over use of digital devices essay

From Use to Overuse: Digital Inequality in the Age of Communication Abundance

• Social Science Computer Review 39(1):089443931985116
• 39(1):089443931985116

• Università degli Studi di Milano-Bicocca

• University of Zurich

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• 10 February 2020

Scrutinizing the effects of digital technology on mental health

• Jonathan Haidt &

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The topic in brief

• There is an ongoing debate about whether social media and the use of digital devices are detrimental to mental health.

• Adolescents tend to be heavy users of these devices, and especially of social media.

• Rates of teenage depression began to rise around 2012, when adolescent use of social media became common (Fig. 1).

• Some evidence indicates that frequent users of social media have higher rates of depression and anxiety than do light users.

• But perhaps digital devices could provide a way of gathering data about mental health in a systematic way, and make interventions more timely.

Figure 1 | Depression on the rise. Rates of depression among teenagers in the United States have increased steadily since 2012. Rates are higher and are increasing more rapidly for girls than for boys. Some researchers think that social media is the cause of this increase, whereas others see social media as a way of tackling it. (Data taken from the US National Survey on Drug Use and Health, Table 11.2b; go.nature.com/3ayjaww )

JONATHAN HAIDT: A guilty verdict

A sudden increase in the rates of depression, anxiety and self-harm was seen in adolescents — particularly girls — in the United States and the United Kingdom around 2012 or 2013 (see go.nature.com/2up38hw ). Only one suspect was in the right place at the right time to account for this sudden change: social media. Its use by teenagers increased most quickly between 2009 and 2011, by which point two-thirds of 15–17-year-olds were using it on a daily basis 1 . Some researchers defend social media, arguing that there is only circumstantial evidence for its role in mental-health problems 2 , 3 . And, indeed, several studies 2 , 3 show that there is only a small correlation between time spent on screens and bad mental-health outcomes. However, I present three arguments against this defence.

First, the papers that report small or null effects usually focus on ‘screen time’, but it is not films or video chats with friends that damage mental health. When research papers allow us to zoom in on social media, rather than looking at screen time as a whole, the correlations with depression are larger, and they are larger still when we look specifically at girls ( go.nature.com/2u74der ). The sex difference is robust, and there are several likely causes for it. Girls use social media much more than do boys (who, in turn, spend more of their time gaming). And, for girls more than boys, social life and status tend to revolve around intimacy and inclusion versus exclusion 4 , making them more vulnerable to both the ‘fear of missing out’ and the relational aggression that social media facilitates.

Second, although correlational studies can provide only circumstantial evidence, most of the experiments published in recent years have found evidence of causation ( go.nature.com/2u74der ). In these studies, people are randomly assigned to groups that are asked to continue using social media or to reduce their use substantially. After a few weeks, people who reduce their use generally report an improvement in mood or a reduction in loneliness or symptoms of depression.

The best way forward

Third, many researchers seem to be thinking about social media as if it were sugar: safe in small to moderate quantities, and harmful only if teenagers consume large quantities. But, unlike sugar, social media does not act just on those who consume it. It has radically transformed the nature of peer relationships, family relationships and daily activities 5 . When most of the 11-year-olds in a class are on Instagram (as was the case in my son’s school), there can be pervasive effects on everyone. Children who opt out can find themselves isolated. A simple dose–response model cannot capture the full effects of social media, yet nearly all of the debate among researchers so far has been over the size of the dose–response effect. To cite just one suggestive finding of what lies beyond that model: network effects for depression and anxiety are large, and bad mental health spreads more contagiously between women than between men 6 .

In conclusion, digital media in general undoubtedly has many beneficial uses, including the treatment of mental illness. But if you focus on social media, you’ll find stronger evidence of harm, and less exculpatory evidence, especially for its millions of under-age users.

What should we do while researchers hash out the meaning of these conflicting findings? I would urge a focus on middle schools (roughly 11–13-year-olds in the United States), both for researchers and policymakers. Any US state could quickly conduct an informative experiment beginning this September: randomly assign a portion of school districts to ban smartphone access for students in middle school, while strongly encouraging parents to prevent their children from opening social-media accounts until they begin high school (at around 14). Within 2 years, we would know whether the policy reversed the otherwise steady rise of mental-health problems among middle-school students, and whether it also improved classroom dynamics (as rated by teachers) and test scores. Such system-wide and cross-school interventions would be an excellent way to study the emergent effects of social media on the social lives and mental health of today’s adolescents.

NICK ALLEN: Use digital technology to our advantage

It is appealing to condemn social media out of hand on the basis of the — generally rather poor-quality and inconsistent — evidence suggesting that its use is associated with mental-health problems 7 . But focusing only on its potential harmful effects is comparable to proposing that the only question to ask about cars is whether people can die driving them. The harmful effects might be real, but they don’t tell the full story. The task of research should be to understand what patterns of digital-device and social-media use can lead to beneficial versus harmful effects 7 , and to inform evidence-based approaches to policy, education and regulation.

Long-standing problems have hampered our efforts to improve access to, and the quality of, mental-health services and support. Digital technology has the potential to address some of these challenges. For instance, consider the challenges associated with collecting data on human behaviour. Assessment in mental-health care and research relies almost exclusively on self-reporting, but the resulting data are subjective and burdensome to collect. As a result, assessments are conducted so infrequently that they do not provide insights into the temporal dynamics of symptoms, which can be crucial for both diagnosis and treatment planning.

By contrast, mobile phones and other Internet-connected devices provide an opportunity to continuously collect objective information on behaviour in the context of people’s real lives, generating a rich data set that can provide insight into the extent and timing of mental-health needs in individuals 8 , 9 . By building apps that can track our digital exhaust (the data generated by our everyday digital lives, including our social-media use), we can gain insights into aspects of behaviour that are well-established building blocks of mental health and illness, such as mood, social communication, sleep and physical activity.

Stress and the city

These data can, in turn, be used to empower individuals, by giving them actionable insights into patterns of behaviour that might otherwise have remained unseen. For example, subtle shifts in patterns of sleep or social communication can provide early warning signs of deteriorating mental health. Data on these patterns can be used to alert people to the need for self-management before the patterns — and the associated symptoms — become more severe. Individuals can also choose to share these data with health professionals or researchers. For instance, in the Our Data Helps initiative, individuals who have experienced a suicidal crisis, or the relatives of those who have died by suicide, can donate their digital data to research into suicide risk.

Because mobile devices are ever-present in people’s lives, they offer an opportunity to provide interventions that are timely, personalized and scalable. Currently, mental-health services are mainly provided through a century-old model in which they are made available at times chosen by the mental-health practitioner, rather than at the person’s time of greatest need. But Internet-connected devices are facilitating the development of a wave of ‘just-in-time’ interventions 10 for mental-health care and support.

A compelling example of these interventions involves short-term risk for suicide 9 , 11 — for which early detection could save many lives. Most of the effective approaches to suicide prevention work by interrupting suicidal actions and supporting alternative methods of coping at the moment of greatest risk. If these moments can be detected in an individual’s digital exhaust, a wide range of intervention options become available, from providing information about coping skills and social support, to the initiation of crisis responses. So far, just-in-time approaches have been applied mainly to behaviours such as eating or substance abuse 8 . But with the development of an appropriate research base, these approaches have the potential to provide a major advance in our ability to respond to, and prevent, mental-health crises.

These advantages are particularly relevant to teenagers. Because of their extensive use of digital devices, adolescents are especially vulnerable to the devices’ risks and burdens. And, given the increases in mental-health problems in this age group, teens would also benefit most from improvements in mental-health prevention and treatment. If we use the social and data-gathering functions of Internet-connected devices in the right ways, we might achieve breakthroughs in our ability to improve mental health and well-being.

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Competing Interests

N.A. has an equity interest in Ksana Health, a company he co-founded and which has the sole commercial licence for certain versions of the Effortless Assessment of Risk States (EARS) mobile-phone application and some related EARS tools. This intellectual property was developed as part of his research at the University of Oregon’s Center for Digital Mental Health (CDMH).

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Listen to the essay, as read by Antero Garcia, associate professor in the Graduate School of Education.

As a professor of education and a former public school teacher, I’ve seen digital tools change lives in schools.

I’ve documented the ways mobile technology like phones can transform student engagement in my own classroom.

I’ve explored how digital tools might network powerful civic learning and dialogue for classrooms across the country – elements of education that are crucial for sustaining our democracy today.

And, like everyone, I’ve witnessed digital technologies make schooling safer in the midst of a global pandemic. Zoom and Google Classroom, for instance, allowed many students to attend classrooms virtually during a period when it was not feasible to meet in person.

So I want to tell you that I think technologies are changing education for the better and that we need to invest more in them – but I just can’t.

Given the substantial amount of scholarly time I’ve invested in documenting the life-changing possibilities of digital technologies, it gives me no pleasure to suggest that these tools might be slowly poisoning us. Despite their purported and transformational value, I’ve been wondering if our investment in educational technology might in fact be making our schools worse.

Let me explain.

When I was a classroom teacher, I loved relying on the latest tools to create impressive and immersive experiences for my students. We would utilize technology to create class films, produce social media profiles for the Janie Crawfords, the Holden Caulfields, and other literary characters we studied, and find playful ways to digitally share our understanding of the ideas we studied in our classrooms.

As a teacher, technology was a way to build on students’ interests in pop culture and the world around them. This was exciting to me.

But I’ve continued to understand that the aspects of technology I loved weren’t actually about technology at all – they were about creating authentic learning experiences with young people. At the heart of these digital explorations were my relationships with students and the trust we built together.

“Part of why I’ve grown so skeptical about this current digital revolution is because of how these tools reshape students’ bodies and their relation to the world around them.”

I do see promise in the suite of digital tools that are available in classrooms today. But my research focus on platforms – digital spaces like Amazon, Netflix, and Google that reshape how users interact in online environments – suggests that when we focus on the trees of individual tools, we ignore the larger forest of social and cognitive challenges.

Most people encounter platforms every day in their online social lives. From the few online retail stores where we buy groceries to the small handful of sites that stream our favorite shows and media content, platforms have narrowed how we use the internet today to a small collection of Silicon Valley behemoths. Our social media activities, too, are limited to one or two sites where we check on the updates, photos, and looped videos of friends and loved ones.

These platforms restrict our online and offline lives to a relatively small number of companies and spaces – we communicate with a finite set of tools and consume a set of media that is often algorithmically suggested. This centralization of internet – a trend decades in the making – makes me very uneasy.

From willfully hiding the negative effects of social media use for vulnerable populations to creating tools that reinforce racial bias, today’s platforms are causing harm and sowing disinformation for young people and adults alike. The deluge of difficult ethical and pedagogical questions around these tools are not being broached in any meaningful way in schools – even adults aren’t sure how to manage their online lives.

You might ask, “What does this have to do with education?” Platforms are also a large part of how modern schools operate. From classroom management software to attendance tracking to the online tools that allowed students to meet safely during the pandemic, platforms guide nearly every student interaction in schools today. But districts are utilizing these tools without considering the wider spectrum of changes that they have incurred alongside them.

Antero Garcia, associate professor of education (Image credit: Courtesy Antero Garcia)

For example, it might seem helpful for a school to use a management tool like Classroom Dojo (a digital platform that can offer parents ways to interact with and receive updates from their family’s teacher) or software that tracks student reading and development like Accelerated Reader for day-to-day needs. However, these tools limit what assessment looks like and penalize students based on flawed interpretations of learning.

Another problem with platforms is that they, by necessity, amass large swaths of data. Myriad forms of educational technology exist – from virtual reality headsets to e-readers to the small sensors on student ID cards that can track when students enter schools. And all of this student data is being funneled out of schools and into the virtual black boxes of company databases.

Part of why I’ve grown so skeptical about this current digital revolution is because of how these tools reshape students’ bodies and their relation to the world around them. Young people are not viewed as complete human beings but as boxes checked for attendance, for meeting academic progress metrics, or for confirming their location within a school building. Nearly every action that students perform in schools – whether it’s logging onto devices, accessing buildings, or sharing content through their private online lives – is noticed and recorded. Children in schools have become disembodied from their minds and their hearts. Thus, one of the greatest and implicit lessons that kids learn in schools today is that they must sacrifice their privacy in order to participate in conventional, civic society.

The pandemic has only made the situation worse. At its beginnings, some schools relied on software to track students’ eye movements, ostensibly ensuring that kids were paying attention to the tasks at hand. Similarly, many schools required students to keep their cameras on during class time for similar purposes. These might be seen as in the best interests of students and their academic growth, but such practices are part of a larger (and usually more invisible) process of normalizing surveillance in the lives of youth today.

I am not suggesting that we completely reject all of the tools at our disposal – but I am urging for more caution. Even the seemingly benign resources we might use in our classrooms today come with tradeoffs. Every Wi-Fi-connected, “smart” device utilized in schools is an investment in time, money, and expertise in technology over teachers and the teaching profession.

Our focus on fixing or saving schools via digital tools assumes that the benefits and convenience that these invisible platforms offer are worth it.

But my ongoing exploration of how platforms reduce students to quantifiable data suggests that we are removing the innovation and imagination of students and teachers in the process.

Antero Garcia is associate professor of education in the Graduate School of Education .

In Their Own Words is a collaboration between the Stanford Public Humanities Initiative  and Stanford University Communications.

If you’re a Stanford faculty member (in any discipline or school) who is interested in writing an essay for this series, please reach out to Natalie Jabbar at [email protected] .

September 11, 2018

Are Digital Devices Altering Our Brains?

Some say our gadgets and computers can help improve intelligence. Others say they make us stupid and violent. Which is it?

By Elena Pasquinelli

Do video games make people more aggressive, or are they beneficial—improving certain abilities, such as reaction time? Probably a bit of both, according to recent research, although any benefits are modest.

John Lund Getty Images

Ten years ago technology writer Nicholas Carr published an article in the Atlantic entitled “Is Google Making Us Stupid?” He strongly suspected the answer was “yes.” Himself less and less able to focus, remember things or absorb more than a few pages of text, he accused the Internet of radically changing people’s brains. And that is just one of the grievances leveled against the Internet and at the various devices we use to access it–including cell phones, tablets, game consoles and laptops. Often the complaints target video games that involve fighting or war, arguing that they cause players to become violent.

But digital devices also have fervent defenders—in particular the promoters of brain-training games, who claim that their offerings can help improve attention, memory and reflexes. Who, if anyone, is right?

The answer is less straightforward than you might think. Take Carr’s accusation. As evidence, he quoted findings of neuroscientists who showed that the brain is more plastic than previously understood. In other words, it has the ability to reprogram itself over time, which could account for the Internet’s effect on it. Yet in a 2010 opinion piece in the Los Angeles Times, psychologists Christopher Chabris, then at Union College, and Daniel J. Simons of the University of Illinois at Urbana-Champaign rebutted Carr’s view: “There is simply no experimental evidence to show that living with new technologies fundamentally changes brain organization in a way that affects one’s ability to focus,” they wrote. And the debate goes on.

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The Case for Stupidity

Where does the idea that we are becoming “stupid” come from? It derives in part from the knowledge that digital devices capture our attention. A message from a friend, an anecdote shared on social networks or a sales promotion on an online site can act like a treat for the human brain. The desire for such “treats” can draw us to our screens repeatedly and away from other things we should be concentrating on.

People may feel overwhelmed by the constant input, but some believe they have become multitaskers: they imagine they can continually toggle back and forth between Twitter and work, even while driving, without losing an ounce of efficiency. But a body of research confirms that this impression is an illusion. When individuals try to do two or more things at once that require their attention, their performance suffers. Moreover, in 2013 Stéphane Amato, then at Aix-Marseille University in France, and his colleagues showed that surfing Web pages makes people susceptible to a form of cognitive bias known as the primacy effect: they weight the first few pieces of information they see more heavily than the rest.

Training does not improve the ability to multitask. In 2009 Eyal Ophir, then at Stanford University, and his colleagues discovered that multitasking on the Internet paradoxically makes users less effective at switching from one task to another. They are less able to allocate their attention and are too vulnerable to distractions. Consequently, even members of the “digital native” generation are unlikely to develop the cognitive control needed to divide their time between several tasks or to instantly switch from one activity to another. In other words, digital multitasking does little more than produce a dangerous illusion of competence.

The good news is that you do not need to rewire your brain to preserve your attention span. You can help yourself by thinking about what distracts you most and by developing strategies to immunize yourself against those distractions. And you will need to exercise some self-control. Can’t resist Facebook notifications? Turn them off while you’re working. Tempted to play a little video game? Don’t leave your device where you can see it or within easy reach.

Evidence for Aggression

What about the charge that video games increase aggression? Multiple reports support this view. In a 2015 review of published studies, the American Psychological Association concluded that playing violent video games accentuates aggressive thoughts, feelings and behavior while diminishing empathy for victims. The conclusion comes both from laboratory research and from tracking populations of online gamers. In the case of the gamers, the more they played violent games, the more aggressive their behavior was.

The aggression research suffers from several limitations, however. For example, lab studies measure aggressiveness by offering participants the chance to inflict a punishment, such as a dose of very hot sauce to swallow—actions that are hardly representative of real life. Outside the lab, participants would probably give more consideration to the harmful nature of their actions. And studies of gamers struggle to make sense of causality: Do video games make people more violent, or do people with a fundamentally aggressive temperament tend to play video games?

Thus, more research is needed, and it will require a combination of different methods. Although the findings so far are preliminary, researchers tend to agree that some caution is in order, beginning with moderation and variety: an hour here and there spent playing fighting games is unlikely to turn you into a brainless psychopath, but it makes sense to avoid spending entire days at it.

Gaming for Better Brains?

On the benefit side of the equation, a number of studies claim that video games can improve reaction time, attention span and working memory. Action games, which are dynamic and engaging, may be particularly effective: immersed in a captivating environment, players learn to react quickly, focus on relevant information and remember. In 2014, for example, Kara Blacker of Johns Hopkins University and her colleagues studied the impact games in the Call of Duty series—in which players control soldiers—on visual working memory (short-term memory). The researchers found that 30 hours of playing improved this capacity.

The assessment consisted of asking participants a number of times whether a group of four to six colored squares was identical to another group, presented two minutes earlier. Once again, however, this situation is far from real life. Moreover, the extent to which players “transfer” their learning to everyday activities is debatable.

This issue of skill transfer is also a major challenge for the brain-training industry, which has been growing since the 2000s. These companies are generally very good at promoting themselves and assert that engaging in various exercises and computer games for a few minutes a day can improve memory, attention span and reaction time.

Posit Science, which offers the BrainHQ series of brain training and assessment, is one such company. Its tools include UFOV (for “useful field of view). In one version of a UFOV-based game, a car and a road sign appear on a screen. Then another car appears. The player clicks on the original car and also clicks on where the road sign appeared. By having groups of objects scroll faster and faster, the activity is supposed to improve reaction time.

The company’s Web site touts user testimonials and says its customers report that BrainHQ “has done everything from improving their bowling game, to enabling them to get a job, to reviving their creativity, to making them feel more confident about their future.” Findings from research, however, are less clear-cut. On one hand, Posit Science cites the Advanced Cognitive Training for Independent and Elderly (ACTIVE) Study to claim that UFOV training can improve overall reaction time in elderly players and reduce the risk that they will cause car crashes by almost 50 percent. But in a 2016 analysis of research on brain-training programs, Simons and his colleagues are far less laudatory. The paper, which includes an in-depth analysis of the ACTIVE study, says that the overall risk of having an accident—the most relevant criterion—decreased very little. Several reviews of the scientific literature come to much the same conclusion: brain-training products enhance performance on tasks that are trained directly, but the transfer is often weak.

Dr. Kawashima’s Brain Traininggame, released by Nintendo in the mid-2000s, provides another example of contrary results. In addition to attention and memory exercises, this game has a player do calculations. Does the program improve overall arithmetic skills? No, according to work done in 2012 by Siné McDougall and Becky House, both at Bournemouth University in England on a group of seniors. A year earlier, though, Scottish psychologists David Miller and Derek Robertson found that the game did increase how fast children could calculate.

Overall then, the results from studies are mixed. The benefits need to be evaluated better, and many questions need answering, such as how long an intervention should last and at what ages might it be effective. The answers may depend on the specific interventions being considered.

No Explosive Growth in Capacity

Any cognitive improvements from brain-training games probably will be marginal rather than an “explosion” of human mental capacities. Indeed, the measured benefits are much weaker and ephemeral than the benefits obtained through traditional techniques. For remembering things, for example, rather than training your recall with abstract tasks that have little bearing on reality, try testing your memory regularly and making the information as meaningful to your own life as possible: If you memorize a shopping list, ask yourself what recipe you are buying the ingredients for and for which day’s dinner. Unlike brain-training games, this kind of approach involves taking some initiative and makes you think about what you know.

Exercising our cognitive capacities is important to combating another modern hazard: the proliferation of fake news on social networks. In the same way that digital devices accentuate our tendency to become distracted, fake news exploits our natural inclination to believe what suits us. The solution to both challenges is education: more than ever, young people must be taught to develop their concentration, self-control and critical-thinking skills.

Elena Pasquinelli is a project manager at La Main à la Pâte Foundation, which works to improve science instruction in higher education, and an associate member of the Jean Nicod Institute, a cognitive science laboratory in Paris.

Home — Essay Samples — Information Science and Technology — Digital Era — Digital Devices And Well-Being

Digital Devices and Well-being

• Categories: Digital Era

About this sample

Words: 849 |

Published: Sep 19, 2019

Words: 849 | Pages: 2 | 5 min read

Works Cited

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• Rozgonjuk, D., Sindermann, C., Elhai, J. D., & Montag, C. (2020). Comparing digital behavior measures and psychopathological symptoms among adolescents and their parents during the COVID-19 pandemic. Computers in Human Behavior, 114, 106524.
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• Thomée, S., Härenstam, A., & Hagberg, M. (2011). Mobile phone use and stress, sleep disturbances, and symptoms of depression among young adults: A prospective cohort study. BMC Public Health, 11(1), 66.

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The Overuse of Digital Technologies: Human Weaknesses, Design Strategies and Ethical Concerns

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• Published: 08 July 2021
• Volume 34 , pages 1409–1427, ( 2021 )

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• Marco Fasoli   ORCID: orcid.org/0000-0001-6176-8257 1  

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This is an interdisciplinary article providing an account of a phenomenon that is quite widespread but has been thus far mostly neglected by scholars: the overuse of digital technologies. Digital overuse (DO) can be defined as a usage of digital technologies that subjects perceive as dissatisfactory and non-meaningful a posteriori. DO has often been implicitly conceived as one of the main obstacle to so-called digital well-being . The article is structured in two parts. The first provides a definition of the phenomenon and a brief review of the explanations provided by various disciplines, in particular psychology and the evolutionary and behavioural sciences. Specifically, the article distinguishes between the endogenous and exogenous factors underlying digital overuse, that is between causes that seem to be intrinsic to digital technologies, and design techniques intentionally aimed at nudging users towards this behaviour. The second part is devoted to a discussion of the ethical concerns surrounding the phenomenon of the overuse of digital technologies, and how it may be possible to reduce such overuse among users.

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Fasoli, M. The Overuse of Digital Technologies: Human Weaknesses, Design Strategies and Ethical Concerns. Philos. Technol. 34 , 1409–1427 (2021). https://doi.org/10.1007/s13347-021-00463-6

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Use and abuse of digital devices: influencing factors of child and adolescent neuropsychology.

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Share and Cite

Costanza, C.; Vetri, L.; Carotenuto, M.; Roccella, M. Use and Abuse of Digital Devices: Influencing Factors of Child and Adolescent Neuropsychology. Clin. Pract. 2023 , 13 , 1331-1334. https://doi.org/10.3390/clinpract13060119

Costanza C, Vetri L, Carotenuto M, Roccella M. Use and Abuse of Digital Devices: Influencing Factors of Child and Adolescent Neuropsychology. Clinics and Practice . 2023; 13(6):1331-1334. https://doi.org/10.3390/clinpract13060119

Costanza, Carola, Luigi Vetri, Marco Carotenuto, and Michele Roccella. 2023. "Use and Abuse of Digital Devices: Influencing Factors of Child and Adolescent Neuropsychology" Clinics and Practice 13, no. 6: 1331-1334. https://doi.org/10.3390/clinpract13060119

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Peer-reviewed

Research Article

Addictive use of digital devices in young children: Associations with delay discounting, self-control and academic performance

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliation School of Business and Economics, Freie Universität, Berlin, Germany

• Tim Schulz van Endert

• Published: June 22, 2021
• https://doi.org/10.1371/journal.pone.0253058
• Peer Review
• Reader Comments

The use of smartphones, tablets and laptops/PCs has become ingrained in adults’ and increasingly in children’s lives, which has sparked a debate about the risk of addiction to digital devices. Previous research has linked specific use of digital devices (e.g. online gaming, smartphone screen time) with impulsive behavior in the context of intertemporal choice among adolescents and adults. However, not much is known about children’s addictive behavior towards digital devices and its relationship to personality factors and academic performance. This study investigated the associations between addictive use of digital devices, self-reported usage duration, delay discounting, self-control and academic success in children aged 10 to 13. Addictive use of digital devices was positively related to delay discounting, but self-control confounded the relationship between the two variables. Furthermore, self-control and self-reported usage duration but not the degree of addictive use predicted the most recent grade average. These findings indicate that children’s problematic behavior towards digital devices compares to other maladaptive behaviors (e.g. substance abuse, pathological gambling) in terms of impulsive choice and point towards the key role self-control seems to play in lowering a potential risk of digital addiction.

Citation: Schulz van Endert T (2021) Addictive use of digital devices in young children: Associations with delay discounting, self-control and academic performance. PLoS ONE 16(6): e0253058. https://doi.org/10.1371/journal.pone.0253058

Editor: Baogui Xin, Shandong University of Science and Technology, CHINA

Received: April 8, 2021; Accepted: May 27, 2021; Published: June 22, 2021

Copyright: © 2021 Tim Schulz van Endert. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The author received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Digital devices, such as smartphones, tablets and laptops, have become an integral part in the lives of the majority of people around the world. Recent surveys e.g. in the US estimate that 81% of adults own a smartphone, 74% own a laptop and 52% own a tablet [ 1 ]. Notably, not only adults but also children have been increasingly surrounded by digital devices; a report from the UK states that in 2019 more than two thirds of 5- to 16-year-olds owned a smartphone and that 80% of 7- to 16-year-olds had internet access in their own room [ 2 ]. The same report also estimates that children’s average time spent online is 3.4 hours per day, with the main activities being watching videos (e.g. on YouTube and TikTok), using social media (e.g. Instagram and Snapchat) or gaming (e.g. Fortnite or Minecraft). These numbers have seen an unprecedented increase since the COVID-19 pandemic, which has, to a large extent, forced children to remain home, receive online schooling and interact with friends digitally. While the effects of these measures vary from country to country, a 163% increase in daily screen time during the first lockdown in Germany is not an unusual occurrence as observed by Schmidt et al. [ 3 ].

These developments have added momentum to the debate about the addiction potential of digital devices—especially for children, who are particularly at risk of developing addictive behaviors [ 4 ]. Evidence of negative implications of excessive digital device use, such as stress [ 5 ], sleep disturbance [ 6 ] or poor academic performance [ 7 ], has accumulated in recent years. However, researchers have not yet agreed on a standardized definition of digital addiction, which clearly separates it from other, possibly underlying disorders [ 8 ]. For one aspect of problematic use of digital devices, namely Internet Gaming Disorder, existing research has matured to stage where it suggests a potential future inclusion in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), as an officially diagnosable condition. Other aspects, such as smartphone addiction, are less mature and the literature has so far only identified a significant overlap between addiction to smartphones and substance-related disorders defined in the DSM-5 [ 9 , 10 ]. One area of research, which seeks to explore overall addiction to digital devices, encompassing various media (e.g. smartphones, tablets and laptops/PCs) and activities (e.g. gaming, social media), seems promising but is still in its infancy [ 11 ]. Unlike the aforementioned strands of literature, research on overall digital addiction takes into account the newly emerged usage behavior of performing a multitude of activities on and across several different digital devices (e.g. sending WhatsApp messages on a smartphone, playing games on a tablet and watching movies on a laptop). This may promote a degree of consolidation of the large number of concepts of technology addiction and their corresponding scales, which have emerged over the years but have recently been shown to be highly similar on a dimensional level [ 12 ].

A scale assessing digital addiction particularly among young children was recently introduced [ 11 ]. The Digital Addiction Scale for Children (DASC) measures to which degree children’s use of smartphones, tablets and laptops/PCs negatively affects their educational, psychological, social and physical well-being. To account for the ongoing debate about a standardized definition of digital addiction and the corresponding lack of a firm diagnosis, throughout this paper the softer formulation “addictive use of digital devices” is used rather than “digital addiction” when referring to children’s use of digital devices with adverse consequences. To further our understanding of this behavioral pattern and enable possible future intervention, the scale needs to be investigated in connection with personality factors, which may contribute to problematic behavior towards digital devices [ 13 ].

In this context, delay discounting, i.e. the tendency to discount rewards as a function of the delay of their delivery, suggests itself as an avenue for research. This cognitive process underlies human and non-human animals’ preference for smaller, immediate rewards over larger, delayed rewards and is often used as a measure of impulsivity [ 14 ]. Delay discounting has been studied extensively in the past decades, mostly by means of intertemporal choice problems, in which participants are faced with the tradeoff between the amount and the delay of a reward (e.g. choosing between 100€ today or 150€ in one month). Several models seeking to capture behavior have emerged, with hyperbolic discounting providing the best fit for most empirical data [ 15 ]. Its equation V = A / (1+kD) (V is the present value of the future reward, A is the reward amount and D is the delay to the reward) contains one free parameter k, which represents an individual’s discount rate. The lower this discounting parameter, the less the individual devalues future rewards and is therefore relatively less impulsive than a person with a higher discount rate. Due to the relative temporal stability of individuals’ discount rates, delay discounting may be seen as a trait variable [ 16 ]. Also, a plethora of studies has shown an association between delay discounting and a variety of maladaptive behaviors, such as substance abuse [ 17 ], smoking [ 18 ] and pathological gambling [ 19 , 20 ] or overeating [ 21 ]. In these studies, addicted individuals discounted future rewards more steeply than control subjects, which makes delay discounting a reliable indicator for various kinds of addictions [ 22 ]. Given that the discounting of future rewards is not only related to substance-based but also to behavioral addictions, this raises the question if delay discounting is also associated with addictive use of digital devices. Past studies have only been able to show relationships between delay discounting and single aspects of digital use, such as internet gaming [ 23 ] or smartphone screen time [ 24 ]. In addition, the samples studied consisted of adolescents or adults, despite regular use of digital devices already starting in childhood [ 2 ].

Furthermore, researchers agree on the key role of self-control in the development [ 25 ] and treatment [ 26 ] of addictive behaviors. On the one hand, a decreased ability to regulate thoughts and emotions contributes to risk-taking behavior, such as initiating use of addictive drugs, which is a common phenomenon in adolescents [ 27 ]. On the other hand, impaired self-control is a key symptom of addicted individuals, i.e. the inability to stop engaging in addictive behavior despite a willingness to do so. Thus, behavioral training to strengthen control functions has been proposed as an effective approach to reduce addiction [ 28 ]. Additionally, prominent models of decision-making have also highlighted self-control as a mechanism underlying delay discounting [ 22 , 29 ]. According to these accounts, exertion of self-control suppresses the impulse of choosing a smaller, immediate reward and biases choice behavior towards the larger, delayed reward. However, the interrelationships between delay discounting, addictive use of digital devices and self-control have yet to be explored.

Lastly, a number of studies have shown an association between various kinds of addictive behavior and poor academic performance [ 30 – 32 ]. Being distracted in the classroom or while studying, concentration lapses due to lack of sleep or missing classes and exams have been put forth as explanations for this finding. Given the novelty of the concept of digital addiction, the question whether the pattern suggested by the literature also holds in the context of addictive use of digital devices, particularly by young children, needs empirical investigation. This issue is of great importance as fundamental reading, writing and mathematics skills are taught at this stage. It is also relevant for the debate about increasingly integrating digital media in classroom activities and homework as part of the digitalization of schools. Therefore, this present study examines the following three hypotheses:

• H1: Delay discounting is positively correlated with children’s addictive use of digital devices
• H2: Self-control is negatively correlated with children’s addictive use of digital devices
• H3: Children’s addictive use of digital devices is negatively correlated with academic success

This study contributes to the literature by showing behavioral similarities between addictive use of digital devices and other problematic behaviors, by highlighting the central role that self-control seems to play in the context of digital addiction and by uncovering an intriguing pattern when comparing the relationships of problematic use vs. raw usage duration of digital devices with academic success.

Participants

75 children aged 10 to 13 (mean 11.3 years, 47% female) with no officially diagnosed mental disorders (e.g. Attention-Deficit/Hyperactivity Disorder, Obsessive-Compulsive Disorder) were recruited from a public elementary school in Berlin, Germany. The participants were 5 th and 6 th grade students and were selected for two reasons. On the one hand, participants needed to be able to understand the tasks and questionnaires employed in this study. On the other hand, this age represents a major crossroad for the children of Berlin; within the city’s school system, students graduate from elementary school after 6 th grade and progress to either high school (“Gymnasium”) or integrative secondary school (“Integrierte Sekundarschule”) depending on their academic performance (a German high school diploma provides eligibility to attend University, while students from Integrative Secondary School graduate after 9 th or 10 th grade in order to start an apprenticeship). This age group, prior to above-mentioned separation, thus had the positive side effect of implying a variety of academic skills as well as socio-economic backgrounds. Furthermore, the school’s headmaster affirmed that there was a significant diversity of ethnicities and nationalities among students and that no mental disorders existed in the observed classes. Parents (or guardians) of all participants were informed that participation was voluntary as well as anonymous and did not have an impact on their children’s grades. Roughly 15% of invited students chose not to participate in the study. Informed consent documents were signed before each study session.

Addictive use of digital devices.

To measure the degree of addictive use of smartphones and tablets the Digital Addiction Scale for Children (DASC) [ 11 ] was employed. The DASC is a 25-item self-report instrument based on the theoretical framework of DSM-5 Internet Gaming Disorder as well as on the components model of addiction [ 33 ]. The resulting nine addiction criteria are Preoccupation, Tolerance, Withdrawal, Problems, Conflict, Deception, Displacement, Relapse and Mood Modification, each represented by two to four items within the scale. Scores range from 25 to 125, higher scores indicating a greater risk of addiction to digital devices. As only the degree of smartphone and tablet use with adverse consequences rather than the identification of addicts was relevant to this study, the scale was not used to distinguish between addicts and non-addicts in the analyses. Correspondingly, throughout this paper the formulation “addictive use of digital devices” is used rather than “digital addiction”, to avoid suggesting a firm diagnosis, which is not available at the moment. The scale was specifically developed for 9- to 12-year-old children and has been shown to be a reliable and valid instrument to assess the risk of being addicted to digital devices [ 11 ]. A German translation of the DASC was used, after having been checked for understandability by one 5 th grade and one 6 th grade teacher independently. The internal consistency of the scale was excellent (α = 0.94).

Delay discounting.

The participants’ preference for smaller immediate rewards over larger delayed rewards was assessed with a German translation of the 27-item Monetary Choice Questionnaire [ 17 ]. In this questionnaire participants repeatedly choose between a smaller, immediately available reward and a larger reward available in the future, all rewards being hypothetical and consisting of small (e.g. €20), medium (e.g. €54) and large amounts of money (e.g. €78). The proportion of choices of the larger delayed reward (LDR) is used as a measure of impulsivity, i.e. the lower the proportion, the more impulsive the individual. The scale is widely used in the literature for studying adults and has also been shown to be a valid instrument for young children [ 34 – 36 ]. Also, the Monetary Choice Questionnaire provides similar results to more extended instruments [ 37 ] as well as to paradigms that use real or potentially real rewards [ 38 ]. Furthermore, the proportion of LDR measure is a simple yet reliable and valid measure, which does not require the assumption of hyperbolic discounting [ 39 ]. Within the present dataset the LDR proportion was highly correlated (r = -0.98, p<0.001) with the natural log of the discount parameter k according to Kirby et al. [ 17 ], indicating that the LDR measure was accurately assessing participants’ discounting of future rewards. The responses to the Monetary Choice Questionnaire were scored using automated scoring [ 40 ]. This tool also provides consistency scores in order to identify insufficient comprehension or a lack of or attending to the questionnaire. Three participants had consistency scores below 75%, the recommended threshold for good quality of responses [ 41 ], resulting in their exclusion from the analyses.

Self-control.

As a measure of self-control the German adaptation [ 42 ] of Tangney et al.’s Brief Self-Control Scale [ 43 ] was used, which is a widely used self-report measure of trait self-control. Scores range from 13 to 65, higher scores representing better ability to regulate thoughts, emotions and behavior. Research has shown that the 13-item brief self-control scale provides equally reliable and valid results as the long version [ 43 ] and is appropriate for use with young children [ 44 ]. Good internal consistency was indicated by Cronbach’s α of 0.75.

Additional variables.

As a measure of academic performance, the most recent semester’s grade average with a possible range from 1.0 (best possible, “straight A”) to 6.0 (worst possible, “straight F”) was used. Also, children were asked to estimate their average daily duration of several popular activities on digital devices (e.g. social media, games) as well as their typical total screen time on weekdays and weekends to attain various measures for self-reported usage, thereby allowing for robustness checks of results. Lastly, age, gender, years of smartphone ownership and weekly pocket money were elicited as control variables.

Data was collected in June 2020, several weeks after reopening of schools following the initial seven-week lockdown in Germany. The study was conducted in five sessions, which were held in the school’s computer lab. At the beginning of each session, the researcher instructed participants about the tasks, while a teacher assisted in ensuring a setting comparable to class examination (silence, no copying from neighbors etc.). Throughout all sessions the order of tasks was fixed as follows: 1) self-reported usage patterns, 2) Monetary Choice Questionnaire, 3) Digital Addiction Scale, 4) control variables and 5) Brief Self-Control scale. One session lasted about 30 minutes. The study was approved by the Central Ethics Committee of the Freie Universität Berlin (approval no. 2020–005)

Addictive use of digital devices and delay discounting

To investigate the first hypothesis, initially the relationship between scores of the DASC and the LDR proportion was analyzed. A negative correlation (r = -0.28, p = 0.016) between the two variables was found. On average, the more often children chose the larger delayed reward, the less they addictively used digital devices. When breaking down the DASC into its nine subscales, delay discounting was significantly correlated with Withdrawal (r = 0.30, p = 0.014), Deception (r = 0.24, p = 0.043) and Mood Modification (r = 0.29, p = 0.010). Next, to control for possible effects of gender, age, years of ownership of digital devices and pocket money a regression analysis was performed with the control variables and the proportion of LDR choices as independent variables and the overall DASC score as the dependent variable. All assumptions for multiple regression analysis were met. As shown in Table 1 , the LDR proportion was the only significant predictor of scores in the DASC (β = -0.27, p = 0.032). The overall model yielded an R 2 of 0.10, F-statistic of 1.50 and p-value of 0.201. The similarity in correlation patterns of the natural log of the discount parameter k and the LDR proportion indicated that the latter measure was accurately assessing participants’ delay discounting. Additionally, self-reported usage of digital devices was positively correlated to the DASC score (r = 0.37, p = 0.001), but no relationship was found with delay discounting (r = 0.09, p = 0.465). Self-reported usage was positively related to the DASC subscales Preoccupation, Withdrawal, Displacement, Relapse and Problems, the latter showing the strongest correlation of r = 0.41 (p<0.001). Table 2 shows bivariate correlations of the main variables in this study. The breakdown of the DASC and its correlations with key variables can be found in S2 Table .

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https://doi.org/10.1371/journal.pone.0253058.t001

https://doi.org/10.1371/journal.pone.0253058.t002

Addictive use of digital devices and self-control

The second hypothesis required an investigation of the relationship between addictive digital device use and self-control. There was a strong negative correlation between self-control and the DASC score (r = -0.69, p<0.001). On average, the higher children’s scores were on the brief self-control scale the less they tended to addictively use digital devices. Correspondingly, self-control was negatively associated with all nine subscales of the DASC, having the strongest relationship with Tolerance (r = -0.65, p<0.001). Furthermore, self-control was also correlated to the LDR proportion (r = 0.25, p = 0.034), indicating possible confounding between addictive behavior and delay discounting. Therefore, a regression analysis was performed with the control variables (gender, age, years of ownership of digital devices and pocket money), self-reported usage, self-control as well as the proportion of LDR choices as independent variables and the overall DASC score as the dependent variable. As displayed in Table 3 , self-control (β = -0.58, p<0.001) and self-reported usage (β = 0.32, p = 0.003) were the only significant predictors of the DASC score. Notably, with the variable self-control in the model the LDR proportion no longer significantly predicted the DASC score (β = -0.15, p = 0.100). The overall model’s R 2 was 0.59 with an F-statistic of 13.21 and p-value of <0.001.

https://doi.org/10.1371/journal.pone.0253058.t003

Addictive use of digital devices and academic success

Lastly, for hypothesis 3 the relationship between addictive use of digital devices and performance in the classroom was examined. The DASC scores and grade averages were not correlated (r = 0.15, p = 0.197). However, there was a positive correlation between self-reported usage of digital devices and grade average (r = 0.43, p<0.001). On average, the more time was reportedly spent with digital devices the worse the academic performance. Furthermore, self-control was also correlated to academic success (r = -0.31 p = 0.007). Again, to take into account possible effects of gender, age, years of ownership of digital devices and pocket money a regression analysis with the latter variables, self-control and self-reported usage predicting grade average was performed. As displayed in Table 4 , self-control (β = -0.30, p = 0.009) and self-reported usage (β = 0.26, p = 0.040) were the only significant predictors of grade average. R 2 of the overall model was 0.31 with an F-statistic of 4.89 and p < 0.001. See S1 Appendix for robustness checks related to self-reported usage.

https://doi.org/10.1371/journal.pone.0253058.t004

The main goal of this present study was to investigate the relationship between children’s addictive use of digital devices and delay discounting. Consistent with previous studies on more established addictive behaviors among adolescents and adults (e.g. substance abuse, gambling, smoking), children who discounted future rewards more heavily tended to more addictively use smartphones, tablets and computers. Children showing more addictive use seem to be drawn to the immediate rewards of watching videos, gaming or social media in spite of negative long-term consequences of that behavior. The implications of this finding are twofold. First, digital addiction as a fairly new concept compares to other problematic behaviors in the context of delay discounting, suggesting its further investigation as a potentially diagnosable addiction in the future. Second, children as young as ten years old may show problematic behavior towards digital devices which has previously been observed only in adolescents and adults.

Another question addressed by this study was which role self-control played in the relationship between delay discounting and addictive use of digital devices. The regression analysis yielded that self-control confounded the relationship between the two main variables, implying that steeper discounters tended to more addictive use of digital devices due to differences in self-control. The present data suggest that children’s ability to control thoughts and emotions is the mechanism underlying the association between delay discounting and addictive use and thus is a superior predictor of problematic behavior towards digital devices. Existing studies focusing on smartphone use and delay discounting found mixed results on a mediating role of self-control (mediation see Wilmer & Chein [ 45 ], no mediation see Schulz van Endert & Mohr [ 24 ]). Due to the cross-sectional and observational nature of the data, no conclusion with regard to mediation can be made in this present study [ 46 ]. Nonetheless, the moderate to strong association between self-control and addictive digital device usage found in this present study at least indicates that children who are better able to regulate thoughts and emotions tend to show a lower degree of addictive use of smartphones, tablets etc. Although the present data do not allow for firm conclusions on the direction of causality, it seems that self-controlled children resist the temptation of continued engagement with digital devices before negative effects (conflict, mood modification etc.) occur. Children lower in self-control on the other hand seem to be less able to refrain from gaming, watching videos or chatting despite recognizing adverse consequences of that behavior. Considering previous findings on the positive effect of self-control training on preventing internet addiction [ 47 ], the present finding hints at the importance of developing children’s self-control in order to lower the risk of developing addictive behaviors towards digital devices.

The third association of interest was that of addictive digital device use and academic performance. Based on previous findings with other problematic behaviors, a negative relationship between these two variables was hypothesized. However, no significant association was found in this current study. Instead, self-reported usage turned out to be a significant predictor of grade average; the longer children reported to use digital devices the worse their grade average tended to be. This pattern of results suggests that children need not show symptoms of addiction, but that screen time alone may already implicate lower academic achievement. The latter finding is in line with related studies which investigated the relationship between smartphone use and students’ academic success [ 48 ]. The classical interpretation for this result is that more screen time implies less study time, which leads to worse classroom performance. However, due to the correlational nature of results in this current study, the opposite causal direction cannot be ruled out. Last but not least, in line with previous large-scale studies [ 43 , 44 ], self-control was found to be a significant predictor of academic success. This highlights once more the key role of children’s self-control in achieving better grades already in elementary school.

The findings of this study need to be seen in light of several limitations. First, despite the (partially highly) significant results, the sample was limited in size and stemmed from one elementary school. Future studies should investigate samples from different cities and countries to allow for higher generalizability of results. Second, key variables (addictive use of digital devices, self-control, usage duration of digital devices) in this study were elicited using self-report questionnaires. While this method is standard practice in fields such as addiction or personality research, self-estimations of screen time have been shown to diverge from actual data [ 49 ]–a phenomenon which is likely amplified due to the young age of participants. To reduce response biases, future studies might include additional sources of reports (e.g. parents, teachers or peers) or even actual screen time data, as shown in e.g. Schulz van Endert & Mohr [ 24 ]. Third, due its novelty the DASC has not yet undergone extensive validation yet. Recent research has highlighted the importance of repeated validation of psychometric scales [ 50 , 51 ], which is why the results of the DASC should be interpreted tentatively at this stage. Fourth, the Monetary Choice Questionnaire is an efficient but—compared to more extensive alternatives—less sensitive instrument to assess delay discounting [ 52 ]. For example, it does not include intertemporal choices in which both rewards are given at different points in the future, which bears the risk of overweighting present bias [ 53 ]. Alternatively, adjusting delay discounting tasks, e.g. as proposed by Koffarnus & Bickel [ 54 ], could be used in future studies. Fifth, this study presented correlational results, which do not allow for causal interpretations. Looking at the reported association between self-control and addictive use of digital devices, one cannot determine using the present data whether a lack of self-control causes more addictive use or whether more problematic engagement with digital devices decreases self-control. Such conclusions may only be drawn from longitudinal or experimental studies, which are greatly needed in the future.

This study highlighted the importance of studying and monitoring the use of digital devices in children as early as at elementary school level. 10- to 13-year-olds may already show problematic behavioral patterns which have so far been only observed in older individuals. Furthermore, the central role of self-control in the context of addictive behavior as well as academic success was further underlined in this study. As experiences and influences in childhood greatly impact the trajectory of a person’s entire life, researchers, politicians, educators and parents/guardians are well-advised to closely observe the impact of omnipresent digital devices on children and to assist in the development of traits which promote their well-being in the present and in the future.

Supporting information

S1 table. descriptive statistics of key variables..

https://doi.org/10.1371/journal.pone.0253058.s001

S2 Table. Correlations between DASC subscales and key variables.

https://doi.org/10.1371/journal.pone.0253058.s002

S1 Appendix. Additional correlations.

https://doi.org/10.1371/journal.pone.0253058.s003

S2 Appendix. Mediation analysis.

https://doi.org/10.1371/journal.pone.0253058.s004

S1 Dataset. Raw data from the questionnaires.

https://doi.org/10.1371/journal.pone.0253058.s005

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Cover Story

Treating the misuse of digital devices

Psychologists are spearheading efforts to help wean people off technology

By Rebecca A. Clay

November 2018, Vol 49, No. 10

Print version: page 76

• Digital Impact
• Social Media and Internet
• Video Games

People’s love of social media, emails and texts has created a new category of tech users: "constant checkers," who relentlessly scan their smartphones, computers and tablets for the next wave of messages. And it is fueling some people’s anxiety. According to APA’s 2017 Stress in America survey , 43 percent of Americans qualify as constant checkers and almost a fifth of Americans report that technology use is a very or somewhat significant source of stress for them.

Increased stress is just one of the negative side effects that can come with too much technology use. Problematic smartphone use—addiction-like behavior in which excessive smartphone use results in negative outcomes in daily life—has been linked with depression and anxiety in a review of the literature by University of Toledo psychology professor Jon D. Elhai, PhD, and colleagues ( Journal of Affective Disorders , Vol. 207, 2017). "We can’t determine cause and effect, because most of the studies were correlational," says Elhai.

And while problematic device use in general does not yet qualify as an addiction, there is enough evidence about internet gaming in particular that the World Health Organization (WHO) added gaming disorder to the latest update of its International Classification of Diseases, and the American Psychiatric Association lists it as a condition that warrants further study in the latest version of the Diagnostic and Statistical Manual of Mental Disorders. In response to these controversial moves, APA’s Div. 46 (Society for Media Psychology and Technology) issued a statement expressing concern over WHO’s decision, noting that the research base is still insufficient; APA’s Div. 50 (Society of Addiction Psychology) created a task force to come up with a response.

In the meantime, a growing number of psychologist-led efforts aim at helping people develop healthier relationships with technology.

Children’s media use is of special concern. A 2017 United Nations Children’s Fund (UNICEF) report found that children under 18 represent a third of all internet users globally. And adolescents and young adults ages 15 to 24 are the most connected cohort, with 71 percent online versus just 48 percent of the overall population.

APA has issued guidance for promoting healthy technology use for children, which emphasizes the need for parents to discuss the benefits as well as the risks of technology with their children. The guidelines urge parents to monitor the websites their children are visiting, teach good online citizenship and discuss digital decision-making. APA CEO Arthur C. Evans Jr., PhD, says that the association "is concerned about the increasing amount of time children are spending on digital devices" and that APA is examining psychology’s role in technology development.

Now, a new Device Management and Intelligence Committee of Div. 46 is developing guidance for the public and psychologists on device and social media use. The document will address such topics as good online citizenship on social media and recovery from online embarrassment. One key concern is "absent presence"—the phenomenon of being physically present with other people but paying more attention to a phone or other device than to them, says Joanne Broder-Sumerson, PhD, a committee co-chair.

"One of our taglines is ‘Unplug and hug,’" she says. "Technology helps facilitate our relationships with people far away, but not the people sitting next to us."

Of course, screen time isn’t always a negative. In one study, Facebook use was associated with increased face-to-face communication, especially for introverts ( Psychology of Popular Media Culture , online first publication, 2017). Facebook may help introverts develop trust and rapport in a less threatening environment before they venture into real-life relationships, speculates lead author Alexander Spradlin, PhD, an instructor in the department of psychology at Washington State University.

Other psychologists are developing measures that clinicians can use to assess whether patients have a problematic relationship with digital technology. Sarah E. Domoff, PhD, an assistant professor of psychology at Central Michigan University, has developed and validated the Problematic Media Use Measure, which clinicians can use to assess whether screen-based media use is causing difficulties for children ages 4 to 11 ( Psychology of Popular Media Culture , online first publication, 2017).

"If a child becomes upset or has a meltdown when a parent tries to take away a tablet or screen, that could indicate a problem," says Domoff, who is now developing a similar assessment tool for older children.

Other red flags include disruption of family events by video games or other media, missing out on opportunities because of screen time and screen time as the only activity a child looks forward to.

For kids whose results indicate a problem, Domoff encourages a gradual weaning from devices coupled with alternative activities that help fill gaps in a child’s development. If a child is excessively gaming, for instance, Domoff recommends that parents provide opportunities to engage with peers offline. A family approach to reducing screen time is key, she adds. "A lot of times parents are also struggling with putting down their phones," she says, adding that her clinic at the Center for Children, Families and Communities treats children with problematic screen media use and serves as a practicum site for training future psychologists on how to assess and treat the problem.

Helping pediatricians screen for problematic digital media usage during well-child visits is the goal of the Media and Child Health Clinician Toolkit , developed by research scientist David Bickham, PhD, and colleagues at Boston Children’s Hospital’s Center on Media and Child Health.

The toolkit helps pediatricians, parents and children assess whether media use is contributing to such problems as aggression, obesity and attention deficit.

"Rather than saying, ‘Are you having trouble with media use?’ it is ‘Do you have these behaviors or experience these things, and how might media use be related to that?’" explains Bickham, also an instructor in pediatrics at Harvard Medical School.

The toolkit tries to get at the complexity of children’s media use and its impact, says Bickham, explaining that the problem may be either the content a child is exposed to via media or the amount of time a child spends on a device. "There are kids who are playing video games all night and missing school," says Bickham. "There are kids who are viewing a lot of porn and being exposed to violent porn. There are information seekers who get drawn down rabbit holes of Wikipedia and YouTube, which leads to huge amounts of use."

Adults often have different media use problems than their children, says Paula Durlofsky, PhD, a private practitioner in Bryn Mawr, Pennsylvania, who has seen the number of adults with social media concerns soar in recent years.

Durlofsky urges these adult patients to reflect on what they hope to get out of social media, whether it is new friends, deeper connections or networking. She counsels patients to use social media to enhance offline friendships, not replace them. She also advises patients to find alternative responses to feelings of boredom or whatever emotion is driving overuse of social media and to schedule social media breaks.

Specialized treatment clinics are also springing up. In Santa Monica, California, Don Grant, PhD, who co-chairs the Div. 46 Device Management and Intelligence Committee, runs an intensive outpatient program for adolescents called Resolutions Teen Center, which combines device-management help with mental health and substance use treatment. In addition to therapy, he encourages patients to connect with the present—to look at the ocean instead of taking a selfie with it, for instance. Meanwhile, a parents’ group he runs helps families create healthier household media environments.

"You can write ‘LOL’ all you want," says Grant. "It’s not going to have the same effect as laughing with people."

APA Digital Guidelines: Promoting Healthy Technology Use for Children https://www.apa.org/topics/healthy-technology-use-children

Media and Child Health Clinician Toolkit http://cmch.tv/clinicians

APA Div. 46 (Society for Media Psychology and Technology) www.apa.org/about/division/div46

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• Parenting Children in the Age of Screens
• 1. Children’s engagement with digital devices, screen time

Table of Contents

• 2. Parental views about YouTube
• 3. Parenting approaches and concerns related to digital devices
• 4. Parents’ attitudes – and experiences – related to digital technology
• Acknowledgments
• Methodology

The use of the internet and the adoption of mobile devices like smartphones and tablets is widespread, and digital technologies play a significant role in the everyday lives of American families. This is also true for children, who may begin interacting with digital devices at young ages.

In March, Pew Research Center asked parents a series of questions about their children under the age of 12 and how they engage with digital technologies.

The most common device parents say their young child engages with is a television, with 88% of parents saying their child ever uses or interacts with a TV. Smaller – yet still large – shares of parents say their child ever uses or interacts with a tablet computer (67%) or a smartphone (60%). Some 44% of parents of young children say their child ever uses or interacts with a desktop or laptop computer or a gaming device.

There are substantial age differences in the types of devices parents report their child engaging with. For example, 73% of parents with a child age 9 to 11 say their child uses a desktop or laptop computer, compared with 54% of those whose child is age 5 to 8 and just 16% of those with a child younger than 5. The use of gaming devices follows a similar pattern: 68% of parents with a child age 9 to 11 say their child uses this device, compared with 58% of those with a child age 5 to 8, one-quarter of those whose child is age 3 to 4 and 9% of those with a child age 2 or younger. Similarly, 80% of parents with a child age 5 to 11 say their child uses or interacts with a tablet computer, compared with 64% of parents with a child age 3 to 4 who do this and 35% with a child or a child age 2 or younger.

These differences by the child’s age are less pronounced when other devices are considered. For instance, parents with a child age 9 to 11 are more likely to say their child engages with a smartphone (67%), compared with parents with a child age 5 to 8 (59%) or age 2 or younger (49%). Parents with a child age 3 to 4 fall in the middle – 62% say their child uses or interacts with a smartphone.

Parents of the youngest children are less likely to say their child engages with a television, but majorities of all age groups still report doing so – 74% of parents with a child age 2 or younger say their child uses or interacts with a television, compared with 90% or more of parents with a child in somewhat older age groups.

More than one-third of parents with a child under 12 say their child began interacting with a smartphone before the age of 5

Among the 60% of parents who say their child younger than 12 ever uses or interacts with a smartphone, six-in-ten say their child began engaging with a smartphone before the age of 5, including roughly one-third (31%) who say their child began this before age 2 and 29% who say it started between ages 3 and 4. Some 26% of parents whose child uses a smartphone say the smartphone engagement began between the ages 5 and 8. This share falls to just 14% for parents with a child age 9 to 11. 5

Nearly one-in-five parents of a child younger than 12 say their child has their own smartphone

Aside from just using and engaging with a smartphone, some children younger than 12 years old have their own device. Nearly one-in-five parents of a child 11 or younger (17%) say that their child has their own smartphone.

There are differences in child smartphone ownership by parents’ education level and the age of the child. Parents with a high school education or less are twice as likely as parents who are college graduates to say their child has their own smartphone (21% vs. 11%). Parents with some college education fall in the middle, with 19% saying their child under the age of 12 has their own smartphone.

Parents with somewhat older children are also more likely to say their child has their own device. For example, 37% of parents of a child age 9 to 11 say their child has their own smartphone, compared with 13% of those with a child 5 to 8, 5% of those with a child 3 to 4 and 3% of those with a child who is 2 or younger.

Among the share of parents who say their child under age 12 has their own smartphone (17%), roughly half (51%) say this child was between the ages of 9 and 11 when they got their own device, and about one-third of parents (35%) say this happened between ages 5 and 8. Much smaller shares of these parents say the same for younger ages.

Majorities of parents of children who have their own smartphones and are under the age of 12 say making it easy for their child to contact them (78%) and being able to easily get in touch with their child (73%) are major reasons their child has their own smartphone.

Far fewer parents with a child in this age range say that major reasons their child has their own smartphone are to have something to keep them entertained (25%) or because their friends or classmates have a phone (6%). About one-in-ten parents of a child ages 5 to 11 (9%) say that a major reason this child has their own smartphone is to do their homework.

More than a third of parents say their child under the age of 12 uses or interacts with a voice-activated assistant

In addition to details about smartphone engagement and ownership, parents of children under 12 were also asked some questions about their child’s engagement with voice-activated assistants.

Roughly one-third of parents of a child age 11 or younger (36%) say their child ever uses or interacts with a voice-activated assistant such as Apple’s Siri or Amazon Alexa. There are differences in a child’s interaction with this type of device by age of the child, race or ethnicity, parent’s level of educational attainment and community type.

Parents who have an older child, between the ages of 5 and 11, are more likely than parents with a child age 3 to 4 or age 2 or younger to say their child uses or interacts with a voice-activated assistant.

Among parents with a child under age 12, those with lower levels of formal education are less likely to say their child engages with a voice-activated assistant – 26% of parents with a high school education or less say their child does this, compared with 38% of parents who have some college education and 42% of college graduates.

White parents are more likely than Hispanic parents to say their child ever interacts with or uses a voice-activated assistant. Those living in suburban locations are also more likely than those living in rural communities to say their child does this.

Among the 36% of parents of a child under the age of 12 who say their child ever uses or interacts with a voice-activated assistant, majorities say their child uses this device to play music (82%) or get information (66%). Smaller shares of these parents say their child uses a voice-activated assistant to hear jokes (47%) or play games (30%).

The use of a voice-activated assistant varies substantially by the age of the child for all but one of these activities – with older children being more likely to use these functions. Fully 78% of parents with a child age 5 to 11 say their child uses a voice-activated assistant to get information, compared with 29% of parents with a child age 4 or younger who say the same.

When it comes to using the voice-activated assistant to hear jokes, more than half of parents (54%) with a 5- to 11-year-old child say their child uses a voice-activated assistant to do this, compared with roughly one-quarter of parents (24%) with a younger child, 4 or younger, who say the same. And more than twice as many parents with a child age 5 to 11 say their child uses a voice-activated assistant to play games compared with parents with a child age 4 or younger (34% vs. 16%). There is no difference by age of child when it comes to parents saying their child uses a voice-activated assistant to play music.

Some parents of a child under 12 are concerned about the data collected by these voice-activated assistants. Among parents of children under age 12 who say their child ever uses or interacts with a voice-activated assistant, about four-in-ten (39%) say they are at least somewhat concerned about the data these assistants collect about their child, including 11% who say they are very concerned. But a majority of parents say they are not too (47%) or not at all (14%) concerned about the data voice-activated assistants collect about their child.

A portion of parents say their child younger than 12 uses social media; use varies by age of child, parents’ level of education

Relatively few parents of a child age 11 or younger say that, as far as they know, their child uses social media, though shares are higher for parents of children ages 9 to 11. Despite most social media sites having age guidelines in place, which usually restrict children younger than 13 from joining, some 13% of these parents say their child uses TikTok and 10% say their child uses Snapchat. Just 5% say their child uses Instagram, and even fewer (3%) say their child uses Facebook. Some 7% of parents say their child uses some other social media site. There are differences in child social media use by age of the child and parents’ level of educational attainment.

Parents with a child age 9 to 11 are more likely than parents with a child in younger age groups to say their child uses any of the social media platforms asked about in the survey. For example, three-in-ten parents of a child age 9 to 11 say their child uses TikTok, compared with 11% of parents of a child between the ages of 5 and 8 and 3% of parents of children ages 4 and younger.

Parental education level is also a factor in their child’s use of certain social media sites. For example, parents of a child age 11 or younger with a high school education or less are more likely than those with a postgraduate degree to say their child uses TikTok (19% vs. 6%). This trend also holds for a child’s use of Snapchat and Facebook.

Parents are more likely to say their child under age 12 uses a social media site if this child has their own smartphone. For instance, 42% of parents who say their child has their own smartphone also say their child uses TikTok, and 31% say their child uses Snapchat. These shares fall to 10% or less across all platforms for parents who say their child does not have their own smartphone.

CORRECTION (Aug. 5, 2020): An earlier version of this report included a chart with a headline that read “Roughly half of parents say their child got their own smartphone between the ages of 9 and 11.” This headline has been edited for accuracy to explain that this was only among those whose child had their own smartphone. The chart, now titled “51% of parents whose young child has their own smartphone say this child got the device between the ages of 9 and 11,” was also edited so that all figures displayed in the bar chart are scaled correctly.

• When all parents with a child under the age of 12 are considered, 35% say their child began engaging with a smartphone before the age of 5, 15% say this happened between the ages of 5 and 8, and 8% say their child began engaging with this device between the ages of 9 and 11. ↩

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A qualitative case study about overuse of digital play at home

Nesrin işıkoğlu.

1 Department of Early Childhood Education Program, Pamukkale University, Denizli, Turkey

Abdullah Atan

Serkan aytekin.

2 Department of Primary Education Program, Pamukkale University, Denizli, Turkey

Associated Data

(data transparency)

(Not applicable)

The prevalence of digital play devices, including tablets and smartphones, has led to overuse among some young children. The purpose of this research is to examine the overuse cases among young children. Participants of this qualitative case study were five children aged five to seven years, their parents, and a psychiatrist. The data were mainly obtained through semi-structured interviews. Interviews were further supported by close observations, a collection of digital play diaries, as well as an interview with a psychiatrist who specializes in childhood gaming addiction. Then data analyzed using content analysis techniques. The results are presented in five themes: practices, reasons, feelings about overuse, restricting playtime, and content. The first three themes described the nature of the overuse, while the last two themes described the parents’ efforts to restrict their children’s digital play. Findings revealed that the joint effects of different factors triggered children’s overuse, that parents and children felt a range of emotions from happiness to aggression, and that parents’ restrictive mediation strategies were mostly infective.

Introduction

In today’s digital societies, many young children have benefited from digital devices designed for education, entertainment, and play. The use of digital devices including tablets, smartphones, and electronic toys has increased significantly among early ages in Turkey (TurkStat, 2017 ). Recently, the digital game market was 878 million dollars (Digital Game Report, 2019 ) and the market is growing around 10 % each year in Turkey (ByNoGame, 2018 ). Approximately 90 % of the Turkish population has home internet access 70% of internet users play online games (Ilgaz Büyükbaykal & Cansabuncu, 2020 ; TUIK, 2020 ). A recent cross-cultural study compared results from Turkey, the USA, South Korea, and China revealed that the screen time of preschool children also varied from 2 h to 4 h per day and in all four countries 4–6 years old children spend the longest time watching TV, tablet usage took second place in USA, Turkey, and China, with smartphone usage second highest in South Korea. It is important to note that these research findings should not be generalized to the entire countries, Turkish children spend approximately an hour playing with computer /tablet games and forty minutes with smartphones (Isikoglu Erdogan, Johnson, Dong, & Qiu, 2019 . Evidence revealed that Turkish preschool-age children interacted with screens for more than 30 min a day recommended by the Green Crescent Foundation, the national institution fighting technology addiction (Yeşilay, 2020 ). As the context of the research in Turkish culture, playing with young children is perceived as a valuable way of spending time (Ivrendi & Isikoglu Erdoğan, 2015 ). In a recent cross-cultural study, Turkish parents valued play as an important medium for children’s learning and development (Ivrendi, Cevher-Kalburan, Hansen Sandseter, Storli, & Holla Sivertsen, 2019 ). Newly emerging digital play is also noteworthy since the use of digital devices as play tools have increased significantly among early ages in Turkey (TurkStat, 2017 ).

Although there is little evidence, children’s screen time had increased and their physical activities decreased during the COVİD-19 pandemic (Guan, Okely, Aguilar-Farias, Del Pozo Cruz, Draper, El Hamdouchi, Florindo, Jáuregui, Katzmarzyk, Kontsevaya, Löf, Park, Reilly, Sharma, Tremblay, & Veldman, 2020 ). The ubiquity of such devices in the hands of children has created an emergent phenomenon called “digital play,” which refers to using technologies as a primary form of play (Marsh, Plowman, Yamada-Rice, Bishop, & Scott, 2016 ). Digital play includes playing digital games and applications, watching, and making videos, and taking pictures. This new form of play has become an increasingly popular and cultural context for young children (Edwards, 2018 ; Işıkoğlu Erdoğan, 2019 ; Heider & Jalongo, 2015 ). Currently, researchers argue that digital play is just a play for children, and their traditional play activities and engagement with digital play become interwoven (Bird & Edwards, 2014 ; Edwards, 2018 ; Marsh, 2010 ).

On the other hand, there is an ongoing debate about nature and the role digital play may have in the lives of children. Some researchers argue that children need “free play”; a type of play that is divorced from watching and interacting with screens or digital tools (Jeong, Kim, & Lee, 2017 ; Levin, 2015 ; Slutsky, Slutsky, & DeShetler, 2014 ). Others claim that digital play has positive contributions, such as relaxation, abreaction, entertainment, learning and the development of many skills (Biddiss & Irwin, 2010 ; Marsh et al., 2016 ; Prot, Anderson, Gentile, Brown, & Swing, 2014 ). Existing research about the value of digital play indicates that digital play supports children’s problem-solving, reasoning, analysis, and decision-making skills (Kim & Smith, 2017 ), academic achievement (Barr, 2019 ; Lieberman, Fisk, & Biely, 2009 ), hand-eye coordination, and motor skills (Lin & Hou, 2016 ). Studies also caution that the content of the games and adult mediation has important roles in gaining such advantages. However, a growing body of evidence links long hours in front of a screen to serious risks for young children including game addiction, violence, cyberbullying, and obesity, as well as an increased potential to view sexual content (Balkam & Dönmez, 2017 ; Livingstone, 2017 ; Neumann, 2015 ; Nikken & Schols, 2015b ).

Recently, the American Academy of Pediatrics (AAP, 2016 ) recommended that parents should avoid digital media use (except video-chatting) in children younger than 18 to 24 months and use less than an hour per day for children aged 2 to 5 years. Similarly, Turkish Green Crescent an official public organization founded to combat addictions such as alcohol, drug, and technology defined technology addiction as a situation in which an addict felt deprived to access digital devices. This organization also recommended no more than 30 min per day for children aged 3–5 (Yeşilay, 2020 ). In line with these recommendations, more than two hours of daily use of digital devices was considered as overuse in this study. Several studies have also shown that young children are often exposed to the screen for more than the recommended time (Işıkoğlu Erdoğan, 2019 ; Lauricella, Wartella, & Rideout, 2015 ; Montag & Walla, 2016 ).

In the past decade playing with digital tools has increased among young children, much of the research in this area approaches age, gender and parental issues as major factors that construct children’s play choices (Magladry & Willson, 2019 ). Whereas previous research mainly focused on adolescents or school-age children’s game habits, recent studies began to examine digital play for children under the age of eight and this research mostly emphasized that young children’s media use is mediated by parents and caregivers (Connell, Lauricella, & Wartella, 2015 ; Kucirkova, Littleton, & Kyparissiadis, 2018 ; Nevski & Siibak, 2016a ). Specifically, McDaniel and Radesky ( 2017 ) revealed that parents introduce digital media to their toddlers or pre-schoolers during family activities such as meals, doctor visits, or car drives. Again challenging behaviors and emotional dysregulation have been shared by parents as reasons for young children’s problematic digital media use (Domoff, Borgen, & Radesky, 2020 ). A child’s gender is an important factor concerning access to digital tools and parental mediation of digital play. Children in a Digital World Report stated that the global gap in internet use between boys and girls widening and girls from twenty-two low and middle-income countries has less access to smartphones than boys (UNİCEF, 2017 ). In the UK, Ofcom ( 2017 ) has reported that boys aged 3–4 years had a handheld/portable games player more than girls of the same age. A large survey study in the UK revealed parents of boys were more concerned about the health implications of their children’s digital media use (Kucirkova et al., 2018 ).

The parental role is particularly important during a child′s early life when parents are responsible for the majority of their child′s experiences. Parents influence their children’s play in terms of providing play materials, participating in games and taking time to play with them (Johnson & Christie, 2009 ). Drawing upon Vygotsky’s socio-cultural theory of human learning, parental guidance is understood to be an essential component in scaffolding or supporting, the learning outcomes of children (Bodrova & Leong, 2015 ). According to Vygotsky, if the child is given appropriate support in the zone of proximal development (ZPD), a space between what the learner can do independently and a zone requiring adult support, he or she will reach the level to complete that duty. Moving from this, parents need to guide children during play with digital devices. Similar to other forms of play, parents need to supervise, monitor and engage in children’s digital play. Within the ZDP, parents can play an important role in supporting the child’s use of digital devices, particularly in how to take precautions and to set limits, by actively teaching, suggesting, guiding, modeling, and cooperating (Isikoglu Erdogan et al., 2019 ; Nikken & Jansz, 2014 ; Selwyn, 2017 ).

Common parental digital mediation strategies include active, restrictive and technical mediation (Livingstone, Mascheroni, Dreier, Chaudron, & Lagae, 2015 ; Nikken & Schols, 2015a ; Wu et al., 2014 ). Active meditation involves practices such as talking about digital content and activities, sitting nearby and actively sharing the child’s play experiences. Restrictive mediation involves setting rules that limit time spent online, location of use, as well as directing content choices and activities. Technical restrictions contain technical tools to filter, restrict and monitor children’s digital activities (Livingstone et al., 2015 ). Studies focused on parental mediation delineate between parents who worried about the potential negative effects of digital devices tended to apply time and content constraints, versus parents who believed in the positive effects of technology and tended to use the tools interactively/cooperatively and preferred active guidance strategies (Nevski & Siibak, 2016a ). While mothers mostly implement restrictive guidance strategies, fathers take a more active role in the guidance process than the mother in the sense that digital tools provide new life and learning opportunities. Contrary to fathers, mothers focus on situations such as technical constraints (using passwords), monitoring (controlling browser history), and setting content and time rules to ensure girls’ online safety (Nevski & Siibak, 2016b ). Besides, Nikken and Jansz ( 2014 ) mention parental guidance processes such as active guidance, collaboration, monitoring, and restrictive guidance in children’s internet use. Research suggests that game addiction can increase in children when parents use digital tools as toys for children, and when they have followed inadequate guidance strategies (Park & Park, 2014 ). From this perspective, it is clear that parents can provide valuable digital experiences for their young children (Neumann, 2015 ). It is imperative, then, that parents learn how to use digital devices to encourage learning, enrich the play, and protect children from the potential risks of digital devices (Johnson & Christie, 2009 ).

Despite these facts, research in this area remains limited, especially on how the overuse of digital devices may directly affect the health and development of young children. Research in this area is mostly descriptive and is mainly conducted as investigations of social-cultural patterns and family factors related to the digital play (Bird & Edwards, 2014 ; Nevski & Siibak, 2016b ; Nikken & Schols, 2015b ). Moreover, the corpus of research on childhood digital device use is primarily focused on Western cultures (Lauricella et al., 2015 ). Therefore, this study expands a descriptive analysis of overuse cases by structuring interviews around children’s experiences of digital play and their parents’ guidance strategies. Interviews were further supported by close observations, collection of a digital play diary, as well as an interview with a psychiatrist who specializes in childhood gaming addiction. Close examination of overuse cases will provide significant contributions in understanding the nature of overuse and offer valuable suggestions to this issue, as well as providing potential applications specific to the context of overuse in Turkish society. The present study aims to examine the overuse cases among young children. Three questions guide the investigation: (1) What is the nature of overuse? (2) What are the reasons for the overuse of digital tools? and (3) How do parents’ mediation strategies relate to the overuse? The answers to these research questions will be discussed from the perspective of sociocultural theory regarding the nature of overuse, reasons behind overuse, and parental mediation.

This study is framed as a qualitative case study of five young children who experienced excessive digital play. According to Yin ( 1993 ), a qualitative case study is appropriate to cover contextual conditions that are relevant to the phenomenon under study. In this research, overuse cases were examined within their family contexts.

Participants and Research Context

The criterion sampling method was used to select participant children and families. According to Patton ( 2002 ), critical situations can be a source of criterion sampling because they are rich in information. Accordingly, the following criteria were taken into account when determining the participants; (a) kindergarten-aged children who play with digital games for more than two hours per day; (b) kindergarten-aged children who were treated at University’s psychiatric clinic for game addiction.

Following institutional review board approvals, the purpose and process of the study was explained to six parents, all of whom had applied to the clinic for their children’s game addiction and related behavioral problems. At the end of these procedures, only one child and his/her parents volunteered to participate in this study.

Later, the researchers contacted the public kindergarten to recruit more participants. The administrator of the school sent prospective parents a short survey related to their children’s daily screen time. After identifying children who daily engaged in screen time for more than two hours, the parents were invited to participate in the study. At the end of this process, four children and their parents agreed to participate in the study. A total of five children and nine parents (4 mothers and 5 fathers) and one psychiatrist, from the clinic where a child was being treated for game addiction, participated in the study. In the study, legal permissions followed the framework of ethical principles, ensuring that the participants’ identities were kept confidential and that the design of the questions did not inadvertently reveal the identity of any individual(s). Following the initial completion of the study, the questions and the results of the study were shared with the participants.

Participant children were one girl and four boys aged 5 to 7 years old. Three of the participant children attended a half-day kindergarten, and two of them attended a full-time kindergarten. None of the children received special education or inclusion. All the children came from families in which parents were living together. Four of the parents had a high school diploma and five parents had a college degree. All parents worked outside the home in different occupations. The participant specialist was a professor in a psychiatric hospital, working in the department of child and adolescent mental health and illnesses.

Data Collection

The data were collected through interviews, observations, and documents (Merriam, 2009 ). Semi-structured interviews were held with five children, nine parents, and a specialist. Interviews with children were conducted in two stages on two different days by two researchers. During the interview session, while one researcher was interviewing the parent, the other interviewed and played with the child. In the first stage, one of the researchers visited the child’s house and met with the child and family. During the interview, the researcher played with the child and asked questions about what he/she likes to play? This was seen as necessary for the children to feel safe and comfortable, allowing the interview to be conducted at the desired level. In the second interview, the children were asked questions such as, “I want to play games on the smartphone, but I do not know what to play?” “What should I do?” “How do you feel playing with the tablet and the smartphone?” “What do you say to me when I play games on the phone or the tablet all my spare time?” “If all the phones, tablets and computers in our house were broken, how would that be?” “How do your parents play with you?” The interviews lasted approximately 15–25 min and were tape-recorded with the child’s permission. Working with the parent’s schedules and preferences, interviews were held in the children’s homes, the parents’ workplaces, or at the school.

Semi-structured interviews with parents were conducted to learn about their thoughts, attitudes, and practices about their children’s digital play. Interview questions focused on the parents’ thoughts about their child’s digital play, descriptions of their practices with digital tools, and their guidance strategies. Some of the sample questions: “Can you describe how your child starts to play with digital tools?” “How do you describe your child’s digital play?” “How do you guide your child’s digital play activities?” The interviews lasted from 30 to 45 min and were tape-recorded with the participants’ permission. Participants were informed of the confidentiality of the recordings and the interview transcripts.

Lastly, a semi-structured interview was conducted with the specialist. During the interview information about game addition, diagnosis and treatment, and the commonality of game addition in the early childhood period, provided a base of clinical characteristics commonly found amongst addicted children and their families. The interview lasted 45 min and was tape-recorded.

Observations

Participant observations were conducted to closely examine the children’s and their parent’s digital play practices, along with recording the types of digital devices that they owned and used daily. During the observation, parents and children were asked to play with their digital tools (tablet, computer or smartphone). Parent and child play behaviors were observed for approximately 20 min.

Digital Play Diaries

Within the scope of the study, the parents were asked to keep a digital play diary for one week. The diary contained information about the child’s digital play beginning and finishing times, name of the game, and the behaviors child exhibited while playing (such as screaming, raging, laughing, jogging, running, crying and looking).

In this case study, the researchers played an active role in the data collection and analysis process (Creswell, 2009 ). During data collection, the researchers tried to be as objective as possible and they were careful to not embed, imply, or suggest an answer to a question they asked the participants.

Data Analysis and Trustworthiness

Analyses of the data were carried out in four stages. During the first stage, two researchers independently reread each participant’s interview transcripts, observation notes, and collected documents. In the second stage, each researcher separately coded all the data. In the third stage, they compared their codes and categories to revise and resolve any differences. In the last stage, they identified and agreed upon the emerging themes, selected representative excerpts, and defined the categories within the themes (Seidman, 2006 ). Data source, method, and investigator triangulation (Patton, 2002 ; Stake, 2010 ) were employed to ensure that the information obtained was vigorously validated. Data source triangulation aims to compare the perspectives of all stakeholders’ points of view including children, parents, and specialists. Methodological triangulation was ensured by collecting information through interviews, observations, and documents. Through investigator triangulation, two researchers closely examined the data. The interrater reliability of the study was calculated by Consensus / (Consensus + Disagreement) and was determined as 80%. It is expected to have reliability calculations above 70% (Miles & Huberman, 1994 ) and so that interrater reliability of the study was ensured. For the transferability of the study findings, rich and detailed descriptions were created, and participant quotations were provided. Additionally, except for word processors, no other software was used in the qualitative analysis.

At the end of the detailed analysis of qualitative data, five major themes emerged: (1) practices about overuse, (2) reasons for overuse, (3) feelings about overuse, (4) restricting playtime (5) restricting content. These themes are described and discussed in the following sections.

Practices about Overuse

Personally owning at least one digital device and spending more than an average of two hours playing with these devices stood out as a primary indicator of overuse and was evident in all of the participant children. Home observations and interview results showed that all of the participant children had a tablet, two of them had a computer and a tablet and, from time to time, all of them used their parent’s smartphones. Parents’ reported that their children started to play digital games at around age 2. Digital play diaries kept by the parents indicated that the children played an average of 235 min (about 4 h) of digital play per day. With 164 min per day, Child 2 spent the least time, while Child 1 spent the longest time (480 min) on the digital play. Father 1 explained his son’s digital play as “ My son plays a lot on the weekends, maybe 10 hours in total. ” All participating parents agreed that their child played a lot with digital devices and they have had serious concerns about possible health risks including obesity, screen addiction, as well as eye and posture problems. Except for Child 1’s parents, who were recruited from the clinic, the other parents did not believe that their child’s digital device use was problematic.

Close examination of diary findings also indicated that the content of these games included strategy, education, violence, sports, and YouTube. All of the participant children watched YouTube videos every day. Children preferred various content on YouTube such as game videos, music, and cartoons. Four children often played strategy games such as Minecraft. Three children preferred to play violent games such as Grand Theft Auto (GTA), Shadow Fight, and Clash of Clans. Only two children preferred to play with educational games such as Alphabet blocks, Tangram, and Pipe Puzzle. The other two played with sports games such as a High Ball and Roll the Ball. Some of these games can be considered inappropriate because of violent content, inappropriate language, and advertisements.

Reasons for Overuse

In terms of reasons for overuse, the data revealed two main factors: (1) Children’s interest and; (2) Parental issues. First, the children, their parents and the participating psychiatrist confirmed that children were interested in playing with digital games and simply loved to play them. Children used the following expressions to describe their love of digital play such as “ I love to play with the tablet (Child3)” For some children, the digital play was their favorite form of play, and they preferred digital games more than playing with other things. They all shared a common perception that the child’s interest was the main reason for overuse.

Second, participants raised several other issues caused by overuse. These issues included believing in benefits, being a bad role model, a lack of time for their children, and using it as a reward. Although participant parents had different views, many stated that digital play provides certain benefits for their children and they were not opposed to it. Mother 1 summed up her views as, “ Well, for me, every game is useful. After all, they are all made for a purpose. You can learn something. Since my son is playing strategy games, these games are useful in my eyes .” Again, Mother 2 explained that digital games were useful for her daughter to learn chess and English. Logically, parents who believed that digital play was useful, allowed their children to overuse. Participant children highlighted that their parents were not good role models of technology use. For instance, Child 2 complained about her mother as “ Of course my mother, she always on the phone, always. Even in the bathroom. So I also play .” Similarly, Child 1 mentioned that he often played games with his father.

I downloaded a game and I played it once. I said to my dad, "Come and play with me". He said, "OK, let's do it". When he lost, he played again, and again, and again, because he loved it. Then I downloaded the game on his smartphone. And he didn't delete it. When I turned on the phone and the game was there. This means he likes it too. So I play as well as he does .”

The above comments suggest that children often replicate their parents’ behaviors. When the children observed their parents using digital devices, they thought, “if they play, why shouldn’t I?” Parents’ behaviors of playing games and sharing the excitement with their children fostered a desire amongst the children to play more with these games. Besides these issues, parents claimed that their lack of time had an important impact on their children’s overuse. Parents’ time is often consumed with other activities, (e.g. work, cleaning, cooking, commuting, etc.), they turn to digital devices to, in effect, “babysit” their child. These issues were reflected below:

My idea is to give it (tablet) to the child and you can spend a day without any problems. More precisely it will be for me, not for the child… I think it is necessary to spend good quality time with children. Just give it to the child and say “play with it.” The child may have a lot of fun, but it is not obvious how the child will be affected in the future. Everybody says that it will be bad.” (Father 2).

The above comments suggest that parents tended to use tablets for keeping their child occupied and quiet. Parents perceived digital play as a helper or sitter. Even though they thought that overuse could be harmful to their child, they chose to take advantage of the convenience of digital play. Interestingly, instead of allocating playtime for his son, Father 1 stated, “ Loneliness is the real problem here. Loneliness. I wish he had a brother. ”

The other parental issue was using digital play as a reward. For instance, Mother 3 expressed “ if you behave well, you can play it (tablet). ” Similarly, Father 5 reported using expressions such as “ if you eat your meal, you can have it .” This pattern was particularly present with parents who attempted to modify the child’s behavior by using digital play as a reward. These behaviors raised the interest and penchant to overuse in children already predisposed to this type of play. Inadvertently, the parents supported the overuse of their children.

Feelings about the Overuse of Digital Play

Participants mainly expressed various emotions related to digital play including fun, happiness, anger, sadness, fear or uneasiness. Playing digital games has caused them to experience a variety of emotions, from happiness to anger. For example, Child 5 expressed his feelings as, “ I get crazy if I win a very difficult game. I feel really happy .” At the same time, observational recordings of the same child captured him screaming while winning a game. Along with positive emotions, some children expressed negative emotions during digital play. Child 4 stated, “ I usually feel uneasy when I cannot win ”. Child 2 expressed more negative feelings by stating that, “ I feel angry, furious and I throw the tablet. ” Home observations of Child 4 also indicated negative feelings, such as hitting the screen. Besides the frustrations of losing a game, the violent content of the games produced another source of negative emotions for the children. Child 3 expressed his feelings as “ I’m afraid, it’ll come into my dream ”, while Child 5 said that, “ if I use it too much, I become a game addict, I become hypnotized ”. The participant psychiatric specialist summed up the relationship between playing violent games and the production of negative feelings:

When the content of the games is related to violence and fear, the anger increases in children's social lives, relations with the family deteriorate and aggression tendencies may increase in later periods. The intense experience of negative feelings can also have negative effects on family relationships and other social behaviors .

Parents expressed different problems related to negative emotions. According to parents, they often had arguments with their child, or even with their spouse, due to the setting of time limits and rules about the digital play. Mother 4 stated, “ No matter what, we do not allow him to sit too close to the screen. I mean, there are health risks here. So I frequently warn my child and we constantly argue. ” Father 5 expressed that sometimes setting time limits caused negative emotions not only with the child but also within the whole family.

Sometimes we all get nervous. For example, my wife slapped him because of not quitting the game. But my wife’s reaction was very wrong. I know she got very mad. But she shouldn’t have done it. So I got mad at her and then we fought .

Like their parents, children also voiced their complaints about negative emotions that resulted from the imposition of rules on game playing. Children felt a strong need to express that parent should treat them with respect and tolerance, as exemplified in the following statement:

While I am playing with my tablet, mom says “you played too much”. Even before half an hour, she says angrily “Stop playing the tablet.” She never says, “Can you please stop playing? So I feel angry at her.(Child 2)

The above comments reflect that overuse of digital play can cause different emotions ranging from happiness to aggression. Such comments indicate that digital play, which is expected to give happiness and pleasure to children, can cause negative feelings for both children and parents when used excessively and inappropriately. Even the children expressed negative emotional reactions when playing digital games because they had played for an excessive amount of time and had become overly involved in the game.

Restrictive Strategies for Screen Time

All of the participant parents voiced a common concern that their children spent too much time engaged in digital play. They explained some strategies to reduce their child’s digital playtime. These were setting time limits, reward-based managements, blocking or banning digital play, punishment, and redirecting to alternative activities. During home observations, the parents usually told their children how long they could play with digital games. Although setting time limits was the main strategy for parents, each family used various periods for digital play. For instance, Father 5 stated;

We're keeping track of time such as 15 minutes. We are showing the clock because he doesn't know how to read the clock. We are saying, “You're gonna play until that long line is on ten. Then, you're gonna stop playing with the tablet . Interviewer: When you tell him to stop, does he stop playing? It takes very long. He sometimes begs, “Please dad let me play until the game is over. Sometimes, he is not stopping. We often argued about the tablet. In some cases, I have to take the tablet by force. He cries when he gets forced .

The above comments reflected the fact that setting time limits were not easy for these parents. Children at this age are not cognitively mature enough to be responsible for self-determining the time restrictions. Perhaps, it was not a developmentally appropriate expectation from a 5-year-old boy to read the clock and stop playing by himself. Again, forcing the child or removing the tablet was not considered a positive discipline. While some parents also reported that they punished their child for not quitting the game, others yelled at them. For example, Mother 2 expressed, “ Sometimes I yell at him when he doesn’t stop playing. Sometimes I raise my voice ”. Father 2 mentioned that “ When it is necessary, I warn him with a loud voice ”. Despite all these strategies to set time limits, parents have accepted that such efforts can be futile. As such, some parents simply tried to get their children to take short breaks while playing with the tablet. When these strategies did not work, parents said they had taken stricter measures. Father 5 declared, “ I remove the tablet and I do not allow him to play. It is hidden now .” Although parents tended to prevent their children from overusing digital devices, their restrictive mediation strategies were often ineffective.

Restrictive Strategies for Content

The content of digital play has emerged as another issue that parents were concerned about and tried to restrict. Echoing the concerns of many parents, Father 2 stated that he was aware of problems with the content of digital games. He expressed amazement over a violent version of an innocent game like chess.

In one digital chess game for children, when you capture a pawn with a queen, she takes its head off and everywhere soaks with blood. I don’t know if you have ever seen this. There was a chess game like this, a different version. We didn’t allow it. Because there were things like beheading, you know it is in everywhere. So we don’t allow such games. The content is important. (Father 2)

As in the example above, parents stated that they tended not to expose their children to violence in digital games. Although Father 4 shared similar views about violence in digital games, he interestingly explained that instead of completely banning fighting games, he allowed fighting games preconditioned on his observation, examination, and approval of the game content, stating that:

…but when my child plays fighting games and so on, I still look at the content of the game. I'm not saying you can't play a fighting game here. I don't let him play when I see something harmful” (Father 4)

Similarly, Father 1 checked the usage history after his child played with the tablet, “ I can control what games he played when I get the tablet. I mean, I can see and follow what he downloaded .” These comments revealed that there were differences in what parents understand about restrictive strategies about the content. Regardless of parental attempts to govern content, it appeared that children played games that contained various forms of inappropriate content, such as violence, deadly weapons, or blood. Child 3 openly expressed that, “ I take machine gun in GTA and kill the men .” Parents’ strategies to restrict content did not prevent the children from playing violent games. Likewise, checking the search history was insufficient to prevent children from seeing inappropriate content.

Discussion and Implications

This study uncovered a range of issues related to young children’s overuse of digital play at home from a non-Western cultural perspective. First, the study revealed that there were obvious features of overuse cases such as starting to play on devices at an early age, owning at least one device, spending a long time playing with it, and engaging in inappropriate content. Even though participant children aged five to seven and attending kindergarten, playing with digital devices dominated the lives of these children. Regardless of their age, they all preferred to play popular digital games, behave, and react similarly during their digital play. While the parents in this study recognized possible risks of overuse, their precautionary efforts were not been sufficient to regulate or prevent the situation. Plowman and Stephen ( 2014 ) argue that exploring children’s digital play demands attention to the context in which the engagement occurs. In these cases, participant children were guided without planning where, how and what to play and circumstances playing with digital devices.

Overuse created a range of emotions from happiness to aggression, and that increases in negative, and unregulated, emotional states often lead to conflicts among parents and children. The majority of participant children felt a sense of accomplishment and happiness when they won the games, whereas they felt anger and frustration when they lost the game. These reactions seem natural but, in social play, children regulate their emotions according to their peers’ reactions and this helps children to gain emotional regulation skills (Rubin, Coplan, Fox, & Calkins, 1995 ). In this study, children acted out their feelings rather than regulating them while playing with digital devices. The absence of these skills is a risk to children’s well-being. Again, our findings identified that overuse caused negative emotions resulting in conflicts between children and parents. On one hand, parents appreciated some of the positive aspects of digital play (e.g., baby sitter, keep them quiet), but on the other hand, they were aware of the risks (e.g., health, isolation). This dilemma made parents feel internally conflicted about their child’s digital play and they occasionally struggled to limit it. When inconsistencies between parents were added to these conflicts, including arguments with their children, disrespectful behaviors and punishments increased. In line with Hiniker, Suh, Cao, and Kientz ( 2016 ) our study indicated setting limits on young children’s digital can be a challenge for parents that can result in arguments and painful experiences. Therefore, parental education and support programs that provide concrete examples of solving conflicts about digital play habits, content, and time restrictions should be offered for parents. Specifically, pediatricians and early childhood institutions serve as a gatekeeper for providing such education programs or connecting parents to reach available programs.

Second, this study indicated that the joint effects of different factors triggered children’s overuse. Children’s interest in playing games and parental difficulties in mediating these desires had important impacts. Research studies have revealed similar results, indicating that children’s interest and enjoyment are important factors affecting the excessive use of digital games (Abdul Aziz, 2013 ; Heider & Jalongo, 2015 ; Naisbitt, Naisbitt, & Philips, 2004 ). A child’s interest, though, is not a sufficient cause for overuse. Several additional factors are contiguous to child interest, such as parental beliefs of digital play, their lack of time for their children, being a poor role model, and the allowance of digital playtime as a reward are all contributing factors to the phenomenon of overuse. These findings are compatible with previous research that found relations between parental factors and children’s screen time (Lauricella et al., 2015 ; Nikken & Schols, 2015b ). In this respect, examination and regulation of parental factors may be necessary to prevent children’s overuse (Chiong & Schuler, 2010 ; Wartella, Rideout, Lauricella, & Connell, 2013 ). Vygotsky ( 1978 ) theorized that play creates the “zone of proximal development” in which parents must negotiate their role in digital play to support children’s rich play experiences. Empowering parents to change these factors may be a useful strategy, including the dissemination of information about digital parenting that contains practices for reducing overuse.

Indeed, the emergence of digital overuse must be construed within what variously termed the digital era, the digital revolution, or the information age. Regardless of the choice of words, the digital era is one marked by disruptions to traditional economic and social practices. This analysis examines the effects of these disruptions concerning how specific technologies are produced for, and integrated into, the daily lives of children. Captured in this particular age of digital transformation, traditional forms of play have been disrupted in the lives of both children and their parents. This new generation of ‘digital parents’ wants to learn about the best practices for providing digital media to their young children (Livingstone et al., 2015 ). From a public health perspective, there is a strong need to have positive parenting programs or sharing lists of recommended imaginative, creative and educational sites and apps for parents (Özyurt, Dinsever, Çalişkan & Evgin, 2018 ). In dealing with the disruptions to traditional forms of play, parent training programs can provide a vital role in reducing parental screen time and increasing parent-child interactions.

Lastly, the results showed that parents mainly preferred restrictive mediation strategies to reduce the overuse of digital play activities. Research examining mediation strategies indicated that parents used a range of strategies from active to restrictive mediation (Nevski & Siibak, 2016a ; Nikken & Jansz, 2014 ; Nikken & Schols, 2015a ; Selwyn, 2017 ). These strategies included explaining to the children about rules and safety (active mediation), using educational and instructional programs with children (co-user), residing and observing when the child is using the tools (supervision /monitoring), and using filter programs (technical) (Nikken & Schols, 2015a ). It is not sufficient to use only restrictive mediation to overcome the risks of overuse. Rather than restrictions, or just active mediation approaches, experts recommend an approach that mixes restrictive and active approaches to guide their children’s media use (Livingstone et al., 2015 ). Parent-child discussions also enhance children’s critical thinking development, which can assist children in choosing between appropriate and inappropriate media content (Wu et al., 2014 ). It is also important to note that there were also inconsistencies amongst the participating parents’ behaviors about establishing rules about the time and/or content of the digital play. For these reasons, using appropriate mediation strategies can play a vital role in teaching children how to use digital devices. Specifically, in the context of Turkey, there is insufficient, inconsistent, or even conflicting information about mediation strategies and screen time. Again, the basic information about how much screen time is considered to be overuse, what are the risks and best practices for setting appropriate time and content restrictions should be disseminated to parents. Parental training programs are necessary for Turkey, and in similar countries, where there is a high percentage of the population owning and playing on a variety of devices, and where the overuse of digital play is now recognized as a serious public health issue. Currently, though, there is a dearth of government guidelines to inform parents about these mediation strategies. In a recent study, Sanders, Parent, and Forehand ( 2018 ) proved that a novel one-session intervention has the potential to limit screen time. Therefore, it is suggested that parental training in early childhood education centers, in family healthy offices or online platforms can provide valuable education for all parents about the risks of overuse and best practices for prevention.

Traditionally, “authoritarian” parenting is common among Turkish families and currently, industrialization, economic growth and women’s entrance into the workforce influenced both family relations and child-rearing practices (Kagitcibasi, 1996 ). In recent times, there are notable tendencies in decreasing authoritarian parenting and increase democratic and permissive parenting styles (Sanlı & Öztürk, 2015 ). It is also important to consider such cultural factors to explain the reasons behind the participant parents’ restrictive mediation strategies. As a part of traditional parenting, Turkish parents are expected to assume greater responsibilities, so they tend to require their children to do certain things including rules about digital play (Kagitcibasi & Ataca, 2005 ). When their child did not listen, the participant parents state that they raised their voices or used punishment. Culturally, these kinds of restrictive strategies are acceptable while raising children.

Overall, this study revealed the risky and often conflicted nature of overuse in Turkey and contributes to the literature about understanding this new phenomenon. Considering that young children are turning to more digital play due to the pandemic, the findings of this study will draw attention to the appropriate media mediation strategies of parents. Specifically, parents’ use of active mediation as well as restrictive strategies will be effective in preventing excessive use of digital play of children. From a research design perspective, the research questions were narrowly focused on only examining cases of overuse in very young children. These parameters made recruitment difficult, but they also provided one of the strengths of this study. Producing qualitative information about overuse cases amongst very young children made this study unique and offered novel insights into how parents and children experienced digital play. Additionally, the robustness of the data collected from parents, children, and an expert in the psychiatric care and treatment of children suffering from game addiction and overuse greatly enhanced the validity of the study (Creswell, 2009 ). The study is, however, limited by the descriptive nature of the research. This case study provided detailed and descriptive information about overuse cases in families who had young children. Future research should be increasingly focused on examining a wide range of effective intervention strategies that produce solutions to overuse cases. Additionally, this study only focused on the overuse experiences of children aged five to seven and the participants were mainly boys because of criterion sampling. Future research should begin by selecting a randomized cohort of pre-school children, including those whose parents do not allow their children to use devices. Once selected, these cohorts can participate in a longitudinal study that examines childhood overuse patterns from pre-school to middle childhood, and then into adolescence.

More importantly, this is an exploratory study about the five young Turkish children who experienced excessive digital play at home. Due to the limited number of participants and the qualitative nature of the study prevent generalization of the results to all families having a young child play excessively with digital games. Happily, the results of this study are useful to understand the nature of children’s overuse and the role of parents in this situation. Consequently, parents of young children should provide the same guidance and support to their children in digital play as they do in other play.

Authors’ Contributions

Data availability, code availability, declarations.

The reported study complies with the American Psychological Association’s ethical standards in the treatment of participants and was approved by the Social Sciences Research Ethical Review Board of the Pamukkale University, Denizli TURKEY.

Informed consent was obtained from all participant parents included in the study. Participant children gave verbal consents.

The authors declare that we have no conflict of interest.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Nesrin Işıkoğlu, Email: rt.ude.uap@ulgokisin .

Ahmet Erol, Email: rt.ude.uap@etemha .

Abdullah Atan, Email: rt.ude.uap@nataa .

Serkan Aytekin, Email: rt.ude.uap@niketyas .

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