 3.1.6. Effort and reward.
Job satisfaction among nurses: a literature review
While numerous factors have been linked to nurses' turnover, job satisfaction is the most frequently cited ( Cavanagh and Coffin, 1992; Blegen, 1993; Irvine and Evans, 1995 ), and therefore merits attention. This review examines the extensive empirical literature regarding nurses' job satisfaction and its associated factors. 2.
Job satisfaction among hospital nurses: A literature review
The literature review by (Lu et al., 2019) explores recent studies on job satisfaction among qualified general nurses in acute care hospitals, emphasizing its significant role in nurse turnover ...
Job satisfaction among hospital nurses: A literature review
The literature relating to job satisfaction and nurses was identified through electronic databases using the same method as in the previous review (Lu et al., 2012). The electronic databases searched were: PubMed (2012-2017), Web of Science (2012-2017), CINAHL (2012-2017), Embase (2012-2017), PsycINFO (2012-2017) and the Applied ...
Interventions to improve nurses' job satisfaction: A systematic review
The Journal of Advanced Nursing (JAN) is a world-leading nursing journal that contributes to the advancement of evidence-based nursing, midwifery and healthcare. Abstract Aims To identify current best evidence on the types of interventions that have been developed to improve job satisfaction among nurses and on the effectiveness of these ...
Job satisfaction among nurses: a literature review
Job satisfaction among nurses: a literature review. 2005 Feb;42 (2):211-27. doi: 10.1016/j.ijnurstu.2004.09.003. The current nursing shortage and high turnover is of great concern in many countries because of its impact upon the efficiency and effectiveness of any health-care delivery system. Recruitment and retention of nurses are persistent ...
Hospital nurses' job satisfaction: a literature review
Aim A literature review of nurses' job satisfaction.. Background Little is known about factors evoking job satisfaction among nurses, whereas more is known about stress, burnout and dissatisfaction. The positive viewpoint is an important research area and needs to be studied. Methods Original studies were accessed by a systematic search from electronic databases (Abi/Inform, PsycINFO, Cinahl ...
Job satisfaction among hospital nurses: A literature review
2023. TLDR. The results indicated a direct or indirect association between a positive work environment and job satisfaction among nurses in Jordan, providing further evidence that nurses are more likely to feel satisfied in their jobs if they work in healthy environments, which has implications for staff retention and performance. Expand.
Job satisfaction among nurses: a literature review.
TLDR. Walker and Avant's concept analysis methodology is used to examine and clarify the phenomenon of job satisfaction in nursing and suggests that job satisfaction is an affective reaction to a job that results from the incumbent's comparison of actual outcomes with those that are desired, expected, and deserved. Expand.
(PDF) Workplace empowerment and nurses' job satisfaction: A systematic
Abstract and Figures. Aims: This systematic review aimed to synthesize and analyse the studies that examined the relationship between nurse empowerment and job satisfaction in the nursing work ...
Job satisfaction among nurses: a literature review
Job satisfaction among nurses: a literature review. Alison While. 2005, International Journal of Nursing Studies. The current nursing shortage and high turnover is of great concern in many countries because of its impact upon the efficiency and effectiveness of any health-care delivery system. Recruitment and retention of nurses are persistent ...
Job satisfaction among hospital nurses: A literature review.
Results: A total of 59 papers were included in this review. The impact of job satisfaction upon sickness absence, turnover intention, as well as the influencing factors of job satisfaction such as working shift and leadership, job performance, organizational commitment, effort and reward style has been identified in a number of research studies ...
Happiness, quality of working life, and job satisfaction among nurses
Job satisfaction is an essential predictor of absence from work, occupational burnout, quitting the nursing profession, or intention to do so among nurses . One of the essential steps in increasing productivity is to understand factors that are involved in job satisfaction, quality of life, and happiness of the nurses [ 18 ].
Hospital nurses' job satisfaction: A literature review
A literature review of nurses' job satisfaction. Little is known about factors evoking job satisfaction among nurses, whereas more is known about stress, burnout and dissatisfaction. The positive ...
Job satisfaction among nurses: a literature review
The impact of job satisfaction upon nursing absenteeism, burnout and nurses' intention to quit and turnover has been explored in a number of research studies, however, the findings are equivocal. Siu's (2002) study of nurses in Hong Kong found that involvement (the degree of commitment displayed towards employees by the organization) ( β ...
PDF Job Satisfaction Among Registered Nurses Data from the 2022 NSSRN
Impact of job satisfaction components on intent to leave and turnover for hospital-based nurses: a review of the research literature. Int J Nurs Stud. 2007 Feb;44(2):297-314. doi: 10.1016/j.ijnurstu.2006.02.004. 2 Includes nurses employed in jobs that require an RN or APRN license but excludes nurses with an RN license working as icensed a L
Job satisfaction and its relationship with burnout among nurses working
Nursing managers should take special measures such as increasing the nurse-to-patient ratio and reducing nurses' workload to raise job satisfaction among nurses working in COVID-19 wards to an acceptable level. Yu et al. (2020) concluded that the job satisfaction of the nursing staff was high at the forefront of fighting against COVID-19 . It ...
(Pdf) Systematic Literature Review of Job Satisfaction: an Overview and
Abstract and Figures. Job satisfaction is the main variable that must be considered in managing human resource practices. Job satisfaction discusses the extent to which employees are satisfied or ...
Job satisfaction and its related factors: A questionnaire survey of
Lu H., While A., Barriball L. Job satisfaction among nurses: a literature review. International Journal of Nursing Studies. 2005; 42:211-227. [Google Scholar] Lundh U. Job satisfaction among Swedish nurses and laboratory technologists. British Journal of Nursing. 1999; 8 (14):948-952. [Google Scholar] Ministry of Health, China .
[PDF] Job Satisfaction among Nurses in Saudi Arabia: A Review of the
Job Satisfaction among Nurses in Saudi Arabia: A Review of the Literature. M. Alshmemri, Lina Shahwan-Akl, P. Maude. Published 2016. Medicine. TLDR. Identifying factors that impact nursing job satisfaction and dissatisfaction is critical to developing strategies to retain and recruit Saudi nurses, and the future of nursing in SA may hinge on a ...
Special Article Job Satisfaction of Nurses: A Literature Review
Nurses' work performance and satisfaction from it have been proven to affect the provision of care and being an indicator of quality of healthcare services. Conclusion: Low nurses' job ...
Frontiers
Where n is the sample size, Z α / 2 value is 1.96 typically, p is the overall staff job satisfaction rate and δ is the desired level of precision. And then, we assumed 95% confidence and 5% precision. The overall staff job satisfaction in this study is 25.62%. Therefore, the minimum sample size was: n = 1.96 2 ∗ 0.2562 ∗ 1 − 0.2562 0.05 2 ≈ 293.The number of effective simple in this ...
(PDF) Social Support Affect Nurses' Job Satisfaction: A Literature Review
Social Support A󰀨ect Nurses' Job Satisfaction: A Literature Review. Istichomah Istichomah* , I. Putu Juni Andika, Hillary V. E. Pesirahu. Department of Nursing, Sekolah Tinggi Ilmu Kesehatan ...

Job satisfaction among nurses: a literature review

Publication types

Job satisfaction among nurses: a literature review

Related Papers

RELATED PAPERS

RELATED TOPICS

Job satisfaction and its related factors: A questionnaire survey of hospital nurses in Mainland China

Conclusions

What is already known about the topic?

What this paper adds

1. Introduction

2. Background and literature review

2.2. Nursing in Mainland China

2.2.2. Nursing shortage and turnover

3.1. Aim and objectives

3.2. Research design and sample

3.3. Instruments

3.3.1. Instrument translation

3.4. Ethical considerations and negotiation of access

3.5. Analysis of data

4. Findings

4.2. Respondents’ job satisfaction

4.3. Respondents’ organizational commitment

4.4. Respondents’ occupational stress

4.5. Respondents’ professional commitment

4.6. Respondents’ role conflict and role ambiguity

5. Discussion

5.1. Hospital nurses’ job satisfaction

5.2. Hospital nurses’ organizational commitment

5.3. Hospital nurses’ occupational stress

5.4. Hospital nurses’ professional commitment

5.5. Hospital nurses’ role conflict and role ambiguity

5.6. The impact of nurses’ educational level upon their working lives

6. Conclusion

ORIGINAL RESEARCH article

Sample and methods

Study design and samples

Method of investigation

Sample quality control

Multiple logistic regression

Gradient boosting decision tree algorithm

Naive Bayesian algorithm

K-nearest neighbor algorithm

Random forest algorithm

Building an optimal evaluation model

Overall description of the analysis

Single factor analysis of medical staff job satisfaction

Multiple logistic regression analysis of medical staff job satisfaction

Optimal evaluation model

Importance of different explanatory variables

Conclusion and discussion

Strengths and limitations of this study

Data availability statement

Author contributions

Acknowledgments

Conflict of interest

Publisher’s note

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