Shared Mental Task Models in Elite Ice Hockey and Handball Teams: Does It Exist and How Does the Coach Intervene to Make an Impact?

Analyzing shared and team mental models

<p>Background: The quality of team-based care impacts patient post-hospitalization outcomes, yet there is a gap in our understanding of how specific team processes impact patient post-hospitalization outcomes. Shared Mental Models (SMMs) is a team process from organizational psychology; it provides an understanding of how providers coordinate complex tasks as a team. SMMs are the team members’ organized knowledge needed for effective team performance. Military research shows that teams with more convergent SMMs have higher performance and better outcomes. In healthcare, patient discharge exemplifies an activity that requires a high level of coordination among interprofessional team members. Two relevant domains of SMMs are Taskwork SMM (team assessment of patient’s readiness for hospital discharge) and Teamwork SMM (quality of day of discharge teamwork). Because of the newness of SMM to healthcare, we lack measures to understand SMMs among interprofessional discharge teams.</p><p>Study Purpose & Aims: The purpose was to pilot a novel measurement approach assessing SMMs of discharge teams, and explore their relationships to patient 30-day post-hospitalization outcomes (quality of care transition and utilization of unplanned medical services). Aim 1 determined the content and degree of convergence of discharge teams’ SMMs (taskwork and teamwork). Aim 2 examined the relationship between discharge team SMMs and patient post-hospitalization outcomes.</p><p>Methods: A prospective longitudinal pilot study was used to examine the SMMs of 64 unique discharge events in three inpatient units at a single hospital. Discharge team members independently completed a questionnaire measuring the Teamwork SMM (using the Shared Mental Model Scale) and the Taskwork SMM (using the Discharge Provider-Readiness for Hospital Discharge Scale). Data were collected from the patient 30 days post-discharge to determine the quality of transition (using the Care Transition Measure or CTM-15) and use of unplanned utilization of medical services (unplanned readmission or ED visit). Interrater Agreement (r*wg(j)) was used to determine the SMM convergence (or level of agreement) among the discharge team. The relationship between SMMs and the quality of transition outcome (n = 42) was determined using standard regression analysis. Logistic regression was used determine the relationship of SMMs with utilization of unplanned medical services (n = 56).</p><p>Results: Overall, discharge teams reported high levels of Taskwork SMMs (M = 8.46, SD =.91) and Taskwork SMM Convergence (M = .90, SD =.10), indicating that the discharge team perceived and agreed that patients had high levels of readiness for hospital discharge. Discharge teams also reported having high-quality Teamwork SMMs (M = 6.11, SD = 0.39) and Teamwork SMM Convergence (M = .85, SD = .10), suggesting that most discharge teams perceived and agreed that high quality teamwork was provided during the discharge process. Discharge events from the three inpatient units significantly differed in their Teamwork and Teamwork SMM content and convergence scores. Discharge teams’ Teamwork SMMs and Taskwork SMMs were positively associated with the CTM-15 score, while controlling for key contextual factors (t = 3.94, p = .001; t = 3.94, p = .001, respectively).</p><p>Conclusion : Discharge teams’ Taskwork SMM and Teamwork SMM was positively associated with patient-reported quality of transition from the hospital. There was insufficient evidence to support that utilization of unplanned medical services is related to discharge teams’ SMMs. Measuring the SMMs of the discharge team provides a method for assessing a team process critical to safe patient discharges.</p>

The aim of this study was to test a multiple mediation model linking athletes’ shared mental models (SMMs) to social loafing through role clarity and team identity. The following hypothesis was tested: An SMM is directly and negatively associated with social loafing; athletes’ perceived SMMs are positively related to role clarity and team identification, which in turn is negatively related to social loafing. In total, 152 male professional senior players from all 10 teams in an elite ice hockey league participated. Data were analysed using a linear regression procedure and bias-corrected bootstrapping technique to measure indirect effects. The results confirm the hypothesis and demonstrate that SMMs have an indirect effect through the mediators. Coaches and sport psychologists should be aware of the significance of SMMs in their work to enhance team performance. Facilitating SMMs may reduce social loafing through role clarity and team identification.

In this article, we analyze how shared team and task mental models, developed prior to an acquisition, affect exploration and exploitation activities in the postacquisition phase, and how these effects are dependent on relative size. With a sample of 101 transactions of acquirers from the German-speaking part of Europe, we provide empirical evidence that both shared team and task mental models positively influence exploitation activities following an acquisition, whereby only shared team mental models (TMMs) are beneficial for exploration. We provide empirical evidence that shared mental models in terms of task and team are an important informal source for enhancing exploration and exploitation innovation activities. However, this source of informal coordination is contextual. Although the relationships on exploitation are stable, the beneficial effect of TMMs on exploration is sensitive and devitalized by an increasing relative size. Implications for further research and management practice are given.

Mental models are knowledge structures employed by humans to describe, explain, and predict the world around them. Shared Mental Models (SMMs) occur in teams whose members have similar mental models of their task and of the team itself. Research on human teaming has linked SMM quality to improved team performance. Applied understanding of SMMs should lead to improvements in human-AI teaming. Yet, it remains unclear how the SMM construct may differ in teams of human and AI agents, how and under what conditions such SMMs form, and how they should be quantified. This paper presents a review of SMMs and the associated literature, including their definition, measurement, and relation to other concepts. A synthesized conceptual model is proposed for the application of SMM literature to the human-AI setting. Several areas of AI research are identified and reviewed that are highly relevant to SMMs in human-AI teaming but which have not been discussed via a common vernacular. A summary of design considerations to support future experiments regarding Human-AI SMMs is presented. We find that while current research has made significant progress, a lack of consistency in terms and of effective means for measuring Human-AI SMMs currently impedes realization of the concept.

Important non-technical skills enable operating teams to establish shared mental models (SMMs). The importance of SMMs in regards to surgical performance and peri-operative outcomes remains to be investigated. The aim of this study was to explore whether shared mental models (SMMs) of team resources and the current situation, respectively, were predictive of technical skills, duration of surgery, and amount of intra-operative bleeding in video-assisted thoracoscopic surgery (VATS). A prospective multi-center observational study was conducted at four tertiary academic hospitals during VATS lobectomy procedures. Data included pre-operative and post-operative questionnaires answered by each of the six team members to measure the SMMs; thoracoscopic video recordings assessed using the previously validated VATS lobectomy Assessment Tool (VATSAT); surgery-related time stamps; and amount (volume) of intra-operative bleeding. Linear regression analyses were conducted to adjust for confounders. Fifty-eight lobectomy procedures were included. Median (interquartile range) VATSAT score was 33.3 (scale 8-40) duration of surgery 101min (88-123), and amount of intra-operative bleeding 100ml (20-150). The mean (± SD) of teams' SMMs of the current situation was 20 (± 5). They were not predictive of the surgeons' technical skills, but every one point increase in SMM score significantly predicted a 1min 52s decrease in duration of surgery and an 11% decrease in amount of bleeding. The SMMs of team resources were not predictive of any outcomes. VATS teams' superior SMMs of the current situation related to significantly shorter duration of surgery and decreased intra-operative bleeding, indicating an effect on team performance and patient care. NCT02999113 at http://www. gov .

Crew Resource Management (CRM) training focuses on situation awareness, communication skills, teamwork, task allocation, and decision making. More recently, an interest in cognitive skill is beginning to appear in relation to CRM. One aspect of cognitive skill that has been examined in a variety of team domains is the notion of overlapping or mental models among teammates. While a growing amount of evidence on the relationship between shared mental models and team performance exists, only limited research has focused on the role that shared mental models have-in crew resource management. The purpose of this paper is to provide researchers and practitioners an understanding of the shared mental model construct and the role of shared mental models in team performance, as well as to encourage additional research on this topic within the aviation domain. Crew Resource Management and Shared Mental Models Human error is a major factor in aviation accidents. As a result, pilot training has shifted fiom an emphasis on purely technical skills, to a combination of both technical and teamwork skills (Reynolds & Rhoades, 2004). These training programs have a variety of names, but the most common is Crew Resource Management (CRM). is currently required by all 185 International Civil Aviation Orgauization members, is incorporated into each of the US military branches, and is gaining steady support outside aviation in industries as diverse as nuclear power producers and medical practitioners (American Psychological Association, 2005; Flin, Meams, & O ' C o ~ o r , 2002). Typically, three main skill clusters are targeted: communication, team building and workload management. Within these broad categories, however, content may vary to include: adaptability, assertiveness, communication, leadership, mission analysis, situational awareness, forward planning, risk assessment, group dynamics, stress and coping techniques, and how to monitor automated equipment (Naval Education and Training Command, 2003). The Federal Aviation Administration (FAA) (2004) suggests that CRM training focuses on situation awareness, communication skills, teamwork, task allocation, and decision making within a comprehensive m e w o r k of standard operating procedures (SOP) @. l). Under the topic of team building, the FAA notes that 'This topic includes interpersonal relationships and practices. Effective leadership/followership and interpersonal relationships are key concepts to be stressed. Cunicula can also include recognizing and dealing with diverse personalities and operating styles (p. l2). One area not emphasized is team cognition. The goal of this paper is to foster an understanding of the impact of team cognition in promoting effective team work, and to suggest the addition of team cognition, particularly shared mental models, as a focus of CRM. To accomplish this, we begin by discussing the evolution of CRM. Next, we discuss one aspect of team cognition, shared mental models, and how both implicit communication and team performance can be linked to shared mental models. This discussion includes a review of current research on shared mental models, as well as methods of measuring and training such models. We conclude by suggesting that future research and training incorporate shared mental models. Evolution of Kern (200 1) suggested that the roots of can be found in a 1951 U.S. Air Force Inspector General's report which analyzed data fiom 7518 major accidents between 1948 and 195 1, and found that poor teamwork and

To conduct a scoping review to explore the construct of shared mental models (SMMs) in the context of clinical teamwork among health professions learners. The authors searched the PubMed, ERIC, CINAHL, Scopus, Web of Science, PsychINFO, and EMBASE databases for English-language articles published between 2000 and 2016. Eligible articles mentioned SMMs in relation to clinical teamwork and included health professions learners. Two reviewers screened studies for eligibility and extracted data to determine the depth and breadth of the literature on SMMs. The authors examined definitions of the SMM construct in the context of clinical teams, educational interventions using SMMs, and the measurement of SMMs. Of the 1,273 articles retrieved, 23 met the inclusion criteria. SMMs were defined in less than two-fifths of the articles (9/23). All articles applied the construct to improvements in hospital-based patient safety, often in high-intensity settings (14/23). Most articles included graduate-level physicians (21/23) within clinical teams (18/23). Interventions designed to foster SMMs (6/23) included teamwork curricula/training and teamwork supportive tools. Measurements of SMMs (7/23) included a qualitative task analysis, quantitative analyses of speech, a concept mapping, and Likert-type surveys. In health professions education, the SMM construct lacks clear definition. Few studies described educational interventions aimed at SMM development, and few attempted to measure the construct. The authors propose an operational definition of SMMs in health care and illustrate how interventions intended to foster SMMs, such as team trainings or planning exercises and communication tools, could be developed, implemented, and assessed.

Converging evidence from psychology, human factors, management and organizational science, and other related fields suggests that humans working in teams employ shared mental models to represent and use pertinent information about the task, the equipment, the team members, and their roles. In particular, shared mental models are used to interact efficiently with other team members and to track progress in terms of goals, subgoals, achieved and planned states, as well as other team-related factors. Although much of the literature on shared mental models has focused on quantifying the success of teams that can use them effectively, there is little work on the types of data structures and processes that operate on them, which are required to operationalize shared mental models. This paper proposes the first comprehensive formal and computational framework based on results from human teams that can be used to implement shared mental models for artificial virtual and robotic agents. The formal portion of the framework specifies the necessary data structures and representations, whereas the computational framework specifies the necessary computational processes and their interactions to build, update, and maintain shared mental models.

Think like a team: Shared mental models predict creativity and problem-solving in space analogs

Shared Mental Models, with respect to the cognitive architecture of teams, are believed to be important for team functioning and performance. One influencing factor for building and optimizing shared mental models in teams is knowledge-sharing behavior, which is assumed to be affected by individual factors. These factors include attitude, subjective norms, self-efficacy and intention. Additionally, there are five organizational factors: social ties, organizational communication, team communication, perceived appraisal and organizational support. One hundred and twenty-three shop floor workers took part in our study to investigate the importance of individual and organizational factors for knowledge-sharing behavior and its impact on shared mental models. The results indicate that taken together, the assumed predictors, especially subjective norms, organizational communication and social ties, explained 31% of the variance in knowledge-sharing behavior. In turn, knowledge-sharing behavior had a significant impact on all four types of shared mental models. We discuss the implications of our findings in terms of supporting interventions in organizations and of further shared mental model research in production settings.

Large corporations increasingly use multinational teams to integrate their global operations. To perform this complex task efficiently, team members need to develop shared mental models (SMMs), i.e. an organized understanding of the knowledge base they are sharing. In multinational teams, the heterogeneity of team members makes SMM formation especially challenging. While previous research has investigated the influence of different diversity factors on SMMs, the impact of language differences has surprisingly been neglected so far. To address this important gap we investigate how different elements of the language barrier impede the formation of different types of SMMs. Based on 84 semi-structured interviews with team leaders, members and senior managers of 15 multinational teams in three German automotive corporations we develop a model showing how pragmatic and paraverbal barriers between team members obstruct SMMs about roles, responsibilities and interaction patterns and how shortcomings in lexical, syntactical and phonetic proficiency impede SMMs about team members' preferences, strengths, weaknesses as well as values and attitudes. These findings integrate linguistic and psychological theories with management studies and complement our understanding of the antecedents of SMMs in multinational teams. This is of crucial importance since SMMs have been established as important prerequisites for team performance.

It is desirable to integrate knowledge of team members toward performance. However, a smart team does not always perform as expected, especially when the team members differ in their knowledge backgrounds. Previous literature has indicated that team members must develop a shared mental model (SMM) such that their actions are effectively coordinated and innovations are induced. Scholars noted that SMMs did not become more similar as predicted in work teams with complex task however. This inconsistency has yet been resolved. This study conducted a case study to explore how multiple SMMs were developed in a heterogeneous work team in the process of achieving a complex goal. The results of this study showed that SMMs are grown as a hierarchical structure. In such a structure, superordinate SMMs work as a more robust frame in which subordinate SMMs are developed. Based on such a robust frame, subordinate SMMs are more locally developed and thus enhance team efficiency. Superordinate SMMs are revisited when the team appeals for innovations.

Objective To review common qualitative and quantitative methods of measuring shared mental models appropriate for use in the healthcare setting. Background Shared mental models are the overlap of individuals’ set of knowledge and/or assumptions that act as the basis for understanding and decision making between individuals. Within healthcare, shared mental models facilitate effective teamwork and theorized to influence clinical decision making and performance. With the current rapid growth and expansion of healthcare teams, it is critical that we understand and correctly use shared mental model measurement methods assess optimal team performance. Unfortunately, agreement on the proper measurement of shared mental models within healthcare remains diffuse. Method This paper presents methods appropriate to measure shared mental models within healthcare. Results Multiple shared mental model measurement methods are discussed with regard to their utility within this setting, ease of use, and difficulties in deploying within the healthcare operational environment. For rigorous analysis of shared mental models, it is recommended that a combination of qualitative and quantitative analyses be employed. Conclusion There are multitude of shared mental model measurement methods that can be used in the healthcare domain; although there is no perfect solution for every situation. Researchers can utilize this article to determine the best approach for their needs.

This paper presents a review of fundamental concepts behind the shared mental model and its processes. Shared mental model has two properties which are similarity and accuracy where both of these properties have different emphasis. Types of shared mental model refers to four (4) different ways on what type of cognitive process is being shared in team, which includes task-specific knowledge, task-related knowledge, knowledge of teammates and attitude or beliefs. These four (4) types of shared mental model are grouped into two (2) major content domains, i.e. task-work and team-work. It further describe the aspects of shared mental model on how cognitive process is being shared, includes shared vs. overlapping, similar vs. identical, compatible vs. complimentary and distributed. Shared mental model has to be evaluated using three (3) aspects of characteristics in order to show its operationalization: elicitation method, structure representation, and representation of emergence. A specific evaluation technique called cognitive task analysis that focuses on the analysis of difficulties in cognitive structures is introduced in evaluating shared mental model. This paper also discusses Collaborative Visualisation as technological approach in shared mental model, which includes the benefit of user participation in the aspects of joining or leaving, floor control, privacy and global view. Specific areas on big data, visual analytics, multimedia interface, mobility, disability, awareness and learning analytics that can benefit from the shared mental model approach is discussed.