EHT has compiled a short list of citations on the health impact of screens on children’s health, sleep, education and more.

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Health Impacts of Screens

Gadi Lissak. “Adverse physiological and psychological effects of screen time on children and adolescents: Literature review and case study.” Environmental Research, Volume 164, 2018, Pages 149-157, ISSN 0013-9351.

 

• Concerns about the potential vulnerability of children to radio-frequency electromagnetic radiation (RF-EMR) fields is increasing as children’s exposure to wireless devices is on the rise. Children are considered potentially more vulnerable to RF-EMR fields because of the susceptibility of their developing nervous system. Additionally, their brain tissue is more conductive, consequently allowing more RF-EMR penetration relative to the size of their head. Moreover, they will be exposed to RF fields for more years than adults (Kheifets et al., 2005). For years researchers believed that non-heating RF-EMR radiation could not cause harm. Evidence which links RF radiation to cancer were published by the National Toxicology Program (NTP) of the U.S. National Institute of Health, which released partial findings from its cell phone study on rats.”
• Infertility is a prevalent disorder that affects, in the US about 7% of men and 11% of women (National Institute of Health, 2017). Experimental animal and humans studies explored the effects of RF-EMR on the male reproductive function. RF-EMR was found to affect various organs, including the testes, directly or through a thermal effect, e.g., when a cell phone is carried in the trouser pocket near the testes (Yildirim et al., 2015). With emerging data of a decline in male semen quality, mobile phones were examined as a possible contributing factor. Results of these studies show that exposure to RF-EMR through cellular phone use or through use of laptops or tablets is related to carcinogenic risk and reproductive damage (Adams et al., 2014; Yildirim et al.; Sepehrimanesh et al., 2017; La Vignera et al., 2012).”
• Abstract: A growing body of literature is associating excessive and addictive use of digital media with physical, psychological, social and neurological adverse consequences. Research is focusing more on mobile devices use, and studies suggest that duration, content, after-dark-use, media type and the number of devices are key components determining screen time effects. Physical health effects: excessive screen time is associated with poor sleep and risk factors for cardiovascular diseases such as high blood pressure, obesity, low HDL cholesterol, poor stress regulation (high sympathetic arousal and cortisol dysregulation), and Insulin Resistance. Other physical health consequences include impaired vision and reduced bone density. Psychological effects: internalizing and externalizing behavior is related to poor sleep. Depressive symptoms and suicidal are associated to screen time induced poor sleep, digital device night use, and mobile phone dependency. ADHD-related behavior was linked to sleep problems, overall screen time, and violent and fast-paced content which activates dopamine and the reward pathways. Early and prolonged exposure to violent content is also linked to risk for antisocial behavior and decreased prosocial behavior. Psychoneurological effects: addictive screen time use decreases social coping and involves craving behavior which resembles substance dependence behavior. Brain structural changes related to cognitive control and emotional regulation are associated with digital media addictive behavior. A case study of a treatment of an ADHD diagnosed 9-year-old boy suggests screen time induced ADHD-related behavior could be inaccurately diagnosed as ADHD. Screen time reduction is effective in decreasing ADHD-related behavior.

  Conclusions:  Components crucial for psychophysiological resilience are none-wandering mind (typical of ADHDrelated behavior), good social coping and attachment, and good physical health. Excessive digital media use by children and adolescents appears as a major factor which may hamper the formation of sound psychophysiological resilience.

Garrett C. Hisler, Brant P. Hasler, Peter L. Franzen, Duncan B. Clark, Jean M. Twenge, Screen media use and sleep disturbance symptom severity in children, Sleep Health, Volume 6, Issue 6, 2020, Pages 731-742, ISSN 2352-7218, https://doi.org/10.1016/j.sleh.2020.07.002.
(http://www.sciencedirect.com/science/article/pii/S2352721820301935)

• This study examined associations of different types of screen media with symptom severity of different classes of sleep-wake disturbances. Results: Greater screen media use, TV, video, and video game use, was associated with decreased sleep duration, increased sleep onset latency as well as greater excessive sleepiness, insomnia, and overall sleep disturbance symptom severity. Use of these screen medias were also associated with clinically relevant sleep problems. Ethnoracial differences emerged in screen use and sleep, but did not moderate the association between screen use and sleep.
• Conclusions: Greater use of screen medias was not just associated with longer sleep onset latency and shorter sleep duration, but also increased severity of multiple types of sleep-wake disturbances. Future research should use longitudinal designs to determine the direction of these associations in adolescent populations. 

Stiglic N, Viner RM. “Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews.” BMJ Open 2019; 9:e023191. doi:10.1136/ bmjopen-2018-023191

 

Boers, Elroy, Mohammad H Afzali, Nicola Newton, and Patricia Conrod. 2019. “Association of Screen Time and Depression in Adolescence.” JAMA Pediatrics 173(9): 853–59. https://doi.org/10.1001/jamapediatrics.2019.1759.

 

Hutton, John S et al. 2019. “Associations Between Screen-Based Media Use and Brain White Matter Integrity in  Preschool-Aged Children.” JAMA pediatrics 174(1): e193869.

 

Madigan, Sheri et al. 2019. “Association Between Screen Time and Children’s Performance on a Developmental Screening Test.” JAMA Pediatrics 173(3): 244–50. 

Buabbas, A.J., Al-Mass, M.A., Al-Tawari, B.A. et al. The detrimental impacts of smart technology device overuse among school students in Kuwait: a cross-sectional survey. BMC Pediatr 20, 524 (2020). https://doi.org/10.1186/s12887-020-02417-x

• “The overuse of ST devices per day and per session by school-aged children has the potential to have a detrimental impact on their health, as has been noticed among students in Kuwait.”

Tamana SK, Ezeugwu V, Chikuma J, Lefebvre DL, Azad MB, Moraes TJ, et al. (2019) Screen-time is associated with inattention problems in preschoolers: Results from the CHILD birth cohort study. PLoS ONE 14(4): e0213995.

 

Stiglic N, Viner RM, Effects of screentime on the health and well-being of children and adolescents: a systematic review of reviews BMJ Open 2019;9:e023191. doi: 10.1136/bmjopen-2018-023191

 

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Smartphones and Sleep

 

Carter, Ben et al. 2016. “Association Between Portable Screen-Based Media Device Access or Use and Sleep Outcomes: A Systematic Review and Meta-Analysis.” JAMA Pediatrics 170(12): 1202–8. 

 

“Schoeni A, Roser K, Röösli M. Symptoms and cognitive functions in adolescents in relation to mobile phone use during night. PLoS One. 2015 Jul 29;10(7):e0133528. doi: 

 

Moreno, Megan A. 2016. “Media Use and Sleep.” JAMA Pediatrics 170(12): 1236. 

 

Madigan, Sheri et al. 2019. “Association Between Screen Time and Children’s Performance on a Developmental Screening Test.” JAMA Pediatrics 173(3): 244–50. 

 

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Health Effects from Wireless and Cell Phone Radiation 

 

Bandara, Priyanka, and David O Carpenter. “Planetary Electromagnetic Pollution: It Is Time to Assess Its Impact.” The Lancet Planetary Health 2, no. 12 (December 1, 2018): e512–14.

 

Pall M. “Wi-Fi is an important threat to human health.” Environmental Research, Volume 164, July 2018, Pages 405-416.

 

Foerster M., Thielens A., Joseph W., Eeftens M., Röösli M. (2018) “A prospective cohort study of adolescents’ memory performance and individual brain dose of microwave radiation from wireless communication.” Environmental Health Perspectives.   

 

Anthony B. Miller, L. Lloyd Morgan, Iris Udasin, Devra Lee Davis. “Cancer epidemiology update, following the 2011 IARC evaluation of radiofrequency electromagnetic fields (Monograph 102).” Environmental Research, Volume 167, 2018, Pages 673-683, ISSN 0013-9351.

 

 IARC Working Group on the Evaluation of Carcinogenic Risks to Humans. “IARC monographs on the evaluation of carcinogenic risks to humans. Non-Ionizing Radiation, Part 2: Radiofrequency Electromagnetic Fields.” IARC Monographs on the Evaluation of Carcinogenic Risks to Humans/World Health Organization, International Agency for Research on Cancer vol. 102, 2013.

 

Sangün Ö, Dündar B, Çömlekçi S, Büyükgebiz A. The effects of electromagnetic field on the endocrine system in children and adolescents. Pediatr Endocrinol Rev. 2015 Dec;13(2):531-45.

 

Oni, M.O., D.B. Amuda and C.E. Gilbert. “Effects of radiofrequency radiation from WiFi devices on human ejaculated semen.” International Journal of Recent Research and Applied Studies, vol. 9, no. 2, 2011, pp. 292-4.

 

Farah Hanan Fathihah Jaffar, Khairul Osman, Nur Hilwani Ismail, Kok-Yong Chin, Siti Fatimah Ibrahim, Adverse Effects of Wi-Fi Radiation on Male Reproductive System: A Systematic Review, The Tohoku Journal of Experimental Medicine, 2019, Volume 248, Issue 3, Pages 169-179, Released July 26, 2019

 

Papageorgio, C.C., et al. “Effects of Wi-Fi signals on the p300 component of event-related potentials during an auditory hayling task.” Journal of Integrative Neuroscience, vol. 10, no. 2, 2011, pp. 189-202.

 

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Children More Vulnerable to Wireless Radiation 

 

Fernández, C., A.A. de Salles, M.E. Sears, R.D. Morris, D.L. Davis. “Absorption of wireless radiation in the child versus adult brain and eye from cell phone conversation or virtual reality.” Environmental Research, 2018, ISSN 0013-9351.

 

Gandhi, O. P. (2019). “Microwave Emissions From Cell Phones Exceed Safety Limits in Europe and the US When Touching the Body.” IEEE Access, 7, 47050-47052. 

 

Fernandez-Rodriguez, C.E., A.A.A. De Salles and Devra Lee Davis. “Dosimetric Simulations of Brain Absorption of Mobile Phone Radiation–The Relationship Between psSAR and Age.”  IEEE Access 3 (2015): 2425-2430.

 

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Paper, Pen, Notebooks and Real Books Are Superior To Electronic Media

Moreno, Megan A. 2016. “Media Use and Sleep.” JAMA Pediatrics 170(12): 1236. https://doi.org/10.1001/jamapediatrics.2015.2575.

 

Munzer, Tiffany G et al. 2019. “Parent-Toddler Social Reciprocity During Reading From Electronic Tablets vs Print Books.” JAMA Pediatrics 173(11): 1076–83. https://doi.org/10.1001/jamapediatrics.2019.3480.

 

Madigan, Sheri et al. 2019. “Association Between Screen Time and Children’s Performance on a Developmental Screening Test.” JAMA Pediatrics 173(3): 244–50. https://doi.org/10.1001/jamapediatrics.2018.5056.

 

Bouygues, H. (2020). Does Educational Technology Help Students Learn | REBOOT FOUNDATION. Reboot-foundation.org. Retrieved 6 April 2020, from https://reboot-foundation.org/does-educational-technology-help-students-learn/.

Students, Computers and Learning: Making the Connection. 2015. Organisation for Economic Co-operation and Development 

 

Wood, Eileen et al. 2012. “Examining the Impact of Off-Task Multi-Tasking with Technology on Real-Time Classroom Learning.” Computers & Education 58(1): 365–74. https://www.sciencedirect.com/science/article/abs/pii/S0360131511002077 (April 6, 2020).

 

Mueller, Pam A, and Daniel M Oppenheimer. 2014. “The Pen Is Mightier than the Keyboard: Advantages of Longhand over Laptop Note Taking.” Psychological science 25(6): 1159–68.

 

May, C. (2020). A Learning Secret: Don’t Take Notes with a Laptop. Scientific American. Retrieved 6 April 2020, from 

 

Fried, Carrie B. 2008. “In-Class Laptop Use and Its Effects on Student Learning.” Computers & Education 50(3): 906–14. 

 

Sovern, Jeff, Law Student Laptop Use During Class for Non-Class Purposes: Temptation v. Incentives (April 7, 2011). 51 University of Louisville Law Review 483 (2013); St. John’s Legal Studies Research Paper No. 11-004. 

Junco, Reynol, and Shelia R. Cotten. 2012. “No A 4 U: The Relationship between Multitasking and Academic Performance.” Computers & Education 59(2): 505–14. 

 

Ravizza, Susan M, Mitchell G Uitvlugt, and Kimberly M Fenn. 2016. “Logged In and Zoned Out: How Laptop Internet Use Relates to Classroom Learning.” Psychological Science 28(2): 171–80.

 

Faria Sana, Tina Weston, Nicholas J. Cepeda, Laptop multitasking hinders classroom learning for both users and nearby peers, Computers & Education, Volume 62, 2013, Pages 24-31 

Smartphones and Addiction

Ying Li, Guangxiao Li, Li Liu, Hui Wu. Correlations between mobile phone addiction and anxiety, depression, impulsivity, and poor sleep quality among college students: A systematic review and meta-analysis. J Behav Addict. 2020 Sep 8. doi: 10.1556/2006.2020.00057.

• The current meta-analysis provided solid evidence that MPA was positively correlated with anxiety, depression, impulsivity, and sleep quality. This indicated that college students with MPA were more likely to develop high levels of anxiety, depression, and impulsivity and suffer from poor sleep quality. More studies, especially large prospective studies, are warranted to verify our findings.

Carbonell X, Chamarro A, Oberst U, Rodrigo B, Prades M. Problematic Use of the Internet and Smartphones in University Students: 2006-2017. Intl J Environ Research Publ Health. 15(3). Article 475. Mar 2018.

• The perception of problematic Internet and mobile phone use has increased over the last decade, social networks are considered responsible for this increase, and females are perceived to be more affected than males. The current study shows how strong smartphone and Internet addiction and social media overlap. Participants from 2017 report higher negative consequences of both Internet and mobile phone use than those from 2006, but long-term observations show a decrease in problematic use after a sharp increase in 2013. We conclude that the diagnosis of technological addictions is influenced by both time and social and culture changes.

O’Donnell S, Epstein LH. Smartphones are more reinforcing than food for students. Addict Behav. 2018 Oct 18;90:124-133. doi: 10.1016/j.addbeh.2018.10.018. 

Abstract: College students engage in high-frequency smartphone use, despite potential negative consequences. One way to conceptualize this behavior is to consider it a highly reinforcing activity. Comparing motivation for smartphones to a powerful primary reinforcer, such as food, can establish their relative reinforcing value. This study investigated whether smartphones were more reinforcing than food, as well as the relationships between smartphone reinforcement, texting use, and smartphone motives. Participants were 76 college students (50% female, M_age = 18.9, SD = 0.99) who had no access to food for three hours and to their smartphones for two hours. After this modest deprivation period, participants worked for time to use their smartphones and 100-cal portions of their favorite snack food concurrently, with the work to obtain portions of both commodities increasing. The amount of smartphone use earned during the task was manipulated across groups (20, 30, 60, 120 s) to establish what amount of smartphone use was needed to motivate responding. Additionally, reinforcing efficacy of smartphones and food using a hypothetical purchase task and motivations for smartphone use was collected. Smartphones were more reinforcing than food using either measurement methodology (p’s < 0.001). Smartphone reinforcement predicted number of text messages, controlling for age, sex, and family income. Positive smartphone use motives were associated with reinforcing efficacy of smartphones. These data show that smartphones are potent reinforcers, and are more reinforcing than food given modest food deprivation. These methods provide one important reason why people may use smartphones.

Excerpt

College students share a perception that smartphone ownership is beneficial; however smartphone use has been linked to increased anxiety (Jenaro, Flores, Gómez-Vela, González-Gil, & Caballo, 2007), social dysfunction (Jenaro et al., 2007) insomnia (Jenaro et al., 2007), low self-esteem (Bianchi & Phillips, 2005; Smetaniuk, 2014), emotional instability (Roberts, Pullig, & Manolis, 2015; Smetaniuk, 2014) and depression (Ezoe et al., 2009; Smetaniuk, 2014). Temporarily removing cell phones from high frequency cell phone users increased self-reported anxiety over a 75 min time period in comparison to less frequent users (Cheever et al., 2014). Despite the negative outcomes associated with problematic smartphone use, college students are highly motivated to use their smartphones.