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Updated: Jun 12, 2026

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Insomnia disorder and occupational demand in commercial freight driving: A qualitative analysis of symptoms and
Iuliana Hartescu1, Aron P Sherry1,2, Elizabeth Stamp1
1School of Sport, Exercise and Health Sciences, National Centre for Sport and Exercise Medicine, Loughborough University, Loughborough, UK.
Background:
Inadequate sleep prior to driving professionally is internationally recognized as a preventable crash risk. Nevertheless, insomnia in commercial drivers remains underrecognized both as a driving hazard and as a public health issue. To identify unmet sleep-health needs within this workforce, we explored the correspondence between driver sleep experiences and DSM-5 symptoms of insomnia disorder.
Materials And Methods:
Semistructured interviews addressing the nature, causes, and consequences of impaired driver sleep quality were conducted with commercial freight drivers (n = 20, 19 male) and industry stakeholders (n = 11; 9 male) occupying managerial and executive roles. Interviews were transcribed verbatim and thematically analyzed.
Results:
"Sleep symptoms and causal attributions" emerged as a dominant theme among drivers, with most describing insomnia symptoms linked to driving stress/anxiety, shift patterns and work schedules, and sleeping in vehicles. There was consensus in associating stress/anxiety with sleep onset problems, shift patterns/work schedules with disturbed sleep habits and uncertain bedtimes, and sleeping in vehicles with disturbed sleep habits and poor sleep hygiene. Although prioritizing driver wellbeing and alertness, most stakeholders were less likely to associate driver sleepiness with sleep quality prior to driving, emphasizing instead boredom, monotony, and stress.
Conclusion:
Driver narratives indicate high levels of untreated insomnia symptoms that align with factors known to precipitate and perpetuate insomnia disorder (e.g. cognitive arousal, degraded sleep routines, and poor sleep hygiene). These behavioral factors are amenable to digital (app-based) cognitive-behavioral sleep improvement programs. With appropriately informed management support, such programs could address an important and safety critical unmet need in this workforce.
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