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Harnessing technology to improve sleep in frontline healthcare workers: A pilot study of electronic noise-masking earbuds on subjective and objective sleep measures.

Heinrich C HallerSusan L MooreKatherine K GreenRachel L JohnsonMary D SammelC Neill EppersonAndrew M Novick
Published in: Science progress (2024)
Objective: This pilot study assessed the effects of electronic noise-masking earbuds on subjective sleep perception and objective sleep parameters among healthcare workers (HCWs) reporting sleep difficulties during the COVID-19 pandemic. Methods: Using a pre-post design, 77 HCWs underwent 3 nights of baseline assessment followed by a 7-night intervention period. Participants wore an at-home sleep monitoring headband to assess objective sleep measures and completed subjective self-report assessments. The difference in mean sleep measures from baseline to intervention was estimated in linear mixed models. Results: Compared to baseline assessments, HCWs reported significant improvements in sleep quality as measured by the Insomnia Severity Index (ISI) (Cohen's d = 1.74, p  < 0.001) and a significant reduction in perceived sleep onset latency (SOL) during the intervention ( M  = 17.2 minutes, SD = 7.7) compared to baseline ( M  = 24.7 minutes, SD = 16.1), (Cohen's d = -0.42, p  = 0.001). There were no significant changes in objective SOL ( p =  0.703). However, there was a significant interaction between baseline objective SOL (<20 minutes vs >20 minutes) and condition (baseline vs intervention) ( p  = 0.002), such that individuals with objective SOL >20 minutes experienced a significant decrease in objective SOL during the intervention period compared to baseline ( p =  0.015). Conclusions: HCWs experienced a significant improvement in perceived SOL and ISI scores after using the electronic noise-masking earbuds. Our data provide preliminary evidence for a nonpharmacological intervention to improve the sleep quality of HCWs which should be confirmed by future controlled studies.
Keyphrases
  • sleep quality
  • depressive symptoms
  • physical activity
  • randomized controlled trial
  • deep learning
  • big data