Spotlight on Dr. Stephen Guastello: Cognitive Workload and Fatigue
There seems to be a stereotype that psychology doesn’t have any sort of mathematical component to it, but Dr. Stephen Guastello disagrees.
“When you get to topics that you find in human factors engineering, they (mathematical components) are a lot more likely and very useful,” stated Guastello, a Professor of Psychology at Marquette University for the last 36 years.
Guastello’s research interests fall into several areas but his current work is focusing on cognitive workload and fatigue. A distinctive point of his research is the topic of nonlinear dynamical systems, which include things that change over time in a catastrophic fashion. “The essential thought with nonlinear processes is that sometimes a big intervention at the wrong time and place could do nothing, but a small one at exactly the right time could have a major effect.”
Part of his work with cognitive workload and fatigue involves two catastrophe models for discontinuous change. Each involves two stable states separated by a bifurcation variable - a parameter that forces the system in either a positive or negative direction. Guastello is also looking for another parameter that would bring the individual closer to that change point.
“In the conventional literature on cognitive workload and fatigue - there’s a lot of it - so many of the previous researchers have confounded workload effects with fatigue effects and felt we really had to separate those two effects because they’re two separate processes that are usually going on at the same time.”
A good example of this is in corporate jobs, especially during this work-at-home period as a result of COVID-19. Many companies have transitioned to work routines where employees can work at home, an option that has certain pros and cons depending on several factors in a person’s life, that can add to that individual’s stress and workload level.
“In terms of work performance, there’s the belief that if you’re doing tougher work, you’ll fatigue faster. This is true, but if you work on a task for a longer period of time, you build momentum. Once you do it repeatedly it starts to become more automatic. So you have effects that push performance up and down at the same time.”
Guastello is contacting people outside of the lab who are frequently engaged in a lot of distance work, something that is different from previous experiments. From there he will identify which variables help with workload and a person’s engagement in each task. He’s already encountered some new types of downsides to tele-work including disorientation with time and the struggle with how employees once did a task and how they might have to re-learn a new way of doing the same task.
“The amount of flow or engagement that a person has will be a dependent variable and we’ll compare other factors to this. I expect to see some industry-related patterns emerge. I don’t know what they are yet, but I think it’s easy to guess that work patterns in different industries are going to make different demands and will have different impacts for flow.”
Dr. Guastello is working with Dr. Anthony Peressini, a Professor of Philosophy at Marquette, on this research and several students in computer science and psychology, both graduate and undergraduate, who use data science practices in theory building and data analysis techniques including orbital decomposition and catastrophe modeling. To learn more about this project, please contact Dr. Guastello or visit his Research Lab, or check out some of the below resources supporting Dr. Guastello’s work.
- Cognitive Workload and Fatigue Dynamics in a Chaotic Forecasting Task
- Cognitive Workload and Fatigue in Telework
- New Paradigm for Task Switching Strategies While Performing Multiple Tasks: Entropy and Symbolic Dynamics Analysis of Voluntary Patterns
- Development of a Synchronization Coefficient for Biosocial Interactions in Groups and Teams