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Purpose Teams across a wide range of contexts must look beyond task performance to consider the affective, cognitive and behavioral health of their members. Despite much interest in team health in practice, consideration of team health has remained scant from a research perspective. The purpose of this paper is to address these issues by advancing a definition and model of team health. Design/methodology/approach The authors review relevant literature on team stress, processes and emergent states to propose a definition and model of team health. Findings The authors advance a definition of team health, or the holistic, dynamic compilation of states that emerge and interact as a team resource to buffer stress. Further, the authors argue that team health improves outcomes at both the individual and team level by improving team members’ well-being and enhancing team effectiveness, respectively. In addition, the authors propose a framework integrating the job demands-resources model with the input-mediator-output-input model of teamwork to illustrate the behavioral drivers that promote team health, which buffers teams stress to maintain members’ well-being and team effectiveness. Originality/value This work answers calls from multidisciplinary industries for work that considers team health, providing implications for future research in this area.

(1) Background: Gender differences between men’s and women’s parenting roles are well-documented as the “second shift”. We examined the main effects and interaction of work distress and parenting distress with energy (i.e., vigor) in a sample of 310 dual-income, different-sex couples with kids married for approximately nine years. (2) Methods: We used actor–partner interdependence modeling (APIM) to examine how spouses’ distress was associated with their energy. (3) Results: For both wives and husbands, there were negative associations between the actor’s parenting distress and their energy level and between the actor’s work distress and their energy level. However, only wives experienced a significant interaction of work and parenting distress such that high levels of both forms of distress were associated with low levels of energy, indicating that only wives experience this form of work–family conflict. (4) Conclusions: When women experience more strain at home than men, they may need more time to recover from their work and family duties. If they cannot do so, they will have less energy to carry out their responsibilities and may be at a higher risk of future adverse health outcomes.

The social support paradox describes inconsistent findings on the role of social support for wellbeing, as some studies have found a negative correlation between social support and wellbeing, while others have found a positive correlation between social support and wellbeing. Thus far, some researchers have addressed this paradox by considering an individual’s relative desired support and perceived support, but often in only one domain (i.e. either focused on home or work). This study extends research by considering both the work and nonwork domains at the within-person level. Thus, complementary fit between perceived and desired support from both domains was hypothesized to predict mood and burnout such that when perceived support matches desired support, fit would be directly related to positive mood and indirectly related to negative mood and burnout. Similarly, there was a hypothesized partial mediation from support fit to burnout through mood. Testing these models did not result in strict congruence effects, although a dearth of perceived support (relative to desired support) predicted higher burnout at the within- and between-person levels. Unexpectedly, the results also imply that some cases of excess perceived support (relative to desired support) predict lower burnout at the between-person level. Results demonstrate the value of examining social support and burnout at the within-person level, as the study indicates that social support may be a response to acute burnout such that it stops feedback loops leading to chronic burnout.

Abstract Trait self-control (TSC) is a well-known predictor of well-being. TSC may reduce distraction from hedonistic pursuits and enable more effective goal-directed behavior. Attachment anxiety (AA) is a trait that predicts lower relationship quality and lower well-being; people high on AA are characterized by hyper-sensitivity, proximity-seeking and excessive rumination. In retirement, these traits may interact to predict wellbeing. Methods: 120 retired participants took part in data collection (M = 62.37 years old; SD = 10.07 years; 68% women, 70% white). Data collection included self-reported AA (Experience in Close Relationships), TSC (Brief Self-Control Scale), depressive symptoms (Center for Epidemiological Studies Depression Scale) and emotional well-being (RAND 36-Item Health Survey). We conducted hierarchical linear regressions and accounted for demographic and health-related covariates. Results: TSC was negatively related to depressive symptoms and positively related to emotional well-being. AA was positively related to depressive symptoms and negatively related to emotional well-being. We found an interaction predicting depressive symptoms such that participants with low TSC and high AA had the highest depressive symptoms (p = .036). This interaction was not significant for emotional well-being. Discussion: After retiring, maintaining a healthy social life may be more effortful, as there are fewer 'built-in' social interactions (i.e., with coworkers). Retirees with higher TSC may be able to maintain their social life more effectively than those with lower TSC. Similarly, people with lower AA may be able to obtain more enjoyment from their social lives. Together, lower AA and higher TSC may be protective mechanisms for depressive symptoms.

[...]nearly every industry has witnessed layoffs, furloughs, and other unfortunate personnel decisions as a result of the economic fallout of the pandemic (Voytko, 2020). [...]in addition to the challenges that virtual teams often face in general, it is also important to take into consideration the unique challenges that the COVID-19 pandemic presents. [...]it may be more difficult to discern whether messages are received and understood, and team communication processes may be impaired (Cramton, 2001; Gibson & Cohen, 2003; Hertel etal., 2005). [...]it is clear that the shift to remote work can pose multiple challenges to new virtual teams; however, there are multiple strategies that team members and managers can use to improve their virtual team experiences.

Understanding why certain individuals work well (or poorly) together as a team is a key research focus in the psychological and behavioral sciences and a fundamental problem for team-based organizations. Nevertheless, we have a limited ability to predict the social and work-related dynamics that will emerge from a given combination of team members. In this work, we model vocal turn-taking behavior within conversations as a parametric stochastic process on a network composed of the team members. More precisely, we model the dynamic of exchanging the `speaker token' among team members as a random walk in a graph that is driven by both individual level features and the conversation history. We fit our model to conversational turn-taking data extracted from audio recordings of multinational student teams during undergraduate engineering design internships. Through this real-world data we validate the explanatory power of our model and we unveil statistically significant differences in speaking behaviors between team members of different nationalities.