0391 Bedtime Technology Use is Associated with Sleepiness, Poor Sleep Quality, and Poor Mental Health (Burnout, Stress, and Coping) in Firefighters

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Abstract Introduction Sleep disorders and poor sleep quality are prevalent in firefighters (30.49% and 51.43% respectively). Factors associated with poor sleep among firefighters include shiftwork, depression, stress, psychosomatic disorders, and post-traumatic stress. Poor sleep quality, sleep disorders, and insufficient sleep negatively impact physical and mental performance and productivity. Traditional sleep hygiene behaviors (e.g. consistent bed and wake times, comfortable sleeping conditions, reducing caffeine and exercise before bed) are related to better sleep, but can be challenging for firefighters to change due to dynamic schedules and the nature of their jobs. We assessed the relationship between sleep hygiene, sleepiness, sleep quality, and mental health in firefighters focusing on the specific modifiable sleep hygiene behavior of bedtime technology use. Methods 95 firefighters (M = 44.8 years, SD = 11.7; 12 females, 83 males) completed a 20-minute questionnaire packet at a statewide firefighter conference: Pittsburg Sleep Quality Index, Epworth Sleepiness Scale, Sleep Hygiene Index-Technology, Oldenburg Burnout Inventory (Disengagement and Exhaustion), Perceived Stress Scale, and firefighter coping questions. Results Sleep hygiene, sleep and mental health: Poor sleep hygiene was significantly related to greater sleepiness (r(80)=.511, p<.001), poorer sleep quality (r(73)=.539, p<.001), more stress (r(82)=.480, p<.001), greater exhaustion (r(86)=.317, p=.001) , and poorer firefighter coping (r(84)=.239, p=.013). Bedtime technology use, sleep and mental health: Active, but not passive, bedtime technology use by firefighters was significantly related to greater sleepiness (r(88)=.310, p=.001), and poorer sleep quality (r(80)=.353, p<.001). Firefighter active technology use also predicted stress (r(91)=.345, p<.001) and exhaustion (r(94)=.171, p=.048). Additionally, active, but not passive, bedtime technology use by the firefighters’ bed partners was significantly related to greater sleepiness (r(85)=.245, p=.011), and poorer sleep quality (r(77)=.349, p<.001). Bedpartner active technology use also predicted stress (r(88)=.241, p=.011) and exhaustion (r(91)=.215, p=.019). Conclusion Maladaptive sleep hygiene, in particular active bedtime technology use (either by firefighters or their bed partners), was related to sleepiness, poor sleep quality, and poor mental health. Although causation is not clear, it suggests education and incentives to reduce bedtime technology use could improve sleep and mental health in firefighters who would likely have difficulty altering more traditional sleep hygiene variables. Support (if any) The Poling Foundation

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