|Year : 2019 | Volume
| Issue : 1 | Page : 68-74
Eyeing computer vision syndrome: Awareness, knowledge, and its impact on sleep quality among medical students
Ashwini Patil1, Bhavya1, Suprakash Chaudhury2, Smiti Srivastava3
1 Department of Physiology, Dr. D.Y. Patil Medical College, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
2 Department of Psychiatry, Dr. D.Y. Patil Medical College, Dr. D. Y. Patil Vidyapeeth, Pune, Maharashtra, India
3 Consultant Psychotherapist, Pune, Maharashtra, India
|Date of Submission||25-Nov-2018|
|Date of Acceptance||11-Jul-2019|
|Date of Web Publication||11-Dec-2019|
Dr. Suprakash Chaudhury
Department of Psychiatry, Dr. D.Y. Patil Medical College, Dr. D. Y. Patil Vidyapeeth, Maharashtra, Pimpri, Pune
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Computer vision syndrome (CVS) encompasses a constellation of ocular and extraocular symptoms in computer users who either habitually or compulsively use computers for long periods of time. Electronic devices such as computers, smart phones, and tablets emit blue light (400–490 nm) from their light-emitting diodes and produce electromagnetic fields, both of which interfere with the circadian rhythm. Aim: This study aims to assess the awareness, knowledge, and impact on sleep quality of CVS among medical students. Materials and Methods: This study included 500 medical students. All participants anonymously filled up a pro forma including sociodemographic details and three questionnaires that (a) tested for awareness and knowledge about CVS, (b) tested for CVS, and (c) the Pittsburgh sleep quality index (PSQI), respectively. Data from 463 complete questionnaires were analyzed. Results: The mean (±standard deviation) age of the 463 individuals was 19.55 (±1.04) years. The prevalence of CVS was 77.5%. The prevalence was higher in boys (80.23%) compared to girls (75.87%), but the difference was not statistically significant. Only 34.1% of the medical students were aware of CVS. Good knowledge regarding various aspects of CVS was observed in 22.46% individuals, while 53.99% and 23.56% had average and poor knowledge, respectively. Poor sleep quality was present in 75.49% of individuals with CVS compared to 50.96% of students without CVS; the difference was statistically significant (odd's ratio [95% confidence interval]: 0.338 [0.214–0.531]). All the components of PSQI score, except components 1 and 6, had statistically significantly (P < 0.05) higher values in individuals with CVS as compared to individuals without CVS. Conclusions: There is high prevalence but low level of awareness and knowledge about CVS among medical students. CVS is significantly associated with poor sleep quality in medical students.
Keywords: Circadian rhythm, computer vision syndrome, quality of sleep
|How to cite this article:|
Patil A, Bhavya, Chaudhury S, Srivastava S. Eyeing computer vision syndrome: Awareness, knowledge, and its impact on sleep quality among medical students. Ind Psychiatry J 2019;28:68-74
|How to cite this URL:|
Patil A, Bhavya, Chaudhury S, Srivastava S. Eyeing computer vision syndrome: Awareness, knowledge, and its impact on sleep quality among medical students. Ind Psychiatry J [serial online] 2019 [cited 2020 Apr 3];28:68-74. Available from: http://www.industrialpsychiatry.org/text.asp?2019/28/1/68/272703
Phenomenal advances in technology have made computers and visual display terminals an integral part of our professional and personal life. There is extensive use of computers as a medium of teaching and learning in universities. Doctors are now able to hold textbooks on their smartphone and use resources such as medical calculators and drug formularies. This calls for introspection into the potential deleterious health disorders resulting due to increased “screen time” in digital natives.
Computer vision syndrome (CVS) encompasses a constellation of ocular and extraocular symptoms in computer users who are either habitually or on compulsion using computers for a long time during day and night., These symptoms comprise of dry eyes, irritated eyes, eye strain/fatigue, blurred vision, red eyes, burning eyes, excessive tear secretion, double vision, headache, light or glare sensitivity, contact lens discomfort, slowness in changing focus, changes in color perception, and neck, shoulder, and backache. CVS can be due to ocular (ocular-surface abnormalities or accommodative spasms) and/or extraocular (ergonomic) etiologies.
Awareness is an important step in healing. It is of utmost importance for future doctors to be aware of what is going on in the society. Prevention remains the mainstay in managing of CVS. Reasonable knowledge gives understanding, and understanding the disease gives the key to implement early preventive measures and treatment initiation.
Endogenous melatonin rhythm exhibits a close association with the endogenous circadian component of the sleep propensity rhythm. Thus, melatonin is an internal sleep “facilitator” in humans. Owing to their consistency, efficiency, and durability, light-emitting diodes (LEDs) have become the prevalent light source in electronic devices such as computers, smart phones, tablets such as iPads and e-readers, and large liquid crystal display television sets. Although the light emitted by most LEDs appears white, LEDs have peak emission in the blue light range (400–490 nm)., This emitted optical radiation at short wavelengths is close to the peak sensitivity of melatonin suppression. Using a tablet (e-reader) at night just before sleeping while in bed induces circadian phase delay and melatonin suppression altering sleep quality,, while enhancing alertness and cognitive performance.,, Elimination of short wavelength using appropriate blocking goggles in the evening can improve sleep duration and quality, and reduce subjective alertness. Electromagnetic field exposure in the evening influences physiological factors such as sleep quality and the melatonin rhythm.
Memory consolidation through the gradual assimilation of episodic memories into long-term memory is strongly influenced by sleep. Given that sleep and its specific architecture serves vitally important physiological, cognitive, and psychological processes, restoring sleep is essential in adults as well as in children and adolescents. The consequences of sleep deprivation and daytime sleepiness are especially problematic to college students and can result in lower grade point averages, increased risk of academic failure, compromised learning, impaired mood, and increased risk of motor vehicle accidents.
There is a paucity of Indian studies assessing the level of awareness and knowledge among medical students and the quality of sleep in those with CVS. This study is an attempt to fill in this knowledge gap.
| Materials And Methods|| |
This cross-sectional, analytical study was conducted among I and II year MBBS students of a deemed to be university situated in an urban area. The ethical permission to conduct the study was obtained from the institutional ethical committee. Written informed consent was taken from all the individuals.
The study was conducted in 500 medical students (250 I year MBBS students and 250 II year MBBS students). Confidentiality of the information was maintained thoroughly by excluding names as identification in the questionnaire and keeping individual results secured. Since 9 students did not consent, 16 questionnaires were incomplete, and 12 were incorrectly filled, the final sample size was 463.
Initially, the students were asked to fill a pro forma designed to collect sociodemographic data (age, gender, ethnicity, year of MBBS, previous diagnosis of eye diseases, and family with history of eye diseases). Then, the students were given self-administered questionnaires to fill up.
Plan of the study is shown in [Figure 1].
Questionnaire 1 tested for awareness and knowledge: having heard of CVS was defined as “awareness” and having some understanding of CVS was defined as “knowledge.” For rating knowledge, score of 3 and below was taken as poor, score of 4–6 was taken as average, and score of 7 and above was taken as good. This questionnaire was given to all I and II MBBS students without applying any inclusion/exclusion criteria.
Questionnaire 2 tested whether the individual suffers from any symptoms suggestive of CVS or not. The study included only those students who actually used digital device (computer, tablet, smart phone) in the past 1 month. Of these, all those suffering from any eye diseases were excluded. Symptoms of CVS were adapted from a previous study and involved dry eyes, irritation, eye strain/fatigue, blurred vision, red eyes, burning eyes, excessive tear secretion, double vision, headache, light or glare sensitivity, contact lens discomfort, slowness in changing focus, changes in color perception, and neck, shoulder, and backache. Due to the absence of a definite diagnostic criterion for CVS, “presence of CVS” was defined as the presence of any one of the above symptoms experienced during or after prolonged digital device use during the past 1 month. The individuals had to indicate whether they experienced no symptoms, mild (transient symptoms for few minutes to hours), moderate (for few hours but and abates after rest or sleep), or severe (requires referral to a doctor) visual problems during or after using digital device.
Questionnaire 3 comprises of the Pittsburgh sleep quality index (PSQI) – a self-rated questionnaire assessing sleep quality over a 1-month time interval. It has been used in many settings, including research and clinical activities, and has been used in diagnosis of sleep disorders. PSQI studies seven components of sleep, the sum of which gives the global PSQI score ranging from 0 to 21, where lower scores denote a healthier sleep quality and higher scores indicate worse sleep quality. Individuals who get PSQI global score of 5 or less were classified as “good sleepers” and those who get > 5 as “poor sleepers.” The PSQI has internal consistency and reliability coefficient (Cronbach's alpha) of 0.83.
Statistical analysis of the data was done using the software SPSS version 20 (IBM, USA) after filling the data in excel sheet. Statistical tests used included Chi-square test, odds ratio, 95% confidence interval, and Mann–Whitney U-test.
| Results|| |
In our study, the mean (±standard deviation) age of the 463 individuals (1st and 2nd year medical students) was 19.55 (±1.04) years. Distribution of different demographic variables, knowledge about CVS, frequency of CVS, and sleep quality scores are given in [Table 1]. [Table 2] depicts the presence of CVS according to gender. Males showed higher prevalence of CVS – 80.22% as compared to females – 75.87%, although the difference was not statistically significant. Poor quality of sleep was seen in 75.49% of individuals with CVS as compared to 50.96% in individuals without CVS, and it is statistically significant (ODD'S ratio [95% confidence interval]: 0.338 [0.214–0.531]) [Table 3]. All the components of PSQI score have statistically significantly higher values in individuals with CVS as compared to those in individuals without CVS, except component 1 and 6 [Table 4]. About 34.1% of the medical students were aware of CVS (had heard of CVS) and 65.9% were not aware of CVS (had not heard of CVS) [Figure 2]. Moderate symptoms were present in 50.8%, mild in 24.8%, severe in 2.2%, and 22.2% medical students had no symptoms of CVS [Figure 3]. Spearman's rank correlation coefficient (Spearman's rho = 0.102, P = 0.028) showed that there is a weak positive but significant correlation between hours spent in front of computers with Global PSQI score [Figure 4].
|Table 3: Comparison of sleep quality in individuals with and without computer vision syndrome|
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|Table 4: Comparison of various components and total score of Pittsburg sleep quality index in individuals with and without computer vision syndrome|
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|Figure 2: Diagram representing the percentage of medical students aware and unaware of computer vision syndrome|
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|Figure 3: Diagram representing the severity of symptoms of computer vision syndrome in medical students|
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|Figure 4: Correlation between hours spent in front of computers and global Pittsburgh sleep quality index score|
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| Discussion|| |
The prevalence of CVS was found to be 77.5% (359/463) in the present study [Table 1]. Our finding is consistent with an earlier study that reported a prevalence rate of 78.6% in medical students and 81.9% in engineering students. Ranasinghe et al. and Reddy et al. found prevalence rate of 67.4% and 89.9% in their respective studies. It was also seen, in our study, that CVS was relatively more prevalent in males (80.22%) as compared to females (75.87), though statistically insignificant [Table 2]. Logaraj et al. found higher prevalence of dry eyes in males as compared to females. On the contrary, number of studies have found that CVS was more prevalent in females as compared to males.,,,, This was attributed to dry eye being more prevalent in females. Awareness of CVS among the participants in our study was found to be only 34.1%. The scores for knowledge regarding various aspects of CVS showed that only 23.54% medical students had poor knowledge, while 53.99% and 22.46% had average and good knowledge, respectively. This finding of our study concurs with an earlier study which found the awareness of CVS to be only 26.4% in students of faculty of medical sciences. In contrast, the majority of undergraduate students (87%) of medical, pharmacy, and nursing faculties were aware of the bad effects of prolonged use of computer on the eye. Although all Indian ophthalmologists were aware of CVS, they were confused regarding the treatment modalities for CVS.
CVS is still underdiagnosed, and there is a need to make people aware of the bad effects the prolonged use of gadgets has on eyesight. Ranasinghe et al. reported that ergonomics' practices and knowledge was associated significantly with increased risk of developing CVS, attributing this to higher knowledge among frequent computer users with higher daily computer usage than among infrequent computer users. They found that in those who had heard of the term “ergonomics,” only 44.6% implemented them at work place as 25.5% were not convinced about the impact of digital devices. This shows that the prevalent level of awareness and knowledge of CVS among students is insufficient, and there is less translation of knowledge into practice. If medical students are not aware and having the requisite knowledge, they would harm their own and others health as well, raising quite an alarming situation.
In the present study, majority of individuals with CVS had moderate symptoms (50.8%), 24.8% had mild symptoms, 2.2% had severe symptoms, while 22.2% had none. This indicates that the rest needed for the symptoms to subside would certainly cause interruptions in the work (studying in this case) performed leading to poor performance.
About 66.31% participants spent >2 h/day with various devices such as mobile, i-pad, laptop, and computer. In an earlier study, 94.4% individuals used computers for >2 h/day. Our study showed poor positive but significant correlation between hours spent in front of computers with global PSQI score [Figure 3]. A significant association of hours of usage and sleep indices has been observed. Quality of sleep in individuals with CVS is poorer as compared to that in individuals without CVS, and it is statistically significant (odd's ratio [95% confidence interval]: 0.338 [0.214–0.531]). Hence, CVS is associated with poor sleep quality. Overall, it was found that only 24.5% were good sleepers (PSQI global score of 5 or less), and 75.5% were “poor sleepers” (PSQI > 5), and this may be linked to the high prevalence of CVS in our study sample. It has been reported in various studies that sleep quality is affected by high usage of digital devices.,,,,,
All the components of PSQI score have statistically significant (P < 0.05) higher values in individuals with CVS as compared to those in individuals without CVS, except component 1 and 6 [Table 4]. This implies that sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, and daytime dysfunction are affected significantly with the usage of digital devices. Only use of sleep medications and subjective sleep quality showed no statistically significant difference in between the two groups. There can be various mechanisms underlying the poor sleep associated with electronic media use: Electronic media use may displace sleep due to its time-consuming nature. It may cause interference with sleep through increased psychophysiological arousal. Considering the reverse causality that some adolescents actively use media and technology as a sleeping aid, or to counteract boredom when not being able to sleep, the relationship between poor sleep and electronic media use tends to reflect a self-perpetuating cycle. Blue light emission of the screen of devices may affect sleep: light mediates the synchronization of mammalian circadian rhythms with environmental time by modulating retinal input to the circadian pacemaker – the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN contains neurons exhibiting a circadian pattern of activity and regulating melatonin secretion by the pineal gland in response to the environmental light/dark cycle. Melatonin hormone released in dim light conditions is involved in the physiological control of sleep. The intrinsically photosensitive retinal ganglion cells (ipRGCs) play a major role in nonimage-forming photoreception like regulating circadian photic entrainment. The release of melatonin from the pineal gland is controlled by a retinohypothalamic tract pathway originating from these ipRGCs containing melanopsin (having a peak sensitivity of approximately 482 nm, that is, longer wavelength blue-turquoise light). The bright light of a computer screen may suppress melatonin secretion and delay the onset of sleep.
Blue light emitted by digital devices has also been implicated as a cause of digital eye strain. In addition to the above proposed mechanisms, the role of electromagnetic fields emitted by mobile phones on sleep should also be taken into account. It has been reported that evening exposure to electromagnetic field influences sleep quality, attributing this to its probable modulatory effects on the circadian pacemaker; it may also result in altered cerebral blood flow and brain electrical activity. Exposure to mobile phone emissions at night time could have an effect on melatonin onset time. Electromagnetic field produced due to electrical appliances may play a significant role in influencing the circadian system, because a substantial number of studies demonstrated the changes in melatonin and cortisol secretion (two major markers of the circadian system) as well as in sleep after exposition to these fields. In addition, physical discomfort such as muscle pain and headaches can be caused due to long hours engaged in mobiles, laptops, etc., hampering sleep.
It has been shown that late-night smartphone usage reduced the amount and quality of sleep, increased fatigue the next morning and consequently, led to diminished work engagement the next day. Sleep deprivation affects mental, social, and physical health.,, Sleep being a significant biological mechanism regulating mood, students with disrupted sleep because of technology use may be more prone to experiencing markers of depression such as loss of energy, concentration problems, and daytime sleepiness. Poor sleep affects cognitive and learning abilities which in turn lowers academic performance.,
One of the limitations of the study was that this was a cross-sectional study; hence, it just presented a snapshot regarding CVS at one point in time without giving much idea about the causative factors. The symptoms were only self-reported, and there was no ophthalmic examination to make the diagnosis of CVS (especially when CVS is a diagnosis of exclusion today as almost everyone is working on computers).
| Conclusions|| |
There is low level of awareness and knowledge about CVS among medical students. There is need to translate knowledge into practice. CVS is significantly associated with poor sleep quality in medical students.
The level of awareness and knowledge of CVS among medical students can be increased by incorporation of the topic of CVS and related ergonomics in the 1st year MBBS itself by revision of medical syllabus. Sleep education programs should be held as there is a need to improve sleep hygiene (behavior improving quality and quantity of sleep).
Further investigation on the pathophysiological effects on exposure to electronic devices is warranted because the acute responses to the short-wavelength light emitted by them may be just the tip of iceberg and may have longer-term health effects than previously considered.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Parihar JK, Jain VK, Chaturvedi P, Kaushik J, Jain G, Parihar AK. Computer and visual display terminals (VDT) vision syndrome (CVDTS). Med J Armed Forces India 2016;72:270-6.
Payne KB, Wharrad H, Watts K. Smartphone and medical related app use among medical students and junior doctors in the United Kingdom (UK): A regional survey. BMC Med Inform Decis Mak 2012;12:121.
Al Rashidi SH, Alhumaidan H. Computer vision syndrome prevalence, knowledge and associated factors among Saudi Arabia University Students: Is it a serious problem?. Int J Health Sci (Qassim). 2017;11:17–9.
Gangamma MP, Poonam, Rajagopala M. A clinical study on “Computer vision syndrome” and its management with triphala eye drops and Saptamrita Lauha. Ayu 2010;31:236-9.
] [Full text]
Loh K, Redd S. Understanding and preventing computer vision syndrome. Malays Fam Physician 2008;3:128-30.
Cajochen C, Kräuchi K, Wirz-Justice A. Role of melatonin in the regulation of human circadian rhythms and sleep. J Neuroendocrinol 2003;15:432-7.
Stringham JM, Stringham NT, O'Brien KJ. Macular carotenoid supplementation improves visual performance, sleep quality, and adverse physical symptoms in those with high screen time exposure. Foods 2017;6. pii: E47.
Tosini G, Ferguson I, Tsubota K. Effects of blue light on the circadian system and eye physiology. Mol Vis 2016;22:61-72.
Figueiro MG, Wood B, Plitnick B, Rea MS. The impact of light from computer monitors on melatonin levels in college students. Neuro Endocrinol Lett 2011;32:158-63.
Chang AM, Aeschbach D, Duffy JF, Czeisler CA. Evening use of light-emitting eReaders negatively affects sleep, circadian timing, and next-morning alertness. Proc Natl Acad Sci U S A 2015;112:1232-7.
Cajochen C, Frey S, Anders D, Späti J, Bues M, Pross A, et al
. Evening exposure to a light-emitting diodes (LED)-backlit computer screen affects circadian physiology and cognitive performance. J Appl Physiol 2011;110:1432-8.
Chinoy ED, Duffy JF, Czeisler CA. Unrestricted evening use of light-emitting tablet computers delays self-selected bedtime and disrupts circadian timing and alertness. Physiol Rep 2018;6:e13692.
Münch M, Kobialka S, Steiner R, Oelhafen P, Wirz-Justice A, Cajochen C, et al
. Wavelength-dependent effects of evening light exposure on sleep architecture and sleep EEG power density in men. Am J Physiol Regul Integr Comp Physiol 2006;290:R1421-8.
Ayaki M, Hattori A, Maruyama Y, Nakano M, Yoshimura M, Kitazawa M, et al
. Protective effect of blue-light shield eyewear for adults against light pollution from self-luminous devices used at night. Chronobiol Int 2016;33:134-9.
van der Lely S, Frey S, Garbazza C, Wirz-Justice A, Jenni OG, Steiner R, et al
. Blue blocker glasses as a countermeasure for alerting effects of evening light-emitting diode screen exposure in male teenagers. J Adolesc Health 2015;56:113-9.
Huber R, Treyer V, Borbély AA, Schuderer J, Gottselig JM, Landolt HP, et al
. Electromagnetic fields, such as those from mobile phones, alter regional cerebral blood flow and sleep and waking EEG. J Sleep Res 2002;11:289-95.
Hennies N, Lambon Ralph MA, Kempkes M, Cousins JN, Lewis PA. Sleep spindle density predicts the effect of prior knowledge on memory consolidation. J Neurosci 2016;36:3799-810.
Brand S, Kirov R. Sleep and its importance in adolescence and in common adolescent somatic and psychiatric conditions. Int J Gen Med 2011;4:425-42.
Hershner SD, Chervin RD. Causes and consequences of sleepiness among college students. Nat Sci Sleep 2014;6:73-84.
Logaraj M, Madhupriya V, Hegde S. Computer vision syndrome and associated factors among medical and engineering students in Chennai. Ann Med Health Sci Res 2014;4:179-85.
] [Full text]
Buysse DJ, Reynolds CF 3rd
, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Res 1989;28:193-213.
Ranasinghe P, Wathurapatha WS, Perera YS, Lamabadusuriya DA, Kulatunga S, Jayawardana N, et al
. Computer vision syndrome among computer office workers in a developing country: An evaluation of prevalence and risk factors. BMC Res Notes 2016;9:150.
Reddy SC, Low CK, Lim YP, Low LL, Mardina F, Nursaleha MP, et al
. Computer vision syndrome: A study of knowledge and practices in university students. Nepal J Ophthalmol 2013;5:161-8.
Shantakumari N, Eldeeb R, Sreedharan J, Gopal K. Computer use and vision-related problems among university students in Ajman, United Arab Emirate. Ann Med Health Sci Res 2014;4:258-63.
] [Full text]
Mowatt L, Gordon C, Santosh AB, Jones T. Computer vision syndrome and ergonomic practices among undergraduate university students. Int J Clin Pract 2018;72:13035.
Xu L, You QS, Wang YX, Jonas JB. Associations between gender, ocular parameters and diseases: The Beijing eye study. Ophthalmic Res 2011;45:197-203.
Toomingas A, Hagberg M, Heiden M, Richter H, Westergren KE, Tornqvist EW. Risk factors, incidence and persistence of symptoms from the eyes among professional computer users. Work 2014;47:291-301.
Sheppard AL, Wolffsohn JS. Digital eye strain: Prevalence, measurement and amelioration. BMJ Open Ophthalmol 2018;3:e000146.
Bali J, Navin N, Thakur BR. Computer vision syndrome: A study of the knowledge, attitudes and practices in Indian ophthalmologists. Indian J Ophthalmol 2007;55:289-94.
] [Full text]
Bogdănici CM, Săndulache DE, Nechita CA. Eyesight quality and computer vision syndrome. Rom J Ophthalmol 2017;61:112-6.
Yogesh S, Abha S, Priyanka S. Mobile usage and sleep patterns among medical students. Indian J Physiol Pharmacol 2014;58:100-3.
Demirci K, Akgönül M, Akpinar A. Relationship of smartphone use severity with sleep quality, depression, and anxiety in university students. J Behav Addict 2015;4:85-92.
Mohammadbeigi A, Absari R, Valizadeh F, Saadati M, Sharifimoghadam S, Ahmadi A, et al
. Sleep quality in medical students; the impact of over-use of mobile cell-phone and social networks. J Res Health Sci 2016;16:46-50.
Exelmans L, Van den Bulck J. Bedtime mobile phone use and sleep in adults. Soc Sci Med 2016;148:93-101.
Xie X, Dong Y, Wang J. Sleep quality as a mediator of problematic smartphone use and clinical health symptoms. J Behav Addict 2018;7:466-72.
Cain N, Gradisar M. Electronic media use and sleep in school-aged children and adolescents: A review. Sleep Med 2010;11:735-42.
Hysing M, Pallesen S, Stormark KM, Jakobsen R, Lundervold AJ, Sivertsen B. Sleep and use of electronic devices in adolescence: Results from a large population-based study. BMJ Open 2015;5:e006748.
Berson DM, Dunn FA, Takao M. Phototransduction by retinal ganglion cells that set the circadian clock. Science 2002;295:1070-3.
Benarroch EE. Suprachiasmatic nucleus and melatonin: Reciprocal interactions and clinical correlations. Neurology 2008;71:594-8.
Gooley JJ, Lu J, Chou TC, Scammell TE, Saper CB. Melanopsin in cells of origin of the retinohypothalamic tract. Nat Neurosci 2001;4:1165.
Higuchi S, Motohashi Y, Liu Y, Ahara M, Kaneko Y. Effects of VDT tasks with a bright display at night on melatonin, core temperature, heart rate, and sleepiness. J Appl Physiol 2003;94:1773-6.
Wood AW, Loughran SP, Stough C. Does evening exposure to mobile phone radiation affect subsequent melatonin production? Int J Radiat Biol 2006;82:69-76.
Lewczuk B, Redlarski G, Zak A, Ziółkowska N, Przybylska-Gornowicz B, Krawczuk M. Influence of electric, magnetic, and electromagnetic fields on the circadian system: Current stage of knowledge. Biomed Res Int 2014;2014:169459.
Thomée S, Härenstam A, Hagberg M. Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults – A prospective cohort study. BMC Public Health 2011;11:66.
Lanaj K, Johnson RE, Barnes CM. Beginning the workday yet already depleted? Consequences of late-night smartphone use and sleep. Organ Behav Hum Decis Process 2014;124:11-23.
Touitou Y, Touitou D, Reinberg A. Disruption of adolescents' circadian clock: The vicious circle of media use, exposure to light at night, sleep loss and risk behaviors. J Physiol Paris 2016;110:467-79.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]