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Gringras, P., Middleton, B., Skene, D. J., & Revell, V. L. (2015). Bigger, Brighter, Bluer-Better? Current Light-Emitting Devices – Adverse Sleep Properties and Preventative Strategies. Front Public Health, 3, 233.
Abstract: OBJECTIVE: In an effort to enhance the efficiency, brightness, and contrast of light-emitting (LE) devices during the day, displays often generate substantial short-wavelength (blue-enriched) light emissions that can adversely affect sleep. We set out to verify the extent of such short-wavelength emissions, produced by a tablet (iPad Air), e-reader (Kindle Paperwhite 1st generation), and smartphone (iPhone 5s) and to determine the impact of strategies designed to reduce these light emissions.
SETTING: University of Surrey dedicated chronobiology facility.
METHODS: First, the spectral power of all the LE devices was assessed when displaying identical text. Second, we compared the text output with that of “Angry Birds” – a popular top 100 “App Store” game. Finally, we measured the impact of two strategies that attempt to reduce the output of short-wavelength light emissions. The first strategy employed an inexpensive commercially available pair of orange-tinted “blue-blocking” glasses. The second strategy tested an app designed to be “sleep-aware” whose designers deliberately attempted to reduce short-wavelength light emissions.
RESULTS: All the LE devices shared very similar enhanced short-wavelength peaks when displaying text. This included the output from the backlit Kindle Paperwhite device. The spectra when comparing text to the Angry Birds game were also very similar, although the text emissions were higher intensity. Both the orange-tinted glasses and the “sleep-aware” app significantly reduced short-wavelength emissions.
CONCLUSION: The LE devices tested were all bright and characterized by short-wavelength enriched emissions. Since this type of light is likely to cause the most disruption to sleep as it most effectively suppresses melatonin and increases alertness, there needs to be the recognition that at night-time “brighter and bluer” is not synonymous with “better.” Ideally future software design could be better optimized when night-time use is anticipated, and hardware should allow an automatic “bedtime mode” that shifts blue and green light emissions to yellow and red as well as reduce backlight/light intensity.
Mortazavi, S. A. R., Faraz, M., Laalpour, S., Kaveh Ahangar, A., Eslami, J., Zarei, S., et al. (2019). Exposure to Blue Light Emitted from Smartphones in an Environment with Dim Light at Night Alters the Reaction Time of University Students. Shiraz E-Med J, , e88230.
Abstract: Background: Substantial evidence now indicates that exposure to visible light at night can be linked to a wide spectrum of disorders ranging from obesity to cancer. More specifically, it has been shown that exposure to short wavelengths in the blue region at night is associated with adverse health effects, such as sleep problems.
Objectives: This study aimed at investigating if exposure to blue light emitted from common smartphones in an environment with dim light at night alters human reaction time.
Methods: Visual reaction time (VRT) of 267 male and female university students were recorded using a simple blind computer-assisted VRT test, respectively. Volunteer university students, who provided their informed consent were randomly divided to two groups of control (N = 126 students) and intervention (N = 141 students). All participants were asked to go to bed at 23:00. Participants in the intervention group were asked to use their smartphones from 23:00 to 24:00 (watching a natural life documentary movie for 60 minutes), while the control group only stayed in bed under low lighting condition, i.e. dim light. Before starting the experiment and after 60 minutes of smartphone use, reaction time was recorded in both groups.
Results: The mean reaction times in the intervention and the control groups before the experiment (23:00) did not show a statistically difference (P = 0.449). The reaction time in the intervention group significantly increased from 412.64 ± 105.60 msec at 23:00 to 441.66 ± 125.78 msec at 24:00 (P = 0.0368) while in the control group, there was no statistically significant difference between the mean reaction times at 23:00 and 24:00.
Conclusions: To the best of the author’s knowledge, this is the first study, which showed that exposure to blue-rich visible light emitted from widely used smartphones increases visual reaction time, which would eventually result in a delay in human responses to different hazards. These findings indicate that people, such as night shift or on call workers, who need to react to stresses rapidly should avoid using their smartphones in a dim light at night.
Walch, O. J., Cochran, A., & Forger, D. B. (2016). A global quantification of “normal” sleep schedules using smartphone data. Science Advances, 2(5), e1501705.
Abstract: The influence of the circadian clock on sleep scheduling has been studied extensively in the laboratory; however, the effects of society on sleep remain largely unquantified. We show how a smartphone app that we have developed, ENTRAIN, accurately collects data on sleep habits around the world. Through mathematical modeling and statistics, we find that social pressures weaken and/or conceal biological drives in the evening, leading individuals to delay their bedtime and shorten their sleep. A countryâs average bedtime, but not average wake time, predicts sleep duration. We further show that mathematical models based on controlled laboratory experiments predict qualitative trends in sunrise, sunset, and light level; however, these effects are attenuated in the real world around bedtime. Additionally, we find that women schedule more sleep than men and that users reporting that they are typically exposed to outdoor light go to sleep earlier and sleep more than those reporting indoor light. Finally, we find that age is the primary determinant of sleep timing, and that age plays an important role in the variability of population-level sleep habits. This work better defines and personalizes ânormalâ sleep, produces hypotheses for future testing in the laboratory, and suggests important ways to counteract the global sleep crisis.