6 Things to Understand About FAID Quantum

Issue #80 – April 24

Welcome to Focus on Fatigue!

In this edition of Focus on Fatigue, we’re highlighting some of the elements of FAID Quantum that every user should understand. This article may serve as both a brief introduction for newcomers and a refresher for seasoned users.

We are also pleased to share some video resources about FAID Quantum and fatigue in the workplace.

We hope you find this issue useful and informative.

The FRMS Team

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).

While FAID Quantum is a relatively simple tool to use (input work hours + analyse = fatigue scores), all users of a biomathematical model should have a solid understanding of the model they are using. This ensures that you’re not only using the tool correctly but also fully comprehending the insights it provides. Whether you are exploring FAID Quantum for the first time or are an experienced user, here are six key points to consider.

1. Two Biomathematical Models

FAID Quantum Software incorporates two biomathematical models of fatigue – the FAID biomathematical model (providing FAID Score outputs) and the FAID Quantum biomathematical model (providing KSS outputs). While initially this may seem conflicting, once both models are understood, this approach provides a richer understanding of fatigue exposures. To understand more about the two models and how they compliment each other, read here.

2. Work History

To provide accurate fatigue scores, the FAID biomathematical model requires 7 days of work history (15 days for time zone version) prior to the analysis period. FAID considers the probability of sleep and recovery over the prior seven days. If the work history is not entered, the fatigue exposure will be underrated.

3. Commute Times

The modelling within FAID Quantum assumes average commute times of 30-45 minutes, with the standard sleep buffer settings set to 1 hour (sleep cannot be achieved within 1 hour of work start/end times). In the case where commute times are greater than 45 minutes between home and work, FAID Quantum may overestimate the recovery value of non-work periods. If commute times are known to be greater than 45 minutes between home and work, an organisation should consider how this is taken into account. There are a number of ways to address this (such as extending the work period or the sleep buffer). You can read further about FAID and commuting here.

4. Sleep

The FAID Quantum biomathematical model provides predicted sleep times. FAID Quantum does provide the option for actual sleep obtained to be considered in its calculations, if such data is available. While this enables FAID Quantum to reflect more closely the experience of an individual, the results are still based upon a statistical model representing the general population response to that sleep pattern and not a prediction of the individual’s level of fatigue.

5. Fatigue Tolerance Levels

FAID Quantum allows a user to set FAID Score and KSS Tolerance Levels as benchmark figures. Analysis results are compared against the Tolerance Levels and exceedances are highlighted and quantified in magnitude and duration.

There are no magical Tolerance Levels within FAID Quantum at which operations are ‘safe’ or ‘unsafe’. Each organisation need to determine their Tolerance Levels and compliance criteria using a risk assessment methodology that quantifies the risks associated with the job task/role, environmental and other factor that could contribute to an intolerable event occurring when a worker is in a state of heightened fatigue. You can read more about fatigue tolerance levels here.

6. Statistical Models

FAID & FAID Quantum are statistical models that consider the probability of sleep and recovery of the average person and predicts fatigue exposure associated with hours of work only. It is not a pure measure of fatigue. Models can not detect individual fatigue and therefore should not be used as the sole determinant of an individual’s fitness for work. Individual circumstances, operating environments, task impacts and other fatigue risk factors should also be considered when assessing work-related fatigue risks. To understand where FAID Quantum fits in to a risk based approach to managing fatigue, you can read here.

Training

We hope you have found this brief overview helpful. We offer comprehensive training in FAID Quantum, which we highly recommend for all users. Please get in touch if you would like to discuss training options.

InterDynamics has been working with MATES. MATES aim to reduce suicide and support the mental wellbeing of those in the construction industry. MATES have been developing a Resource Hub for FIFO and DIDO workers, their families, friends and mental health providers. As part of this, InterDynamics’ Peter Page was interviewed for a series of videos about FAID Quantum and Fatigue Management. We are pleased to share this resource with you:

Using Research to Inform Rostering

Fatigue model supporting FIFO – How the model helps industry

Use of Multiple Biomathematical Models to Help with Shift Planning

FAID BMM & FAID Quantum BMM as complementary models – Tracking and predicting sleep

Fatigue and Mental Health

How does fatigue affect your mental health?

Fatigue and Decision Making

How the FAID Score relates to decision making

Podcasts

These discussions are also accessible as podcasts.

We’ve come across a number of interesting and informative resources on sleep recently. Here’s a couple that we thought were worth a listen/watch.

Podcast: Sleep: How Do We Get More?

Science Vs, Nov 2023
Not sleeping enough turning you into a monster? In one of their most popular episodes, ‘Science Vs’ bring you the cutting-edge science that helps us understand why, and sort though the fads to find out what really works to get more ZZZs.

Video Series: Australia’s Sleep Revolution with Dr Michael Mosley

SBS, Mar 2024
Dr Michael Mosley and the sleep scientists from Flinders University are on a mission to inspire a sleep revolution.