Something as simple as two coworkers talking nearby can complicate tasks that are normally managable. Yan Krukau/Pexels, FAL
Is it possible to read your e-mails while keeping weekend plans in mind and listening to someone on the phone? Multitasking is part and parcel of our daily lives, with teleworking and the rapid expansion – if not invasion – of digital technology.
We may feel like we’re doing two things at the same time, but in reality our brain unconsciously shifts its attention from one task to another very quickly. After more than 50 years of scientific research, the expression “mental workload” is starting to be heard in everyday life and a variety of professional contexts. But the concept still raises many questions, both about its precise definition and about how to study it or manage it on a day-to-day basis.
Also known as cognitive workload, mental workload corresponds to a quantity of mental work to be done in a given time, with potential consequences for the individual, such as rising fatigue or the number of errors in carrying out tasks. Examples include searching through a cluttered visual display, taking a difficult exam or driving on a busy motorway. These and other activities call on perceptual, cognitive and/or motor processes to produce flexible and adaptive behaviour.
The engagement, maintenance and control of these processes require different levels of mental effort depending on the circumstances (routine activities versus sudden events). Sometimes this massive mental effort leads to what scientists call “cognitive overload” or “mental overload”.
Searching for a universal definition
Researchers are still struggling to come up with a universal definition that cuts across the disciplines concerned with mental workload, including psychology, management and cognitive science. For some, it corresponds to the notion of an individual’s limited capacity to process information – a “reservoir” of attentional resources. For others, it refers to the management of attentional resources and focuses on the demands of the task in hand. Among the many definitions proposed, mental workload can be defined as the effort invested by the individual in carrying out a task as a function of the resources available and the characteristics of the task.
In neuroscience, cognitive psychology and ergonomics (the scientific discipline concerned with the relationship between human beings and their work), the study of mental workload relates in particular to so-called safety-critical applications.
When the cognitive cost exceeds the available resources, the result can be “inattentional deafness”.
The overload produced accentuates the risk of accidents. In fields such as aviation, space flight, defence and medicine, the result can be catastrophic – for example, when a pilot is landing in poor weather conditions.
While laboratory studies have advanced our knowledge of brain function during a given task, it is important to assess an individual’s performance and mental load in the complex work environments encountered in everyday life. The discipline of neuroergonomics, which was founded in the late 20th century, brings together the approaches and tools of neuroscience, ergonomics and engineering. It’s defined as the study of the human brain in relation to performance at work and in everyday life. One example is the measurement of brain activity in surgeons, for whom increased mental workload can lead to errors and adversely affect performance.
How can mental workload be studied?
No single tool or method can give a complete picture of how an individual responds to a particular task. Approaches that combine data from several sensors or measurements can be more accurate and reliable for estimating mental workload in real time. This is all the more true in changing environments (fluctuations in lighting, temperature, noise, etc.) or contexts requiring adaptation to the situation (discomfort, technical incidents, etc.).
Self-assessment questionnaires can be used to collect people’s perceptions of the task they are performing. For example, by incorporating a multidimensional evaluation procedure, the NASA-TLX questionnaire provides an overall mental workload score during or after the task. It is based on a weighted average of the scores (from 0 to 100) of six subjective areas. These are:
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Mental demand: level of mental activity.
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Physical demand: level of physical activity.
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Temporal demand: feeling of pressure to complete the task within a given time.
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Performance: level of achievement of the task objectives.
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Effort: amount of effort involved.
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Frustration: feeling of dissatisfaction while completing the task.
Analysing performance on a single task can also help to estimate mental workload. For example, more frequent errors or a reduction in the speed with which information is processed may indicate a higher mental load if the demands of the task increase. In the case of a dual cognitive-motor task (phoning while driving, finding your way while cycling or walking…), the sharing of resources thus created can lead to a drop in performance compared with performing each of the two tasks separately.
Neuroergonomics also proposes the integration of objective measures to assess mental workload using several techniques in environments that vary over time – workplaces, classrooms, hospitals, motorways, and so on. For example, eye-tracking analysis can provide information on mental workload by measuring where an individual directs her or his attention. Physiological measures such as heart rate and its variability, electrodermal activity and even portable brain imaging can provide specific neurophysiological indicators of mental workload.
The brain’s prefrontal cortex is a key indicator
Mental workload manifests itself particularly in the prefrontal cortex, the area of the brain that has undergone the greatest development in human beings over the last few million years. This part of our brain is heavily involved in cognitive control, a mechanism for supervising and managing the decision-making process. It involves conflict resolution, error detection and inhibition, and aims to guarantee a sufficient level of performance in relation to the demands of the task and unforeseen events, while maintaining an acceptable cognitive cost.
Measuring the activation of the prefrontal cortex can provide information about the quantity of resources mobilised. Indeed, difficult tasks or those requiring sustained attention lead to more pronounced activation of the prefrontal cortex and associated brain networks.
This also occurs during demanding physical effort in complex environments, such as in traffic situations with a bicycle, where each cyclist acts individually, weighing up the costs and benefits of each choice. In this dual-task situation, both physical and cognitive, the speed choice decision is cognitively controlled.
Managing the load
In demanding contexts, our mental load can shift under the influence of various external and internal factors. So how do we deal with the multitude of factors to which we have to pay attention? Here are four specific suggestions:
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Draw up an overview of all the tasks that need to be done and prioritise them. This allows building up a sequence of tasks to be completed in order, and to set aside the nonessential ones.
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Each task should correspond to specific short-term objectives of 20 minutes or so.
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Adapt work breaks to the task in hand. This allows you to manage mental workload effectively and reduce distracting interruptions.
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Always allow yourself adequate recovery time (reading, sport, etc.).
Applying the principles of neuroergonomics can provide personalised and effective solutions for managing mental workload. Research remains extremely relevant, particularly when taking account individual ways people process information and interact with the environment. In this respect, the use of artificial intelligence methods to extract information from several measurements is an interesting way of continuously assessing the mental load of an individual engaged in a task.
Stéphane Perrey, Professeur des Universités en Physiologie de l'Exercice / Neurosciences Intégratives, Directeur Unité Recherche EuroMov Digital Health in Motion, Université de Montpellier
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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