Network analysis of perceived stress and burnout among Chinese nurses

doi:10.21203/rs.3.rs-4825399/v1

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Research Article

Network analysis of perceived stress and burnout among Chinese nurses

https://doi.org/10.21203/rs.3.rs-4825399/v1

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Background

Burnout poses a significant threat to clinical nurses' mental health and the quality of healthcare services. This study constructed a burnout-perceived stress network model and explored its associations with job satisfaction.

Methods

An online cross-sectional survey was conducted from November 13 to December 15, 2023, across 23 hospitals in China. The Chinese versions of the Perceived Stress Scale, the Maslach Burnout Inventory General Survey, and the Nurse Working Satisfaction Scale were used to assess stress, burnout, and job satisfaction, respectively. Network analysis was employed to identify central nodes and bridges in the burnout-perceived stress network and their connections to job satisfaction.

Results

"Good at job" demonstrated the highest expected influence in the entire stress-burnout network, followed by "Stressed" and "Less enthusiasm". "Contributing", "Effective", "Felt yourself on top of things", and "Confident about the ability to handle personal problems" were identified as the most critical bridge symptoms connecting the stress-burnout network. Within the burnout community, "Contributing" and "Doubt significance" showed the strongest direct associations with job satisfaction.

Conclusion

Burnout-related symptoms play a crucial role in the central nodes, bridge symptoms, and associations with job satisfaction within the stress-burnout network of clinical nurses. These symptoms have significant implications for improving the quality of work life for nursing staff.

Burnout

perceived stress

nurses

network analysis

Psychological disorders threaten the health and quality of healthcare services provided by clinical nurses in China. Nurses play a crucial role in China's healthcare system, boasting the highest number of registered nurses globally, approximately 3.8 million(1). Compared to other medical professions, nursing in China faces significant stress, burnout, and relatively low wages(2, 3). Furthermore, there is a severe shortage of nurses in China, with only 2.7 nurses per 1000 people, far below the global average and levels seen in developed countries such as the United States and Switzerland(4). This shortage has substantially increased nurse turnover rates, rising from 6.5% in recent years to 30%(5).

The relationship between perceived stress and burnout among nurses has been the subject of extensive research, with numerous studies consistently demonstrating a significant positive correlation between these two constructs(6, 7). The Job Demands-Resources (JD-R) theory provides a comprehensive framework for understanding this relationship(8). According to the JD-R model, job characteristics can be categorized into job demands (e.g., high workload, emotional labor, time pressure) and job resources (e.g., social support, autonomy, skill variety). Job demands require sustained physical or psychological effort and are associated with physiological and psychological costs, while job resources help achieve work goals, reduce job demands, or stimulate personal growth(9).

The JD-R model posits that burnout develops through two primary processes: (1) an energy depletion process, where high job demands exhaust employees' mental and physical resources, leading to emotional exhaustion, and (2) a motivational process, where lack of resources leads to disengagement and reduced personal accomplishment(10). In this context, perceived stress acts as a mediator, particularly in the energy depletion process. As nurses perceive higher levels of stress due to increased job demands, they experience greater emotional exhaustion, which is the core component of burnout(11). Longitudinal studies have further revealed a potentially cyclical and self-reinforcing relationship between stress and burnout: prolonged high-stress states can lead to burnout, which in turn may increase an individual's sensitivity to stress(12). This dynamic interplay creates a negative spiral, where burnout can lead to an increased perception of job demands and a decreased ability to utilize available resources(13). Notably, China's unique cultural background, including collectivist values and hierarchical social structures, might influence nurses' stress perception and coping strategies, thereby affecting the development of burnout(14). This cultural aspect adds a layer of complexity to the stress-burnout relationship in the Chinese nursing context. Given these findings, an in-depth exploration of the specific associations between perceived stress and the dimensions of burnout symptoms among Chinese nurses holds significant theoretical and practical implications.

Network analysis (NA) is increasingly applied in the field of psychology, particularly in studying complex psychological phenomena, interactions between individuals, and patterns of psychological disorders transmission. At its core, network analysis revolves around two key elements: "nodes" and "edges"(15). Each node in a network model represents a specific psychological phenomenon or symptom, while edges denote the strength of relationships between these nodes(16). Central nodes typically have more connections in the network or are connected to other important nodes, playing crucial roles in information dissemination and influence diffusion(17). Removal of these nodes can lead to significant changes or fragmentation within the network, which has important insights into the spread of disease, the structure of society, and the stability of other complex systems(18). In disease control, optimizing resource allocation to regulate the influence of these nodes can greatly enhance intervention effectiveness. In NA, bridge symptoms are often used to describe key nodes or factors that connect different subsystems or groups within complex systems(17). Specifically, bridge symptoms refer to those that facilitate connections between different psychological disorders or symptoms. These symptoms may not be a core feature of any single mental illness, but they are shared across multiple disorders or symptoms and serve to facilitate the interaction or transmission of these disorders or symptoms(19). Bridge symptoms are often critical to understanding how different diseases are interconnected and how cross-disease interventions and treatment strategies can be developed.

Despite extensive research exploring the relationship between stress and burnout, studies to date have yet to elucidate the network structure of perceived stress and burnout among nurses. Such an understanding is crucial for developing tailored interventions to address nurse burnout. This study employed NA to investigate the interrelationships between perceived stress and burnout symptoms in a cohort of Chinese nurses, aiming to identify central symptoms and delineate the specific structure of this network.

2.1 Study Design and Participants

This was a cross-sectional study on the psychological health status of clinical nurses in China, conducted through convenience sampling from November 13 to December 15, 2022, across 11 provinces in China. The study participants were recruited from 23 hospitals throughout the country. Due to COVID-19 isolation policies, we replaced traditional face-to-face surveys with an online survey. Data collection for the online survey was based on "Wenjuanxing," an extension program of WeChat (a Chinese instant messaging software). "Wenjuanxing" is a professional online survey program that offers a range of functions, including online questionnaire design, data collection, and survey result analysis. Participants completed the online informed consent and questionnaire assessment by scanning a QR code generated by "Wenjuanxing" through WeChat. Participants were required to meet the following criteria: 1) registered nurse; 2) voluntary participation and completion of online informed consent; 3) ability to understand the content of the Chinese questionnaire. This study was conducted by the Declaration of Helsinki, and the research protocol was approved by the Ethics Committee of Jining Medical University. To prevent duplicate responses, each IP address was limited to one survey participation.

2.2 Data Collection and Measures

The Maslach Burnout Inventory-General Survey (MBI-GS) is a widely used tool developed by American psychologists Maslach and Jackson to measure the frequency and severity of burnout symptoms(20). With permission from the original developer, Professor Michael Leiter, Professor Li Chaoping from China adapted and translated the MBI-GS into Chinese. The adaptation process involved multiple steps. First, four experts independently translated the English questionnaire into Chinese and discussed the translations to ensure linguistic accuracy and cultural relevance. Next, the questionnaire was refined through pilot testing with employees from various industries, followed by back-translation into English by two experts and submission to Professor Leiter for review and feedback. Based on the feedback, the questionnaire was further revised, resulting in a 16-item Chinese version. Exploratory factor analysis revealed that some items had high cross-loadings, which were addressed through item deletion and revision, ultimately yielding a 15-item scale. The revised Chinese MBI-GS consists of three dimensions: emotional exhaustion (5 items), depersonalization (4 items), and reduced personal accomplishment (6 items), with each item scored on a 7-point Likert scale to assess various aspects of burnout. Professor Li's research has demonstrated that the adapted scale has good reliability and validity in China, and has been widely applied in various research and clinical settings(21). In this study, the Cronbach's alpha coefficient for the Chinese version of the MBI-GS was 0.975.

The Perceived Stress Scale-10 (PSS-10) is a widely used instrument developed by Cohen and Williamson in 1988 as a simplified version of the original 14-item PSS(22). The PSS-10 has been extensively applied to assess individual perceived stress levels. In China, Wang et al. adapted the PSS-10 for the Chinese population(23). The adaptation process involved a systematic approach. First, two Chinese-speaking psychiatrists independently translated the English scale into Chinese, followed by a discussion to form a preliminary Chinese version. Next, a bilingual psychologist who was unfamiliar with the original PSS translated the Chinese version back into English, and the translations were compared to identify inconsistencies. The research team then invited 15 university students to participate in a pilot test, and based on their feedback, some items were revised. The final 10-item Chinese PSS-10 was established. Wang et al. examined the psychometric properties of the Chinese PSS-10, and exploratory factor analysis revealed a two-factor structure, consisting of "perceived stress" and "perceived coping," similar to the original version. Confirmatory factor analysis further confirmed the stability of this structure. The internal consistency of the scale was satisfactory, with a Cronbach's α coefficient of 0.86 for the total scale and 0.82 and 0.77 for the two subscales, respectively(23). The scale has also demonstrated good criterion-related validity and predictive validity(24). The Chinese PSS-10 consists of 10 items, scored on a 5-point Likert scale from 0 (never) to 4 (often). The total score ranges from 0 to 40, with higher scores indicating higher levels of perceived stress. The scale has been widely applied in various Chinese populations, showing good psychometric properties(25). In the present study, the Cronbach's alpha coefficient of the scale was 0.966.

The Nurse Working Satisfaction Scale (NWSS) is a classic scale designed by Warr et al.(26) and has been widely used in modern nursing management research (to measure several work attitudes and mental health scales). The scale was revised in Chinese by Hong Lu of Peking University (who measured the Nurses' Job Satisfaction Scale using factor analysis), and its structural validity was verified by factor analysis(27). The scale was translated and reviewed by three nursing professionals fluent in English and Chinese. First, the first expert translated it from English to Chinese; then, the second expert performed back-translation, i.e., translated the translated Chinese version into English again without viewing the original English version; finally, the third expert compared the back-translated English version with the original English scale and performed the final proofreading. The Chinese version of the NWSS was assessed for surface and content validity by three experts in nursing management, and the results showed that the content validity index was 0.89. Subsequently, the results of 512 clinical nurses were collected for the measurement of the structural validity of the scale. It was finally determined that the Chinese version of the NWSS included 15 items and two factors. Each item was rated from 0 (very dissatisfied) to 4 (very satisfied), and the total score ranged from 0 to 60. Higher scores indicate higher job satisfaction. The scale has been widely used in job satisfaction surveys for Chinese clinical nurses and has shown good reliability and validity(28). The Cronbach's alpha coefficient of the Chinese version of the NWSS in this study was 0.970.

2.3 Statistical Analyses

2.3.1 Network Structure

The graphical Gaussian model (GGM) for work burnout and perceived stress was constructed using "R" (version 4.4.1). The network edges were established by calculating partial correlations between all items of the MBI-GS and PSS. To optimize the network edges between variables, the least absolute shrinkage and selection operator (LASSO) and extended Bayesian information criterion (EBIC) were employed, resulting in a sparse and more interpretable network model. The constructed network was visualized using the "qgraph" package (version 1.9.8) and "bootnet" package (version 1.6.0). The thickness of the edges represents the strength of associations between nodes, with thicker edges indicating stronger associations. The colour of the edges denotes the direction of the associations between nodes, with blue edges representing positive correlations and red edges representing negative correlations.

2.3.2 Centrality and Stability

Node importance was quantified using node centrality indices. Among various centrality measures such as strength, closeness, and betweenness, we selected expected influence (EI) (more suitable for networks with both positive and negative correlations) to assess which nodes occupy more central positions and exert greater influence in the network. The stability of the network model was evaluated by calculating Correlation Stability Coefficients (CS-C). A CS coefficient threshold of 0.25 was set, with values > 0.25 indicating moderate stability and > 0.5 indicating strong stability. Bridge symptoms were identified using the "networktools" package (version 1.5.2). Deactivation of bridge symptoms with high expected influence values can prevent the activation of one symptom by another. The "flow" function in the "qgraph" package was used to identify burnout and perceived stress symptoms directly or indirectly associated with job satisfaction.

2.3.3 Network Comparison

Given the gender differences in burnout and perceived stress, we constructed separate network models for males and females. The differences between these two network models were compared using the "NetworkComparisonTest" package (version 2.2.1) (with 1000 permutations) to examine global strength invariance and edge strength invariance.

This study included 484 nurses (392 females and 92 males). Among the participants, 245 (50.6%) held primary titles, 312 (64.5%) had children, and 333 (68.8%) were married (Table 1).

Table 1

The sociodemographic characteristics and occupational characteristics of the nurses. (N = 484)
Variables	Categories	N	%
Age	< 30	181	37.4
	30–39	209	43.2
	40–50	64	13.2
	> 50	30	6.2
Gender	Male	92	19.0
	Female	392	81.0
Marital status	Unmarried and other	151	31.2
	Married	333	68.8
Children	Yes	312	64.5
	No	172	35.5
Education level	Junior college and below	99	20.5
	Undergraduate or above	385	79.5
Title of occupation	No	43	8.9
	Primary title	245	50.6
	Intermediate title	171	35.3
	Senior title	25	5.2
Administrative position	Yes	63	13.0
	No	421	87.0
Job tenure	1–5 years	133	27.5
	6–9 years	104	21.5
	≥ 10 years	247	51.0
Employment status	Contract worker	369	76.2
	Regular payroll	115	23.8
Night shift	Yes	365	75.4
	No	119	24.6
Hours worked per week	≤ 40 hours	182	37.6
	> 40 hours	302	62.4
Monthly income	≤ 5000 RMB	205	42.4
	> 5000 RMB	279	57.6

3.1 Network structure

Figure 1 illustrates the network structure of comorbid burnout and perceived stress among clinical nurses. The highest edge weight was observed between MBI 11 ("Contributing") and MBI 12 ("Good at job") (weight = 0.40), followed by the connection between MBI 6 ("Less interested") and MBI 7 ("Less enthusiastic") (weight = 0.39), and the connection between PSS 9 ("Angered by things that were outside of control") and PSS 10 ("Difficulties pile up and could not overcome") (weight = 0.38). The strongest connections between the burnout community and the perceived stress community were the edges between PSS 4 ("Confident about the ability to handle personal problems") and MBI 11 ("Contributing") (weight = 0.15) and between PSS 1 ("Upset by unexpected happenings") and MBI 1 ("Exhausted") (weight = 0.09).

MBI 12 ("Good at job") exhibited the highest EI in the entire burnout-perceived stress network, followed by MBI 4 ("Stressed") and MBI 7 ("Less enthusiasm") (Fig. 2). These three symptoms occupied the most central positions in the network and were crucial for understanding the interactions between nurses' burnout and perceived stress. In contrast, PSS 7 ("Able to control irritations"), PSS 6 ("Not cope with all the things that had to do"), and PSS 4 ("Confident about the ability to handle personal problems") were located at the periphery of the network.

MBI 11 ("Contributing") and MBI 10 ("Effective") from the work burnout community, along with PSS 8 ("On top of things") and PSS 4 ("Confident about the ability to handle personal problems") from the stress community, demonstrated the highest bridge EI. These symptoms were identified as the most critical bridge symptoms connecting burnout and perceived stress communities (Fig. 3 and Fig. 4).

3.2 Network stability

Regarding network stability, the burnout-perceived stress network demonstrated a CS coefficient of 0.75 for EI, indicating extremely high stability. This implies that after losing 75% of the sample, the EI of the subset maintained at least a 95% correlation with the EI of the original dataset. Bootstrap difference tests revealed that most comparisons between EIs were statistically significant (Fig. 5 and Figure S1A).

The CS coefficient for bridge EI was 0.13, suggesting an unstable network structure. This low stability indicates that we should exercise extreme caution when interpreting the results of bridge EI, as they may not be sufficiently reliable and should not be over-interpreted. Bootstrap difference tests indicated that only a few comparisons, specifically those involving MBI 11 ("Exhausted") and PSS 4 ("Confident about the ability to handle personal problems"), were statistically significant (Figure S1B).

Figure 6 illustrates a flow diagram depicting the associations between nurse job satisfaction and all other symptoms in the burnout-perceived stress network. The analysis revealed direct relationships between nurse job satisfaction and two key variables: MBI 11 ("Contributing") and MBI 8 ("Doubt significance"). These findings suggest that the perception of contributing to the workplace and doubts about job significance are directly linked to job satisfaction among nurses, potentially serving as critical factors in understanding and addressing burnout in this professional group.

3.3. Network comparisons

Figure S2 and Figure S3 illustrate the network structures generated for both genders, respectively. A Network Comparison Test (NCT) was conducted to examine potential differences between the male and female networks. The analysis revealed no statistically significant differences in either global network strength or edge weights between the two networks (male: 12.109 vs. female: 12.290; S = 0.374, p = 0.050; M = 0.181, p = 0.390). Specifically, the network structure invariance test (S) yielded a p-value of 0.050, while the global strength invariance test (M) resulted in a p-value of 0.390. These findings suggest that the overall network structure and the strength of individual connections are comparable between males and females in our sample.

This was the first NA study to document burnout and perceived stress among Chinese clinical nurses. Throughout the network model, several of the strongest edges of association were within the burnout community and stress community themselves, rather than between the two symptom communities which was generally consistent with the findings of previous studies(29, 30). This is in contrast to the results of a Chinese study that explored the relationship between depressive symptoms and burnout among nurses in an intensive care unit(30). In that study, MBI 8 ("Doubt significance") and MBI 9 ("Indifferent") were the most strongly weighted edges in the burnout community. Part of the reason for this difference may be the different focus of the survey. Specifically, ICU nurses suffer from high work stress and psychological burdens due to dealing with critically ill patients and high mortality rates(31). In contrast, general clinical nurses, while also assuming the role of caring for and treating patients, usually work on more general and routine nursing tasks(32). As they are directly involved in saving lives and protecting public health in the course of primary care monitoring, they are more likely to gain a sense of contribution and enhancement of the significance of their work, thus developing a sense of identity and satisfaction with their work and feeling the importance of their work to patients and society(33).

NA of burnout and perceived stress in our sample revealed that the EI centrality of nodes effectively identified key contributors to the overall symptom network. Notably, the MBI 12 ("Good at job") exhibited the highest centrality value. The high centrality of the "Good at job" item, part of the MBI's personal accomplishment dimension, underscores the crucial role of self-efficacy in the burnout-perceived stress interplay. This observation extends beyond the established burnout literature, suggesting that perceived professional competence plays a pivotal role in maintaining the burnout-perceived stress symptom network(8); high self-efficacy might buffer the impact of perceived stress on burnout development. Conversely, diminished personal accomplishment may not only exacerbate other burnout symptoms, such as emotional exhaustion and depersonalization(34), but also amplify the perception of work-related stressors(35). This finding aligns with recent network studies that have identified self-efficacy as a central node in stress-related psychopathology networks(36), highlighting its potential as a key target for interventions(37). Our results extend these findings by quantifying the relative importance of perceived competence within the broader stress-burnout network, providing a more nuanced understanding of the complex interplay between burnout and perceived stress.

The results of the bridge centrality analysis identified MBI 11 ("Contributing") as a bridge symptom in the burnout-perceived stress network. This finding has significant theoretical and practical implications. From a theoretical perspective, this result lends support to the JD-R model in explaining the mechanisms of occupational burnout formation. The JD-R model posits that job resources (e.g., social support and autonomy) can mitigate the stress caused by job demands, thereby reducing the risk of burnout(8). The bridge symptom identified in this study reflects an individual's positive evaluation of their work contribution, which can be viewed as a crucial psychological resource. When individuals perceive their work as valuable, they are more likely to mobilize positive emotions to cope with work stress, potentially reducing the occurrence of burnout(38). This finding also resonates with Self-Determination Theory (SDT), which emphasizes the importance of satisfying basic psychological needs (e.g., competence, relatedness, and autonomy) for individual psychological health and work motivation(39). The bridge symptom MBI 11 ("Contributing") directly relates to the satisfaction of competence needs, suggesting that enhancing employees' sense of competence may be a key approach to preventing occupational burnout(40). From a practical standpoint, this finding offers new insights for organizational management and occupational mental health interventions. Traditional burnout interventions often focus on reducing work stress or improving individual coping abilities(41). However, our results suggest that strengthening employees' perception of their work value may be a more effective approach. Organizations could implement this through clear performance feedback mechanisms, meaningful job design, recognition culture, and career development opportunities(10). Nevertheless, it is crucial to note that overemphasizing personal contribution may have adverse effects. Research has shown that excessive work engagement can lead to work-family conflicts, potentially increasing the risk of burnout(42, 43). Therefore, in practice, it is necessary to balance personal contribution with demands from other life domains. It is worth noting that the CS value of the expected bridge influence in this study was relatively low, indicating that the network model may not be sufficiently robust. This limitation reminds us to interpret the results cautiously and calls for further validation and refinement of the network model in future research(44). Additionally, considering the complex nature of burnout, future studies should explore more potential bridge symptoms and their manifestations across different occupational groups and cultural contexts(45). Drawing from the network theory of psychopathology(46, 47) and our empirical findings, we propose a novel hypothesis: interventions targeting work-related self-efficacy could potentially mitigate other symptoms within the burnout-perceived stress network. This hypothesis is predicated on the notion that modifying central symptoms may precipitate cascading effects throughout the entire symptom network, a concept supported by recent intervention studies in other psychopathological domains(48). However, it is crucial to acknowledge that network structure may vary across populations and contexts(49), and the temporal stability of these networks remains an open question(50).

For nurses, working satisfaction is not only about their attitudes and emotional experience of the job itself but also directly impacts their mental health, job performance, and long-term career development. We examined the symptoms most closely associated with working satisfaction. MBI 11 ("Contributing") and MBI 8 ("Doubt significance") were the two symptoms with the most significant correlations. The impact of burnout on clinical nurses' working satisfaction was generally consistent with the prominence of burnout symptoms in the burnout-perceived stress network, i.e., the key pivotal nodes and bridge symptoms were mostly found in the burnout symptom community. Based on the results of NA, the important role of burnout symptoms on overall mental health status and job satisfaction cannot be ignored. Interventions specifically targeting burnout symptoms among clinical nurses may profoundly impact alleviating overall insomnia and stress and improving working satisfaction in this population.

This study has several limitations that should be addressed. Firstly, the cross-sectional design limits our ability to capture the dynamic changes in occupational burnout and perceived stress over time and precludes the establishment of causal relationships between variables. Future longitudinal studies would provide more comprehensive insights into the temporal evolution of these constructs and their interrelationships. Secondly, the reliance on self-report measures for all variables introduces potential biases. Nurses may have underestimated or overestimated their levels of burnout and stress, potentially affecting the accuracy of the data. Future research could incorporate objective measures or multi-source data to mitigate these biases. Lastly, the focus on Chinese nurses may limit the generalizability of the findings to nursing populations in other cultural contexts. The unique aspects of Chinese culture, such as collectivism and specific doctor-patient relationship dynamics, may influence nurses' perceptions of stress and manifestations of burnout. Cross-cultural studies would be valuable in examining the universality and cultural specificity of the observed network structures. Despite these limitations, this study provides valuable insights into the network structure of burnout and perceived stress among Chinese nurses, offering a foundation for future research and targeted interventions in this critical healthcare population.

In the Chinese clinical nurse population, burnout-related symptoms were identified as the most critical symptoms in the burnout-stress network model in terms of central nodes and bridge symptoms, as well as associations with job satisfaction. Therefore, specific burnout symptoms deserve attention, both as a way to develop a nursing career assessment program to reduce or prevent common occupational stress syndromes and as an important target for interventions to improve the quality of life of nursing staff.

Ethics approval and consent to participate

This study was an online survey. Before completing the questionnaire, participants were informed of the purpose of the study and a brief description of the questionnaire. Participants were allowed to complete the questionnaire only after providing informed consent. This study was conducted by the Declaration of Helsinki, and the research protocol was approved by the Ethics Committee of Jining Medical University.

Consent for publication

Not applicable.

Availability of data and materials

The raw data supporting the conclusions of this article will be made available by corresponding authors, without undue reservation.

Competing Interests

None.

Funding

This study was supported by the Qingdao Science and Technology Benefit People Program (22-3-7-smjk-19-nsh).

Authors' contributions

M Hu, J Gao, and J Zhai designed this study. X Suo, Ya Zhang, and Yi Zhang performed data analysis and wrote and revised this manuscript. Yi Zhang, S Zhang, J Tian, X Wan and X Yuan conducted investigation and data curation. The final manuscript had been verified and approved by all authors.

Acknowledgements

We would like to express our thanks to all the nurses who participated in the study.

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No competing interests reported.

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Network analysis of perceived stress and burnout among Chinese nurses

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Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1. Introduction

2. Methods

2.1 Study Design and Participants

2.2 Data Collection and Measures

2.3 Statistical Analyses

2.3.1 Network Structure

2.3.2 Centrality and Stability

2.3.3 Network Comparison

3. Results

3.1 Network structure

3.2 Network stability

3.3. Network comparisons

4. Discussion

5. Limitations

6. Conclusion

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1