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Exposure to Blue Light Emitted from Smartphones in an Environment with Dim Light at Night Alters the Reaction Time of University Students

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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 test. Volunteer university students, who provided their informed consent were randomly divided into 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. Just 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 authors’ 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 dim light at night.
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Shiraz E-Med J. 2019 October; In Press(In Press):e88230.
Published online 2019 June 9.
doi: 10.5812/semj.88230.
Research Article
Exposure to Blue Light Emitted from Smartphones in an Environment
with Dim Light at Night Alters the Reaction Time of University
Students
Seyed Ali Reza Mortazavi#1, Mahdi Faraz #1, Sahar Laalpour 1, Azim Kaveh Ahangar2, Jamshid Eslami3,
Sina Zarei 4, Ghazal Mortazavi 1, Farshid Gheisari5, * and Seyed Mohammad Javad Mortazavi 6, **
1Student Research Committee, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
2Vice-Chancellory for Research, Shiraz University of Medical Sciences, Shiraz, Iran
3Anesthesiology Department, School of Nursing, Shiraz University of Medical Sciences, Shiraz, Iran
4Speech Pathology Department, Varastegan University of Medical Sciences, Mashhad, Iran
5Nuclear Medicine Department, School of Medicine, Shiraz, Iran
6Medical Physics and Medical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran
*Corresponding author: Nuclear Medicine Department, School of Medicine, Imam Hossein Square, Shiraz, Iran fgheisari@gmail.com
**Corresponding author: Medical Physics and Medical Engineering Department, School of Medicine, Shiraz University of Medical Sciences, Imam Hossein Square, Shiraz, Iran.
Tel: +98-0732349332, Email: mortazavismj@gmail.com
# These authors are contributed equally as the first author.
Received 2018 December 24; Accepted 2019 May 06.
Abstract
Background: Substantial evidence now indicates that exposure to visible light at night can be linked to a wide spectrum of disor-
ders 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 test. Volunteer university students, who provided their informed consent were randomly divided into 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 interven-
tion 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. Just 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 statisti-
cally 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 authors’ 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.
Keywords: Blue Light, Smartphones, Digital Screens, Reaction Time
1. Background
Substantial evidence now indicates that human expo-
sure to artificial sources of light, especially short wave-
length blue light at night can be associated with alter-
ations in sleep, alertness, circadian physiology, and ad-
verse health effects, such as insomnia and sleep problems,
psychiatric disorders, obesity, diabetes, increased growth
of bacteria, and different cancers (1-4). In many coun-
tries conventional incandescent light bulbs have been re-
placed by energy efficient compact fluorescent light bulbs
(CFL) and light emitting diodes (LED), which relatively de-
liver higher levels of blue light. Light emitting diodes are
also used in devices, such as televisions, computers, smart
phones, and tablets. The light emitted by most LEDs ap-
Copyright © 2019, Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License
(http://creativecommons.org/licenses/by-nc/4.0/) which permits copy and redistribute the material just in noncommercial usages, provided the original work is properly
cited.
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Mortazavi SAR et al.
pear white yet their peak emission lies in the blue range
(400 to 490 nm) (5). The adverse health effects of chronic
exposure to “blue-rich” LED light compared to other light
sources, which emit less blue light is well documented (6).
The high intensities of blue light emitted from the screens
of smartphones, tablets, and laptops look white to the hu-
man naked eye. It has been shown that both blue light and
electromagnetic fields (EMFs) generated by digital screens
can disturb the circadian rhythm of the users of smart-
phones, who use this device at night (7). Moreover, appli-
cations developed for color-shifting that make the smart-
phone’s screen look “warmer” at night and using special
eye glasses or filters which block blue light (e.g. amber
filters) are widely believed to be able to reduce the detri-
mental biological effects of exposure to blue light (8,9). Al-
though mitigation of the blue light seems to be easy, reduc-
ing the effects of radiofrequency electromagnetic fields
(RF-EMF) is more complicated and needs further research
(10,11).
Some studies show the light emitted by computer
screens can alter circadian physiology, alertness, and cog-
nitive performance (12).
2. Objectives
The aim of the current study was to assess whether ex-
posure to blue light emitted from the screens of common
smartphones in an environment with dim light at night al-
ters human reaction time.
3. Methods
3.1. Ethical Considerations
This study was approved by the Medical Ethics com-
mittee of Shiraz University of Medical Sciences (Permit No.
IR.SUMS. REC.1395.108). Written informed consent was ob-
tained from all students.
3.2. Participants
This study was conducted on 267 apparently healthy
students. Participants were randomly divided into two
groups of control (N = 126 students) and intervention (N
= 141 students). The socio-demographic characteristics of
the participants are reported in Table 1.
3.3. Pre-Intervention/Intervention Set-up
All participants, who had declared they usually sleep
at 24:00 were asked to go to bed at 23:00. Participants
in the intervention group were asked to use their smart-
phones from 23:00 to 24:00 (watching a natural life doc-
umentary movie for 60 minutes), while the control group
only stayed in bed under the same low lighting condition
(Figure 1). The researchers’ previous study showed that the
life documentary movie used in this study lacked exciting
scenes. Before the experiment and 60 minutes after us-
ing smartphone, reaction time was recorded in the inter-
vention group. In the control group, reaction time was
recorded both at 23:00 and 24:00. To ensure the unifor-
mity, participants, who used smartphones with the same
size of display, were included in this study.
3.4. Reaction Time Test
A modified simple blind computer-assisted-visual reac-
tion time test, which was previously developed (13,14), was
used in this study. In summary, the participants were asked
to respond as fast as possible by a single right click on a lap-
top mouse when a red square on the display was replaced
by a green one.
3.5. Statistical Analysis
Student’s t-test was used to compare the means of VRT
between the two groups, before the experiment and after
60 minutes of smartphone use (it was after 60 minutes of
staying in bed for the control group). P values of less than
0.05 were considered statistically significant.
4. Results
The mean ±SD age of the participants was 20.94 ±
5.06 years. One hundred and fifty-two (56.9%) of the partic-
ipants were male and 115 (43.1%) were female. One hundred
and sixty (60%) of the participants were medical students
and 107 (40%) were dentistry students. As indicated in Ta-
ble 2, the mean reaction times in the intervention and the
control groups before the experiment (23:00) were 412.64
±105.59 and 423.13 ±120.31 msec, respectively. This differ-
ence was not statistically significant (P = 0.449). However,
there was a statistically significant difference between the
mean reaction times in the intervention (441.66 ±125.78
msec) and the control groups (406.19 ±92.60 msec) after
60 minutes (at 24:00) (P = 0.01).
As shown in the table, the reaction time in the interven-
tion group significantly increased from 412.64 ±105.60 at
23:00 to 441.66 ±125.78 msec at 24:00 (P = 0.037) while in
the control group there was no statistically significant dif-
ference between the mean reaction times at 23:00 (423.13
±120.31 msec) and 24:00 (406.19 ±92.60 msec) (P = 0.211).
5. Discussion
To the best of the author’s knowledge, this is the first
study, which showed that exposure to blue light emitted
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Mortazavi SAR et al.
Table1. Demographic and Occupational Characteristics of the Sample (N = 157)
Intervention Group Controls
Frequency (%) Mean ±SD Frequency (%) Mean ±SD
Age, y 141 (52.8) 20.91 ±5.49 126 (47.2) 20.98 ±4.66
Sex
Male 86 (60.99) 66 (52.38)
Female 55 (39.01) 60 (47.62)
Major
Medicine 89 (63.12) 71 (56.34)
Dentistry 52(36.88) 55 (43.66)
History of smartphone use, y 7.37 (2.08) 7.58 (2.50)
Smartphone’s screens use per day,h 8.02 (2.30) 7.81 (2.43)
Figure 1. graphic presentation of the protocol used in this study
from common smartphones increases the visual reaction
time. This effect can possibly result in a delay in human
responses to different hazards. The current findings re-
veal that the effects of exposure to different parts of non-
ionizing electromagnetic radiations (radiofrequency ver-
sus visible light) are contradictory. Mortazavi et al. pre-
Shiraz E-Med J. 2019; In Press(In Press):e88230. 3
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Mortazavi SAR et al.
Table2. Mean Reaction Times in the Intervention and the Control Groups Before (23:00) and After the Experiment (24:00)
Reaction Time, msec Intervention Groupa(N = 141) Control Groupa(N = 126) P Value (Significance)
Visual reaction time at 23:00 p.m. 412.64 ±105.59 423.13 ±120.31 0.449 (NS)
Visual reaction time at 24:00 p.m. 441.66 ±125.78 406.19±92.60 0.01
P value (significance) 0.037 0.211 (NS)
Abbreviation: NS, not significant.
aValues are expressed as mean ±SD.
viously showed that the visual reaction time of university
students was significantly affected by a short-term expo-
sure (10 min) to RF-EMFs emitted by a common mobile
phone (13). Their experiment revealed that short term ex-
posure to RF-EMFs could significantly decrease the reaction
time in students (the mean ±SD reaction time after real
exposure and sham exposure were 286.78 ±31.35 msec and
295.86 ±32.17 msec, respectively). Furthermore, Mortazavi
et al. showed that occupational exposure to microwave ra-
diation can also decrease the reaction time in radar work-
ers (14). Based on these findings, exposure to RF-EMF scan
decrease the reaction time while the findings of the cur-
rent study showed that exposure to blue-rich visible light,
in contrast with RF-EMFs, could lead to a longer response
time to different hazards, which in turn can increase the
probability of errors and accidents.
The current findings are generally in line with the re-
sults obtained in a study performed by Cajochen et al., who
showed that the spectral pattern of the light generated by
the screens of computers can affect the circadian rhythms,
alertness, and the levels of cognitive performance (12).
However,another study that aimed at investigating the
effects of exposure to a 30-minute pulse of blue light ver-
sus placebo (using amber light) significantly showed bet-
ter long-delay verbal recall compared to individuals, who
received amber light exposure (15). Given this considera-
tion, Alkozei et al. discussed the potential applications of
blue light for optimizing memory performance in healthy
individuals. They also stated that further studies can an-
swer the question of whether exposure to blue light can en-
hance the performance in patients with memory deficits.
The difference between the findings of this study and those
obtained in the current study comes from the exposure
time (morning in the study performed by Alkozei et al. ver-
sus late night in our experiment) (15).
A more recent study on the effect of blue-enriched
white light on reaction time does not support the current
findings. Motamedzadeh et al. showed that during the sus-
tained attention task, exposure decreased both omission
errors and reaction time. This difference may come from
confounding factors, which were ignored in the study of
Motamedzadeh et al. (16).
5.1. Study Limitations
This study had some limitations. For example, the
number of students participated in this study was rela-
tively small. Moreover, the intervention group partici-
pated in a mentally and visually demanding task while the
control group was resting.
5.2. 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 vi-
sual reaction time, which would eventually result in a de-
lay in human responses to different hazards. These find-
ings indicate that people, such as night shift or on call
workers, who need to react to stresses should avoid using
their smartphones in a dim light at night.
Acknowledgments
This study was supported by Shiraz University of Medi-
cal Sciences.
Footnotes
Conflict of Interests: Authors declare no conflict of inter-
est.
Ethical Approval: This study was approved by the Medical
Ethics Committee of Shiraz University of Medical Sciences
(permit No.: IR.SUMS. REC.1395.108).
Funding/Support: This project was funded by Shiraz Uni-
versity of Medical Sciences.
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