Dual-process model of courage.

Courage is one of the most significant psychological constructs for society, but not one of the most frequently studied. This paper presents a process model of courage consisting of decision-based pathways by which one comes to enact a courageous action. We argue the process of courage begins with a trigger involving an actor(s) and a situation(s). The actor(s) then engage(s) in four key assessments concerning (a) immediacy of the situation, (b) meaningfulness, value, and relevance to the actor, (c) adequacy of efficacy to act, and (d) decision to act with courage. The central component of this process entails an approach-avoidance conflict involving assessments of perceived risks and potential noble outcomes of acting with courage. The decision to act may result in courageous actions assuming it satisfies the four elements: intentionality, objective and substantial risk, a noble purpose, and meaning in time and place. Courageous actions have consequences. Finally, the consequences shape the actors' experience, which feeds into the trigger, closing the loop. Potential moderators of the courage process as well as potential tests of the model have been discussed.

Contingency and paradoxes in management practices-development plan as a case.

PURPOSE: As part of a national plan to govern professional and organizational development in Norwegian specialist healthcare, the country's hospital clinics are tasked with constructing development plans. Using the development plan as a case, the paper analyzes how managers navigate and legitimize the planning process among central actors and deals with the contingency of decisions in such strategy work. DESIGN/METHODOLOGY/APPROACH: This study applies a qualitative research design using a case study method. The material consists of public documents, observations and single interviews, covering the process of constructing a development plan at the clinical level. FINDINGS: The findings suggest that the development plan was shaped through a multilevel translation process consisting of different contending rationalities. At the clinical level, the management had difficulties in legitimizing the process. The underlying tension between top-down and bottom-up steering challenged involvement and made it difficult to manage the contingency of decisions. PRACTICAL IMPLICATIONS: The findings are relevant to public sector managers working on strategy documents and policymakers identifying challenges that might hinder the fulfillment of political intentions. ORIGINALITY/VALUE: This paper draws on a case from Norway; however, the findings are of general interest. The study contributes to the academic discussion on how to consider both the health authorities' perspective and the organizational perspective to understand the manager's role in handling the contingency of decisions and managing paradoxes in the decision-making process.

Individual, family and social-related factors of eating behavior among Chinese children with overweight or obesity from the perspective of family system.

Purpose: The purpose of the present study is to examine the factors contributing to the development of eating behavior in overweight and obese children from the perspective of the family system. Methods: A cross-sectional survey was conducted by using convenience sampling method to select 388 participants in two primary schools in Jiangsu, China. Individual, family and social-related factors were collected. Individual factors included age, gender, ethnicity, single child, social anxiety, depression, physical activity, sleep duration, screen time. Family factors included family environment, family structure, family function, family income, parenting style, parental feeding behavior, home food environment and marital satisfaction. Social-related factors included place of residence, number of surrounding restaurants and social support. Univariate analysis, correlation analysis and multivariate analysis were used to identify factors of eating behavior among Chinese children with overweight and obese. Results: In this study, 388 participants took part with a 94.865% response rate. In the univariate analysis, the significant differences regarding Dutch Eating Behavior Questionnaire (DEBQ) scores were found between children aged 6-9 years and those aged >9 years. Correlation analysis indicated that parent's nutrition literacy (r = 0.118, P < 0.05), pressure to eat (r = 0.212, P < 0.01), perception of child weight (r = -0.112, P < 0.05) and family function (r = -0.563, P < 0.01) were associated with children's eating behavior. With regard to psychosocial factors, children's social anxiety (r = 0.299, P < 0.01) and depressive symptoms (r = 0.081, P < 0.05) were in positive correlation with eating behavior. The independent variables included in the initial model were age, father's employment status, social anxiety, maternal punishment and harshness, parents' nutrition literacy, pressure to eat, family function and perception of child weight. These variables in the final model accounted for 20.7% of the variance. Conclusion: We found that age, father's employment status, social anxiety, maternal punishment and harshness, parents' nutrition literacy, pressure to eat, family function and perception of child weight have great effect on children's eating behavior who are overweight or obese. As early childhood is a critical timeline for child development, children's social anxiety, parenting style, parent's nutrition literacy, parent's feeding behavior and family function should be intervened to promote eating behavior. Intervention programs aimed at promoting healthy eating behaviors among children, thereby mitigating the risk of pediatric obesity, should primarily target parents.

The social network perspective on power system co-evolution: responses to "double carbon target" realization in China.

The introduction of dual carbon targets will significantly impact power system development. Despite this, there is currently limited research on achieving system evolution and transition while ensuring safety, low-carbon output, and efficiency, as well as quantitatively analyzing the resulting changes dual carbon targets will have on the power system. Co-evolution of the power system offers a solution to balance the impact of dual carbon goals and enhance interaction among system entities, thereby facilitating the achievement of these goals. Our study focuses on constructing an evolutionary topological network by analyzing the dynamic evolution rule of power systems. We investigate the co-evolution pattern of power systems by analyzing the relationship between the role of power system agents and their dynamic structures. Furthermore, we analyze the future structural changes of power systems, which can provide theoretical support for achieving dual carbon goals in the power system. Our findings highlight key measures to promote synergistic evolution, including increasing energy storage capabilities, stabilizing renewable energy supply, breaking inter-provincial barriers in electricity transmission, and developing a multi-level intelligent power system. Through link analysis, we discover that future power systems will maintain a mild coordination among agents rather than implementing large-scale realignment and reconfiguration. We posit that overcoming obstacles can be achieved by fostering cohesion between the network and agents through technological innovation and widespread market diffusion to drive co-evolution.

Looking beyond vaccines: Cultural tightness-looseness moderates the relationship between immunization coverage and disease prevention vigilance.

Advancements in vaccination technologies mitigate disease transmission risks but may inadvertently suppress the behavioral immune system, an evolved disease avoidance mechanism. Applying behavioral immune system theory and utilizing robust big data analytics, we examined associations between rising vaccination coverage and government policies, public mobility, and online information seeking regarding disease precautions. We tested whether cultural tightness-looseness moderates the relationship between mass immunization and disease prevention vigilance. Comprehensive time series analyses were conducted using American data (Study 1) and international data (Study 2), employing transfer function modeling, cross-correlation function analysis, and meta-regression analysis. Across both the US and global analyses, as vaccination rates rose over time, government COVID-19 restrictions significantly relaxed, community mobility increased, and online searches for prevention information declined. The relationship between higher vaccination rates and lower disease prevention vigilance was stronger in culturally looser contexts. Results provide initial evidence that mass immunization may be associated with attenuated sensitivity and enhanced flexibility of disease avoidance psychology and actions. However, cultural tightness-looseness significantly moderates this relationship, with tighter cultures displaying sustained vigilance amidst immunization upticks. These findings offer valuable perspectives to inform nuanced policymaking and public health strategies that balance prudent precautions against undue alarm when expanding vaccine coverage worldwide.

Forecasting global plastic production and microplastic emission using advanced optimised discrete grey model.

Plastic pollution has become a prominent and pressing environmental concern within the realm of pollution. In recent times, microplastics have entered our ecosystem, especially in freshwater. In the contemporary global landscape, there exists a mounting apprehension surrounding the manifold environmental and public health issues that have emerged as a result of the substantial accumulation of microplastics. The objective of the current study is to employ an enhanced grey prediction model in order to forecast global plastic production and microplastic emissions. This study compared the accuracy level of the four grey prediction models, namely, EGM (1,1, α, θ), DGM (1,1), EGM (1,1), and DGM (1,1, α) models, to evaluate the accuracy levels. As per the estimation of the study, DGM (1,1, α) was found to be more suitable with higher accuracy levels to predict microplastic emission. The EGM (1,1, α, θ) model has slightly better accuracy than the DGM (1,1, α) model in predicting global plastic production. Various accuracy measurement tools (MAPE and RMSE) were used to determine the model's efficiency. There has been a gradual growth in both plastic production and microplastic emission. The current study using the DGM (1,1, α) model predicted that microplastic emission would be 1,084,018 by 2030. The present study aims to provide valuable insights for policymakers in formulating effective strategies to address the complex issues arising from the release of microplastics into the environment and the continuous production of plastic materials.

The effects of COVID-19 event strength on job burnout among primary medical staff.

BACKGROUND: As a global pandemic, The Corona Virus Disease 2019 (COVID-19) has brought significant challenges to the primary health care (PHC) system. Health professionals are constantly affected by the pandemic's harmful impact on their mental health and are at significant risk of job burnout. Therefore, it is essential to gain a comprehensive understanding of how their burnout was affected. The study aimed to examine the relationship between COVID-19 event strength and job burnout among PHC providers and to explore the single mediating effect of job stress and work engagement and the chain mediating effect of these two variables on this relationship. METHODS: Multilevel stratified convenience sampling method was used to recruit 1148 primary medical staff from 48 PHC institutions in Jilin Province, China. All participants completed questionnaires regarding sociodemographic characteristics, COVID-19 event strength, job stress, work engagement, and job burnout. The chain mediation model was analyzed using SPSS PROCESS 3.5 Macro Model 6. RESULTS: COVID-19 event strength not only positively predicted job burnout, but also indirectly influenced job burnout through the mediation of job stress and work engagement, thereby influencing job burnout through the "job stress → work engagement" chain. CONCLUSIONS: This study extends the application of event systems theory and enriches the literature about how the COVID-19 pandemic impacted PHC medical staff job burnout. The findings derived from our study have critical implications for current and future emergency response and public policy in the long-term COVID-19 disease management period.

Investigating health and social outcomes of the Big Local community empowerment initiative in England: a mixed method evaluation.

Background: Most research on community empowerment provides evidence on engaging communities for health promotion purposes rather than attempts to create empowering conditions. This study addresses this gap. Intervention: Big Local started in 2010 with £271M from the National Lottery. Ending in 2026, it gives 150 relatively disadvantaged communities in England control over £1M to improve their neighbourhoods. Objective: To investigate health and social outcomes, at the population level and among engaged residents, of the community engagement approach adopted in a place-based empowerment initiative. Study design, data sources and outcome variables: This study reports on the third wave of a longitudinal mixed-methods evaluation. Work package 1 used a difference-in-differences design to investigate the impact of Big Local on population outcomes in all 150 Big Local areas compared to matched comparator areas using secondary data. The primary outcome was anxiety; secondary outcomes included a population mental health measure and crime in the neighbourhood. Work package 2 assessed active engagement in Big Local using cross-sectional data and nested cohort data from a biannual survey of Big Local partnership members. The primary outcome was mental well-being and the secondary outcome was self-rated health. Work package 3 conducted qualitative research in 14 Big Local neighbourhoods and nationally to understand pathways to impact. Work package 4 undertook a cost-benefit analysis using the life satisfaction approach to value the benefits of Big Local, which used the work package 1 estimate of Big Local impact on life satisfaction. Results: At a population level, the impacts on 'reporting high anxiety' (-0.8 percentage points, 95% confidence interval -2.4 to 0.7) and secondary outcomes were not statistically significant, except burglary (-0.054 change in z-score, 95% confidence interval -0.100 to -0.009). There was some effect on reduced anxiety after 2017. Areas progressing fastest had a statistically significant reduction in population mental health measure (-0.053 change in z-score, 95% confidence interval -0.103 to -0.002). Mixed results were found among engaged residents, including a significant increase in mental well-being in Big Local residents in the nested cohort in 2018, but not by 2020; this is likely to be COVID-19. More highly educated residents, and males, were more likely to report a significant improvement in mental well-being. Qualitative accounts of positive impacts on mental well-being are often related to improved social connectivity and physical/material environments. Qualitative data revealed increasing capabilities for residents' collective control. Some negative impacts were reported, with local factors sometimes undermining residents' ability to exercise collective control. Finally, on the most conservative estimate, the cost-benefit calculations generate a net benefit estimate of £64M. Main limitations: COVID-19 impacted fieldwork and interpretation of survey data. There was a short 4-year follow-up (2016/20), no comparators in work package 2 and a lack of power to look at variations across areas. Conclusions: Our findings suggest the need for investment to support community organisations to emerge from and work with communities. Residents should lead the prioritisation of issues and design of solutions but not necessarily lead action; rather, agencies should work as equal partners with communities to deliver change. Funding: This project was funded by the National Institute for Health and Care Research (NIHR) Public Health Research Programme (16/09/13) and will be published in full in Public Health Research; Vol. 11, No. 9. See the NIHR Journals Library website for further project information.

The Communities in Control study is looking at the health impacts of the Big Local community empowerment programme, funded by the National Lottery Community Fund and managed by Local Trust (a national charitable organisation). Residents of 150 English areas have at least £1M and other support to improve the neighbourhoods. There have been three phases of the research. This report shares findings from their third phase, which began in 2018. First, we used data from a national survey and data from national health and welfare services to compare changes in mental health between people living in Big Local areas and those in similar areas that did not have a Big Local partnership. Furthermore, we also used publicly available data on crime in the neighbourhoods. We found weak evidence that Big Local was linked with improved mental health and a reduction in burglaries. Second, we used data from a survey conducted by Local Trust to look at health and social impacts on the most active residents. We found an increase in mental well-being in 2018 but this was not maintained in 2020, probably due to the COVID-19 pandemic. Third, we did interviews and observations in 14 Big Local areas to understand what helps and what does not help residents to improve their neighbourhoods. We found that partnerships need to have legitimacy, the right balance of support, and learning opportunities. Residents suggested that creating social connections and welcoming social spaces, improving how people view the area and tackling poverty contributed to health improvements. Direct involvement in Big Local was both stressful and rewarding. Finally, we did a cost­benefit analysis by putting a monetary value on residents' increase in life satisfaction due to Big Local and comparing it with the costs of Big Local. We found that the benefits exceed the costs by at least £60M, suggesting that Big Local provides good value for money.

Analytic and heuristic process for prudent antimicrobial use in animals: What are triggers and how do they work?

The over and misuse of antimicrobials in animal agriculture causes a prevailing crisis for humans, animals, and the environment. From the One Health approach perspective, the formation process of adopting prudent antimicrobial use (AMU), once established, can be used to mitigate this crisis. The study aimed to determine the analytic-based and heuristic-based process that evoked prudent AMU among animal farmers by synthesis of stimulus-organism-response framework and dual-system theory and to explore gender differences on risk-benefit trade-offs. A structural equation model was employed to test the proposed hypotheses with field survey data from 1100 small-scale farmers. The results reveal that for the analytic-based process, social influence, antimicrobial-related threats, and self-efficacy are all salient stimuli having indirect effects on intention via the two organisms of perceived risks and perceived benefits. For heuristic-based process, farmers' altruistic value orientations are positively associated with intention. An interesting fact is that threat awareness has two opposite effects on intention, namely, the suppression effect and the enhancement effect. Moreover, the negative effect of perceived risks on intention is greater among female farmers, compared to male counterparts. These findings provide valuable insights for the forming of theory-based intervention strategies to perfect China's national action plan.

In Centralized Health Systems, Much Is Left Out When Analyses of Local HiAP Strategies Are Limited to Public Administration Comment on "A Realist Explanatory Case Study Investigating How Common Goals, Leadership, and Committed Staff Facilitate Health in All Policies Implementation in the Municipality of Kuopio, Finland".

We argue that the lessons drawn by Guglielmin and colleagues, from the Health in All Policies (HiAP) approach in the municipality of Kuopio, are of limited use to centralised health systems. There is a need for research more attuned to the circumstances of local governments that have little power over the provision of health programmes; yet can address a range of determinants of population health. In these cases, adopting a state-centric perspective may fail to capture the role of other actors such as non-governmental organizations (NGOs) and local branches of state agencies. Evidence from France shows that centralised health systems can foster HiAP locally through political commitment and dedicated coordination staff whose role is to mobilise and support NGOs, inhabitants, and other local branches of regional and central governments. We highlight, as three important challenges, the issue of legitimacy, funding and positioning of the HiAP instrument in the local government structure.

Beyond the surface: accounting for confounders in understanding the link between collectivism and COVID-19 pandemic in the United States.

According to the parasite-stress theory, collectivism serves as a trait of ingroup assortative sociality, providing defense against infectious diseases. This study investigated the association between cultural collectivism and COVID-19 severity at the state (Study 1: N = 51), county (Study 2: N = 3,133), and daily (Study 3: N = 52,806) levels from the beginning of 2020 to the end of 2022. State-level collectivism was assessed using two distinct measures: the U.S. collectivism index, focusing on social interconnectedness and interdependence, and the subjective-culture individualism-collectivism index (reversed), capturing attitudes and beliefs related to religion, abortion, and same-sex marriage. By employing random-intercept multilevel models, the results demonstrated significant and negative effects of state-level collectivism, as measured by the U.S collectivism index, on COVID-19 cases per million, COVID-19 deaths per million, and composite COVID-19 severity index, after controlling for confounding factors, such as socioeconomic development, ecological threats, disease protective behaviors, cultural norms, and political influences. A mini meta-analysis (Study 4: N = 9) confirmed the significance of these effects across studies. These findings supported the proactive role of collectivism in defending against the novel coronavirus in the United States, aligning with the parasite-stress theory of sociality. However, the subjective-culture individualism-collectivism index (reversed) did not exhibit a significant relationship with COVID-19 severity when confounding factors were considered. The high correlation between the subjective-culture individualism-collectivism index (reversed) and the controlled variables suggested shared variance that could diminish its impact on COVID-19 outcomes. Accordingly, the present findings underscore the significance of accounting for confounding factors when examining the association between collectivism and COVID-19 severity at population level. By considering relevant confounding factors, researchers could gain a comprehensive understanding of the complex interplay between cultural collectivism and its influence on COVID-19 severity. Overall, this research contributes to our understanding of how cultural collectivism shapes the COVID-19 pandemic in the United States, emphasizing the importance of adjusting for confounding effects in population level studies.

Telerehabilitation in the Finnish Outpatient Rehabilitation Setting from the Perspective of the Socio-Technical Systems Theory.

BACKGROUND: In the development of effective telerehabilitation (TR) interventions, understanding the various characteristics affecting its practice is essential. Remote connection creates a new technically shaped environment for therapy and, therefore, previous therapy methods do not work the same way as before. OBJECTIVE: The objective of this survey was to describe the practice of TR through the socio-technical theory approach. METHODS: The 629 respondents to the online questionnaire included music therapists, occupational therapists, speech and language therapists, physiotherapists, and neuropsychologists. The materials consisted of five open-ended questions. The analysis combined data-based and theory-based analysis. RESULTS: In the data-based content analysis, we identified three main categories and eight generic categories, whereas in the theory-based, we categorised the main results according to the Fit Between Individuals, Tasks, Technology, and Environment (FITTE) framework dimensions. TR is everyday-life based, it requires shared participation, and the approach has to include coaching and collaboration with the client and their close associates. The everyday-life environment is one of the main dimensions that affect all the other dimensions. CONCLUSIONS: TR can be seen as technology-mediated home-based rehabilitation, as it can integrate rehabilitation into the client's everyday life. In TR, therapy becomes multilateral and it creates a new kind of shared partnership into outpatient therapy.

Urban epidemic governance: An event system analysis of the outbreak and control of COVID-19 in Wuhan, China.

The outbreak of a virus such as COVID-19 is composed of a series of seemingly random incidents which are nevertheless interconnected. In a novel approach, this article adopts the event system theory (EST), established in organisational behaviour science, to investigate the mechanism of epidemic governance in Wuhan, the city which reported the first case of COVID-19 and thereafter successfully controlled the outbreak. The event system analysis divided Wuhan's response mechanism to COVID-19 into four dimensions: the graded response systems, the interactive relationship between multilevel entities of epidemic governance, the quarantine regulations and the governance of public sentiment. There are numerous lessons learned and effective measures developed from the 'Wuhan experience'. These lessons and measures can assist other cities around the world to cope with the current COVID-19 crisis and prepare their urban governance systems for similar infectious diseases in the future. We urgently advocate the addition of more scholarly discussion on urban epidemic governance by incorporating interdisciplinary approaches like EST in particular.

The need for ecological nested models as emerging theoretical frameworks in the investigation of affective variables in L2 education.

As an emotionally dynamic process, language learning is marked by fluctuations in students' affective constructs (e.g., enjoyment, playfulness, boredom). Thus, clues supporting an ecological perspective on behavioral trends and changes in language learners' emotional constructs driven by relational person and contextual components may be discovered. Therefore, an ecological approach enriched with the nested ecosystems model and complex dynamic system theory (CDST) can facilitate the investigation of dynamics of language students' affective constructs. These are first categorized and analyzed on the microsystem scale concerning students' motivation, beliefs, linguistic factors, cognitive factors, affective factors, and classroom context. Then, they are analyzed in 3 ecosystems including meso-, exo-, and macrosystems, each revealing an invaluable dimension of the reality of the emergent dynamicity of the variables. The present paper first draws attention to the dynamic nature of L2 learners' emotional factors and raises awareness of the ecological dynamic system theory. Then, it reviews the existing ecological studies of L2 affective variables and summarizes the findings. It ends with several conclusive remarks and suggestions for the future line of research.

Advice as a Form of Structural Coupling: Intersystem Organizations and Scientific Communication in the Japanese Response to COVID-19.

A critical issue in the study of scientific communication from a systems theoretical perspective is its role in multiple intersystem relationships. During COVID-19, politics has adopted scientific findings to inform political decisions. However, science has in response actively coordinated its operations for providing desired stimuli to politics. Luhmann identified advice as a form of structural coupling that links political and scientific systems. Advice is not a monolithic intervention by which one side acts on the other but is rather an interface that enables the two systems to relate through distancing. In this article, I empirically illustrate how the structural coupling of the political system and scientific system through advice manifests itself in an examination of the roles that various organizations (expert meeting and cluster task forces) have played in Japan's response to COVID-19. Through this analysis, I provide a theoretical insight regarding these organizations and a more detailed case analysis of the transformation of certain organizations to re-describe the system theoretical insights of advice in the form of scientific communication between politics and science.

A system theory based digital model for predicting the cumulative fluid balance course in intensive care patients.

Background: Surgical interventions can cause severe fluid imbalances in patients undergoing cardiac surgery, affecting length of hospital stay and survival. Therefore, appropriate management of daily fluid goals is a key element of postoperative intensive care in these patients. Because fluid balance is influenced by a complex interplay of patient-, surgery- and intensive care unit (ICU)-specific factors, fluid prediction is difficult and often inaccurate. Methods: A novel system theory based digital model for cumulative fluid balance (CFB) prediction is presented using recorded patient fluid data as the sole parameter source by applying the concept of a transfer function. Using a retrospective dataset of n = 618 cardiac intensive care patients, patient-individual models were created and evaluated. RMSE analyses and error calculations were performed for reasonable combinations of model estimation periods and clinically relevant prediction horizons for CFB. Results: Our models have shown that a clinically relevant time horizon for CFB prediction with the combination of 48 h estimation time and 8-16 h prediction time achieves high accuracy. With an 8-h prediction time, nearly 50% of CFB predictions are within ±0.5 L, and 77% are still within the clinically acceptable range of ±1.0 L. Conclusion: Our study has provided a promising proof of principle and may form the basis for further efforts in the development of computational models for fluid prediction that do not require large datasets for training and validation, as is the case with machine learning or AI-based models. The adaptive transfer function approach allows estimation of CFB course on a dynamically changing patient fluid balance system by simulating the response to the current fluid management regime, providing a useful digital tool for clinicians in daily intensive care.

A geometrical perspective on development.

Cell fate decisions emerge as a consequence of a complex set of gene regulatory networks. Models of these networks are known to have more parameters than data can determine. Recent work, inspired by Waddington's metaphor of a landscape, has instead tried to understand the geometry of gene regulatory networks. Here, we describe recent results on the appropriate mathematical framework for constructing these landscapes. This allows the construction of minimally parameterized models consistent with cell behavior. We review existing examples where geometrical models have been used to fit experimental data on cell fate and describe how spatial interactions between cells can be understood geometrically.

Coronavirus-Related Searches on the Internet Predict COVID-19 Vaccination Rates in the Real World: A Behavioral Immune System Perspective.

According to the smoke detector and functional flexibility principles of human behavioral immune system (BIS), the exposure to COVID-19 cues could motivate vaccine uptake. Using the tool of Google Trends, we tested that coronavirus-related searches-which assessed natural exposure to COVID-19 cues-would positively predict actual vaccination rates. As expected, coronavirus-related searches positively and significantly predicted vaccination rates in the United States (Study 1a) and across the globe (Study 2a) after accounting for a range of covariates. The stationary time series analyses with covariates and autocorrelation structure of the dependent variable confirmed that more coronavirus-related searches compared with last week indicated increases in vaccination rates compared with last week in the United States (Study 1b) and across the globe (Study 2b). With real-time web search data, psychological scientists could test their research questions in real-life settings and at a large scale to expand the ecological validity and generalizability of the findings.

Erratum: Beyond task-space exploration: On the role of variance for motor control and learning.

[This corrects the article DOI: 10.3389/fpsyg.2022.935273.].

COVID-19 and employee job performance trajectories: The moderating effect of different sources of status.

This study investigates the impact of the COVID-19 pandemic on employee job performance trajectories, and further examines the moderating effects of different sources of status. Drawing from event system theory (EST), we propose that employee job performance decreases upon COVID-19 onset, but gradually increases during the postonset period. Furthermore, we argue that status from society, occupation, and workplace functions to moderate such performance trajectories. We test our hypotheses with a unique dataset of 708 employees that combines survey responses and job performance archival data over 21 consecutive months (10,808 observations) spanning the preonset, onset, and postonset periods of the initial encounter with COVID-19 in China. Utilizing discontinuous growth modeling (DGM), our findings indicate that the onset of COVID-19 created an immediate decrease in job performance, but such decrease was weakened by higher occupation and/or workplace status. However, the postonset period resulted in a positive employee job performance trajectory, which was strengthened for employees with lower occupational status. These findings enrich our understanding of COVID-19's impact on employee job performance trajectories, highlight the role of status in moderating such changes over time, and also provide practical implications to understand employee performance when facing such a crisis.