James M. Oglesby

The Anatomy of Health Care Team Training and the State of Practice: A Critical Review

Purpose As the U.S. health care system enters a new era, the importance of team-based care approaches grows. How is the health care community ensuring that providers and administrators are equipped with the knowledge, skills, and attitudes (KSAs) foundational for effective teamwork? Are these KSAs transferring into daily practice? This review summarizes the present state of practice for health care team training described in published literature. Drawing from empirical investigations of training effectiveness, the authors explore training design, implementation, and evaluation to provide insight into the shape, structure, and anatomy of team training in health care. Method A 2009 literature search yielded 40 peer-reviewed articles detailing health care team training evaluations. Guided by 11 focal questions, two trained raters extracted details regarding training design, implementation, evaluation metrics, and outcomes. Results Findings indicate that team training is being implemented across a wide spectrum of providers and is primarily targeting communication, situational awareness, leadership, and role clarity. Relatively few details indicate how training needs were established. Most studies collected data immediately posttraining; however, less than 30% collected data six months or more posttraining. Content analyses highlight the need for enhanced detail in published training evaluation reports. Conclusions In many respects, health care team training implementation and evaluation align with best practices suggested from the science of training, adult learning, and human performance; however, opportunities for improvement exist. The authors suggest several mechanisms for furthering the health care team training evidence base to enhance patient safety and work environment quality for clinicians.

A Framework to Guide the Assessment of Human–Machine Systems:

Objective: We have developed a framework for guiding measurement in human–machine systems. Background: The assessment of safety and performance in human–machine systems often relies on direct measurement, such as tracking reaction time and accidents. However, safety and performance emerge from the combination of several variables. The assessment of precursors to safety and performance are thus an important part of predicting and improving outcomes in human–machine systems. Method: As part of an in-depth literature analysis involving peer-reviewed, empirical articles, we located and classified variables important to human–machine systems, giving a snapshot of the state of science on human–machine system safety and performance. Using this information, we created a framework of safety and performance in human–machine systems. Results: This framework details several inputs and processes that collectively influence safety and performance. Inputs are divided according to human, machine, and environmental inputs. Processes are divided into attitudes, behaviors, and cognitive variables. Each class of inputs influences the processes and, subsequently, outcomes that emerge in human–machine systems. Conclusion: This framework offers a useful starting point for understanding the current state of the science and measuring many of the complex variables relating to safety and performance in human-machine systems. Application: This framework can be applied to the design, development, and implementation of automated machines in spaceflight, military, and health care settings. We present a hypothetical example in our write-up of how it can be used to aid in project success.

The Issue of Monotony and Low Workload in Spaceflight: Considerations for the Mission to Mars:

The future mission to Mars will present a number of challenges regarding habitability and performance for spaceflight crewmembers. One aspect that needs to be considered is the potential impact of extended periods of low workload relating to monotony and boredom. The following provides an overview of the challenges associated with long duration spaceflight, and specifies the characteristics of interplanetary exploration. Focus is put on these challenges in space and provides possible approaches in mitigating the potential consequences regarding low workload in the high-risk environment. Discussion points are provided regarding possible applications for implementation in future interplanetary expeditions.

Space Flight Task Contexts for Long Distance and Duration Exploration Missions: Application to Measurement of Human Automation Interaction

An effort is currently underway to determine methods for measuring safety and performance of human- automation systems to improve their functioning for future long duration space flights. However, an important step in system evaluation is understanding the contexts in which they operate. The identification of contexts will help in targeting what variables may be related to the overall system’s effectiveness. A review of NASA documents and literature has resulted in the identification of four categories of task contexts that are believed to be important for future Long Distance and Duration Exploration Missions (LDDEM) to Mars and beyond. These four categories include (1) spacecraft navigation, (2) robotic/habitat operations, (3) systems monitoring, and (4) mission planning and scheduling. Within each of these four task categories there exist varying task demands and environmental conditions that impact the user’s interaction with the automation and, subsequently, the types of measurement that are appropriate for analyzing performance and safety within the human-automation system.

Cognition and Physiological Response Towards a Model of Validated Physiological Measurement

Complex tasks in large and error-prone environments require unobtrusive, unbiased and real-time measurement of cognitive variables to promote safety and to achieve optimal performance. Despite the prevalence of physiological measurement of cognitive constructs and cognitive performance, such as workload, little has been done to justify the inference of cognitive states from physiological measures. We develop a framework based on the extant literature to provide the groundwork for further validation of physiological measurement. Specifically, we leverage theoretically-grounded conditions of measurement to aid in investigating the logical sampling and construct validity for use of such metrics. Further meta-analytic investigation is warranted to validate the model and justify use of physiological measures.

Synthetic task environments for improving performance at work: Principles and the road ahead

Forward Eduardo Salas 1. Introduction Part 1: Statistical Analysis 2. Catastrophe Theory and Its Applications in Organizational Psychology Stephen J. Guastello 3. Longitudinal Growth Modeling Robert E. Ployhart and Youngsang Kim 4. Harnessing the Power of Social Network Analysis to Explain Organizational Phenomena Yuval Kalish 5. Latent Class Procedures: Recent Development and Applications Mo Wang and Le Zhou 6. Spurious Relationships in Growth Curve Modeling: The Effects of Stochastic Trends on Regression-based Models Michael Braun, Goran Kuljanin and Richard P. DeShon 7. Practical Applications of Data Mining for Organizational Research Jeffrey M. Stanton Part 2: Research Design and Measurement 8.Use of Conditional Reasoning to Measure the Power Motive Lawrence R. James, James M. LeBreton, Terence R. Mitchell, Daniel R. Smith, Justin A. DeSimone, Robert Cookson, and HyeJoo Lee 9. Qualitative Research Methods for Industrial and Organizational Psychology Robert P. Gephart, Jr. 10. Experience Sampling Methodology NikolaosDimotakis, Remus Ilies, and Timothy A. Judge 11. Synthetic Task Environments for Understanding Human Performance Eduardo Salas, Aaron S. Dietz, Mary Jane Sierra, & Kimberly Smith-Jentsch 12. Petri Nets: Modeling the Complexity of Modern Jobs Michael D. Coovert 13. A Brief Primer on Neuroimaging Methods Cory Adis and James C. Thompson 14. Knowledge and Skill Measurement: Insights from Outside of I/O Psychology Nikki Dudley-Meislahn, E. Daly Vaughn, Eric J. Sydell, &Marisa A. Seeds

Assessing Human-Automation System Safety, Efficiency, and Performance Developing a Metrics Framework

Automation is an important and widely utilized component in work environments across many domains; it is useful for completing tasks too dangerous or cumbersome for personnel to complete by themselves. Despite its benefits, potential issues can occur that may impact safety and efficiency in the overall human-automation system. To realize the benefits of automation, designers must be able to measure and assess the levels of safety and efficiency. This paper will discuss a theoretical framework to guide the development and selection of metrics for assessing human-automation interaction.

The application of waste management systems for long duration spaceflight.

In the future planned interplanetary expedition mission to Mars, spaceflight crewmembers will be exposed to an environment that is completely unique from anything they are accustomed to on Earth. Due to the characteristics of these missions, a challenge will be to design an environment that allows crewmembers to easily work and live in for extended durations. One of the challenges associated with these future missions is supplying the crew with essential resources for survivability such as food and water. In this case, the waste management system can play a role in a closed-loop life support system, as provisions sent with the crew will be severely limited with no opportunity for resupply. The following looks at the rationale of designing a system for collecting, storing, and recycling human bodily waste that (1) is considered user-friendly by crewmembers in regard to habitability in spaceflight, and (2) provides applications for a self sustaining closed-loop life support system that will aid the crew during the mission. Future design processes should consider adhering to these guidelines to help in the spaceflight crews living environment and the conduction of the interplanetary expedition.

The Mediating Effect of Perceived Task Complexity on Perceived Team Sharedness and Performance

An empirical study was conducted to observe macro-cognition and interpersonal interactions between team members during a collaborative resource management task. Teams consisting of three members each were instructed to work together to complete scenario objectives in a simulated military task environment. The task scenarios were manipulated to vary the complexity of the scenario objectives. An exploratory analysis of the results revealed a mediating effect of perceived complexity on the relationship between perceived sharedness and performance. Additionally, a partial mediating effect for perceived complexity on the relationship between perceived sharedness team knowledge building was found. Results indicate that perceived complexity of a collaborative task may play a greater role in the relationship between team level factors and performance than previously thought. Implications for these results are provided alongside suggestions for future research. Specifically, we call for research to determine the mechanism through which perceptions of task complexity influence collective performance.