Title

Mining for sleep data: An investigation into the sleep of fly-In fly-out shift workers in the mining industry and potential solutions

Author Identifiers

Gemma Maisey

https://orcid.org/0000-0002-2189-5697

Date of Award

2023

Degree Type

Thesis

Degree Name

Doctor of Philosophy

School

School of Medical and Health Sciences

First Advisor

Marcus Cattani

Second Advisor

Amanda Devine

Third Advisor

Ian Dunican

Abstract

Shift work in the mining industry is a risk factor for sleep loss leading to impaired alertness, which may adversely impact health and safety risks. This risk is being increasingly recognised by leaders and shift workers in the mining industry, however, there is limited knowledge available on the extent of sleep loss and other potential contributing factors. Furthermore, knowledge of the efficacy of individual interventions to assist shift workers to improve their sleep, and the management of risk at an organisational level is scarce. This PhD thesis involved three studies. The first two studies involved the recruitment of 88 shift workers on a fly-in, fly-out (FIFO) mining operation in Western Australia (WA), undertaken within a business-as-usual model. The third study develops a diagnostic tool to support the systematic assessment of an organisation's Fatigue Risk Management System (FRMS).

Study 1 (Chapter 4) investigated sleep behaviours, the prevalence of risk of sleep disorders and the predicted impact on alertness across the roster schedule. Sleep was objectively measured using wrist-activity monitors for the 21-day study period and biomathematical modelling was used to predict alertness across the roster schedule. The prevalence of risk for sleep problems and disorders was determined using scientifically validated sleep questionnaires. We found sleep loss was significantly greater following days shift and night shift compared to days off, which resulted in a 20% reduced alertness across the 14 consecutive shifts at the mining operation. Shift workers reported a high prevalence of risk for sleep disorders including shift work disorder (44%), obstructive sleep apnoea (OSA) (31%) and insomnia (8%); a high proportion of shift workers were obese with a body mass index (BMI) > 30kg/m2 (23%) and consumed hazardous levels of alcohol (36%). All of which may have contributed to sleep loss. In addition, the design of shifts and rosters, specifically, early morning shift start times ( < 06:00) and long shift durations ( > 12 hrs.) may have also adversely impacted sleep duration, as they did not allow for sufficient sleep opportunity.

Study 2 (Chapter 5) was a randomised control trial (RCT) that investigated the efficacy of interventions to improve sleep, which included a two-hour sleep education program and biofeedback on sleep through a smartphone application. Sleep was objectively measured using wrist-activity monitors across two roster cycles (42 days) with an intervention received on day 21. Our results were inconclusive and suggest that further research is required to determine the efficacy of these commonly used interventions in the mining industry. In line with the results from Study 1, our interventions may not have been effective in improving sleep duration as the shift and roster design did not allow adequate time off between shifts for sleep ( ≥ 7 h) and daily routines.

Study 3 (Chapter 6) used a modified Delphi process that involved 16 global experts, with experience and knowledge in sleep science, chronobiology, and applied fatigue risk management within occupational settings, to define and determine the elements considered essential as part of an FRMS. This study resulted in the development of an FRMS diagnostic tool to systematically assist an organisation in assessing its current level of implementation of an FRMS.

The results of the studies within this PhD thesis present several potential benefits for the mining industry. These include an enhanced understanding of the extent of sleep loss and the potential impact on alertness, in addition to contributing factors, including shift and roster design elements and unmanaged sleep disorders. The development of the FRMS diagnostic tool may practically guide mining operations on the elements required to manage risk. These findings may also inform government, occupational health and safety regulatory authorities and shift work organisations more broadly, on the need to identify and manage fatigue, as a result of sleep loss, as a critical risk.

Access Note

Access to this thesis is embargoed until 18th January 2024.

Access to this thesis is restricted. Please see the Access Note below for access details.

Share

 
COinS