Abstract
Background
Public health physicians are experiencing increased work stress and workload, leading to heightened negative emotions and presenteeism. This study investigates the relationship between job burnout and presenteeism among primary public health physicians in China and explores the potential mediating effect of depressive symptoms, and moderating effects of coping styles and organizational support on these associations.
Methods
955 primary public health physicians were surveyed from September to December 2022 in China. Presenteeism was assessed using the Stanford Presenteeism Scale (SPS-6). A moderated mediation model was used to understand the moderating relationship between job burnout (X), depressive symptoms (M) mediated presenteeism (Y), coping styles (W1), and organizational support (W2), controlling for all possible covariates.
Results
69.95% of participants showed job burnout in work and 50.16% experienced depressive symptoms, with the average score of presenteeism 16.90 ± 5.74. Job burnout was positively associated with presenteeism score (Effect = 2.23, 95%CI [1.93,2.53]). Mediation analyses revealed that depressive symptoms significantly mediated this relationship (indirect effect = 0.96, 95%CI [0.70,1.25]). Moderated mediation further indicated that the interaction of coping styles and job burnout was negatively related to depressive symptoms, and the interaction of organizational support and depressive symptoms was positively related to presenteeism among public health physicians.
Conclusion
High job burnout and higher depressive symptoms may contribute to presenteeism. Positive coping styles and appropriate organizational support could buffer the detrimental effects by reducing job burnout and depressive symptoms.
Clinical trial number
Not applicable.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12909-025-07391-5.
Keywords: Job burnout, Depressive symptoms, Coping styles, Organizational support, Presenteeism
Introduction
Presenteeism, defined as attending work while being in poor health, could lead to diminished performance, reduced productivity, and even worse health problems [1]. Specifically, presenteeism among public health physicians may result in increased errors in chronic diseases management, decreased service quality, and lower patients’ satisfaction [2]. This phenomenon is particularly prevalent among Chinese medical staff [3, 4]. Previous research indicated that 66.4% of Chinese medical staff reported presenteeism [5], the rate higher than that observed in Portugal (55%) and Brazil (36%) [6]. Studies have shown that presenteeism is linked to work-related factors and individual factors, such as work stressors, unbalanced work resources, and negative work-related emotions [1, 7]. While existing research has primarily focused on doctors and nurses [7], there is a notable lack of information regarding primary public health physicians. Public health physicians often encounter significant work stress and limited human resources [8], making them particularly susceptible to presenteeism. Additionally, cognitive factors (such as negative emotions and coping styles), could further disrupt their normal working performance [9]. Moreover, organizational support plays a critical role in influencing employees’ motivation and behavior [10]. Therefore, it is essential to explore the factors and mechanisms that contribute to presenteeism among Chinese primary public health physicians. In this context, depressive symptoms may act as a mediating pathway, while coping styles and organizational support could serve as moderating factors in this relationship.
Job burnout and presenteeism
Public health physicians play a crucial role in disease prevention, public health surveillance and intervention, and population health promotion [11]. In China, the number of public health physicians is insufficient, with only 7.5 per 10,000 people [12]. These professionals face heavy workloads and significant pressures related to career advancement [13]. Such adverse job characteristics are closely linked to job burnout [14], which could lead to negative physical, psychological, and occupational outcomes [15]. Indeed, 73.00% of Chinese public health physicians have reported experiencing job burnout to some extent [16]. Therefore, there is an urgent need to address job burnout among primary public health physicians.
Job burnout, characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment [17]. Notably, job burnout may not only impair individual well-being but also lead to presenteeism, which is a costly organizational behavior with significant implications. Based on the Job Demands-Resources (JD-R) model, the demands and resources present in the workplace can significantly impact employee health [18]. For employees experiencing job burnout, high job demands compel them to work while providing insufficient resources to complete their tasks, thereby increasing the possibility of presenteeism [19]. Although the relationship between job burnout and presenteeism has been established in clinical nurses [20] and doctors [21], few studies have looked at this specific group of primary public health physicians and the mechanisms underlying this relationship remain poorly understood. Therefore, the first hypothesis is proposed as follows:
Hypothesis 1
Job burnout is positively related to presenteeism among Chinese primary public health physicians.
Mediating role of depressive symptoms
Depressive symptoms, a prevalent mental health issue exacerbated by occupational strain, could impair work performance [22]. Nearly half of Chinese public health physicians report experiencing such symptoms yet continue to work [13]. Among primary CDC staff, the incidence of depression is reported at 47.96% [13], which surpasses the 43.48% incidence found among nurses [23]. These findings highlight the importance of prioritizing the mental health of primary public health physicians.
Based on the health impairment pathway of the JD-R model [18], this study constructs a theoretical framework comprising three key dimensions: demand overload, resource depletion, and non-adaptive response. First, job demands continuously consume psychological resources, leading to job burnout [17, 24]. Second, demand overload result in resource depletion, which contributes to job burnout and increases the risk of psychological issues such as depressive symptoms [25]. A review of 36 prospective studies provides consistent evidence that job burnout predicts depressive symptoms [15]. For instance, a three-year study involving 2,555 dentists identified that burnout as a significant predictor of depressive symptoms [26]. Additionally, a three-wave study found that an increase in job burnout from T1 to T2 predicted an increase in depressive symptoms from T2 to T3 among 1,632 Israeli workers [27]. Third, depressive symptoms deplete psychological resources and impair cognitive function, compelling individuals to adopt maladaptive strategies—most notably presenteeism [28]. As a mediator of demand-resource imbalance, depressive symptoms are not only a consequence of resource depletion [29], but also serve as a key psychological mechanism linking job burnout and presenteeism. For public health physicians, this means they may attend work despite experiencing depressive symptoms to avoid perceived professional failure. However, little research has considered the effect of depressive symptoms on the relationship between job burnout and presenteeism. Thus, we can infer that depressive symptoms may play a mediating role in the relationship between job burnout and presenteeism among primary public health physicians in China. Accordingly, the second hypothesis is proposed:
Hypothesis 2
Depressive symptoms may mediate the relationship between job burnout and presenteeism among primary public health physicians.
Moderating roles of coping styles and organizational support
While job burnout may increase the risk of presenteeism by contributing to depressive symptoms, it is essential to acknowledge that not all public health physicians with job burnout experience these issues. In fact, some physicians can maintain a positive psychological state or work engagement even while experiencing job burnout. This observation has initiated an investigation into the protective mechanisms that may mitigate these effects. Importantly, there is a substantial gap in the literature regarding comprehensively addressing these issues.
Coping is defined as an individual’s cognitive and behavioral efforts to manage interactions with the environment that can exert pressure on an individual’s resources [30]. Coping styles are usually classified into positive and negative types [31]. The stress process model suggests that coping skills, which act as mediators of stress, can influence stress outcomes [32]. According to Cognitive Appraisal Theory [33], positive coping styles (e.g., tasks restructuring or enhancing efficiency [34]) promote adaptive emotional responses [33], thereby directly alleviating the emotional exhaustion caused by job burnout and preventing depressive symptoms [35]. Conversely, negative coping styles (e.g., self-talk or avoidance [36]) are often linked to serious psychological issues, such as anxiety and depression [37, 38], by impairing emotion regulation capacity. In the JD-R model [18], positive coping styles serve as an important psychological resource, enabling public health physicians to better manage job stress and reduce the occurrence of negative emotions. Previous evidence has confirmed that coping styles could serve as mediator or moderator variables, playing a regulatory role between stressors and mental health [39]. Consequently, coping styles may alleviate the effects of job burnout on depressive symptoms.
Organizational support is generally defined as the degree to which employees perceive the organization’s recognition, care, and support for their contributions [40]. As a vital component of social support [41], organizational support can help individuals achieve a work-life balance, further enhancing their work engagement [42]. According to the Conservation of Resources (COR) Theory [24], organizational support could reduce presenteeism by providing instrumental resources (e.g., flexible attendance) to alleviate work-life conflicts, as well as emotional resources (e.g., psychological counseling) to enhance mental well-being [7]. As a key contextual resource within the JD-R model [18], organizational support influences employees’ psychological resilience. When organizational support is high, employees view rest as a legitimate resource for managing work demands. Previous research has shown that high organizational support is negatively related to presenteeism among medical staff [43]. By reducing stress [44], alleviating burnout [45], and enhancing job satisfaction [46], organizational support mitigates adverse work outcomes, particularly for public health physicians experiencing negative states. Therefore, organizational support may play a crucial role in alleviating the effects of depressive symptoms on presenteeism among primary public health physicians.
These findings suggest that coping styles and organizational support may significantly moderate the relationship between job burnout and presenteeism among primary public health physicians. However, there is limited evidence regarding how coping styles and organizational support moderate the relationship between job burnout and presenteeism through depressive symptoms among Chinese primary public health physicians. Thus, the following hypotheses are proposed:
Hypothesis
3a. Coping styles may moderate the relationship between job burnout and depressive symptoms.
Hypothesis
3b. Organizational support may moderate the relationship between depressive symptoms and presenteeism.
This study applied a moderated mediation model to examine the association between job burnout and presenteeism. We hypothesized that depressive symptoms mediated the relationship between job burnout and presenteeism, and coping styles and organizational support moderated the above mediating effect. This hypothesis is illustrated in Fig. 1.
Fig. 1.
Hypothetical model
A hypothetical model of relationships among job burnout, coping styles, depressive symptoms, organizational support, and presenteeism.
Methods
Data sources
This cross-sectional survey was conducted in Yancheng City, Jiangsu Province, from September to December 2022, using convenience sampling to recruit participants. The participants from 33 community health service centers and 28 township health centers in Yancheng City were invited to complete an online survey. The inclusion criteria of the participants were as follows: (1) had a public health practitioner certificate; (2) had worked for m for at least 6 months; (3) provided informed consent and volunteered to participate. The exclusion criteria were: (1) interns; (2) off-duty public health physicians.
A total of 1,013 public health physicians completed the survey, yielding 955 valid questionnaires and a response rate of 94.27%. During data cleaning, 58 cases with incomplete core scales or logical inconsistencies were excluded. All participants provided written informed consent online before the study began. The study concerning human participants received review and approval from the Ethics Committee of Nantong University.
Procedure
Based on a review of the literature and previous survey results, the current incidence of presenteeism among medical staff is approximately 32% [47]. We established the following parameters: δ = 0.032, p = 0.32, α = 0.05, and
= 1.96. Using the sample size estimation formula
, we determined that the required sample size was 815 individuals. Considering an expected response rate of 85%, the minimum sample size needed for this survey was calculated to be at least 959 participants.
Variables and measurements
Dependent variable: presenteeism
Presenteeism was measured using the Stanford Presenteeism Scale (SPS-6), which was developed by Koopman et al., Stanford University School of Medicine [48]. Developed in occupational health psychology, the scale aims to assess both cognitive and physical impairments that hinder job performance [48]. This scale encompasses six items, covering two dimensions: completing work and avoiding distraction. Specifically, items 5 and 6 are reverse-scored. Each item was rated on a five-point Likert scale ranging from one (“strongly disagree”) to five (“strongly agree”). The final score of the SPS-6 is calculated by summing up the scores of all six items, with the overall score ranging from 6 to 30 points. The higher the scale score, the more severe the productivity loss caused by presenteeism. The SPS-6 has been widely utilized among the Chinese professional population, demonstrating high internal consistency (Cronbach’s α = 0.806) and strong construct validity [49]. Cronbach’s α of this scale in this study was 0.845.
Independent variable: job burnout
Job burnout was measured using the General Version of the Burnout Scale (MBI-GS) [50] that were designed to assess the three dimensions of job burnout: emotional exhaustion, depersonalization, and reduced personal accomplishment. The scale consists of 15 items and each was rated using a 6-point Likert scale, ranging from 0 (“never”) to 6 (“every day”). In the dimensions of emotional exhaustion and depersonalization, higher scores indicated more significant burnout. On the scale of low personal accomplishment, lower scores reflected more serious burnout problems. The comprehensive score of job burnout is calculated as follows: (0.4 * emotional exhaustion + 0.3 * depersonalization + 0.3 * low personal accomplishment)/15. Based on average scores calculated burnout was graded into three levels: no burnout (0-1.49), mild to moderate burnout (1.5–3.49), and severe burnout (3.5-6.0) [51]. In Chinese medical staff, the scale also showed good validity (Cronbach’s α = 0.856) [52]. In this study, the Cronbach’s α of MBI-GS was 0.908, indicating a high internal consistency of the scale.
Mediating variable: depressive symptoms
To assess depressive symptoms, the study used the nine-item Patient Health Questionnaire (PHQ-9) [53]. Each item assessed the frequency of depressive symptoms on a four-point Likert scale ranging from 0 to 3 (0 = not at all, 1 = a few days, 2 = more than half the days, 3 = almost every day). A total score exceeding 5 was regarded as indicating the presence of depressive symptoms [54]. The PHQ-9 has shown satisfactory reliability and validity among Chinese physicians, with a Cronbach’s α of 0.92 [55]. In this study, Cronbach’s α of PHQ-9 was 0.935.
Moderating variable: coping styles and organizational support
Coping style was measured by the Simplified Coping Style Questionnaire (SCSQ) [31]. There are 20 items in the scale, using a four-level scoring method, that is, 0 points for “not taking”, 1 point for “occasionally taking”, 2 points for “sometimes taking”, and 3 points for “often taking”. The questionnaire was divided into two dimensions: positive coping and negative coping. Coping tendency = Positive coping standard score (Z score) – Negative coping standard score (Z score). If the coping tendency value is greater than 0, it indicates that the subject mainly adopts a positive coping style when under stress. If it is less than or equal to 0, it indicates that the subject is more accustomed to adopting a negative coping style. The SCSQ has been validated to have high reliability and validity among Chinese medical staff [56]. The Cronbach’s α of this scale in the present study was 0.902, and the average scores of the positive and negative coping subscales were 0.889 and 0.826, respectively.
In order to evaluate organizational support, the perceived organizational support scale [57] was used in this study. This scale included 8 items with each item scored on a seven-point Likert scale, ranging from one (“Strongly disagree”) to seven (“Strongly agree”). The higher the total score, the higher the perceived level of organizational support. For Chinese medical staff, this scale has demonstrated well-established reliability and validity [58]. The Cronbach’s α of this scale in the present study was 0.781.
Covariates
The basic characteristics were included as covariates to control the effects as confounding factors: gender, age, marital status, education level, daily working hours, and annual income(yuan). Ages were categorized into four groups (“<30”, “30–39”, “40–49”, and “≥50 years”). Marital statuses were divided into 3 groups (“unmarried”, “married”, and “others”). Education levels were categorized into four groups (“Junior college”, “Bachelor’s degree”, and “Master’s degree”). Daily working hours were divided into 2 groups(“≤8h”, “>8h”). Annual incomes were categorized into four groups (“<30000”, “30000–49999”, “50000–90000” and “>90000”).
Data analysis
Statistical analyses were conducted using SPSS 26.0 and Hayes’ (2015) SPSS macro program PROCESS. Harman’s one-factor test was employed to assess potential common-method bias from self-reported data. A detailed check of given ordinary least squares (OLS) regression assumptions was conducted. First, the basic characteristics of public health physicians were described by frequency distribution, percentage (categorical variables), mean, and standard deviations (continuous variables). Pearson correlation analysis was used to reveal the relationship between job burnout, depressive symptoms, coping styles, organizational support and presenteeism of public health physicians. Second, the mediation and moderated mediation analysis was carried out applying Hayes’ PROCESS macro (Model 4, Model 21) given OLS regression-based path analysis. To visualize the moderation results, the Johnson-Neyman (J-N) technique was used to plot the conditional effects and confidence intervals. Gender, age, marital status, education level, daily working hours, and annual income were considered covariates.
To further investigate subgroup differences, analyses were performed across demographic and occupational characteristics. The participants were categorized by gender, age, marital status, education level, daily working hours, and annual income. Linear regression analyses were employed, with job burnout, depressive symptoms, coping styles, and organizational support as predictors and presenteeism as the dependent variable. These additional analyses were conducted to examine relationships between variables and compare differences across subgroups, as presented in Supplementary Table 1.
All control variables were included in the analyses and systematically accounted for across all models. Results reported in tables and figures were standardized to facilitate interpretability, and a bootstrapping procedure with 5,000 resamples was used to generate 95% confidence intervals (CIs). Effects were considered statistically significant when their 95% confidence intervals did not include zero.
Common-method bias test (CMB)
Data were collected through self-report questionnaires, and common method bias was a potential problem. To minimize this bias, we implemented procedural controls, such as adopting IP address restrictions to prevent duplicate submissions and setting up five attention check questions (e.g., “Please select ‘Strongly Agree’”) to exclude invalid responses. Meanwhile, Harman’s one-factor test was conducted to test for the CMB [59]. The first principal component explained less than 50% of the total variance, indicating that CMB does not pose a significant concern in this study. The result of Harman’s one-factor test indicated that the first factor accounted for 19.511% of the covariance in our study. Therefore, there was no significant CMB in this study.
Assumption checks for OLS regression
To validate the OLS regression model, we tested several key assumptions. The Q-Q plot of the residuals indicated that data points closely aligned with the theoretical normal distribution line, showing no significant deviations from the expected linear pattern. Additionally, the Shapiro-Wilk test for normality produced a non-significant result (p > 0.05), providing statistical evidence that the residuals approximated a normal distribution. In the residual-versus-predicted plot, the residuals were randomly scattered around zero, without fan or funnel shapes, or curvilinear trends, thereby validating the assumptions of linearity and homoscedasticity. The variance inflation factors for all predictors ranged from 1.142 to 2.238, well below the threshold of 5, indicating no severe multicollinearity issues.
Results
Basic characteristics
A total of 955 respondents participated in the survey, mean age was 37.71years and 69.74% were women and the vast majority were married (82.93%) (Table 1). Just over half of the participants had a bachelor’s degree or higher (50.26%). 57.28% worked more than 8hours per day. Nearly 80% of respondents had an annual income of less than 50,000 yuan (77.91%). Among the participants, 69.95% had symptoms of job burnout (MBI-GS mean score > 1.5). 50.16% of participants had depressive symptoms (PHQ-9 score>5). 68.48% of respondents took positive coping styles (SCSQ score > 0).
Table 1.
Basic characteristics of medical staff (n = 955)
| Variables | Item | N(%) |
|---|---|---|
| Gender | Male | 289(30.26) |
| Female | 666(69.74) | |
| Age (years) | < 30 | 218(22.83) |
| 30–39 | 358(37.48) | |
| 40–49 | 241(25.24) | |
| ≥ 50 | 138(14.45) | |
| Marital status | Unmarried | 145(15.18) |
| Married | 792(82.93) | |
| Others | 18(1.89) | |
| Education | Junior college | 475(49.74) |
| Bachelor’s degree | 474(49.63) | |
| Master’s degree | 6(0.63) | |
| Daily working hours | ≤ 8 h | 408(42.72) |
| >8 h | 547(57.28) | |
| Annual income (Yuan) | < 30,000 | 398(41.68) |
| 30,000–49,999 | 346(36.23) | |
| 50,000–90,000 | 159(16.65) | |
| > 90,000 | 52(5.44) | |
| Job burnout | Yes | 668(69.95) |
| No | 287(30.05) | |
| Coping styles | positive | 654(68.48) |
| negative | 304(31.52) | |
| Depressive symptoms | Yes | 479(50.16) |
| No | 476(49.84) |
Bivariate correlations predictor, mediator, moderator, and depressive symptoms
The mean scores and the correlations among job burnout, coping styles, depressive symptoms, organizational support and presenteeism were presented in Table 2. Job burnout was positively correlated with depressive symptoms (r = 0.66, p < 0.001) and presenteeism (r = 0.41, p < 0.001). Coping styles were significantly negatively correlated with depressive symptoms (r = -0.24, p < 0.001) and presenteeism (r = -0.19, p < 0.001). Presenteeism was significantly and positively correlated with depressive symptoms (r = 0.44, p < 0.001). Organizational support was significantly negatively correlated with depressive symptoms (r = -0.35, p < 0.001) and presenteeism (r = -0.21, p < 0.001).
Table 2.
Bivariate correlations among predictor, mediator and moderator (n = 955)
| Variables | Mean ± SD | 1 | 2 | 3 | 4 | 5 |
|---|---|---|---|---|---|---|
| 1. Job burnout | 2.01 ± 1.10 | 1 | ||||
| 2. Coping styles | 7.01 ± 8.39 | -0.32*** | 1 | |||
| 3. Depressive symptoms | 15.25 ± 6.63 | 0.66*** | -0.24*** | 1 | ||
| 4. Organizational support | 37.95 ± 9.56 | -0.55*** | 0.30*** | -0.35*** | 1 | |
| 5. Presenteeism | 16.90 ± 5.74 | 0.41*** | -0.19*** | 0.44*** | -0.21*** | 1 |
Note: *p < 0.05, **p < 0.01, ***p < 0.001
Depressive symptoms as mediator
The results of hierarchical regression were shown in Table 3. Job burnout was significantly and positively related to presenteeism (β = 2.23, 95%CI [1.93,2.53]) after adjusting for covariates, providing support for hypothesis 1 (see Model 1). Greater job burnout significantly predicted higher depressive symptoms (β = 3.98, 95%CI [3.69,4.27]) (see Model 2). When job burnout and depressive symptoms were included, depressive symptoms were significantly associated with higher presenteeism (β = 0.24, 95%CI [0.18,0.31]), and the direct effect of job burnout on presenteeism was still significant (β = 1.27, 95%CI [0.88,1.65]) (see Model 3). Moreover, the bias-corrected percentile Bootstrap test showed that the mediating effect was significant (indirect effect = 0.96, 95%CI [0.70,1.25]), accounting for 43.05% of the total effect. This indicated that depressive symptoms played a partial mediating role in this relationship between job burnout and presenteeism. Thus, hypothesis 2a and 2b were supported.
Table 3.
Mediation models of job burnout on presenteeism
| Model 1 (presenteeism) |
Model 2 (depressive symptoms) |
Model 3 (presenteeism) |
||||
|---|---|---|---|---|---|---|
| Coefficients | 95%CI | Coefficients | 95%CI | Coefficients | 95%CI | |
| Variables | ||||||
| Job burnout | 2.23*** | 1.93,2.53 | 3.98*** | 3.69,4.27 | 1.27*** | 0.88,1.65 |
| Depressive Symptoms | 0.24*** | 0.18,0.31 | ||||
| Adj-R2 | 0.21 | 0.44 | 0.26 | |||
| F | 28.47*** | 82.51*** | 32.70*** | |||
Note: N = 955, 95%CI = Bootstrap confidence intervals with lower and upper limits *p < 0.05, **p < 0.01, ***p < 0.001. Gender, age, marital status, education level, daily working hours, and annual income were analyzed as control variables. Gender: male = 0, female = 1; Marital status: unmarried = 0, married = 1; Education: junior college and below = 0, bachelor’s degree and above = 1; Daily working hours: ≤8 h = 0, >8 h = 1; Annual income:<30,000 = 0, 30,000–49,999 = 1, 50,000–90,000 = 2,>90,000 = 3
Coping styles and organizational support as moderators
The study used Hay’s PROCESS (Model 21) to validate the moderated mediation model. Testing results were displayed in Table 4. The interaction between job burnout and coping styles had a significant predictive effect on depressive symptoms (β = -0.06, 95%CI [-0.09, -0.02]) (see Model 4), indicating that coping styles moderated the relationship between job burnout and depressive symptoms. As shown in Table 4, the interaction between depressive symptoms and organizational support had a statistically significant predictive effect on presenteeism (β = 0.01, 95%CI [0.0003,0.01]) (see Model 5), which indicated that organizational support moderated the relationship between depressive symptoms and presenteeism. The moderated mediation model has been shown in Fig. 2. Therefore, hypothesis 3a and 3b were supported.
Table 4.
Moderated mediation regressions of job burnout, depressive symptoms, coping styles, organizational support and presenteeism
| Model 4 (depressive symptoms) |
Model 5 (presenteeism) |
|||
|---|---|---|---|---|
| Coefficients | 95%CI | Coefficients | 95%CI | |
| Variables | ||||
| Job burnout | 4.27*** | (3.89,4.65) | 1.34*** | (0.90,1.77) |
| Depressive Symptoms | 0.05 | (-0.14,0.24) | ||
| Coping styles | -0.03 | (-0.06,0.01) | ||
| Organizational support | -0.07 | (-0.15,0.02) | ||
|
Job burnout* Coping styles |
-0.06** | (-0.09,-0.02) | ||
| Depressive Symptoms* Organizational support | 0.01* | (0.0003,0.01) | ||
| Adj-R2 | 0.45 | 0.26 | ||
| F | 69.46*** | 27.72*** | ||
Note: N = 955, 95%CI = Bootstrap confidence intervals with lower and upper limits *p < 0.05, **p < 0.01, ***p < 0.001. Gender, age, marital status, education level, daily working hours, and annual income were analyzed as control variables. Gender: male = 0, female = 1; Marital status: unmarried = 0, married = 1; Education: junior college and below = 0, bachelor’s degree and above = 1; Daily working hours: ≤8 h = 0, >8 h = 1; Annual income:<30,000 = 0, 30,000–49,999 = 1, 50,000–90,000 = 2,>90,000 = 3
Fig. 2.
Result for the testing hypothesis. Note: *p < 0.05, **p < 0.01, ***p < 0.001. Gender, age, marital status, education level, daily working hours, and annual income were analyzed as control variables
In order to further explore the moderating roles of coping styles and organizational support, this study used simple slope analysis to illustrate the interaction between 1 SD below the mean and 1 SD above the mean of coping styles and organizational support. This moderating effect was statistically significant in both low positive coping styles (βsimple = 4.27, 95%CI [3.89,4.65]) and high positive coping styles individuals (βsimple = 3.39, 95%CI [2.95,3.82]). The Johnson-Neyman inspection further illustrated that the relationship between job burnout and depressive symptoms diminished as motivation for positive coping styles increased, although this relationship remained statistically significant in Fig. 3a. The findings demonstrated that depressive symptoms had a significantly stronger impact on presenteeism for high organizational support public health physicians (βsimple = 0.32, 95%CI [0.22,0.41]) than for low organizational support individuals (βsimple = 0.21, 95%CI [0.14,0.28]). The Johnson-Neyman inspection revealed that organizational support could moderate the relationship between depressive symptoms and presenteeism when the moderating variable organizational support was >-24.54 in Fig. 3b.
Fig. 3.
Johnson–Neyman visualization of conditional indirect effect of coping styles and organizational support. a. The conditional effect of job burnout on depressive symptoms at the values of coping styles. b. The conditional effect of depressive symptoms on presenteeism at the values of organizational support
Additional analysis
The findings of additional subgroup regression analyses are presented in Supplementary Table 1. Higher organizational support significantly increased presenteeism among males (β = 0.08, 95%CI [0.01,0.16]), but this relationship was not significant for females (β = -0.03, 95%CI [-0.08, 0.02]). The aged-based subgroup analysis revealed that job burnout was positively linked to presenteeism (β = 1.37, 95%CI [0.37,2.36] for < 30 years; β = 1.35, 95%CI [0.66,2.05] for 30–39 years; β = 0.99, 95%CI [0.18,1.95] for 40–49 years). Compared with public health physicians working less than 8hours, those working more than 8hours showed significant relationships with presenteeism concerning job burnout (β = 1.34, 95%CI [0.80,1.87]) and coping styles (β = -0.07, 95% CI [-0.12, -0.02]). Additionally, for those with an annual income of less than 30,000 yuan, job burnout (β = 1.04, 95%CI [0.33,1.75]), depressive symptoms (β = 0.20, 95%CI [0.10,0.31]), and coping styles (β = -0.09, 95%CI [-0.15,-0.02]) were significantly correlated with presenteeism.
Discussion
To our knowledge, this is the first study to propose a theoretical analysis framework based on the JD-R model and then examine the mediating role of depressive symptoms, as well as the moderating roles of coping styles and organizational support, in the relationship between job burnout and presenteeism among Chinese primary public health physicians. Our study had the following findings. First, job burnout was independently associated with presenteeism among public health physicians. Second, depressive symptoms, as the independent mediator, significantly mediated the effect of job burnout on presenteeism. Third, coping styles buffered the mediating pathways of job burnout on depressive symptoms and organizational support strengthened the positive relationship between depressive symptoms and presenteeism. In the presence of high positive coping styles, the harmful effects of job burnout on depressive symptoms declined. In the presence of high organizational support, the harmful effects of depressive symptoms on presenteeism increased. The findings help elucidate key underlying mechanisms and pathways linking above variables.
Job burnout and presenteeism: a core relationship in occupational health
A worthwhile finding of our study is that physicians who have job burnout exhibit significantly higher levels of presenteeism among Chinese primary public health physicians. Consistent with the JD-R model [18], chronic exposure to job demands depletes emotional resources over time, compelling public health physicians to prioritize presenteeism over rest and recovery. Chinese village doctors are responsible for 43.71% of the total workload associated with the National Essential Public Health Services workload, exceeding the Chinese government’s requirement (40%) [60]. This heavy workload, coupled with pressure from policy implementation, has exacerbated emotional exhaustion among public health physicians, adversely affecting their work functioning [61]. Moreover, Chinese employees, influenced by Confucian culture, may be more prone to presenteeism than their British counterparts [62]. This culture, which emphasizes hard work and endurance [63], may lead public health physicians to perceive work dedication as a moral obligation, thereby increasing their likelihood of justifying presenteeism to avoid disrupting team due to their absence. Consequently, job burnout-related presenteeism behaviors among public health physicians deserve more attention, particularly in rural institutions where public health services are relatively scarce. To mitigate job burnout among public health physicians, it is essential to ensure an appropriate workload, a conducive working environment [7], and supportive management policies [64]. Additionally, individuals should view health management as a fundamental aspect of professional responsibility, which can effectively protect psychological resources, diminish the belief that working while ill is necessary, and ultimately reduce presenteeism.
Depressive symptoms as a mediator between job burnout and presenteeism
The main contribution of our study is to demonstrate the important mediating role of depressive symptoms in the association between job burnout and presenteeism, which provides evidence for understanding the detrimental effect of job burnout on individuals’ presenteeism. Consistent with COR theory [24], our study finds that job burnout depletes psychological resources, prompting individuals to conserve their remaining energy through maladaptive coping, such as persisting at work despite experiencing depressive symptoms. When work-related issues lead to depressive symptoms, burnout serves as a critical intermediate step in this developmental process [65]. In addition, depressive symptoms lead to a decline in medical staff’s ability to concentrate, make decisions, and remember information, increasing their risk of medical errors [66]. This impairment is linked to a rise in presenteeism [5]. Therefore, it is essential to enhance training on emotional and behavioral regulation to break the cycle of job burnout and presenteeism [67]. Simultaneously, management should actively foster a harmonious and friendly team atmosphere, be attentive to the psychological well-being of physicians, and ensure a positive working environment [68].
Coping styles and organizational support: moderators of job burnout-presenteeism link
The findings show that job burnout among primary public health physicians with low positive coping style has a stronger positive predictive effect on depressive symptoms compared to those with high positive coping style. Coping styles serve as the key mechanisms of regulating stress response. According to the Stress Coping Theory [69], positive coping styles could help individuals effectively manage work stress and mitigate the negative effects caused by job burnout. Specifically, individuals in the high positive coping group can effectively counteract the cumulative effect of job burnout, creating a defensive barrier against depressive symptoms by adapting to changes in their environment [70, 71]. However, for those with low positive coping styles, the lack of adaptive strategies increases the likelihood that job burnout will overwhelm their psychological defenses, directly triggering depressive symptoms [72]. In primary health institutions, public health physicians may experience heightened work stress due to a lack of effective coping styles. Therefore, efforts should focus on enhancing positive coping skills such as taking scheduled breaks and exercising among rural physicians to reduce negative outcomes [73] like job burnout.
Organizational support, as an important resource for alleviating work stress, typically reduces physicians’ presenteeism by fostering a positive psychological state [43]. However, a surprising finding from our study is that the relationship between depressive symptoms and presenteeism is stronger among physicians who perceive higher levels of organizational support. According to the Social Exchange Theory [74], when employees perceive organizational support, they may feel a sense of obligation to reciprocate. High organizational support may make public health physicians feel accountable and motivated to intensify their efforts, while depressive symptoms may enhance their conscientiousness, thereby increasing presenteeism. Leadership Member Exchange Theory suggests that when employees feel supported, they are more likely to exceed their responsibilities [75]. Additionally, the negative effects of social support may arise from the manner in which it is provided, such as through inappropriate expressions or unwanted support [76]. When employees are over-dependent or under-balanced support, it may hurt work performance [77]. In contrast, for individuals with low organizational support, the pressure brought by support is relatively minimal. This phenomenon highlights the importance of aligning organizational support with individual needs. Therefore, it is important to enhance training for primary medical institutions to improve their ability to identify and address physicians’ psychosocial needs [78], particularly concerning job burnout and presenteeism.
The subgroup findings
The study also revealed notable heterogeneity in demographic and occupational factors influencing presenteeism. First, our results indicated an unexpected negative effect of organizational support on presenteeism, which was only significant among male public health physicians. Some men may feel constrained by traditional gender role norms, making them less inclined to seek help from others [79]. Consequently, when male public health physicians perceive organizational support, they may view work presenteeism as an obligation, thus neglecting health problems. In contrast, female public health physicians may be more likely to leverage organizational support as a resources for managing presenteeism [80]. This suggests that medical institutions should move away from a one-size-fits-all approach organizational support and consider designing anonymous support channels for men, such as anonymous psychological hotlines.
Second, significant age-specific effects were found in the < 30, 30–39, and 40–49 age groups, consistent with previous research [81, 82]. Young and middle-aged public health physicians often serve as the backbone of various units. In addition to their core job responsibilities, they might be required to undertake research obligations, resulting in greater professional pressure. This pressure makes them more susceptible to job burnout, which in turn contributes to presenteeism. Furthermore, the present study highlighted the significant effects of risk factors (depressive symptoms) and protective resources (coping styles and organizational support) in predicting presenteeism, particularly among physicians working more than 8hours a day. This finding is theoretically supported in COR Theory [24], which posits that long working hours and depressive symptoms accelerate the depletion of an individual’s psychological and physiological resources. Under the strain of extended working hours, an active coping approach can serve as a supplementary resource, effectively alleviating resource depletion among public health physicians. This approach not only mitigates long-term job burnout and negative emotions caused by extended work hours but also reduces the tendency toward presenteeism [83]. Therefore, it is suggested to offer flexible working hours for this group and reduce individual work pressure by optimizing labor division.
Finally, this study found that job burnout, depressive symptoms, and coping styles among public health physicians with an annual income of less than 30,000 yuan were related to presenteeism. This phenomenon can be explained by Ecological Systems Theory, which posits that individual traits engage in bidirectional interactions with nested environmental systems [84]. Low-income public health physicians often face greater economic pressure, which may lead them to work harder to maintain their income, thereby neglecting their mental health, overworking, and further intensifying presenteeism. In this context, coping styles act as compensatory factors, helping public health physicians manage stress and depressive symptoms, thereby influencing presenteeism. Organizational managers should strengthen cognitive-behavioral guidance for physicians, correct cognitive biases regarding presenteeism, and aim to improve work efficiency without increasing working hours.
Limitations and future directions
The present study has many limitations. First, although cross-sectional data in this study provide preliminary evidence for associations between variables, they do not allow for definitive conclusions about causal inference. Therefore, it is necessary to conduct future longitudinal studies with cross-lagged designs to verify our findings. For instance, a longitudinal study could examine whether job burnout at Time 1 predicts depressive symptoms at Time 2 and subsequent presenteeism at Time 3, thereby ruling out reverse causality. Second, this study adopted convenience sampling, with samples recruited from Yancheng City, Jiangsu Province. Future research needs to expand the geographical coverage and employ probabilistic sampling to enhance the representativeness of samples. Therefore, caution should be taken as to whether our findings are generalizable. Third, as the questionnaire was self-completed by public health physicians, self-reported data may be prone to potential social desirability bias and retrospective bias. Thus, future research should combine objective data (such as physiological indicators) and third-party evaluations to mitigate measurement biases. Additionally, the missing data were processed using the listwise deletion, which may lead to the loss of sample information. It is suggested that in future research, techniques such as multiple imputation methods should be applied to enhance data integrity.
Implications
The findings of this study have both theoretical and practical implications for preventing and reducing presenteeism in Chinese primary public health physicians.
From a theoretical perspective, previous studies have primarily explored the impact of individual psychological traits on the relationship between job burnout and presenteeism but have largely overlooked the influence of individual psychological resources (e.g., coping styles) and environmental resources (e.g., organizational support). Our study investigated these mechanisms specifically among Chinese primary public health physicians, thereby expanding the understanding of the mediating role of depressive symptoms and the moderating effects of coping styles and organizational support in this population. This study reveals the complex interaction mechanisms between individuals and organizations. Specifically, it further elucidates the synergistic roles of coping styles and organizational support in the career development of primary public health physicians.
Secondly, our findings suggest that severe job burnout, through its association with depressive symptoms, is a significant risk factor for presenteeism. Therefore, interventions such as reducing work stress, providing psychological support, and optimizing workload management can effectively mitigate presenteeism. Importantly, the findings highlight the protective role of positive coping styles in buffering the effects of job burnout on depressive symptoms. Public health practitioners ought to prioritize enhancing individual coping skills and organizations should promote flexible work patterns, especially for those with long working hours and low income.
Thirdly, the influence of organizational support is particularly evident among male public health physicians. While organizational support typically mitigates presenteeism, high organizational support may paradoxically reinforce presenteeism among males with strong organizational identification, as their loyalty to the organization and gender-role expectations of professional dedication may pressure them to prove commitment through prolonged presence. In such cases, moderating excessive support rather than reducing it outright may help alleviate role overload and improve mental health.
Finally, for primary public health physicians, coping styles and organizational support are indispensable cornerstones in their career development. It is vital that the government, medical institutions, social organizations, and individuals collaborate to build a support system covering the entire career development cycle, thereby promoting dynamic balance between work environments and mental health.
Conclusion
The present study, which focuses on primary public health physicians, contributes to the existing body of evidence regarding the relationship between job burnout and presenteeism. This study confirmed the mediating role of depressive symptoms, as well as the moderating roles of coping styles and organizational support in this relationship. The more positive the coping styles, the weaker the effect of job burnout on depressive symptoms, and vice versa. Contrary to expectations, higher organizational support strengthened the positive relationship between depressive symptoms and presenteeism more than lower organizational support. These findings enhance our understanding of how job burnout positively affects presenteeism and underscore the importance of psychological, cognitive and environmental factors. Notably, the results suggest that strategies aimed at improving mental health, strengthening positive coping styles, and appropriate organizational support could effectively alleviate the effect of job burnout on presenteeism. Cooperation among the government, primary medical institutions, and relevant stakeholders should be enhanced to foster a favorable environment for the professional development of public health physicians.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Acknowledgements
We appreciate the public health physicians who provide public health services in Yancheng, Jiangsu Province for their assistance.
Abbreviations
- JD-R
Job Demands-Resources model
- COR
Conservation of Resource theory
- CMB
Common-method bias test
- VIF
Variance inflation factors
Author contributions
KXR and ZMM greatly contributed to conception and design, or analysis and interpretation of data. LRY and LXZ analyzed and interpreted the data. CDF and ZXY contributed to data acquisition. MQ and GYX drafted the article and substantively revised it for important intellectual content. Each author has read and approved the final version of the manuscript.
Funding
This study received no specific grants from the public, commercial, or not-for-profit funding agencies.
Data availability
The raw data that support the conclusions of this article will be made available by the corresponding authors, without undue reservation.
Declarations
Ethics approval and consent to participate
All participants provided written informed consent online before the study began. This study was conducted in accordance with the principles outlined in the Declaration of Helsinki. All methods were performed in compliance with the relevant guidelines. The research concerning human participants received review and approval from the Ethics Committee of Nantong University.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Xinru Kong and Miaomiao Zhao have contributed equally to this work.
Contributor Information
Qiang Ma, Email: qiangma@ntu.edu.cn.
Yuexia Gao, Email: yxgao@ntu.edu.cn.
References
- 1.Lohaus D, Habermann W. Presenteeism: A review and research directions. Hum Resource Manage Rev. 2019;29(1):43–58. [Google Scholar]
- 2.Liu T, et al. Job crafting and nurses’ presenteeism: the effects of job embeddedness and job irreplaceability. Front Public Health. 2022;10:930083. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Zhang X, et al. Sickness presenteeism, job burnout, social support and health-related productivity loss among nurses in the Chinese nurses’ health cohort study (TARGET): A cross-sectional survey. Int J Nurs Stud. 2025;162:104962. [DOI] [PubMed] [Google Scholar]
- 4.Xi X, et al. Evaluation of the association between presenteeism and perceived availability of social support among hospital Doctors in Zhejiang, China. BMC Health Serv Res. 2020;20:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Xi X, et al. Doctor’s presenteeism and its relationship with anxiety and depression: a cross-sectional survey study in China. BMJ Open. 2019;9(7):e028844. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Mosteiro-Díaz MP, et al. Presenteeism in nurses: comparative study of Spanish, Portuguese and Brazilian nurses. Int Nurs Rev. 2020;67(4):466–75. [DOI] [PubMed] [Google Scholar]
- 7.Lui JNM, Andres EB, Johnston JM. Presenteeism exposures and outcomes amongst hospital Doctors and nurses: a systematic review. BMC Health Serv Res. 2018;18:1–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Yingying W, et al. Analysis of human resource allocation and equity in China’s specialized public health institutions from 2012 to 2021. Chin J Health Policy. 2024;17(06):64–71. [Google Scholar]
- 9.Johari FS. Work-Related Stress and Coping Strategies: A Systematic. 2020.
- 10.Canboy B, et al. The impact of perceived organizational support on work meaningfulness, engagement, and perceived stress in France. Eur Manag J. 2023;41(1):90–100. [Google Scholar]
- 11.Wang Y, et al. Analysis of human resource allocation and equity in China’s specialized public health institutions from 2012 to 2021. Chin J Health Policy. 2024;17(06):64–71. [Google Scholar]
- 12.China D. o.P.D.a.I.T.N.H.C.o.t.P.s.R.o., Statistical bulletin of China’s health development in 2023. Chin J Viral Dis. 2024;14(05):416–24.
- 13.Mengru Y, et al. Occupational stress, anxiety, and depression among grassroots disease control and prevention staff in Hebei Province: A qualitative comparative analysis based on fuzzy sets. J Environ Occup Med. 2023;40(06):681–7. [Google Scholar]
- 14.Dall’Ora C, et al. Burnout in nursing: a theoretical review. Hum Resour Health. 2020;18:1–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Salvagioni DAJ, et al. Physical, psychological and occupational consequences of job burnout: A systematic review of prospective studies. PLoS ONE. 2017;12(10):e0185781. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Yajun L, et al. Current situation and influencing factors of job burnout of staff in primary-level institutions for disease prevention and control in Chengdu. Occup Health Emerg Rescue. 2024;42(06):711–5. [Google Scholar]
- 17.Edú-Valsania S, Laguía A, Moriano JA. Burnout: A review of theory and measurement. Int J Environ Res Public Health, 2022;19(3). [DOI] [PMC free article] [PubMed]
- 18.Demerouti E, et al. The job demands-resources model of burnout. J Appl Psychol. 2001;86(3):499–512. [PubMed] [Google Scholar]
- 19.Zhao Z, et al. The mediating effect of job burnout on perceived stress and presenteeism among geriatric caregivers in long-term care facilities. Geriatr Nurs. 2025;61:538–43. [DOI] [PubMed] [Google Scholar]
- 20.Cheng J, et al. Relationship between job burnout and presenteeism in anesthesia nurses: mediating effect of psychological capital. BMC Nurs. 2024;23(1):853. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Pei P, et al. The association between Doctors’ presenteeism and job burnout: a cross-sectional survey study in China. BMC Health Serv Res. 2020;20(1):715. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Saade S et al. Depressive symptoms in helping professions: a systematic review of prevalence rates and work-related risk factors. Int Arch Occup Environ Health, 2022: 1–50. [DOI] [PMC free article] [PubMed]
- 23.Xie N, et al. Prevalence of depressive symptoms among nurses in China: A systematic review and meta-analysis. PLoS ONE. 2020;15(7):e0235448. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Hobfoll SE. Conservation of resources: a new attempt at conceptualizing stress. Am Psychol. 1989;44(3):513. [DOI] [PubMed] [Google Scholar]
- 25.Yu S, et al. The interaction of occupational stress and job burnout on depressive symptoms in railway workers in Fuzhou City. BMC Public Health. 2024;24(1):1432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Ahola K, Hakanen J. Job strain, burnout, and depressive symptoms: A prospective study among dentists. J Affect Disord. 2007;104(1–3):103–10. [DOI] [PubMed] [Google Scholar]
- 27.Toker S, Biron M. Job burnout and depression: unraveling their Temporal relationship and considering the role of physical activity. J Appl Psychol. 2012;97(3):699. [DOI] [PubMed] [Google Scholar]
- 28.Johnston D, et al. The relationship between depression symptoms, absenteeism and presenteeism. J Affect Disord. 2019;256:536–40. [DOI] [PubMed] [Google Scholar]
- 29.Hakanen JJ, Schaufeli WB, Ahola K. The job demands-resources model: a three-year cross-lagged study of burnout, depression, commitment, and work engagement. Work & stress. 2008;22(3):224–41.
- 30.Folkman S, et al. Appraisal, coping, health status, and psychological symptoms. J Personal Soc Psychol. 1986;50(3):571. [DOI] [PubMed] [Google Scholar]
- 31.Xie Y. A preliminary study of the reliability and validity of the brief coping styles scale. Chin J Clin Psychol. 1998;6(2):114–5. [Google Scholar]
- 32.Pearlin LI. The sociological study of stress. J Health Soc Behav, 1989: pp. 241–56. [PubMed]
- 33.Smith CA, Ellsworth PC. Patterns of cognitive appraisal in emotion. J Personal Soc Psychol. 1985;48(4):813. [PubMed] [Google Scholar]
- 34.Lin HS, Probst JC, Hsu YC. Depression among female psychiatric nurses in Southern Taiwan: main and moderating effects of job stress, coping behaviour and social support. J Clin Nurs. 2010;19(15–16):2342–54. [DOI] [PubMed] [Google Scholar]
- 35.Lin J, et al. Factors associated with resilience among non-local medical workers sent to Wuhan, China during the COVID-19 outbreak. BMC Psychiatry. 2020;20:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Chang EM, et al. A survey of role stress, coping and health in Australian and new Zealand hospital nurses. Int J Nurs Stud. 2007;44(8):1354–62. [DOI] [PubMed] [Google Scholar]
- 37.Li Z, et al. Psychological distress, social support, coping style, and perceived stress among medical staff and medical students in the early stages of the COVID-19 epidemic in China. Front Psychiatry. 2021;12:664808. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Gmitrowicz A, Szczepaniak A, Jabłkowska-Górecka K. The evaluation of the stress coping styles and emotional intelligence in psychiatrically treated adolescent patients with deliberate self-harm in relation to chosen clinical features. Psychiatr Pol. 2012;46(2):227–40. [PubMed] [Google Scholar]
- 39.Cheng WLS, Young PMC, Luk KKH. Moderating role of coping style on the relationship between stress and psychological well-being in Hong Kong nursing students. Int J Environ Res Public Health. 2022;19(18):11822. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Rhoades L, Eisenberger R. Perceived organizational support: a review of the literature. J Appl Psychol. 2002;87(4):698–714. [DOI] [PubMed] [Google Scholar]
- 41.Jolly PM, Kong DT, Kim KY. Social support at work: an integrative review. J Organizational Behav. 2021;42(2):229–51. [Google Scholar]
- 42.Chen Y, et al. A chain mediation model on organizational support and turnover intention among healthcare workers in Guangdong Province, China. Front Public Health. 2024;12:1391036. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Wang T, et al. The moderating effect of perceived organizational support on presenteeism related to the inclusive leadership. BMC Nurs. 2024;23(1):139. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Chen L, et al. The impact of paternalistic leadership styles on employee engagement in the pharmaceutical distribution industry: the mediating role of psychological capital. J Chin Hum Resou Ma. 2023;14(2):3–22. [Google Scholar]
- 45.Reitz KM, et al. Healthcare providers’ perceived support from their organization is associated with lower burnout and anxiety amid the COVID-19 pandemic. PLoS ONE. 2021;16(11):e0259858. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 46.Sulistiyani E. Perceived organizational support and performance: the mediating effect of affective values. Jurnal Manajemen Bisnis. 2022;13(1):61–75. [Google Scholar]
- 47.Gerlach M et al. Presenteeism among nurses: an integrative review. Int J Nurs Stud Adv, 2024: p. 100261. [DOI] [PMC free article] [PubMed]
- 48.Koopman C, et al. Stanford presenteeism scale: health status and employee productivity. J Occup Environ Med. 2002;44(1):14–20. [DOI] [PubMed] [Google Scholar]
- 49.Jianlan R et al. Exploring anesthesiology nurse’presenteeism in China: cross-sectional study. BMC Public Health, 2024. 24(1): p. 2008. [DOI] [PMC free article] [PubMed]
- 50.Goldberg R, et al. Burnout and its correlates in emergency physicians: four years’ experience with a wellness booth. Acad Emerg Med. 1996;3(12):1156–64. [DOI] [PubMed] [Google Scholar]
- 51.Kalimo R, et al. Staying well or burning out at work: work characteristics and personal resources as long-term predictors. Work Stress. 2003;17(2):109–22. [Google Scholar]
- 52.Hao S, Zhang X. Job burnout and anxiety among medical staff: A latent profile and moderated mediation analysis. Volume 356. Social Science & Medicine; 2024. p. 117141. [DOI] [PubMed]
- 53.Kroenke K, Spitzer RL, Williams JB. The PHQ-9: validity of a brief depression severity measure. J Gen Intern Med. 2001;16(9):606–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Fortini S, et al. Use of the patient health Questionnaire-9 (PHQ-9) and generalized anxiety Disorder-7 (GAD-7) questionnaires for clinical decision-making and psychological referral in ophthalmic care: a multicentre observational study. BMJ Open. 2024;14(1):e075141. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Jiang N, et al. Comparison of depressive symptoms among emergency physicians and the general population in China: a cross-sectional study based on National data. Hum Resour Health. 2024;22(1):71. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Zhang C, et al. Relationships between self-efficacy, coping style and quality of work‐life among nursing managers in China: A cross‐sectional study. J Nurs Adm Manag. 2022;30(7):3236–46. [DOI] [PubMed] [Google Scholar]
- 57.Eisenberger R, et al. Perceived organizational support. J Appl Psychol. 1986;71(3):500. [Google Scholar]
- 58.Yin C, et al. Impact of long working hours on depressive symptoms among COVID-19 frontline medical staff: the mediation of job burnout and the moderation of family and organizational support. Front Psychol. 2023;14:1084329. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 59.Podsakoff PM, et al. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J Appl Psychol. 2003;88(5):879. [DOI] [PubMed] [Google Scholar]
- 60.Yin D, et al. Model to assess workload of village Doctors in the National essential public health services program in six provinces of China. BMC Health Serv Res. 2020;20:1–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 61.Hui L, Huayi X, Yali C. The ethical challenges faced by disease control and prevention personnel in response to public health emergency based on COVID-19 prevention and control. Volume 44. Medicine & Philosophy; 2023. pp. 11–5. 02.
- 62.Lu L, Cooper CL, Yen Lin H. A cross-cultural examination of presenteeism and supervisory support. Career Dev Int. 2013;18(5):440–56. [Google Scholar]
- 63.Connection CC. Chinese values and the search for culture-free dimensions of culture. J Cross-Cult Psychol. 1987;18(2):143–64. [Google Scholar]
- 64.Challener DW, et al. Healthcare personnel absenteeism, presenteeism, and staffing challenges during epidemics. Infect Control Hosp Epidemiol. 2021;42(4):388–91. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 65.Maslach C, Leiter MP. Understanding the burnout experience: recent research and its implications for psychiatry. World Psychiatry. 2016;15(2):103–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 66.Pereira-Lima K, et al. Association between physician depressive symptoms and medical errors: a systematic review and meta-analysis. JAMA Netw Open. 2019;2(11):e1916097. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 67.Miki A, Lau MA, Moradian H. An open trial of the effectiveness, program usage, and user experience of internet-based cognitive behavioural therapy for mixed anxiety and depression for healthcare workers on disability leave. J Occup Environ Med. 2021;63(10):865–74. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 68.Fond G, et al. Depression in healthcare workers: results from the nationwide AMADEUS survey. Int J Nurs Stud. 2022;135:104328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 69.Folkman S. Stress: appraisal and coping, in Encyclopedia of behavioral medicine. Springer; 2020. pp. 2177–9.
- 70.Ryu GW, Yang YS, Choi M. Mediating role of coping style on the relationship between job stress and subjective well-being among Korean Police officers. BMC Public Health. 2020;20:1–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 71.Zakaria N, et al. Burnout and coping strategies among nurses in Malaysia: a national-level cross-sectional study. BMJ Open. 2022;12(10):e064687. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 72.Yan L, et al. The relationship between perceived stress and emotional distress during the COVID-19 outbreak: effects of boredom proneness and coping style. J Anxiety Disord. 2021;77:102328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 73.Liu Y, et al. Psychological strains, depressive symptoms, and suicidal ideation among medical and non-medical staff in urban China. J Affect Disord. 2019;245:22–7. [DOI] [PubMed] [Google Scholar]
- 74.Homans GC. Social behavior as exchange. Am J Sociol. 1958;63(6):597–606. [Google Scholar]
- 75.Mumtaz S, Rowley C. The relationship between leader–member exchange and employee outcomes: review of past themes and future potential. Manage Rev Q. 2020;70(1):165–89. [Google Scholar]
- 76.Semmer NK et al. Dysfunctional social support: delivering social support at work in an unappreciative way. Occup Health Sci, 2025: pp. 1–26.
- 77.Dennerlein T, Kirkman BL. The hidden dark side of empowering leadership: the moderating role of hindrance stressors in explaining when empowering employees can promote moral disengagement and unethical pro-organizational behavior. J Appl Psychol. 2022;107(12):2220–42. [DOI] [PubMed] [Google Scholar]
- 78.Stringer H. Worker well-being is in demand as organizational culture shifts. Monit Psychol. 2023;54(1):58. [Google Scholar]
- 79.Galdas PM, Cheater F, Marshall P. Men and health help-seeking behaviour: literature review. J Adv Nurs. 2005;49(6):616–23. [DOI] [PubMed] [Google Scholar]
- 80.Gustafsson Sendén M, Schenck-Gustafsson K, Fridner A. Gender differences in reasons for sickness Presenteeism-a study among gps in a Swedish health care organization. Annals Occup Environ Med. 2016;28:1–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 81.Ni WY, et al. The status and influencing factors of presenteeism among clinical nurses: a systematic review. Zhonghua lao Dong wei Sheng zhi ye Bing za zhi = Zhonghua Laodong Weisheng Zhiyebing Zazhi = Chinese. J Industrial Hygiene Occup Dis. 2023;41(4):286–93. [DOI] [PubMed]
- 82.Allemann A, Siebenhüner K, Hämmig O. Predictors of presenteeism among hospital employees—a cross-sectional questionnaire-based study in Switzerland. J Occup Environ Med. 2019;61(12):1004–10. [DOI] [PubMed] [Google Scholar]
- 83.Tang Y-l, Raffone A, Wong SYS. Burnout and stress: new insights and interventions. Sci Rep. 2025;15(1):8335. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 84.Bronfenbrenner U. Ecological systems theory. American Psychological Association; 2000.
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Data Availability Statement
The raw data that support the conclusions of this article will be made available by the corresponding authors, without undue reservation.



