Study design and study population
The Chinese Sixth National Health and Services Survey (NHSS) in Sichuan Province was conducted from August 2018 to October 2018. All healthcare workers who were certified practitioners in third-class comprehensive hospitals, second-class hospitals, community health service centres, and township hospitals of Sichuan Province were eligible to participate in the NHSS. Multistage stratified random sampling was used to acquire the study sample. In the first stage, 14 cities were randomly selected from among 21 prefecture-level cities, and 70 towns and streets were randomly selected from the 14 cities. In the second stage, all third-class comprehensive hospitals and some of the second-class hospitals were selected from the 14 cities, and all the community health service centres and township hospitals in the 70 towns and streets were enrolled in the survey. In the third stage, 20 physicians and 10 nurses were selected from each third-class comprehensive and second-class hospital by a simple random sampling method. Five physicians, three nurses, and two public health professionals were randomly selected from each community health service centre and township hospital. Respondents were asked to complete the questionnaire anonymously. Informed consent was obtained from each healthcare worker following a detailed explanation about the purpose of the study. Overall, 1685 healthcare workers participated, of which 1327 (78.80%) provided valid responses.
Measures
The questionnaire was developed and designed by an expert panel from the National Health Commission of the People’s Republic of China for this study.
Sociodemographic characteristics of healthcare workers
The sociodemographic characteristics examined included the following: gender, age (< 30, 30–39, 40–49, or ≥ 50 years), marital status (single, divorced, widowed, or married), education level (junior college or below, bachelor’s, master’s, or above), specialty (physician, nurse, or public health professional), technical title (no title, primary title, middle title, vice-senior title,or above), working years (< 5, 5–9, 10–19, 20–29, or ≥ 30 years), weekly hours at work (≤ 40, > 40), night shifts per month (none, 1–7, or ≥ 8), and grade of medical institution (community health service centres and township hospitals, second-class hospitals, or above).
Effort-reward imbalance
The Effort-Reward Imbalance Scale assesses three dimensions: extrinsic effort (3 items), reward (7 items), and overcommitment (6 items). Participants responded to the items on a four-point Likert scale (1 = strongly disagree, 4 = strongly agree). To assess the degree of imbalance between high cost and low gain at work, an ERR was calculated as E/(R*C), where E was the total score of the effort dimension, R was the total score of the reward dimension, and C was the correction coefficient based on the difference in the number of numerators and denominators [27]. Here, C = 3/7 = 0.4286. An ERR value of > 1.0 indicates that the amount of effort is not rewarded adequately [19]. Higher scores represented higher overcommitment to work. Cronbach’s alpha coefficient of the scale in this study was 0.786.
Job Satisfaction
Work Engagement
Work engagement was measured by the Chinese version of the Utrecht Work Engagement Scale [28]. It comprises 17 items measuring three aspects of work engagement: work vigour (6 items), work dedication (5 items), and work absorption (6 items). Items were responded to using a seven-point Likert scale ranging from 0 (never) to 6 (every day) and were combined into summary scores. Higher scores indicated higher work engagement. Cronbach’s alpha coefficient of the scale in this study was 0.941.
Outcome variable
Self-rated health status was assigned scores of 5 (good), 4 (relatively good), 3 (fair), 2 (relatively poor) and 1 (poor) by asking the participants ‘How do you feel about your health?’ Higher scores indicated better self-rated health.
Statistical analysis
We first used descriptive statistics to examine the sociodemographic characteristics, ERR, overcommitment, job satisfaction, work engagement, and self-rated health status. Second, Pearson’s correlation coefficients were used to analyse the correlations among ERR, overcommitment, work engagement, job satisfaction, and self-rated health. Third, a structural equation model (SEM) was employed to further test the hypothesized relationships among the study variables.
Several indicators were used to assess the fit between the current data and the hypothesized model. The goodness of fit index (GFI) > 0.9, norm fit index (NFI) > 0.9, relative fit index (RFI) > 0.9, comparative fit index (CFI) > 0.9, incremental fit index (IFI) > 0.9, and Tucker-Lewis Index (TLI) > 0.9 indicate whether the model fit was acceptable. All statistical analyses were performed using IBM SPSS version 23.0 (SPSS Inc., Chicago, IL, USA) and Analysis of Moment Structures (AMOS) version 22.0 (IBM, New York, NY, USA). Statistical significance was set at P < 0.05.