Focus on Fatigue

Focus on Fatigue, Issue 42: Self-monitoring

By July 13, 2016 No Comments

Welcome to Focus on Fatigue

Sleep is not always the easiest thing to come by, especially for those working long shifts. When we are deprived of adequate sleep, many of us are faced with a number of important questions. How tired am I? Can I continue working? Is my work performance suffering? Am I putting myself or others at increased risk?

We all like to think we can accurately identify our level of fatigue and how we’re being affected by it, but is this actually the case? Do we know how tired we really are? This is the question we’ll be investigating in this month’s Focus on Fatigue.

The FRMS Team

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InterDynamics Pty Ltd
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Tel +61 2 8404 0400 Ext 23

Views expressed in articles and links provided are those of the individual authors, and do not necessarily represent the views of InterDynamics (except where directly attributed).

Feature Articles

Do we know how tired we really are?

Many shift workers rely on self-monitoring to assess their fatigue levels. This makes practical sense. Each individual is best placed to know how alert they feel, how much sleep they’ve achieved, how much work they’ve done, what they’ve eaten, etc. This practice does, however, raise an important question: How good are individuals at assessing their own level of fatigue?

Pretty good, but not perfect

A number of studies performed over the years have found that people are moderately good at recognizing when sleep deprivation is hampering their performance on simple tasks. As their performance worsens, so does their confidence in how well they’re doing. The key word to remember here is ‘moderate’. We’re not terrible at self-monitoring fatigue, but we’re not brilliant at it either.

A recent study of Australian fire fighters found that while participants were good at identifying when they were affected by fatigue, they did tend to either over or under-estimate the degree to which their performance was suffering. This ability to self-monitor performance begins to deteriorate after prolonged periods of wakefulness (around 54 hours). That is, once we’ve been awake more than two days, not only will our performance already be suffering greatly, but we may no longer be able to determine how badly we’re performing.

Post-work evaluations are better than predictions of future work performance

Generally, we are better at evaluating our performance after we’ve finished work activities, than we are at predicting how well we’ll perform before we begin. Unfortunately, when it comes to risk management, it’s the pre-performance assessment that is most valuable in reducing the chance of accident or injury.

Feedback helps

When feedback is available during the completion of a task, this will generally lead to a more accurate post-test evaluation of performance. Feedback on past performances can also help with predicting future performance.

Feeling alert makes a difference

Some studies have found that subjective alertness at the time the assessment is made does mediate the performance rating given. That is, if we are feeling alert when asked how well we will do (or how well we did) on a particular task, we are likely to be more confident about our performance, than if we are sleepy when asked.

The ability to self-monitor fatigue can also be reduced during a person’s biological night (that’s the time when our circadian rhythm is telling us we should be asleep). Perhaps this is also related to alertness as we tend to feel drowsier during circadian lows.

Global predictions are most common

We tend to be better at making global predictions about our performance than we are at predicting how well we’ll do on particular tasks. For example, one study found that after a week of simulated night-shifts, participants were better able to predict their performance overall, than they were able to predict their performance for specific shifts.

This means that we aren’t necessarily great at identifying which tasks will be affected by our levels of fatigue. Considering that sleep deprivation does not affect all types of activities equally, such global predictions mean that we may not be good at adjusting our prediction of how well we will perform based on the type of activity we will be performing.

Acknowledging fatigue won’t help improve our performance – much

There can be a tendency to think that if we acknowledge how fatigued we are, then we can improve our performance by ‘trying harder.’ To a certain degree this is true. Studies have found that motivation to do well can make a difference to performance in people who are sleep-deprived (this depends heavily on the severity of the deprivation). However, it is important to remember that the best way to deal with fatigue, especially when we are able to recognize that fatigue is affecting our work performance, is to stop working and take a break or, preferably, have a sleep.

Work culture is also important

Fatigue will most commonly be apparent to a worker long before they cease to be ‘capable’ of working. Therefore, a person who acknowledges they are experiencing a high level of fatigue is not necessarily saying ‘I can’t continue working’ but may actually be saying ‘I believe it may be unsafe for me to continue working.’ It is imperative that workplace culture supports individuals who recognize that fatigue is impeding their work performance and wish to take steps to rectify the situation.

Overall, research tells us that self-monitoring is a good tool to use when determining fatigue risk in the event of sleep deprivation. However, because our own assessment of fatigue is not necessarily as accurate as we would like to think it is, we should also be using the other tools at our disposal to assess risks that might be present as a result of fatigue.


  • Armstrong, T. A., Cvirn, M., Ferguson, S. A., Christoforou, T. and Smith, B. (2013) Can Australian bush fire fighters accurately self-monitor their cognitive performance during a 3-day simulated fire-ground campaign? Sleep, performance and well-being in adults and adolescents, 18-23. 10th Annual Meeting, Australiasian Chronobiology Society: Adelaide.
  • Baranksi, J. V., Pigeau, R. A., and Angus, R. G. (1994) On the ability to self-monitor cognitive performance during sleep deprivation: A calibration study. Journal of Sleep Research, 3(1), 36-44.
  • Dorrian, J., Lamond, N., Holmes, A. L., Burgess, H. J., Roach, G. D., Fletcher, A., and Dawson, D. (2003) The ability to self-monitor performance during a week of simulated night shifts. Sleep, 26(7), 871-877.
  • Muldoon, N., Sargent, C., Zhou, X., Kosmadopoulos, A., Darwent, D. and Roach, G. D. (2013) The efficacy of subjective ratings is limited during the biological night. Sleep, performance and well-being in adults and adolescents, 7-12. 10th Annual Meeting, Australiasian Chronobiology Society: Adelaide.
  • Dorrian, J., Lamond, N. and Dawson, D. (2000) The ability to self-monitor performance when fatigued. Journal of Sleep Research, 9, 137-144.

InterDynamics News

New Product Release: FAID Quantum

InterDynamics FAID software has been an industry standard for alertness prediction and fatigue management since its introduction in the late 1990s. Now InterDynamics is setting a new standard withFAID Quantum, which offers a whole new level of scientifically-verified accuracy based on real-world data.

FAID Quantam has been developed by Dr David Darwent in conjunction with Professor Drew Dawson and Dr Greg Roach of the Appleton Institute. It uses the best sleep-wake predictor algorithms that have yet been published in international peer-reviewed literature and analyses the work-rest schedules of your personnel to produce a fatigue score in the Karolinska Sleepiness Scale (KSS). It also includes output in the original FAID scale for comparison.

Improved accuracy from better data

The researchers at the Appleton Institute have used what may be the largest database of quality sleep-wake data in the world, incorporating nearly 15,000 days and nights of data collected from various industries, including long-haul aviation, to underpin predictions.

With older bio-mathematical models of fatigue, predictions were based on average patterns of sleeping and waking but, with FAID Quantum, actual sleep and wake patterns are used to predict future alertness.

With this superior real-world data, FAID Quantum can justifiably claim to be the most accurate predictor of alertness available on the market today.

Versions and tools to suit your organisation

FAID Quantum is a cost-effective management tool with different options available for different sized organisations. It is easy to use for large data sets, giving quick calculations for multiple workers.

It can be integrated with third party rostering tools or FAID Quantum Roster.

Using the same interface as FAID Standard, it is easy for your organisation to upgrade.

FAID Quantum goes beyond safety compliance to best-practice prediction. While the ultimate vigilance of FAID Quantum is reassuring for aviation and other sensitive industries, the software also brings benefits in the smarter management of work schedules. This needn’t mean more or fewer staff but allocating your existing staff in ways that are better for them, better for safety and better for business efficiency.

For more information about FAID Quantum, please contact InterDynamics.

In the News

Provided below are a selection of articles from around the web on the issues associated with fatigue. We hope you find them useful and interesting.

Article: Caffeine’s ‘boost’ disappears when you’re extremely sleep-deprived

by Laura Geggel, LiveScience (16 June 2016)

People who don’t get enough sleep for several days in a row can’t rely on caffeine to give them a mental boost, new research finds.

Article: Trees seen resting branches while ‘asleep’ for the first time

by Andy Coghlan, New Scientist (18 May 2016)

They don’t snore, but might creak during their slumbers. For the first time, trees have been shown to undergo physical changes at night that can be likened to sleep, or at least to day-night cycles that have been observed experimentally in smaller plants.

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