Skip to main content
Dialogues in Clinical Neuroscience logoLink to Dialogues in Clinical Neuroscience
. 2020 Jun;22(2):179–187. doi: 10.31887/DCNS.2020.22.2/gsmall

Brain health consequences of digital technology use


Consecuencias para la salud del cerebro del empleo de la tecnología digital

Conséquences sur la santé cérébrale de l’usage des technologies numériques

Gary W Small 1, Jooyeon Lee 2, Aaron Kaufman 3, Jason Jalil 4, Prabha Siddarth 5, Himaja Gaddipati 6, Teena D Moody 7, Susan Y Bookheimer 8
PMCID: PMC7366948  PMID: 32699518

Abstract

Emerging scientific evidence indicates that frequent digital technology use has a significant impact—both negative and positive—on brain function and behavior. Potential harmful effects of extensive screen time and technology use include heightened attention-deficit symptoms, impaired emotional and social intelligence, technology addiction, social isolation, impaired brain development, and disrupted sleep. However, various apps, videogames, and other online tools may benefit brain health. Functional imaging scans show that internet-naive older adults who learn to search online show significant increases in brain neural activity during simulated internet searches. Certain computer programs and videogames may improve memory, multitasking skills, fluid intelligence, and other cognitive abilities. Some apps and digital tools offer mental health interventions providing self-management, monitoring, skills training, and other interventions that may improve mood and behavior. Additional research on the positive and negative brain health effects of technology is needed to elucidate mechanisms and underlying causal relationships.


Keywords: emotional intelligence, digital technology, internet, media, neural activation, online searching

Introduction


During the past three decades, digital technology has transformed our daily lives. People at every age are now taking advantage of the vast amounts of available online information and communication platforms that connect them with others. This technology helps us to generate, store, and process enormous amounts of information and interact with each other rapidly and efficiently.


Most adults use the internet daily, and nearly one out of four report being online most of the time.1 Because of this transformation to an online world, neuroscientists have begun focusing their attention on how digital technology may be changing our brains and behavior. The emerging data suggest that constant technology use impacts brain function and behavior in both positive and negative ways. For example, older individuals suffering from cognitive decline could use the internet to access information to help them remain independent longer; however, many seniors with cognitive complaints are reluctant or unable to adopt new technologies.2 Our group’s functional magnetic resonance imaging (MRI) research tracking neural activity during simulated internet searches suggests that simply searching online may represent a form of mental exercise that can strengthen neural circuits.3 By contrast, the persistent multitasking that is characteristic of most technology users impairs cognitive performance.4 In this review, we highlight some of the research suggesting potential benefits and possible risks of using digital technology.


Potential harmful effects of digital technology use


Reduced attention


Multiple studies have drawn a link between computer use or extensive screen time (eg, watching television, playing videogames) and symptoms of attention-deficit hyperactivity disorder (ADHD). A 2014 meta-analysis indicated a correlation between media use and attention problems.5 A recent survey of adolescents without symptoms of ADHD at the start of the study indicated a significant association between more frequent use of digital media and symptoms of ADHD after 24 months of follow-up.6 Although most of the research linking technology use and ADHD symptoms has involved children and adolescents, this association has been identified in people at any age.7

The reason for the link between technology use and attention problems is uncertain, but might be attributed to repetitive attentional shifts and multitasking, which can impair executive functioning.8 Moreover, when people are constantly using their technology, they have fewer opportunities to interact offline and allow their brain to rest in its default mode.9

Impaired emotional and social intelligence


Because of concern that a young, developing brain may be particularly sensitive to chronic exposure to computers, smartphones, tablets, or televisions, the American Academy of Pediatrics has recommended that parents limit screen time for children aged 2 years or younger, when the brain is particularly malleable.10 Spending extensive periods of time with digital media translates to spending less time communicating face to face.11

Kirsh and Mounts12 explored the hypothesis that playing videogames would interfere with the ability to recognize emotions conveyed through facial expressions. They examined the effects of playing videogames on recognition of facial expressions of emotions in 197 students (ages 17 to 23 years). Participants played violent videogames before watching a series of calm faces morph into either angry or happy faces. Participants were asked to quickly identify the emotion while the facial expression changed. The authors found that happy faces were identified faster than angry faces, and that playing violent videogames delayed happy-face recognition time. 


Our team at the University of California, Los Angeles (UCLA)13 hypothesized that preteens restricted from screen-based media would have more opportunities for face-to-face interactions, which would improve their ability to recognize nonverbal emotional and social cues. We studied 51 schoolchildren who spent five days at an overnight nature camp where television, computers, and smartphones were forbidden, and compared them with 54 school-based matched controls who continued their usual media practices (4 hours of screen time per day). At baseline and after 5 days, participants were assessed for their ability to recognize emotions from photographs of facial expressions and videotaped scenes of social interactions (without verbal cues). After 5 days, the nature camp participants restricted from screen time demonstrated significantly better recognition of nonverbal emotional and social cues than participants who continued their usual daily screen time. These findings suggest that time away from screen-based media and digital communication tools improves both emotional and social intelligence.


Technology addiction


Although not formally included in the Diagnostic and Statistical Manual of Mental Disorders ,14 excessive and pathological internet use has been recognized as an internet addiction, which shares features with substance-use disorders or pathological gambling. Common features include preoccupations, mood changes, development of tolerance, withdrawal, and functional impairment.15 ,16 The global prevalence of internet addiction is estimated at 6%, but in some regions such as the Middle East the prevalence is as high as 11%.17 Students with internet addiction are more likely to suffer from ADHD symptoms than from other psychiatric disorders.18 You and colleagues16 reported that schoolchildren with internet addiction experienced significantly greater symptoms of inattention, hyperactivity, and impulsivity than non–internet-addicted students. Panagiotidi and Overton19 reported greater ADHD symptoms in adults aged 18 to 70 years with internet addiction: predictors of addiction included younger age, playing massively multiplayer online role-playing games, and spending more time online. Despite consistent associations between ADHD symptoms and internet addiction, a causal relationship has not been confirmed. It is possible that people with ADHD symptoms have a greater risk for developing technology addiction, but an alternative explanation is that extensive technology use from addictive behavior causes ADHD symptoms.


Social isolation


Ninety percent of young adults in the United States use social media platforms such as Facebook, Twitter, Snapchat, and Instagram, and most visit these sites at least daily.20 Paradoxically, social media use is linked to social isolation (ie, a lack of social connections and quality relationships with others),21 which is associated with poor health outcomes and increased mortality.1

Primack and colleagues20 studied 1787 young adults (ages 19 to 32 years) and found that using social media 2 or more hours each day dou-
bled the odds for perceived social isolation compared with use less than 30 minutes each day. Similar associations between perceived social isolation and social media use were observed in 213 middle-aged and older adults.22 Possible explanations for such findings include reduced offline social experiences and the tendency to make upward social comparisons based on highly curated social media feeds that produce unrealistic expectations of oneself.1 Future research should explore casual explanations for such relationships and seek ways to address the needs of people who may benefit from social media–based interventions, such as geographically isolated individuals.


Adverse impact on cognitive and brain development


Screen time may also adversely impact cognitive and brain development. In a recent review, children under age 2 were reported to spend over 1 hour each day in front of a screen; by age 3, that number exceeded 3 hours.23 Increased screen time (and less reading time) has been associated with poorer language development and executive functioning, particularly in very young children,24 as well as poorer language development in a large cohort of minority children.25 In infants, increased screen time was one of several factors that predicted behavioral problems.26 For infants 6 to 12 months, increased screen time was linked to poorer early language development.27 In children of preschool age and older, digital media directed toward active learning can be educational, but only when accompanied by parental interaction.23

Recent research has examined the effects of media exposure on brain development. In a study of children aged 8 to 12 years, more screen and less reading time were associated with decreased brain connectivity between regions controlling word recognition and both language and cognitive control.24 Such connections are considered important for reading comprehension and suggest a negative impact of screen time on the developing brain. Structurally, increased screen time relates to decreased integrity of white-matter pathways necessary for reading and language.28 Given the growing prominence of screen use among even very young children at stages when brain plasticity is greatest, there is significant concern about the cognitive and brain development of the current generation of screen-exposed children that requires greater understanding


Sleep


Recent studies indicate that screen exposure disrupts sleep, which can have a negative effect on cognition and behavior. Daily touch-screen use among infants and toddlers was shown to negatively impact sleep onset, sleep duration, and nighttime awakenings.29 In adolescents, more time using smartphones and touch screens was associated with greater sleep disturbances, and tablet time was associated with poor sleep quality and increased awakenings after sleep onset.30 In adults, increased smartphone use was associated with shorter sleep duration and less efficient sleep.31 Poor sleep quality is associated with brain changes, such as reduced functional connectivity and decreased gray-matter volume, as well as an increased risk for age-associated cognitive impairment and Alzheimer disease.32,33

It is unclear whether the act of looking at screens or media content disrupts sleep; however, it is well-known that the wavelength of light exposure affects the circadian rhythms that govern sleep. Computer and phone light-emitting diode (LED) screens emit slow wave, blue light that interferes with circadian rhythms. Exposure to LED versus non-LED screens has been shown to produce changes in melatonin levels and sleep quality, and such exposure decreases cognitive performance.34 Thus, it is important to recognize the effects of screen time on sleep as a moderator of various negative effects on cognition and brain function.


Brain-health benefits of digital technology


Despite these potential harmful brain-health effects of digital technology, emerging evidence points to several benefits for the aging brain in particular, including opportunities for brain-strengthening neural exercise, cognitive training, and the online delivery of mental-health interventions and support ( Table I

Table I. Health-promoting digital technology strategies for the aging brain.

Strategies Brain-Health Promoting Targets
Online searching Neural activation of circuits controlling decision-making and complex reasoning
Cognitive training games Global cognition, memory (immediate, delayed, and working), 
attention, learning abilities
Racecar videogames with distracting road signs Multitasking skills
N-back task training games Working memory, fluid intelligence
Action videogames Visual attention, reaction time, task-switching abilities
Monitoring apps Heart rate, breathing patterns
Psychotherapy, educational apps Mood, sleep, social support

Neural exercise


Internet-savvy versus internet-naive adults


Functional neuroimaging allows scientists to observe regional neural activity during various mental tasks. Our group was the first to explore neural activity using functional MRI while research volunteers performed simulated internet searching.3 Previous studies suggested that mentally challenging tasks, such as searching online, may benefit brain health and even delay cognitive decline.35,36 We focused on internet searching because it is so common among people of all ages.37

We assessed patterns of brain neural activation in 24 cognitively normal middle-aged and older adults (ages 55 to 76 years): 12 of them had minimal internet search experience (net-naive group), and 12 had extensive experience (net-savvy group). In addition to the internet-search task, we used a control task of reading text on a computer screen formatted to simulate a printed book layout.


We found that text reading activated brain regions controlling language, reading, memory, and visual abilities (left inferior frontal, temporal, posterior cingulate, parietal, and occipital regions), and the magnitude and extent of activation were similar in the net-naive and net-savvy groups. During internet searching, net-naive subjects displayed activation patterns similar to those observed while reading text. However, net-savvy subjects demonstrated significant activity in neural signal intensity in additional regions controlling decision-making, complex reasoning, and vision (frontal pole, anterior temporal region, anterior and posterior cingulate, and hippocampus). During the internet-search task, the net-savvy group displayed a more than twofold increase in the extent of activation in the major regional clusters compared with the net-naive group (21 782 versus 8646 total activated voxels).


These findings suggest that searching online may be a form of brain neural exercise. Other research indicates that after several months, daily computer-game playing leads to reduced cortical neural activity.38 Our other research indicates that memory training, along with healthy lifestyle behaviors (eg, physical exercise, healthy diet), leads to reduced dorsal prefrontal cortical metabolism after 2 weeks.36 Such findings suggest that task repetition over time leads to lower neural activity during the task, which could reflect greater cognitive efficiency after mental training.


One model that could explain such findings is that novel and stimulating mental experiences, such as searching on the internet, initially lead to minimal activation before the internet user discovers strategies for solving the unfamiliar mental challenge. After such insights, a broader neural network is engaged. After repeated sessions, the initially novel mental task becomes routine and repetitive, no longer posing a mental challenge. The lower activity observed may thus reflect a more efficient neural response. These results also suggest that previous internet-search experience may alter the brain’s responsiveness in neural circuits controlling decision-making and complex reasoning. The net-savvy volunteers showed increased activation during the internet-search task, which suggests that internet searching may remain a novel and mentally stimulating process even after continued practice.


Internet training and brain function


We also used functional MRI to record brain neural activity during simulated internet-search tasks in 12 net-naive and 12 net-savvy subjects before and after internet training.39 Based on our previous findings, we hypothesized that net-naive volunteers would recruit a larger frontal lobe network after internet training and that net-savvy volunteers would show either no increase or a decrease in activation after training because of greater cognitive efficiency due to training.


The training consisted of brief instructions on how to search online along with practice sessions (1 hour per day for a week). To increase motivation, participants were told that they would be quizzed on their knowledge of assigned search topics after the experiment.


During their first session, net-naive subjects recruited a neural network that included the superior, middle, and inferior frontal gyri, as well as the lateral occipital cortex and occipital pole. During the second session (after internet training), additional regions in the middle and inferior frontal gyri were recruited only in the net-naive group. By contrast, during their first scan session, the net-savvy subjects recruited a cortical network that, though overlapping with that of the net-naive subjects, showed more extensive regions of activation ( Figures 1 and 2 ). This cortical network included regions that control mental activities supporting tasks required for internet searches, including decision-making, working memory, and the ability to suppress nonrelevant information. Moreover, net-savvy participants showed a pattern of activation that was reduced after the training. This reduction is consistent with our hypothesis that the brain becomes more efficient and possibly habituates to the internet task over time. Overall, these findings suggest that internet searching for relatively short periods of time can change brain-activity patterns in middle-aged and older adults.


Other groups have explored the effects of internet-search training on brain structure and function. Dong and associates40 studied the influence of short-term internet-search training on white-matter microstructure via diffusion tensor imaging. After 6 training days, they found that the 59 participants (mean age 21 years) showed increased fractional anisotropy (diffusion tensor imaging scans) in the right superior longitudinal fasciculus and within that region, decreased radial diffusivity. These findings suggest that short-term internet-search training may increase white-matter integrity in the right superior longitudinal fasciculus, which could result from increased myelination. 


Figure 1. Internet-searching task activations before and after training in internet-naive and internet-savvy subjects. Areas of activation are indicated in blue for baseline and in red for patterns after training.

Figure 1.

Figure 2. Overlay of pre-training and post-training scanning sessions. Transaxial (left images) and coronal (right) views for pre-training (blue) and post-training (red) sessions showing increase in frontal activity (arrows) after training in the internet-naive group.

Figure 2.

Shapira and colleagues41 assessed the psychological effects of learning computer and internet-search methods. They offered a course to 22 older adults (mean age 80 years), who were compared with 26 participants engaged in other activities. The investigators reported significant improvements in the intervention group in measures of life satisfaction, depression, loneliness, and self-control after 4 months, whereas the control group showed declines in each of these measures. These findings suggest that computer and internet training contribute to older adults’ well-being and sense of empowerment.


White and associates42 performed a randomized controlled trial assessing the psychosocial impact of internet access to older adults during a 5-month period. The intervention group (n=29) received 9 hours of training (6 sessions over 2 weeks) and experienced less loneliness, less depression, and more positive attitudes toward computers than controls (n=19) who were not regular internet users.


Cognitive training


Memory ability


Findings showing that mental stimulation and cognitive training improve memory in older adults43,44 have led to the development of several memory apps and computer games. Miller and associates45 explored whether computerized brain-training exercises (Dakim Brain Fitness) improved cognitive performance in older adults without dementia (mean age of 82 years). Subjects were randomized into an intervention group (n=36) that used a computer program 5 days a week for 20 to 25 minutes each day, or a wait-list control group (n=33). Neuropsychological testing at baseline, 2 months, and 6 months showed that the intervention group improved significantly in delayed memory, and the control group did not. Moreover, participants who played the computer program for at least 40 sessions over 6 months improved in immediate memory, delayed memory, and language. These findings point to the potential benefit of cognitive training using a computerized, self-paced program. 


In a meta-analysis of computerized cognitive training, investigators found an overall moderate effect on cognition in mild cognitive impairment across 17 trials.46 Small to moderate effects were reported for global cognition, attention, working memory, and learning abilities.


Multitasking skills


Multitasking has been defined as performing two simultaneous tasks, which is only possible when the tasks are automatic, but it can also refer to rapid switching between tasks. Research has shown that such task switching increases error rates.47 Multitasking is common thanks to widespread technology use, and multiple studies point to its negative impact on cognitive performance.48 However, certain computer games may enhance multitasking, one of the cognitive domains that declines in a linear fashion across the lifespan.48

Anguera and colleagues49 trained volunteers (ages 60 to 85 years) over 4 weeks using a videogame called NeuroRacer, in which players control a car on a winding road while responding to signs that randomly appear. Out of 46 participants, 16 were trained in multitasking (both driving and sign reading), 15 in single-tasking mode (active controls; either sign reading or driving), and 15 received no training (no-contact controls). Only the multitasking training group showed significant improvements in performance scores, which not only exceeded that of untrained individuals in their twenties but was maintained for 6 months without additional training. Moreover, the multitasking training improved other cognitive skills, including working memory and divided and sustained attention.


Working memory and fluid intelligence


Fluid intelligence refers to the capacity to reason and think flexibly and requires working memory, the ability to retain information over a brief period of time. Investigators have found that training in working memory may improve fluid intelligence.50,51 Jaeggi and associates52 used a training program (n-back task) to investigate the effects of working-memory training on fluid intelligence. Healthy subjects (n=70) were randomized into working-memory training groups that were further randomized according to number of training sessions (8, 12, 17, or 19 days), or a control group that received no training. All subjects received pre- and post-testing on a measure of fluid intelligence at the same time intervals. The four groups not only showed significant improvements in working memory, but also on tests of fluid intelligence. Moreover, results demonstrated that the longer the training period, the greater the improvement in fluid intelligence. These results indicated successful transfer of improved working memory to improved fluid intelligence measures with a dose-dependent training effect. 


Visual attention and reaction time


Videogames have been popular for decades, and many gamers who began playing in the 1980s have continued to play through adulthood. Despite potential negative health effects of excessive playing (eg, attention deficits, social withdrawal, increased risk of obesity), recent research suggests potential benefits, such as improved visual attention processing, spatial visualization, reaction time, and mental rotation. Green and Bavelier53 have shown that playing action videogames more than 4 days per week (at least 1 hour each day) for 6 months enhances visual attention (ie, the ability to recognize and process visual information), spatial attention over the visual field, and task-switching abilities.


Rosser and colleagues54 examined a potential link between action videogaming and laparoscopic surgical skills and suturing. Surgeons who played videogames more than 3 hours each week made 37% fewer surgical errors, were 27% faster in response times, and scored 42% better in measures of laparoscopic and suturing skills than surgeons who do not play videogames. Moreover, the most experienced players in specific videogames (Super Monkey Ball 2, Star Wars Racer Revenge, and Silent Scope) made 47% fewer errors and performed 39% faster. These findings suggest that playing action videogames can improve cognitive and motor skills that improve surgical skills and lower error rates in the operating room.


Other mental health interventions


Technological advances have brought about novel approaches for delivering mental health support and interventions in the form of apps for smartphones or tablets, as well as through telepsychiatry. Internet-based mental health interventions offer the advantages of accessibility, cost-effectiveness, and anonymity. Between 2009 and 2015, the National Institute of Mental Health awarded more than 400 grants totaling $445 million for technology-enhanced mental-health interventions to further investigate roles for technology in preventing and treating mental disorders.55

Investigators have studied the efficacy of various online mental health interventions. For example, Peter and colleagues56 found that an online, 4-week intervention using cognitive behavioral therapy for insomnia reduced depression and insomnia ratings at levels comparable to traditional face-to-face interventions. Segal and associates57 evaluated the effectiveness of treating residual depressive symptoms with a web-based program that delivers mindfulness-based cognitive therapy. They found that use of this program in addition to usual depression care significantly improved depression and functional outcomes compared with usual depression care alone.


Several digital mental health applications have been developed or are in development, such as self-management apps that provide user feedback (eg, medication reminders, stress management tips, heart rate, and breathing patterns). Other programs provide skills training using educational videos on anxiety management or the importance of social support. Some applications have the capacity to collect data using smartphone sensors that record movement patterns, social interactions (eg, number of texts and phone calls), and other behaviors throughout the day.


Despite some promising early research, systematic studies demonstrating the efficacy of these emerging apps are limited. A recent review58 indicated that only 3% of downloadable apps had research to justify their effectiveness claims, and most of that research was performed by the program developers. Another recent survey59 of online-technology use to support mental health and well-being indicated that smartphone apps were the most commonly used technology: 78% of respondents used them either alone or in combination with other technologies. The apps that are being used provide guided activities, relaxation, and tracking; social media and discussion forums; and web-based programs to assist in the management of daily stress and anxiety.


Conclusions


Research on the brain-health consequences of digital technology is beginning to elucidate how these novel devices and programs can both help and harm brain function. Their frequent use heightens ADHD symptoms, interferes with emotional and social intelligence, can lead to addictive behaviors, increases social isolation, and interferes with brain development and sleep. However, specific programs, videogames, and other online tools may provide mental exercises that activate neural circuitry, improve cognitive functioning, reduce anxiety, increase restful sleep, and offer other brain-health benefits. Future research needs to elucidate underlying mechanisms and causal relationships between technology use and brain health, with a focus on both the positive and negative impact of digital technology use.


Acknowledgments

The University of California, Los Angeles, owns a US patent (6,274,119) entitled “Methods for Labeling β-Amyloid Plaques and Neurofibrillary Tangles,” which has been licensed to Ceremark Pharma, LLC. Dr Small is among the inventors and is a cofounder of Ceremark Pharma, LLC. Dr Small also reports having served as an advisor to and/or having received lecture fees from AARP, Acadia, Avanir, Genentech, Handok, Herbalife, Medscape, RB Health, Roche, Theravalues, and WebMD, and having received research funds from The Wonderful Company. Supported in part by the Parlow-Solomon Professorship on Aging

Contributor Information

Gary W. Small, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Jooyeon Lee, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Aaron Kaufman, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Jason Jalil, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Prabha Siddarth, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Himaja Gaddipati, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Teena D. Moody, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

Susan Y. Bookheimer, Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, the UCLA Longevity Center, David Geffen School of Medicine at the University of California, Los Angeles, California, US.

REFERENCES

  • 1.Firth J, Torous J, Stubbs B, et al The “online brain”: how the Internet may be changing our cognition. World Psychiatry. 2019;18(2):119–129. doi: 10.1002/wps.20617. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Hedman A, Lindqvist E, Nygard L. How older adults with mild cognitive impairment relate to technology as part of present and future everyday life: a qualitative study. BMC Geriatr. 2016;16:73. doi: 10.1186/s12877-016-0245-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Small GW, Moody TD, Siddarth P, Bookheimer SY. Your brain on Google: patterns of cerebral activation during Internet searching. Am J Geriatr Psychiatry. 2009;17:116–126. doi: 10.1097/JGP.0b013e3181953a02. [DOI] [PubMed] [Google Scholar]
  • 4.Bohle H, Rimpel J, Schauenburg G, et al Behavioral and neural correlates of cognitive-motor interference during multitasking in young and old adults. Neural Plast. 2019;2019:9478656. doi: 10.1155/2019/9478656. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Anderson M, Jiang J. Teens, social media & technology 2018. [Accessed June 4, 2018];Pew Research Center. May 31, 2018 Available at: http://www.pewinternet.org/2018/05/31/teens-social-media-technology-2018/ [Google Scholar]
  • 6.Ra CK, Cho J, Stone MD, et al Association of digital media use with subsequent symptoms of attention-deficit/hyperactivity disorder among adolescents. JAMA. 2018;320(3):255–263. doi: 10.1001/jama.2018.8931. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Schou Andreassen C, Griffiths MD, Kuss DJ, et al The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: a large-scale cross-sectional study. Psychol Addict Behav. 2016;30(2):252–262. doi: 10.1037/adb0000160. [DOI] [PubMed] [Google Scholar]
  • 8.Nikkelen SW, Valkenburg PM, Huizinga M, Bushman BJ. Media use and ADHD-related behaviors in children and adolescents: a meta-analysis. Dev Psychol. 2014;50(9):2228–2241. doi: 10.1037/a0037318. [DOI] [PubMed] [Google Scholar]
  • 9.Greicius MD, Krasnow B, Reiss AL, Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc Natl Acad Sci U S A. 2003;100(1):253–258. doi: 10.1073/pnas.0135058100. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Pediatrics. 2. Vol. 107. American Academy of Pediatrics, Committee on Public Education; 2001. American Academy of Pediatrics: children, adolescents, and television; pp. 423–426. [DOI] [PubMed] [Google Scholar]
  • 11.Giedd JN. The digital revolution and adolescent brain evolution. J Adolescent Health. 2012;51(2):101–105. doi: 10.1016/j.jadohealth.2012.06.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Kirsh SJ, Mounts JWR. Violent video game play impacts facial emotion recognition. Aggress Behav. 2007;33(4):353–358. doi: 10.1002/ab.20191. [DOI] [PubMed] [Google Scholar]
  • 13.Uhls YT, Michikyan M, Morris J, et al Five days at outdoor education camp without screens improves preteen skills with nonverbal emotion cues. Comput Hum Behav. 2014;39:387–392. [Google Scholar]
  • 14. Arlington, VA: American Psychiatric Association American Psychiatric Association; 2013. Diagnostic and Statistical Manual of Mental Disorders [Google Scholar]
  • 15.Young KS. Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychol Rep. 1996;79(3, pt 1):899–902. doi: 10.2466/pr0.1996.79.3.899. [DOI] [PubMed] [Google Scholar]
  • 16.You JH, Cho SC, Ha J, et al Attention deficit hyperactivity symptoms and Internet addiction. Psychiatry Clin Neurosci. 2004;58(5):487–494. doi: 10.1111/j.1440-1819.2004.01290.x. [DOI] [PubMed] [Google Scholar]
  • 17.Cheng C, Li AY. Internet addiction prevalence and quality of (real) life: a meta-analysis of 31 nations across seven world regions. Cyberpsychol Behav Soc Netw. 2014;17(12):755–760. doi: 10.1089/cyber.2014.0317. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Ko CH, Yen JY, Yen CF, et al The association between internet addiction and psychiatric disorder: a review of the literature. Eur Psychiatry. 2012;27(1):1–8. doi: 10.1016/j.eurpsy.2010.04.011. [DOI] [PubMed] [Google Scholar]
  • 19.Panagiotidi M, Overton P. The relationship between internet addiction, attention deficit hyperactivity symptoms and online activities in adult. Compr Psychiatry. 2018;87:7–11. doi: 10.1016/j.comppsych.2018.08.004. [DOI] [PubMed] [Google Scholar]
  • 20.Primack BA, Shensa A, Sidani JE, et al Social media use and perceived social isolation among young adults in the U.S. Am J Prev Med. 2017;53(1):1–8. doi: 10.1016/j.amepre.2017.01.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Nicholson NR. A review of social isolation: an important but underassessed condition in older adults. J Prim Prev. 2012;33(2-3):137–152. doi: 10.1007/s10935-012-0271-2. [DOI] [PubMed] [Google Scholar]
  • 22.Meshi D, Cotton SR, Bender AR. Problematic social media use and perceived social isolation in older adults: a cross-sectional study. Gerontology. 2020;66(2):160–168. doi: 10.1159/000502577. [DOI] [PubMed] [Google Scholar]
  • 23.Radesky JS, Christakis DA. Increased screen time: implications for early childhood development and behavior. Pediatr Clin North Am. 2016;63(5):827–839. doi: 10.1016/j.pcl.2016.06.006. [DOI] [PubMed] [Google Scholar]
  • 24.Horowitz-Kraus T, Hutton JS. Brain connectivity in children is increased by the time they spend reading books and decreased by the length of exposure to screen-based media. Acta Paediatr. 2018;107(4):685–693. doi: 10.1111/apa.14176. [DOI] [PubMed] [Google Scholar]
  • 25.Duch H, Fisher EM, Ensari I, et al Association of screen time use and language development in Hispanic toddlers: a cross-sectional and longitudinal study. Clin Pediatr (Phila) 2013;52(9):857–865. doi: 10.1177/0009922813492881. [DOI] [PubMed] [Google Scholar]
  • 26.McDonald SW, Kehler HL, Tough SC. Risk factors for delayed social-emotional development and behavior problems at age two: results from the All Our Babies/Families (AOB/F) cohort. Health Sci Rep. 2018;1(10):e82. doi: 10.1002/hsr2.82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Tomopoulos S, Dreyer BP, Berkule S, Fierman AH, Brockmeyer C, Mendelsohn AL. Infant media exposure and toddler development. Arch Pediatr Adolesc Med. 2010;164(12):1105–1111. doi: 10.1001/archpediatrics.2010.235. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Hutton JS, Dudley J, Horowitz-Kraus T, DeWitt T, Holland SK. Associations between screen-based media use and brain white matter integrity in preschool-aged children. JAMA Pediatr. 2019 Nov 4:e193869. doi: 10.1001/jamapediatrics.2019.3869. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Cheung CH, Bedford R, Saez De Urabain IR, Karmiloff-Smith A, Smith TJ. Daily touchscreen use in infants and toddlers is associated with reduced sleep and delayed sleep onset. Sci Rep. 2017;7:46104. doi: 10.1038/srep46104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Cabré-Riera A, Torrent M, Donaire-Gonzalez D, Vrijheid M, Cardis E, Guxens M. Telecommunication devices use, screen time and sleep in adolescents. Environ Res. 2019;171:341–347. doi: 10.1016/j.envres.2018.10.036. [DOI] [PubMed] [Google Scholar]
  • 31.Christensen MA, Bettencourt L, Kaye L, et al Direct measurements of smartphone screen-time: relationships with demographics and sleep. PLoS One. 2016;11(11):e0165331. doi: 10.1371/journal.pone.0165331. eCollection 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Amorim L, Magalhães R, Coelho A, et al Poor sleep quality associates with decreased functional and structural brain connectivity in normative aging: a MRI multimodal approach. Front Aging Neurosci. 2018;10:375. doi: 10.3389/fnagi.2018.00375. eCollection 2018. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Branger P, Arenaza-Urquijo EM, Tomadesso C, et al Relationships between sleep quality and brain volume, metabolism, and amyloid deposition in late adulthood. Neurobiol Aging. 2016;41:107–114. doi: 10.1016/j.neurobiolaging.2016.02.009. [DOI] [PubMed] [Google Scholar]
  • 34.Cajochen C1, Frey S, Anders D, et al Evening exposure to a light-emitting diodes (LED)-backlit computer screen affects circadian physiology and cognitive performance. J Appl Physiol (1985) 2011;110(5):1432–1438. doi: 10.1152/japplphysiol.00165.2011. [DOI] [PubMed] [Google Scholar]
  • 35.Verghese J, Lipton RB, Katz MJ, et al Leisure activities and the risk of dementia in the elderly. N Engl J Med. 2003;348(25):2508–2516. doi: 10.1056/NEJMoa022252. [DOI] [PubMed] [Google Scholar]
  • 36.Small GW, Silverman DHS, Siddarth P, et al Effects of a 14-day healthy longevity lifestyle program on cognition and brain function. Am J Geriatr Psychiatry. 2006;14(6):538–545. doi: 10.1097/01.JGP.0000219279.72210.ca. [DOI] [PubMed] [Google Scholar]
  • 37.Madden M. Internet penetration and impact. [Accessed March 2020];Pew Internet & American Life Project. April 2006 Available at: http://www.pewinternet.org/ pdfs/PIP_Internet_Impact.pdf. [Google Scholar]
  • 38.Haier RJ, Siegel BV Jr, MacLachlan A, et al Regional glucose metabolic changes after learning a complex visuospatial/motor task: a positron emission tomographic study. Brain Res. 1992;570(1-2):134–143. doi: 10.1016/0006-8993(92)90573-r. [DOI] [PubMed] [Google Scholar]
  • 39.Gaddipati H, Moody TD, Shirinyan D, Small GW, Bookheimer SY. Internet training alters working memory neural circuitry in older adults. Annual Meeting of the Society for Neuroscience; November 13-17, 2010; San Diego, CA. [Google Scholar]
  • 40.Dong G, Hui L, Potenza MN. Short-term Internet-search training is associated with increased fractional anisotropy in the superior longitudinal fasciculus in the parietal lobe. Front Neurosci. 2017;11:372. doi: 10.3389/fnins.2017.00372. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Shapira N, Barak A, Gal I. Promoting older adults’ well-being through Internet training and use. Aging Ment Health. 2007;11(5):477–484. doi: 10.1080/13607860601086546. [DOI] [PubMed] [Google Scholar]
  • 42.White H, McConnell E, Clipp E, et al A randomized controlled trial of the psychosocial impact of providing internet training and access to older adults. Aging Ment Health. 2002;6(3):213–221. doi: 10.1080/13607860220142422. [DOI] [PubMed] [Google Scholar]
  • 43.Ball K, Berch DB, Helmers KF, et al Effects of cognitive training interventions with older adults: a randomized controlled trial. JAMA. 2002;288(18):2271–2281. doi: 10.1001/jama.288.18.2271. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Rebok GW, Ball K, Guey LT, et al Ten-year effects of the advanced cognitive training for independent and vital elderly cognitive training trial on cognition and everyday functioning in older adults. J Am Geriatr Soc. 2014;62(1):16–24. doi: 10.1111/jgs.12607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Miller KJ, Dye RV, Kim J, et al Effect of a computerized brain exercise program on cognitive performance in older adults. Am J Geriatr Psychiatry. 2013;21(7):655–663. doi: 10.1016/j.jagp.2013.01.077. [DOI] [PubMed] [Google Scholar]
  • 46.Hill NT, Mowszowski L, Naismith SL, Chadwick VL, Valenzuela M, Lampit A. Computerized cognitive training in older adults with mild cognitive impairment or dementia: a systematic review and meta-analysis. Am J Psychiatry. 2017;174(4):329–340. doi: 10.1176/appi.ajp.2016.16030360. [DOI] [PubMed] [Google Scholar]
  • 47.Skaugset LM, Farrell S, Carney M, et al Can you multitask? Evidence and limitations of task switching and multitasking in emergency medicine. Ann Emerg Med. 2016;68(2):189–195. doi: 10.1016/j.annemergmed.2015.10.003. [DOI] [PubMed] [Google Scholar]
  • 48.van der Schuur WA, Baumgartner SE, Sumter SR, Valkenburg PM. The consequences of media multitasking for youth: a review. Comput Hum Behav. 2015;53:204–215. [Google Scholar]
  • 49.Anguera JA, Boccanfuso J, Rintoul JL, et al Video game training enhances cognitive control in older adults. Nature. 2013;501(7465):91–101. doi: 10.1038/nature12486. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Halford GS, Cowan N, Andrews G. Separating cognitive capacity from knowledge: a new hypothesis. Trends Cogn Sci. 2007;11(6):236–242. doi: 10.1016/j.tics.2007.04.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Gray JR, Chabris CF, Braver TS. Neural mechanisms of general fluid intelligence. Nat Neurosci. 2003;6(3):316–322. doi: 10.1038/nn1014. [DOI] [PubMed] [Google Scholar]
  • 52.Jaeggi SM, Buschkuehl M, Jonides J, et al Improving fluid intelligence with training on working memory. Proc Natl Acad Sci U S A. 2008;105(19):6829–6833. doi: 10.1073/pnas.0801268105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Green CS, Bavelier D. Action video game modifies visual selective attention. Nature. 2003;423(6939):534–537. doi: 10.1038/nature01647. [DOI] [PubMed] [Google Scholar]
  • 54.Rosser JC, Lynch PJ, Cuddihy L, et al The impact of video games on training surgeons in the 21st century. Arch Surg. 2007;142(2):181–186. doi: 10.1001/archsurg.142.2.181. [DOI] [PubMed] [Google Scholar]
  • 55. Bethesda, MD: U.S. Department of Health and Human Services, National Institutes of Health, National Institute of Mental Health; 2019. [Last revised September 2019; Accessed February 2, 2020]. Technology and the future of mental health treatment Available at: https://www.nimh.nih.gov/health/topics/technology-and-the-future-of-mental-health-treatment/index.shtml. [Google Scholar]
  • 56.Peter L, Reindl R, Zauter S, et al Effectiveness of an online CBT-I intervention and a face-to-face treatment for shift work sleep disorder: a comparison of sleep diary data. Int J Environ Res Public Health. 2019;16(17):pii:E3081. doi: 10.3390/ijerph16173081. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Segal ZV, Dimidjian S, Beck A, et al Outcomes of online mindfulness-based cognitive therapy for patients with residual depressive symptoms: a randomized clinical trial. JAMA Psychiatry. 2020 January 29 doi: 10.1001/jamapsychiatry.2019.4693. Epub ahead of print. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58.Marshall JM, Dunstan DA, Bartik W. The digital psychiatrist: in search of evidence-based apps for anxiety and depression. Front Psychiatry. 2019;10:831. doi: 10.3389/fpsyt.2019.0083. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 59.Stawarz K, Preist C, Coyle D. Use of smartphone apps, social media, and Web-based resources to support mental health and well-being: online survey. JMIR Ment Health. 2019;6(7):e12546. doi: 10.2196/12546. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Dialogues in Clinical Neuroscience are provided here courtesy of Taylor & Francis

RESOURCES