Background
Due to China’s large population, there is a large demand for health human resources. However, the shortage of primary medical staff is a leading problem. Primary medical staff are the direct care providers, an irreplaceable role in popularizing medical and health knowledge and improving their self-health promotion level. Therefore, “without the labor force in health care, there is no health” is a generally accepted theory [
1]. The
China Statistical Yearbook 2019 showed the total number of health workers in China was 12.301 million, of which 3.826 million were primary health workers (only 31.1%): 14.5% in community health service centers (stations), 35.5% in township health centers, 29.9% in village clinics, and 20.1% in other primary healthcare institutions (including street health centers, outpatient departments and clinics) [
2].
With the outbreak of the coronavirus pandemic, a Chinese scholar proposed implementing various prevention and control measures in the community [
3]. This pandemic highlights the necessity of primary medical staff; however, it also creates problems for them like increased workload, work pressure and job burnout, and reduced job satisfaction, having profound effects on job satisfaction and enthusiasm. Adding these problems to the lacking incentive mechanism, there is bound to be a serious impact on stability of primary medical staff, all of which also explain why most Chinese medical students rush to work in city hospitals after graduation [
4]. In 2015, Meng et al. [
5] stated that about 8% of primary healthcare workers left their hospitals, and half switched to higher-level hospitals (such as the second-class and third-class hospitals). Moreover, the World Health Organization (WHO) announced the shortage of primary medical staff is a global problem [
6]. During the Third Global Forum on Human Resources for Health, WHO revealed that by 2035, the world will have 12.9 million less medical staff members. Under this circumstance, WHO has proposed a series of evidence-based global policy recommendations promoting the enthusiasm of medical staff in remote and rural areas by improving working conditions and creating incentives [
7].
Anhui is a typical region for primary healthcare reform in China. It has always been committed to improving the social medical insurance system, reforming the public hospital system and strengthening primary healthcare in rural regions [
8]. However, the basic health human resources in Anhui are relatively scarce, and the gap between urban and rural areas is vast; in 2019 there were 2.01 practicing physicians and practicing assistant physicians per 1000 people, of which 2.69 were urban and 1.39 were rural. There are 2.37 registered nurses per 1000 people, of which 3.83 are urban and 1.35 are rural. There are 5.27 health technicians per 1000 population, of which 7.68 are urban and 3.39 are rural [
2]. Anhui’s population accounts for 4.5% of China, while the medical staff accounts for only 1.8% (224,000) and the primary medical staff accounts for 3.5% (135,000) of the country.
Psychological capital is a positive psychological force generated by a person’s positive emotional state to individual development and organizational construction and is an important source of organizational competitiveness [
9]. It is a kind of capital other than human capital, social capital and financial capital which can surpass human and social capital and promote the sustainable development of individuals [
10]. Social support is the personally perceived support of individuals, emphasizing the individual’s self-understanding, experience and feelings about social support from different sources [
11]. Job burnout is a state in which a person suffers from physical and mental fatigue due to excessive work stress beyond his or her own scope [
12]. Turnover intention is the tendency to leave the current job to find a new one. Chinese and international studies have shown that an important ideological act and premise leads to departure behaviors and has a good predictive power for actual departure behaviors [
13].
Our study focused on primary medical staff in Anhui to understand the status of their turnover intention, analyze the influencing factors of their turnover intention, and explore the relationship between psychological capital, social support, and job burnout and their turnover intention. The results of this study will provide a reference for stabilizing the primary medical team, improving quality of primary medical services, and formulating management strategies for primary medical staff.
Methods
Studying setting
Anhui is located east of central China, and its economic development is at a medium level across the country. Each year, 22,635 primary health institutions in Anhui provide outpatient and inpatient services, accounting for 61.27% and 20.90%, respectively, which are higher than the national average of 54.12% and 18.21% [
14].
This province was selected for the following reasons: (1) Anhui has been at the forefront of China in the comprehensive reform of primary medical institutions making its primary healthcare institutions a government priority. (2) Considering feasibility, Anhui guaranteed the compliance of participants. (3) Anhui has a large number of primary healthcare workers.
Participants and data collection
We used a cross-sectional survey design. Primary medical staff in this study refers to the medical staff in community health service centers (CHC), community health service stations (CHS), township health centers, village clinics, and outpatient departments. According to the regional characteristics, Anhui is divided into three regions: Northern Anhui, Central Anhui, and Southern Anhui. We used random sampling to select a district and a county from southern and central Anhui and one district and two counties from northern Anhui (northern Anhui has a larger population). We used a series of questionnaires to collect data, and the respondents filled out the questionnaires anonymously and voluntarily. The questionnaires in each area were collected by special investigators and withdrawn immediately after completion. If the respondent answered regularly to the questionnaires or filled in the questionnaires with incomplete content, it would be regarded as invalid and eliminated.
Before conducting the survey, we held several investigator trainings and set inclusion and exclusion criteria (survey subject must be over 20 years old, held their position for one year, occupation of medical staff is limited to doctors and nurses, pharmacists, administrative staff, etc.). We also held a series of on-site, preliminary investigations before official investigation.
We recovered 1300 questionnaires, of which 1152 were valid, making the effective recovery rate 88.62% (1152/1300).
Measures
Demographic characteristics questionnaire
First, we used the general characteristics questionnaire, which we independently designed based on relevant literature and expert consultation, including three parts: (1) general demographic characteristics: gender (male, female), age (20–30 years old, 31–40 years old, 41–50 years old, over 50 years old), professional title (primary, intermediate and above), education (secondary; technical school and below, college; undergraduate and above), working years (1–10 years, 11–20 years, 20 years or more), marital status (married, other). (2) Job characteristics: monthly income (CNY 3000 and below, higher than CNY 3000), occupations (doctor, nurse, pharmacist and administrative staff), work unit (CHC, CHS, township health center, village clinic, outpatient department) (3) Regional characteristics: The city or county (district) where the respondents are located.
PCQ-24
Psychological capital is measured using the Psychological Capital Scale (PCQ-24) compiled by Luthans et al. [
15], with a total of 24 items. It measures psychological capital from four dimensions: self-efficacy, hope, resilience, and optimism. Points are graded from 1 to 7. A score of 124 indicates extremely high psychological capital; above 100, is high level of psychological capital; above 80, the psychological capital is a medium level; below 80, it is necessary to strengthen and train psychological capital. The reliability of the scale is Cronbach's α coefficient of 0.97, and the results of confirmatory factor analysis showed the scale has good reliability.
PSSS
We used
Perceived Social Support Scale (PSSS) compiled by Zaimet et al. [
16] in 1987 and revised by Chinese scholar Wang XD [
17]. The scale consists of 12 items, divided into two dimensions: in-family support (items 3, 4, 8, 11), and out-of-family support (the remaining items). Points 1 to 7 are used for scoring. Scores between 12 and 36 are considered low support state; between 37 and 60 points are an intermediate support state; between 61 and 84 points are a high support state. The reliability of the scale is Cronbach’s α coefficient is 0.94.
Job burnout scale
We used the Chinese Maslach Burnout Inventory (CMBI) of Li et al. [
18] for scoring. It is revised based on MBI (Maslach Burnout Inventory) questionnaire [
19]. There are 15 questions in the questionnaire, with five questions in each three dimensions: emotional exhaustion, disintegration of personality, and reduction in sense of achievement. It uses Likert's 7-point scoring method, 1 means “strongly disagree” and 7 means “strongly agree”. The scale divides the level of burnout into four levels through three critical values: 25 points for emotional exhaustion, 11 points for disintegration of personality, and 16 points for reduced sense of achievement. When all three dimensions are less than the critical value, it is zero burnout; when any of the three dimensions is higher than the critical value, it is mild burnout; otherwise, it is moderate or severe burnout. The internal consistency test of the scale showed a Cronbach’s α coefficient of 0.767, indicating good reliability.
Turnover intention scale
The scale of turnover intention was translated and revised by Michael et al. [
20]. The scale includes a total of six items, divided into three dimensions: possibility of quitting current job (turnover intention I, items 1 and 6), motivation to find other jobs (turnover intention II, items 2 and 3), and obtaining external possibility of work (turnover intention III, items 4 and 5). It uses reverse scoring on a scale of 1 to 4. If the score is higher, the turnover intention is higher. The reliability of the scale is Cronbach's α coefficient of 0.80.
Statistical analyses
We used Epi Data 3.1 for database building, and researchers double-entered data and performed error detection, SPSS 20.0 (IBM Corp, Armonk, NY, USA) for statistical analysis of data. Count data are described by composition ratio and measurement data are described by mean and standard deviation (M ± SD).
For univariate analysis, we conducted an independent sample t-test for binary variables (gender, professional titles, marital status, monthly income). Then, we divided the age of primary medical staff into four groups: 20–30 years old, 31–40 years old, 41–50 years old, 50 years and older; divided the working years into three groups: 1–10 years, 10–20 years, more than 20 years, which changes the age and working years of primary medical staff from continuous variables to categorical variables. We performed one-way analysis of variance (ANOVA) on multiple categorical variables (age, education, working years, employment agency, occupation, region). In addition, we used Pearson correlation analysis to explore the correlation between turnover intention and the scores of psychological capital, social support, and job burnout among them, the test level α = 0.05.
In multivariate analysis, we used multiple linear regression models to set dummy variables for categorical variables and set a control for each survey item, thereby testing its association with other items under standard and non-standard coefficients, the test level α = 0.05.
Suggestions
Since our research object is from Anhui Province in the central and eastern part of China, we have put forward the following policy recommendations in response to the above identified problems, which can provide reference for the decision-making of Anhui Province's health services and administrative departments.
Our team found that middle-aged medical staff are more willing to leave, so we suggest medical managers need to immediately improve basic medical facilities, provide skilled doctors with matching hardware facilities, and enable them to better exert their professional advantages and enhance their recognition and confidence in their work. They should also encourage young medical staff and let them actively progress and innovate to train the backup talents of the health workforce to stabilize the primary medical staff. Moreover, it is necessary to strengthen communication and collaboration between primary medical institutions, which is conducive to improving the primary medical system.
Aiming at the problem of higher scores for doctors’ turnover intention, we suggest medical managers pay more attention to development status of doctors and discover the difficulties and problems in their work and personal lives, and then strengthen communication and cooperation with foreign hospital managers and introduce advanced human resource management experience.
We found that different PHC departments have different levels of turnover intention in Anhui Province. So, the health management departments should strengthen research to find problems of village-level medical institutions; higher-level primary medical institutions, such as community medical service centers and township hospitals, should increase assistance and technical guidance to village clinics, or have poorly operating village clinics merged to maximize the integration of medical resources. If there is a large staff turnover in the village clinics, it is necessary to innovate incentives and give certain encouragement policies to urban medical staff, encouraging them to stay in village clinics, and then fill the gap in human resources and improve the operating mechanism of village clinics.
There was a positive correlation between job burnout score and turnover intention score. Therefore, medical managers need to provide comfort, subsidies, and necessary psychological assistance to primary medical staff so they can face stressors and appreciate positive factors in current work. Additionally, Herzberg's two-factor theory [
36] cautions managers: the key to improving staff motivation is to invest in incentives, because for the excellent medical staff, endogenous incentives are more attractive than exogenous one’s force. In addition to paying attention to health factors such as compensation and benefits, managers need to determine motivating factors such as career development and job significance, sense of achievement, and challenges, to further retain high-quality medical personnel and stabilize the team of primary health staff.
Study limitations
Despite the size and findings of the study, it has limitations. First, the collected samples mainly come from central China's Anhui province, but samples from other provinces and other countries should be included and further researched. Secondly, we only analyzed the turnover intention and influencing factors of some primary medical staff in Anhui, limiting the sample size to a specific region. Finally, although many factors affecting the turnover intention are controlled here, there are still potential confounding factors, such as the hardware facilities of medical institutions, regional customs and culture (Additional file
1).
Conclusions
According to the scoring criteria for the turnover intention, this study found that primary medical staff in Anhui province has a high level of turnover intention. Middle-aged doctors are more likely to have turnover intention than nurses and doctors of other age group. Staff of village clinics have significantly higher turnover intention than those of other primary medical institutions, indicating this province’s primary medical system is likely to remain incomplete, and the village medical units are facing greater development difficulties. Job burnout also profoundly affects the level of turnover intention, which shows that the psychological status of primary medical staff needs to be improved urgently. Medical managers need to think about more than just physical incentives. These findings will provide ideas and inspiration for the management of primary medical staff.
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