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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.

The authors review relevant literature on team stress, processes and emergent states to propose a definition and model of team health.

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.

This work answers calls from multidisciplinary industries for work that considers team health, providing implications for future research in this area.

The reliance on teams in today’s work environment underscores the importance of understanding how teams function. To better understand teams, one must be able to measure team dynamics or interaction. The purpose of this chapter is to outline an unobtrusive approach to measuring team dynamics from verbal communications.

The basic premise of this approach is that the words we use provide insight into how we feel and think at any given time. The methodology described in this chapter employs a lexical analytic approach to examining team dynamics. To best accomplish this, we first identify the principal features or dimensions of teamwork and then we propose lexical measures that may map to these processes.

This approach can be employed to track team functioning over time “at a distance” without interrupting task performance.

This chapter describes an approach to measuring relevant teamwork dimensions through verbal content. This approach has the potential to give us direct, unobtrusive insight into the emotional and cognitive states of teams. It is original in its examination of how team dynamics can be indexed in speech.

Teams do not operate in a vacuum, but in specific real-world contexts. For many teams, this context includes high-demand, high-stress conditions which can negatively impact team functioning. In this chapter, we discuss how stress may impact team cohesion and examine stress mitigation strategies to overcome these effects.

A key challenge for cost-effective Intelligent Tutoring Systems (ITSs) is the ability to create generalizable domain, learner, and pedagogical models so they can be re-used many times over. Investment in this technology will be needed to succeed in developing ITSs for team training. The purpose of this chapter is to propose an instructional framework for guiding team ITS researchers in their development of these models for reuse. We establish a foundation for the framework with three propositions. First, we propose that understanding how teams develop is needed to establish a science-based foundation for modeling. Toward this end, we conduct a detailed exploration of the Kozlowski, Watola, Jensen, Kim, and Botero (2009) theory of team development and leadership, and describe a use case example to demonstrate how team training was developed for a specific stage in their model. Next, we propose that understanding measures of learning and performance will inform learner modeling requirements for each stage of team development. We describe measures developed for the use case and how they were used to understand teamwork skill development. We then discuss effective team training strategies and explain how they were implemented in the use case to understand their implications for pedagogical modeling. From this exploration, we describe a generic instructional framework recommending effective training strategies for each stage of team development. To inform the development of reusable models, we recommend selecting different team task domains and varying team size to begin researching commonalities and differences in the instructional framework.

Adaptive capacity has commonly been defined as the “general ability of institutions, systems, and individuals to adjust to potential damage, to take advantage of opportunities, or to cope with the consequences” (http://www.greenfacts.org). Adaptive capacity is herein described as the ability to facilitate the process of adaptive team performance and the resulting outcome of team adaptation (see Stagl, Burke, Salas, & Pierce, this volume). More specifically, although often spoken of with regard to environmental and global changes, it is spoken of here with regard to the ability of individuals (and correspondingly teams) to recognize and understand contextual changes, dynamically revise and implement plans accordingly, and learn from each implementation so as to be better prepared in the future.

As operational environments become increasingly fluid, organizations are turning to teams as a proven performance arrangement to structure complex work. Teams are ubiquitous in modern organizations because they can be used to create synergies, streamline workflow, deliver innovative services, satisfy incumbent needs, maximize the benefits of technology connecting distributed employees, and seize market opportunities in a global village. Teams are also increasingly used because coordinating the “…activities of individuals in large organizations is like building a sand castle using single grains of sand” (West, Borrill, & Unsworth, 1998, p. 6).

My warm thanks to Dean James Hunt, Provost, and Professor Jacqueline Muir-Broaddus, Chair of the Psychology Department, for making a home at Southwestern University, Georgetown, Texas, for cultural ergonomics and the International Center of Cultural Ergonomics, and for facilitating preparation of this book. Southwestern students Kendra Francisco, Staci Benson, and Ellen Gass contributed helpful assistance. At Elsevier, Fiona Barron, Publishing Editor, has been extraordinarily helpful, and the consideration and support there from Becky Lewsey and Deborah Raven have been particularly noteworthy. Dr. Pierre Falzon, Conservatoire des Arts et Metiers in Paris, made possible the acquisition of documents written by Professor Alain Wisner, who died recently. Computer advice and assistance provided by Richard H. Troxell have been invaluable. Communication and interchange of documents and information with Dr. Eduardo Salas at the University of Central Florida were facilitated by Marcella Maresco and Diana Furman.

Across many high-stakes contexts, teams influence their members’ physical and psychological Well-Being. For example, teams can provide social support and backup behaviors to reduce demands on team members. On the contrary, teams engaged in conflict or other deleterious processes can serve as a source of stress for their members. Despite these potential impacts, existing research primarily focuses on the impact of teamwork on team-level, rather than individual-level outcomes. This chapter argues that teams play an important role in members’ Well-Being, synthesizing existing research on the topic and focusing on synthesizing research that suggests teams play an important and overlooked role in members’ Well-Being, and providing recommendations for future research in this domain.

Distributed performance arrangements are increasingly used by organizations to structure dyadic and team interactions. Unfortunately, distributed teams are no panacea. This chapter reviews some of the advantages and disadvantages associated with the geographical and temporal distribution of team members. An extended discussion of the implications of distributed team performance for individual, team, and organizational decision making is provided, with particular attention paid to selected cultural factors. Best practices and key points are advanced for those stakeholders charged with offsetting the performance decrements in decision making that can result from distribution and culture.

Although the practice of multiteam systems (MTSs) has been around for decades, the science of these systems has only just begun. Within the past decade and a half, although much remains to be investigated, substantial progress has been made in breaking the surface of this research. The current volume provides a review of MTS case studies and the current chapter provides a synopsis of this research. The goal of this chapter is to identify how MTSs are operating under real-world conditions in order to bridge MTS science and practice.

In this chapter, the authors provide a case analysis of the presented MTSs in the current volume in order to identify issues innate to MTSs. An approach based on the SWOT analysis technique was utilized to identify strengths, weaknesses, threats, and opportunities of the identified MTSs. In addition, six lessons learned were extracted from a content analysis of the successes and failures of these MTSs.

Although MTSs may be unique to the environment in which they operate, there are several features which seem to be inherent to all. Strengths include possessing the ability to manage complex tasks and unexpected events, being flexible in nature, and integrating communication across levels. In opposition, weaknesses include the use of nontraditional communication patterns, challenges stemming from unit diversity and resources, and the lack of common training. Lessons learned from identified MTSs include (1) utilize effective communication; (2) establish shared mental models; (3) identify roles and responsibilities; (4) convey accountability and ownership; (5) consider the ramp-up period; and (6) train individuals in an MTS at multiple levels. Opportunities and threats to MTSs are also discussed in this chapter.

This chapter offers several contributions to the state of the field in regard to MTSs. The current chapter provides a detailed content analysis of several real-world MTSs. Characteristics inherent to MTSs are identified and discussed, and lessons learned are extracted. Traditionally, science and practice has focused on the presentation of lab-based MTSs; the current volume breaks new ground by identifying how MTSs operate “in the wild.” This chapter provides a summation of this volume and offers lessons learned for MTS researchers and those working within MTSs.