presentation on negative impact of mobile phone

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Harmful Effects of Mobile Phones on Human Health

Mobile phones have become an indispensable part of modern life. With the advent of smartphones, their usage has skyrocketed, integrating deeply into our daily routines. From communication to entertainment, navigation to education, mobile phones serve myriad purposes, making them virtually indispensable. This widespread adoption raises a critical question: what are the implications of such pervasive use on human health?

• 1 Why Investigate Mobile Phone Health Effects?
• 2.1 Radiation Exposure
• 2.2 Sleep Disruption
• 2.3 Eye Strain and Vision Problems
• 2.4 Hearing Loss
• 2.5 Musculoskeletal Disorders
• 2.6 Potential Cancer Risks
• 3.1 Increased Stress Levels
• 3.2 Addiction and Dependency
• 3.3 Impact on Attention Span and Cognitive Function
• 3.4 Impact on Child Development
• 4.1 Personal Health Practices
• 4.2 Technological Solutions
• 5 Conclusion
• 6.1 1. What is the main health risk associated with mobile phone radiation?
• 6.2 2. How can I reduce my exposure to mobile phone radiation?
• 6.3 3. What are the signs of mobile phone addiction?
• 6.4 4. How does mobile phone use affect sleep?

Why Investigate Mobile Phone Health Effects?

Despite their numerous benefits, there is growing concern about the potential health risks associated with prolonged mobile phone use. Scientific curiosity and public health considerations drive the investigation into these effects. As research evolves, it becomes increasingly important to understand both the immediate and long-term impacts of mobile phone use on physical, mental, and behavioral health. This article delves into these concerns, examining the evidence and providing strategies for mitigating potential risks.

Physical Health Effects

Radiation exposure.

Mobile phones emit a form of non-ionizing radiation called radiofrequency (RF) radiation. While short-term exposure to this radiation is generally considered safe, there is concern about the potential long-term effects. Prolonged exposure to RF radiation has been linked to various health issues, although conclusive evidence is still under study. It is crucial to understand the types of radiation emitted by mobile phones and the possible health risks associated with long-term exposure.

Sleep Disruption

One significant physical health effect of mobile phone use is sleep disruption. The blue light emitted by phone screens can interfere with the production of melatonin, a hormone that regulates sleep cycles. This can lead to difficulties in falling asleep, reduced sleep quality, and shorter sleep duration. Chronic sleep deprivation can result in various health problems, including weakened immunity, cognitive impairments, and increased risk of chronic conditions such as obesity and heart disease.

Eye Strain and Vision Problems

Extended use of mobile phones can cause digital eye strain, characterized by symptoms such as dry eyes, blurred vision, and headaches. The small text and bright screens of mobile phones force the eyes to work harder, which can lead to long-term vision problems. Preventative measures, such as taking regular breaks and adjusting screen settings, can help mitigate these effects.

Hearing Loss

Using earphones and headsets at high volumes for prolonged periods can damage the delicate structures within the ear, leading to noise-induced hearing loss. This condition is particularly concerning among younger users who frequently listen to music or other audio content at high volumes. It’s essential to promote safe listening practices to prevent hearing damage.

Musculoskeletal Disorders

Frequent use of mobile phones can lead to musculoskeletal issues such as “text neck,” a condition resulting from the prolonged forward head posture while looking at screens. Additionally, repetitive strain injuries (RSIs) can occur from excessive typing or swiping. These conditions can cause chronic pain and discomfort in the neck, shoulders, and hands. Adopting proper ergonomics and taking regular breaks can help prevent these disorders.

Potential Cancer Risks

There is ongoing debate in the scientific community about the potential link between mobile phone use and cancer, particularly brain tumors. Some epidemiological studies suggest a possible association, while others find no significant risk. The International Agency for Research on Cancer (IARC) has classified RF radiation as “possibly carcinogenic to humans,” indicating that more research is needed to draw definitive conclusions. It is prudent to stay informed about new findings and adopt precautionary measures where possible.

Understanding and addressing these physical health effects is essential for minimizing the risks associated with mobile phone use. By being aware of these potential issues and taking appropriate steps to mitigate them, users can enjoy the benefits of mobile technology while safeguarding their health.

Mental Health Effects

Increased stress levels.

The constant connectivity afforded by mobile phones can lead to heightened stress levels. The pressure to be constantly available and responsive can create a sense of urgency and anxiety. Social media platforms, messaging apps, and emails contribute to this phenomenon by fostering a culture of immediate communication. This perpetual state of alertness can strain mental health, leading to increased stress and burnout. Managing notifications and setting boundaries for mobile phone use are crucial strategies for mitigating this stress.

Addiction and Dependency

Mobile phone addiction, also known as “nomophobia” (fear of being without a mobile phone), is a growing concern. This addiction manifests through compulsive checking of messages, social media, and other apps, leading to significant time spent on mobile devices. Symptoms include anxiety when separated from the phone, neglect of personal relationships, and decreased productivity. Understanding the psychological mechanisms behind this dependency is essential for addressing it. Cognitive-behavioral strategies and digital detoxes can be effective in breaking the cycle of addiction.

Impact on Attention Span and Cognitive Function

Frequent mobile phone use, especially for activities like social media and gaming, can negatively affect attention span and cognitive function. Multitasking with mobile phones can lead to cognitive overload, impairing the ability to concentrate and perform tasks efficiently. Studies have shown that constant switching between tasks can reduce overall productivity and the ability to focus deeply. To combat this, users can implement focused work periods, minimize distractions, and use apps designed to enhance concentration.

Impact on Child Development

Children are particularly vulnerable to the mental health effects of mobile phone use. Excessive screen time can impede cognitive and emotional development, leading to issues such as attention problems, delayed language skills, and behavioral issues. It is essential to establish screen time guidelines appropriate for different age groups and encourage activities that promote healthy development. Parents and educators can play a pivotal role in modeling balanced mobile phone use and providing alternative activities that foster growth and learning.

Understanding the mental health effects of mobile phone use is critical for fostering a balanced and healthy relationship with technology. By recognizing these potential risks and implementing strategies to mitigate them, individuals can maintain their mental well-being while benefiting from the conveniences of modern mobile technology.

Indirect health effects refer to the consequences of mobile phone usage that are not directly related to physical or mental well-being but can still have significant implications for overall health and environmental sustainability. These effects often arise from the broader impact of mobile phone production, usage, and disposal on the environment and societal well-being. Here’s a breakdown of some key indirect health effects:

Mitigation Strategies

Mitigation strategies are essential to minimize the harmful effects of mobile phones on human health. These strategies encompass personal habits, technological advancements, regulatory measures, and community initiatives. By adopting a comprehensive approach, we can reduce the risks associated with mobile phone use and promote healthier interactions with technology.

Personal Health Practices

Individuals can take several steps to reduce their exposure to the potential harmful effects of mobile phones:

• Limit Screen Time: Set specific times for using mobile phones and take regular breaks to reduce eye strain and prevent musculoskeletal issues.
• Use Hands-Free Devices: Utilize speakerphone or hands-free accessories to minimize direct contact with the head and reduce radiation exposure.
• Maintain Proper Posture: Be mindful of ergonomics to prevent text neck and other musculoskeletal problems. Hold the phone at eye level and avoid prolonged periods of looking down.
• Create a Sleep-Friendly Environment: Reduce blue light exposure by enabling night mode on devices, and avoid using phones at least an hour before bedtime to improve sleep quality.

Technological Solutions

Technological advancements can play a crucial role in mitigating the adverse effects of mobile phones:

• Radiation-Reducing Technologies: Use phones with lower specific absorption rates (SAR) and consider using protective cases designed to reduce radiation exposure.
• Screen Time Management Apps: Utilize apps that monitor and manage screen time to encourage healthy usage patterns and reduce dependency.
• Blue Light Filters: Install blue light filtering software or use screen protectors that reduce blue light emission, helping to minimize sleep disruption and eye strain.
• Improved Ergonomics in Device Design: Manufacturers can design phones with ergonomic considerations, making them more comfortable to use for extended periods.

The widespread use of mobile phones has undeniably transformed modern life, offering unparalleled convenience and connectivity. However, this pervasive technology also brings several health risks that cannot be overlooked. From physical ailments like radiation exposure, sleep disruption, and musculoskeletal disorders to mental health challenges such as increased stress levels, addiction, and social isolation, the potential adverse effects are significant and multifaceted.

1. What is the main health risk associated with mobile phone radiation?

The primary health risk associated with mobile phone radiation is prolonged exposure to radiofrequency (RF) radiation, which some studies suggest may increase the risk of cancer, particularly brain tumors. However, the evidence is still inconclusive, and more research is needed to fully understand the long-term effects.

2. How can I reduce my exposure to mobile phone radiation?

To reduce exposure to mobile phone radiation, use hands-free devices or speakerphone, limit the duration of calls, avoid carrying your phone close to your body, and use phones with lower specific absorption rates (SAR). Additionally, texting instead of calling and using your phone in areas with good reception can help minimize radiation exposure.

3. What are the signs of mobile phone addiction?

Signs of mobile phone addiction include compulsive checking of the phone, anxiety when separated from the phone, neglect of personal relationships and responsibilities, reduced productivity, and an inability to reduce phone usage despite wanting to do so.

4. How does mobile phone use affect sleep?

Mobile phone use can affect sleep through the emission of blue light, which interferes with melatonin production and disrupts sleep cycles. Using phones before bedtime can lead to difficulties falling asleep, reduced sleep quality, and shorter sleep duration. To improve sleep, avoid phone use at least an hour before bedtime and use blue light filters.

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Education resources › Blog › The negative impact of mobile phones: Research around the world

The negative impact of mobile phones: Research around the world

• Phones, AI & technology

Written by the InnerDrive team | Edited by Bradley Busch

What is the negative cost for students for being on their mobile phones too much? With mobile phones increasingly finding a home in the classroom, any teaching and learning policy around them must consider both the potential learning gain as well as the potential learning loss. This blog looks at research from around the world on what the potential downsides are.

Globally, there are  6.378 billion  smartphone users around the world today — around 80.69% of the population. Smartphone use can be hard to manage, especially for students, and research shows that there are many  reasons to put your phone away . One study even  found that students who just study in close proximity of their phone  found it much harder to concentrate, even if they weren’t using it. Other research has highlighted how smartphone usage can lead to  low sleep quality, increased stress and reduced concentration .

Schools may have three main concerns around mobile phones, which typically are:

• Impact on grades
• Impact on well-being
• Impact on online bullying and other safe-guarding issues

THREAD: there is a growing body of evidence to show that mobile phone use is linked with lower academic achievement, a decrease in wellbeing and can often facilitate bullying in schools. Here's some of the available evidence. — Carl Hendrick (@C_Hendrick) April 25, 2021

Inspired by a brilliant thread by teacher and author Carl Hendrick, we’ve examined some of the research from around the world to look at the negative impact that mobile phones can have. Here is what these studies have found…

The negative impact of mobile phones around the world

Research from the uk.

There are many  ways to get better grades , and banning mobile phones in schools may be one of them.  One study  tracked schools for a number of years about their mobile phone policies in four different English cities: Birmingham, Leicester, London and Manchester. 

They found that introducing a mobile phone ban in schools increased students’ GCSE scores, especially for lower-achieving students. The results suggest that schools could significantly reduce the academic attainment gap across students by implementing a mobile phone ban.

Research from the USA 

In the USA,  one study  specifically examined the relationship between how much students use their phones in class (be it for social media, texting, searching relevant information online, playing games and/or updating their calendars) and their grades. 

Results of this study show that there was a significant negative association between mobile phone use during class time and the students’ grade point average. This suggests that when students spend a lot of time on their phone in class, their learning and academic achievement may suffer. 

Another study  from America found that moderate use of mobile phones (4 hours per day) was also associated with lower psychological well-being. For high users (7+ hours per day), they were more than twice as likely to:

• Have been diagnosed with depression or anxiety
• Have been treated by a mental health professional
• Have taken medication for behavioural issues in the last 12 months

Research from Brazil

Researchers in Brazil tested the  relationship between smartphone use and academic performance . They used an app to measure phone use and a survey to measure participants’ personal information, self-efficacy while learning, and phone usage perception. 

Results suggest that there is a significant relationship between a greater total time spent using smartphones and a lower academic performance. They found that for every 100 minutes spent using smartphones, students’ ranking at their school fell by 6.3 points. This effect is twice as high when the smartphone is used during class time instead of during free time or the weekend.

Research from Spain

Research has also looked at the impact of mobile phone uses on academic performance by doing  a comparative case study in two regions in Spain , Galicia and Castile-La Mancha. In Spain, autonomous governments of these two regions established mobile phone bans in schools as of 2015. 

The mobile phone ban significantly reduced bullying among students, particularly among those aged between 12 and 17. The phone ban also resulted in an increase in student test scores in Mathematics and Science. 

Another study from Spain  found that excessive use of mobile phones was bad for students’ psychological health, with constant over-use being associated with high levels of anxiety, reduced self-esteem and feelings of loneliness.

Research from Norway

Norwegian schools have implemented a wide range of phone policies across schools, including mobile phone bans in some.  One study  investigated schools across the country about their opinions and policies on mobile phone use at school. They found that schools that supported a mobile phone bad reported significantly less incidents of bullying amongst their students.

Research from Nigeria

Students in Nigeria were surveyed  to measure how much time they spent on their phones and their academic achievement. Researchers found that there was a significant correlation between increased phone usage and decreased academic achievement.

In an ideal world, smartphones could be adapted to improve learning, but they must be adapted in a way that makes them tools to help rather than hinder students’ academic achievement.

Research from South Africa

Researchers surveyed and interviewed students, from urban high-density neighbourhoods to remote locations across South Africa. Both teachers and students stated that they used their phones to support their work and learning, but 61% of students  believed that there were downsides to phone use in the classroom . These included:

• Disrupted classes due to mobile phone use –  70% of students claimed that disruptions came from their own or their classmates’ phones, while 90% claimed that disruptions came from teachers using their phones during lesson time.
• Disruptions in adolescent sleep patterns –  58% of students said that cheaper night-call rates encouraged them to use their phones at night, resulting in less sleep.
• Wasted time through prolonged sessions on social network sites –  20% of students said that they spent over 2 hours on social networks the last time they used them.
• Harassment and bullying –  55% of students said that they had experienced unwanted or unpleasant calls or texts.

Research from India

Sleep is vital to  maintaining focus, enhancing memory, and improving cognition , but mobile phones may affect its efficacy. Researchers studied the  level of mobile phone dependence and sleep quality  of university engineering students in India. 

Results showed that there was a significant correlation between mobile phone dependence and sleep quality. Higher levels of mobile phone dependence results in lower sleep quality. Subsequently, this effect can result in increase anxiety and depression in students.

Research from China

In China, researchers looked at  prolonged mobile phone use across over 11,000 adolescents . A self-report questionnaire measured mobile phone use in addition to: 

• Sleep duration 
• Insomnia 
• Depression 
• Academic performance in Mathematics and English 

The research found that students were significantly more likely to report poor academic performance and scored significantly lower on mathematics and English when they used their phones for:

• More than 2 hours per day on weekdays
• More than 5 hours per day on weekends 

The findings suggest that adolescents should spend less time using mobile phones to reduce its negative effects on sleep, mental health and academic performance.

Another study in China examined   493 rural Chinese households  and assessed the effects of smartphone use on subjective well-being. Smartphone use intensity was associated with lower levels of subjective well-being, including life satisfaction and happiness, especially when smartphone use exceeded 3 hours per day.

Research from Malaysia

The extent to which mobile phones can support student learning is another area of interest for researchers. In Malaysia, one study looked specifically at  the effects of using of mobile phone use to support academic learning  on students’ compound GPA. 

Students reported that their smartphone use in class included: 

• Texting friends about class assignments 
• Downloading and viewing course materials 
• Looking up word meanings 
• Taking notes 
• Referencing materials

Researchers found that the more students used their phones, even if it was to support school learning, the lower their compound GPA.

Research from Australia  

One study measured smartphone use and current GPA of  Australian students . A negative relationship was found between smartphone use and their GPA. Interestingly, results also suggested that there was a positive relationship between smartphone use and problematic smartphone use such as: 

• Driver distraction 
• Constant phone checking 
• Sleeping with one’s phone nearby, resulting in cognitive deficits

Final thoughts

So, there you have it: research across the globe from a range of study designs have found that there can be a significant negative impact on  students using their mobile phones . These range from hindering academic performance, increasing rates of bullying, decreasing well-being and reducing sleep quantity and quality. 

But we all know that smartphones are not going away anytime soon. The question now remains to see:

• If the positives outweigh the negatives (and given the range of negatives, one would want to see strong concrete support for a lot of benefits to justify their inclusion in the classroom);
• If schools choose not to ban phones, then under which conditions do they work best?

We should be under no illusions. There is absolutely a mobile phone addiction crisis sweeping the world. Do we really think students need more screen time when they are at school? That is for each institution to decide themselves.

But that decision shouldn’t be rushed — the research should be consulted and their application greatly considered first.

About the editor

Bradley Busch

Bradley Busch is a Chartered Psychologist and a leading expert on illuminating Cognitive Science research in education. As Director at InnerDrive, his work focuses on translating complex psychological research in a way that is accessible and helpful. He has delivered thousands of workshops for educators and students, helping improve how they think, learn and perform. Bradley is also a prolific writer: he co-authored four books including Teaching & Learning Illuminated and The Science of Learning , as well as regularly featuring in publications such as The Guardian and The Telegraph.

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Understanding the Positive and Negative Impact of Smartphones On Our Health

By now, most people have a smartphone. You might not have the latest, greatest iPhone, but you probably have something that can access the internet and stores apps. But do you know what it’s doing to your health? For better or worse, it’s having an effect.

Smartphone Ownership on the Rise

  The Pew Research Center has done a phenomenal job of tracking data on mobile devices and smartphones over the past 15-plus years. What they’ve discovered is that ownership and dependence on these devices continues to increase as the years go by.

In their most recent 2018 Mobile Fact Sheet , Pew Research Center found that 95 percent of Americans now own a cellphone, with 77 percent owning a smartphone of some kind. That latter statistic is up from just 35 percent in 2011.

While smartphone ownership rates are high across all demographics, they’re particularly robust in Americans under the age of 50. Approximately 94 percent of those between the ages of 18 and 29 have a smartphone, while 89 percent of those in the 30 to 49-age bracket are smartphone owners.

It’s also interesting to note that just over one-in-ten American adults are classified as “smartphone-only” internet users. In other words, they don’t own a personal computer or traditional home broadband service. They rely 100 percent on their smartphone and data plan for access to the web.

Positive Impact of Smartphones on Our Health

When you hear the term “smartphone dependency,” what comes to mind? Most people have been programmed to think that dependence on these devices only yields negative results. And while it certainly produces a number of negative outcomes – and we’ll touch on a handful of these in the following section – there are also some potential positives.

Let’s take a look at two of these value points.  

• Predicting Personal Health Issues

Most people are acutely aware of their bodies and can tell when something is wrong with their physical health. Mental health issues, on the other hand, often go undetected by the individual and must be identified by someone else.

Could smartphones, which are the primary connection point to social media, be the answer to spotting mental health issues?

According to DentalSave , “Leaders at Facebook have developed artificial intelligence that scans posts and videos to find evidence of changes in mental health. For instance, if a person’s account receives several comments asking things like ‘Are you okay’ and ‘Do you need any help,’ Facebook’s AI may determine that the person is living through a difficult period.”

This AI technology is still quite new, but Facebook may eventually be able to send messages to users, or encourage them to call helplines in certain scenarios.

• Identifying Disease Outbreaks

Speaking of social media, researchers and epidemiologists believe they’re making progress in how they use data and can now do a reasonably good job of tracking disease outbreaks using things like social posts, keyword searches, and other data.  

“Having these types of clues can help government agencies, and independent epidemiologists, understand how to allocate resources necessary for fighting and preventing illness and disease,” Health Administration Degrees explains.

In this sense, smartphone usage could actually lead to better localized care during health scares – such as flu season.

“There’s a lot of opportunity, but there’s challenges as well, and I think that’s where a lot of the science could be focused,” says Rumi Chunara, an NYU computer sciences and engineering professor who is currently running a project that hopes to improve the ability to assess the spread of viruses and disease remotely. The key is to find a way to reduce noise and inaccuracies, while complimenting the clinical data doctors and scientists already have.  

Negative Impact of Smartphones on Our Health  

Now that we’ve unpacked some of the little-known positives, let’s turn the focus towards two potentially negative impacts smartphones are having on our health.

• Distracted Living

Let’s be real: smartphones are a distraction. We’re constantly using them, checking them, or looking for them. And in this sense, they’re a huge distraction from what’s actually happening in the real world.

Distracted driving is the most obvious issue , but millions of Americans are also distracting themselves from their jobs, relationships, and responsibilities.

Next time you’re in a crowded public space – such as a coffee shop, subway station, waiting room, or shopping mall – make a mental note of how many people are looking down at a smartphone and how many are interacting with the people around them. Don’t be shocked if the former outnumbers the latter.  

• Digital Amnesia

  Cybersecurity firm Kaspersky Lab has coined the term “digital amnesia,” which they use to describe society’s growing dependence on digital technology for memory. Their research shows that 91 percent of Americans aged 16 to 55 admit to using their smartphones as an extension of their brains, while 44 percent say their smartphones serve as their memories.

“Memory is highly capacity-limited,” says Dr. Nathan Rose, assistant professor of cognition, brain, and behavior at the University of Notre Dame’s psychology department. “There’s only so much information we can attend to at any given time. We’re constantly turning to outside devices to kind of supplement this limitation.”

In fact, many Americans are so far along this path that, in order to reverse the effects of digital amnesia, people will have to retrain the way their brains think, process, and store information. This could take years and, in all likelihood, isn’t something that most are going to bother to do.

Smartphones Aren’t Going Away

Here’s the thing: smartphones aren’t going anywhere. While the actual physical devices and software inside of these devices will probably change rather dramatically over the next couple of decades, it’s hard to imagine any scenario in which we don’t have ubiquitous access to the internet in our pockets at all times. There’s no turning back.

Understanding this, it’s imperative that we, as a society, look for ways to exploit the advantages and suppress the negatives. Only then can we truly prioritize our health and well-being.

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Can't put down the phone? How smartphones are changing our brains — and lives

Until a year and a half ago, Samuel Veissiere's smartphone was the last thing he saw before he fell asleep and the first thing that greeted him when he woke up. During the day, the device bombarded him with constant notifications — from four different email accounts as well as Instagram, Facebook, WhatsApp, Reddit and Twitter.

"It was abominable," said Veissiere, co-director of the Culture, Mind and Brain Program at McGill University in Montreal.

It's also a daily storyline familiar to many of us. In the U.S., at least three of every four people now own a smartphone . And one estimate suggests that Americans touch their mobile devices more than 2,600 times a day on average. But what do all those pings and buzzes, scrolls and swipes actually add up to? Is it worrisome — or not so much? After all, Socrates once warned that writing would "introduce forgetfulness" and make people "difficult to get along with."

"I think we know enough now to be deeply concerned about how these very, very powerful and seductive devices are influencing pretty much every aspect of our life," said Nicholas Carr, a technology and culture author.

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Veissiere and Carr are among researchers and public figures calling attention not just to the more widely discussed impacts of our phones — such as dinner disruptions and distracted drivers — but also to their subtler effects, which some fear could result in profound changes to our brains and to society.

Initial data from a $300-million study by the National Institutes of Health , for example, now provides evidence that a child's brain may indeed develop differently with heavy use of digital devices. Those of us whose brains matured before the first iPhone came to market in 2007 may also be vulnerable to mental changes. The more tethered we are to our phones, studies show, the harder it is to think deeply, attentively and conceptually — not to mention remember basic information . (Some of us may recall an era when our brains — not our devices — managed to remember our friends' phone numbers and birthdays.)

Laws of attraction and distraction

Our smartphones seem to wield their influence even when we're not using them. The mere presence of a smartphone seemed to reduce the quality of conversations in one study. Another study found a link between having a smartphone within sight, even if turned off, with lower scores on tests of short-term memory and problem solving.

"The effect is biggest for people who rely on their phones the most," said Adrian Ward, an expert in technology and cognition at the University of Texas at Austin, and the author of that last study. "The more you give it control over different things — social connections , news, work, etc. — the more you are going to be attracted to this device."

Simply trying to resist that automatic attraction, he explained, takes up cognitive resources.

Even basic human decency may be sacrificed. Research suggests that smartphones can inhibit people from offering help to strangers on the street, reduce how much we smile at unfamiliar faces in a waiting room and even lessen our trust of strangers, neighbors and people of other religions or nationalities.

"People don't talk about or realize that we actually get quite a lot from casual social interactions," said Kostadin Kushlev, a social psychologist at the University of Georgetown University and an author of several smartphone studies. "Even when phones are at their most useful — such as when we're bored to death in the waiting room — there might be other things we're missing out on."

Perhaps not surprisingly, researchers have also begun to link weakened social skills, including the inability to read emotions or initiate casual conversations, to smartphone use.

"It takes time and practice to develop those skills," said Jean Twenge, a psychology professor at San Diego State University. She studies generational differences and is currently focused on the post-millennial generation , or people born in 1995 or later. The iGen, as she calls them, is the first generation to spend its entire adolescence with smartphones.

The rise of the smartphone

Twenge noticed a troubling correlation between when smartphones became popular and when rates of mental health problems among teens and young adults began skyrocketing.

"It's also when the decline of in-person social interaction began to accelerate," Twenge said, adding that she can't be certain smartphones are the cause. "Whether it's someone you've never met or it's friends and family, spending time with people face to face is linked with happiness."

The less skilled we are at social interaction, of course, the less likely we probably are to seek it out. It's a self-perpetuating cycle that could have further unanticipated consequences, including less exposure to alternative points of view.

A lack of trust or understanding of other people and their perspectives may be among various ways smartphones could divide a society. Since the dawn of the internet, scholars have worried that users would seek only information that reinforces their existing point of view. Now, thanks to Facebook, Twitter and other smartphone apps whose makers push us information that they think will appeal to us, we no longer need to search for that confirming information; it simply pours out of our phones, Carr said.

"It clearly adds to the polarization of society and people getting more and more extreme in their views," he said. "I don't think we can blame the technology for all of this, but it's definitely amplifying the effect of negative trends that are shaping society at quite a deep level."

Our personal contributions to the streaming information may be altered by our smartphones as well. "We are likely to be less deliberate in our tweets and online posts when composing them on our phones compared to our laptops," said S. Shyam Sundar, co-director of the Media Effects Research Laboratory at Penn State University and author of the study on helping strangers. "We will be more glib, more raw and less sugar-coated in our commentary, leading to more trolling and polarization in online spaces."

Finding a balance

None of this is to say that smartphones don't have great practical and entertainment value. It's harder now to get lost, but easier to find a date and keep up with friends, kids and the news. And in some ways, a greater diversity of people is at our fingertips. Apps such as Tinder allow people to easily connect with others outside their typical social networks. Occasional smiles from watching cute cat videos aren't necessarily bad for us either.

"The crux of the problem is figuring out how to get all these amazing benefits of this globally interconnected world without abandoning the things that make us most human," said Adam Gazzaley, a neuroscientist at the University of California, San Francisco.

For him, that means taking back control over how we use the technology. He is co-developing technology — for smartphones — that aims to improve how our brains function. His video game is in the final stages of FDA approval and would be the first non-drug treatment for ADHD .

Meanwhile, Veissiere's lab is now testing simple interventions for smartphone users, such as turning off instant notifications, not sleeping with the phone next to you and switching the screen to gray scale to make it less attractive.

In early 2017, Veissiere became concerned enough about the consequences of his own smartphone use to make a bold move: He swapped out his latest greatest iPhone for an old flip phone with no internet connectivity. He now relies on his computer for news, social media and the like. "I have been more productive at work. My social interactions are great. My mood is great," said Veissiere, adding that he appreciates how the keyboard on his flip phone exercises his brain. "Perhaps it's a placebo effect. But it has worked really well for me."

"It's possible to slow down," he added. "We're not necessarily doomed and trapped."

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Smartphone impacts on teenagers: Positive and negative

“sometimes kids can’t make the clarification between what is real and what isn’t real.".

Olivia Johnson and her friends are typical teenagers. They’re involved in extracurricular activities at school, have part-time jobs to make spending money, enjoy each other’s company and use a smartphone to stay in the loop.

“For most kids, I think we probably could live without our phone. But we prefer not to,” said Johnson, a senior at Bemidji (Minnesota) High School. “I enjoy looking at pictures and reading. I also text, use Instagram, Twitter and Snapchat. For me, and for my friends, having a phone is a positive and not a negative. But I don’t know if it is that way for everyone.”

Grown up with them

Shawn Whiting, the clinical supervisor of behavioral health at Sanford Health in Bemidji , said the smartphone has changed how people communicate.

“(Today’s) kids have had cellphones their whole lives. This is the technology that has been present and they don’t know anything else,” he said. “They use their phones and social media to connect with their peers, but what they can lose are the human interactions that people, as social animals, need.”

Find a provider: Behavioral health at Sanford

On a day that offers an open schedule, Johnson estimates that she and her friends would spend four to five hours on their phones texting and talking. With more than 100 contacts, Johnson do esn’t lack a friend to talk to.

Among her contacts are mom, dad, her brother and sister, her cousins, plus her aunts and uncles, so those close to her are fully aware of what Johnson is posting and receiving.

“I know who her friends are on social media,” said her mother, Tracy Johnson. “I am one of her contacts and there are many other relatives who can serve as checks and balances on her phone. Olivia is willing to be part of the broader family group and, because of that, we don’t worry about her phone use. We know what she is doing.”

Know what they’re doing

Whiting believes that sort of arrangement among the family members and the teenager would benefit everyone.

“What I tell parents is, if your child is going to have a smartphone and be on social media, have a relationship that enables you to know what your child is doing and who the child is communicating with,” Whiting said. “Smartphones (can be) great tools for the parents to check on their kids and know where they are.”

Like any other tool, when used properly, a smartphone can significantly add to someone’s knowledge and enjoyment. But it can also cause pain and embarrassment.

“The adult brain doesn’t fully develop until a person is 24 or 25 years old, and the rational part of the brain is the last to develop, so kids can be impacted by peer pressure on social media,” Whiting said. “Sometimes kids can’t make the clarification between what is real and what isn’t real. When that happens it can have a negative impact on self-esteem.

Learn more: When media changes adolescent moods & anxiety

“There also is a lot of cyber-bullying going on. And, unfortunately, there have been some kids who have committed suicide because of cyber-bullying. We have to find ways to manage (smartphone use). Parents, school administrators, and the kids themselves need to ask ‘what is appropriate smartphone use and what is too much.’”

Know the signs

People who spend time with kids also need to be able to identify the signs that indicate that a child is struggling or may be depressed.

“The tricky part is determining what is normal adolescent development and what isn’t,” Whiting said. “It can be tough for a parent to know that, but that is what we (behavioral health specialists) are trained to do. Developmentally, kids at this age are moving away from parents and their peers become a bigger influence than the parents are. That’s (part of the normal) development process. But, generally speaking, if the child isn’t acting normally, I would ask some questions.”

Warning signs include:

• More isolation than usual
• Difficulty sleeping, or falling asleep at inappropriate times
• Mood swings
• Feeling down
• Lacking interest

What to do for at-risk kids

Based on those indicators, Olivia Johnson sees kids every day who may be at risk.

“I don’t see much bullying at school, but sometimes I see it online,” she said. “And I would say that 20 to 25 percent of the kids I see at school don’t have many social skills and hang around mostly by themselves. But my friends are in extracurricular activities and I think those activities help develop social skills.”

If parents notice that their child is demonstrating some of those signs, Whiting said it is time for them to start or extend the communication process.

“Try to talk with the child. Try to see what is going on,” he advises. “If you are noticing something bigger (you can) talk with the school teachers and the school counselors and see if they are noticing anything different. And from there, maybe a mental health referral (would be warranted).

“And sooner is better than later.”

More stories

• Childhood suicide: Bullying, ADHD and relationships
• Parenting tips: How to talk about tragedies with your kids
• Best ways to communicate with your child

Posted In Behavioral Health , Children's , Health Information , Healthy Living

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Impact of mobile phones and wireless devices use on children and adolescents’ mental health: a systematic review

• Open access
• Published: 16 June 2022
• Volume 33 , pages 1621–1651, ( 2024 )

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• Braulio M. Girela-Serrano   ORCID: orcid.org/0000-0002-3813-2610 1 , 2   na1 ,
• Alexander D. V. Spiers 3 , 4   na1 ,
• Liu Ruotong 1 ,
• Shivani Gangadia 1 ,
• Mireille B. Toledano 3 , 4 , 5 &
• Martina Di Simplicio 1  

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Growing use of mobiles phones (MP) and other wireless devices (WD) has raised concerns about their possible effects on children and adolescents’ wellbeing. Understanding whether these technologies affect children and adolescents’ mental health in positive or detrimental ways has become more urgent following further increase in use since the COVID-19 outbreak. To review the empirical evidence on associations between use of MP/WD and mental health in children and adolescents. A systematic review of literature was carried out on Medline, Embase and PsycINFO for studies published prior to July 15th 2019, PROSPERO ID: CRD42019146750. 25 observational studies published between January 1st 2011 and 2019 were reviewed (ten were cohort studies, 15 were cross-sectional). Overall estimated participant mean age and proportion female were 14.6 years and 47%, respectively. Substantial between-study heterogeneity in design and measurement of MP/WD usage and mental health outcomes limited our ability to infer general conclusions. Observed effects differed depending on time and type of MP/WD usage. We found suggestive but limited evidence that greater use of MP/WD may be associated with poorer mental health in children and adolescents. Risk of bias was rated as ‘high’ for 16 studies, ‘moderate’ for five studies and ‘low’ for four studies. More high-quality longitudinal studies and mechanistic research are needed to clarify the role of sleep and of type of MP/WD use (e.g. social media) on mental health trajectories in children and adolescents.

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Introduction

Over the last ten years, the communication and information landscape has changed drastically with the development and rapid uptake of new portable devices such as smartphones or tablets, which are able to provide instant access to the internet anywhere. The likelihood of owning a smartphone increases with age, with market research reporting 83% of children in the UK aged 12–15 own a smartphone and 59% own a tablet. Up to 64% of children aged 12–15 have three or more devices of their own [ 1 ]. Alongside increased ownership rates, multifunctionality has expanded; a child’s phone may now enable internet browsing, games, applications, learning, online communication, and social networking.

The growing use of these technologies has raised concerns about how exposure patterns may affect children and adolescents’ wellbeing, as mental health disorders constitute one of the dominant health problems of this age group [ 2 ]. Increases in digital device usage have been hypothesized to be responsible for the secular trend of increasing internalizing symptoms, poorer wellbeing, and suicidal behaviours in adolescent populations [ 3 ]. It is reported that between 10–20% of children and adolescents suffer from a mental health problem globally [ 4 , 5 ] and up to 50% of mental disorders emerge under the age of 15 [ 6 ]. A recent meta-analysis estimates the prevalence of any depressive disorder in children and adolescents is 2.6% (95% CI 1.7–3.9), and of any anxiety disorder is 6.5% (95% CI 4.7–9.1) [ 7 ]. Recent studies have shown that the usage of mobile devices in children and adolescents may be associated with depression [ 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ], anxiety [ 8 , 10 , 15 , 16 ] and with behavioural problems [ 17 ]. Particular patterns of smartphone-related behaviour, termed as ‘problematic smartphone use’ may be responsible for poor mental health associations [ 18 ].

Initially, research focussed on the physiological aspects of exposure to mobile phones or wireless devices (MP/WD) that use radiofrequency electromagnetic fields (RF-EMF). The Stewart Report identified that children and adolescents may be especially susceptible to exposure due to their developing nervous systems, greater average RF deposition in the brain compared with adults, and a longer lifetime of exposure [ 19 ]. It is still unclear whether exposure to RF-EMF from MP/WD can affect cognitive and emotional development in children and adolescents [ 20 ].

However, health effects of MP/WD on children and adolescents could also stem from psychological, social and behavioural factors related to their use. Adolescence is a dynamic phase of social and emotional development characterised by a change in the intensity and quality of communications among peers [ 21 ]. Adolescents have a constant need to interact and to be acknowledged by others, so that they can define their role and status in the peer group [ 22 ]. This distinctive pattern of socialization contributes to and is reflected by the pervasive use of social media embedded in MP/WD at this stage of life and research so far has focussed on this aspect.

Physiologically, adolescence is characterized by a delay in bedtime and a decrease in length of sleep with age [ 23 ], and sleep deficits are highly prevalent [ 24 ]. Given the pivotal role of sleep in adolescents’ health and development, research has investigated the associations between bedtime use of MP/WD, sleep disturbance and poor mental health outcomes. Studies to date report growing evidence of the detrimental impact of these technologies on sleep, although the specific relationship with mental health remains to be fully understood [ 25 ], including potential mechanisms such as (1) displacement of sleep by directly interrupting sleep time [ 26 ], (2) impact on circadian rhythm due to exposure to blue and bright light from screens [ 27 ] and (3) sleep disturbance due to the content of messages received pre-bedtime [ 28 ].

The complex relationship between factors including (but not limited to) exposure to RF-EMF, light from screens, engagement with internet or social media content, peer communication and their physiological and psychological consequences represents a challenge to determining definitive associations of interest between children and adolescents’ MP/WD use and mental health. This research field has evolved through different theoretical approaches and become the centre of media interest. However, previous reviews have either focussed on the psychological or behavioural aspects [ 29 ], or specifically on RF-EMF exposures for MP only [ 30 , 31 ], and overlooked key information on confounders, such as socio-demographic factors. It is important when synthesizing these findings that all aspects of MP/WD use are considered. For example, mobile phone use is related to exposures hypothesized to have psychological effects (e.g., RF-EMF, screen-light), but these often occur simultaneously with changes of behaviour (e.g., reduced sleep, physical activity). Furthermore, different purposes of use may have different levels and temporal patterns of usage. Disentangling these effects often requires complex, tailored study-designs with advanced exposure measurement tools, and discussion of these issues with respect to MP/WD use and mental health is often missing. An assessment of the methodological quality of the available evidence to date could direct future research, policy and health recommendations around children and adolescents’ use of MP/WD. This evidence synthesis is also much needed now that digital tools for mental health hold the promise to overcome barriers to access support [ 32 ]. As the current COVID-19 pandemic has further accelerated the move towards a “digital mental health revolution”, it is crucial to identify if and under which conditions MP/WD use may be detrimental.

Our aims are to undertake a systematic review and appraisal of the evidence with a primary objective of assessing the relationship between duration or frequency of MP/WD use and children and adolescents’ mental health through synthesis of findings from individual quantitative observational studies conducting inferential analysis on this relationship. We define our exposure as any mobile or portable technologies that use RF-EMF to connect with the internet, cellular network, or cordless base station. This includes mobile phones, tablets and smartphones. Studies investigating only the use of devices that are not wireless (e.g. TV) or handheld in the same manner as tablets and phones (e.g. laptops) were excluded.

Secondary objectives are to synthesise findings on whether:

Impact on mental health is influenced by the temporal pattern (e.g. bedtime)

Different modes of use (e.g. calls, social media, instant messaging) have distinct effects on mental health

Impact on mental health differs for specific outcomes, in particular: internalizing symptoms (e.g. anxiety, depression, suicidal ideation/self-harm), externalizing symptoms (e.g. attention, concentration) and general wellbeing.

Search strategy and selection criteria

This review was written in accordance with PRISMA statement recommendations (see Supplementary Material Table S1 for PRISMA checklist) [ 33 ] and was prospectively registered on PROSPERO (CRD42019146750) [ 34 ]. Relevant published articles were identified using tailored electronic searches developed with experts on MP/WD exposure and mental health (see Supplementary Material Table S2 for search terms list where we outline examples of exposures and mental health outcomes in detail). We originally searched Medline, Embase and PsycINFO using OVID interface for all studies published prior to July 15th 2019 (see PRISMA Flowchart Fig.  1 ). Both published and unpublished studies with abstracts and full texts in English, Spanish and French were searched. BGS and AS completed backward and forward citation tracking of included studies. Any inconsistencies between selected studies were resolved by discussing this with a third author (MDS).

PRISMA Flowchart

Each study identified in the search was evaluated against the following predetermined criteria:

Population: Studies examining children or adolescent populations where at least 70% of participants are aged 18 years or under.

Exposure: Studies measuring daily or weekly duration or frequency of mobile phone or wireless device use (devices can include smartphones, cordless phones, tablets e.g., iPad).

Outcomes: Studies that report a standardized and/or quantifiable measure (i.e., administered in a consistent manner across subjects) of mental health symptoms or psychopathology prevalence, which we define as to include: measures of internalizing symptoms and disorders (e.g. anxiety, depression, suicidal ideation/self-harm), externalizing symptoms and disorders (e.g. attention, and conduct disorders), and well-being measures (e.g. measures of self-esteem, health-related quality of life) among children and adolescents.

Published in a peer-reviewed journal in English, Spanish or French.

Reported inferential statistics describing cross-sectional or longitudinal associations between MP/WD usage and mental health outcomes.

Studies were excluded if: (1) specific wireless device use could not be identified as a separate variable (i.e., the main independent variable in the statistical model is a composite such as “digital media use”, “screen time”); (2) only clinical populations; (3) only investigated: physical health (e.g.: headaches, fingers/neck pain), somatic symptoms, cognitive functions (attention, memory), safety (driving, related accidents), relational consequences (relationships, physical fitness, worse academic performance, sexual behaviour (sexting), cyberbullying, sleep habits, personality, study assessment or intervention of substance use/addiction, specific apps, smartphone and social media loss, reviews or qualitative studies. (4) Case studies, opinion pieces, editorials, comments, news, letters and not available in full text. After reviewer feedback, we excluded all articles published before January 1st 2011 as MP/WD devices used before this period are unlikely have the same interactivity of devices used at the time of search.

Data extraction and quality assessments

We (BGS, AS, ER, SG) extracted the data using a standard data extraction form (data extraction started on Aug 20, 2019). Data was verified by a second author, and then checked for statistical accuracy (AS or BGS). We chose to extract the estimands of associations from the final covariate-adjusted model specified by each group of study author, as not every iteration of the models was available to us. For transparency, the adjustment factors can be viewed clearly in the column second to the right of Tables 1 , 2 , 3 , 4 .

Authors of original papers were contacted to provide missing (subsample) data where necessary. AS and BGS both appraised each study independently for methodological quality and risk of bias using checklists adapted from the Newcastle–Ottawa Scale (NOS), originally designed to evaluate cohort studies [ 35 ], and considered a useful tool to assess risk of bias [ 36 ]. We used a customized checklist for cross-sectional studies, following an approach taken by previous systematic reviews of observational research [ 37 , 38 ]. We also used the STROBE individual component checklist to critically appraise the aspects of reporting related to risk of bias, e.g. study design or sampling methods [ 39 ]. We defined the most important covariate adjustment factors as previous diagnosis of mental disorder or prior mental health and demographic confounders (sex, age, socioeconomic status (SES)) based on the Newcastle–Ottawa quality assessment Scale (NOS). We then categorized studies by quality and risk of bias based on accepted thresholds for converting the Newcastle–Ottawa scales to AHRQ standards [ 40 ]. A description of the conversion rules can be found in the footnotes to Table S6 and S7 in the Supplementary Material.

Data synthesis

Given the high heterogeneity of the retrieved studies with regards to the primary explanatory variable of interest (MP and WD usage), the outcomes of interest (mental health), the objectives and the statistics used, statistical pooling was considered to be inappropriate and the quantitative data is synthesised narratively.

We classified studies by MP/WD exposure: (a) general MP/WD use (frequency/duration) and (b) bedtime MP/WD use; and by mental health outcomes: internalising symptoms, externalising symptoms and wellbeing. Children and adolescents’ emotional, behavioural and social difficulties are widely conceptualised in internalizing and externalizing symptoms groupings [ 41 ], endorsed by the DSM-V to provide directions in clinical and research settings [ 42 ]. We added a third category of wellbeing, to group scales measuring resilience, self-esteem, self-efficacy, optimism, life satisfaction, hopefulness etc., which are important indicators of how mental health is subjectively perceived and often valued by individuals above clinical symptoms [ 43 , 44 ].

All retrieved studies meeting eligibility criteria ( N  = 25) were observational and investigated both genders. Ten (40%) employed a longitudinal design, while the remaining 15 (60%) had a cross-sectional design. One study [ 45 ] reported both cross-sectional and longitudinal findings. There were multiple studies drawing from the same population: three from the HERMES cohort [ 46 , 47 , 48 ], two from the LIFE cohort [ 49 , 50 ] and two from the same sample of high-school students [ 11 , 12 ].

The total number of research subjects was 164,284 who were aged between five and 21 years old. Most studies examined typically developing adolescents aged 8–18 years old. Three studies looked at young children aged 2–7 years old [ 50 , 51 , 52 ]. One study that included young people aged up to 21 years old was included in the review as ~ 70% of the samples met the ≤ 18-years old criteria [ 8 ].

Studies investigating associations of mental health outcomes with only aggregated screen time without device-specific measures were excluded from the review. All studies measured MP use. Three studies also investigated the effect of cordless phone usage [ 14 , 17 , 48 , 52 , 53 ]. Two studies also included specific measures of tablets [ 51 , 54 ]; one study investigated other categories of WD including: eBook reader, laptop, portable media player and portable video game console [ 54 ]. Most studies used self-report questionnaires to assess MP/WD use: for example, asking participants to rate their daily or weekly use to best match an interval provided by the questionnaire [ 8 , 9 , 10 , 11 , 12 , 13 , 15 , 16 , 46 , 48 , 53 , 55 , 56 ], or with ordinal scales of frequency [ 14 , 28 , 47 , 57 , 58 ]. Studies with young children instead used parent questionnaires [ 50 , 51 , 52 ]. Twenty studies reported MP/WD general use and five with bedtime use. Seven studies collected data of MP/WD usage on weekends and weekdays separately [ 9 , 10 , 45 , 46 , 55 , 56 , 59 ], with five of these reporting associations with mental health separately for weekday and weekends [ 9 , 10 , 55 , 56 , 59 ]. Twenty studies reported internalizing symptoms, 11 externalizing symptoms, and ten well-being measures.

Details on study aim, sample characteristics, MP/WD use, mental health outcomes and measures, and findings are summarised in Tables 1 , 2 , 3 , 4 .

Quality assessment

The median and mean NOS scores of the longitudinal studies were 6 and 6.3 respectively. The median and mean scores for cross-sectional studies were 5 and 5.0 respectively. We converted each NOS Score for the 25 studies to AHRQ standards: risk of bias was rated as “high” for 16 studies, “moderate” for 5 studies and “low” for 4 studies. Risk of information bias was common as self-report measures were prevalent for outcome and exposure assessment. Additional factors contributing to high risk of bias included: risk of selection bias, attrition, and the absence of adjustment for confounding factors. All details regarding quality assessment, including summaries of risk of bias across studies, are reported in the Supplementary Material (Tables S4-S8).

Main Research Findings

Findings are presented by exposure time (general or bedtime), design (longitudinal or cross-sectional) and outcome assessed (internalising symptoms, externalising symptoms and wellbeing). For each group of longitudinal findings, we report the AHRQ Quality Band (“high”, “moderate” or “low” below refer to risk of bias). Figure  2 categorises effects reported by direction of association with mental health outcome and by whether bedtime or daily aggregate MP/WD usage was investigated. All cross-sectional studies were rated as high risk of bias, so for brevity these are not reported in the text below. Unless otherwise stated, we describe associations adjusted for all confounding variables reported in each study (see Tables 1 , 2 , 3 , 4 for details of covariates included in adjusted models).

Harvest plot of associations between MP/WD usage and mental health outcomes among children and adolescents included in the systematic review. Numbers refer to study references as cited in the reference list. Two studies [ 46 , 47 ] were excluded from this plot as they did not report direct inferential statistics between MP/WD and mental health

General use of wireless devices

Longitudinal findings.

Nine out of the 10 longitudinal studies included in this review examined associations between mental health outcomes and general use of MP/WD (Table 1 ).

Internalising symptoms : Two out of five studies (one low risk, one high) found a significant association between general use of MP/WD and measures of internalising symptoms. Bickham et al. [ 9 ] found that more frequent MP use recorded via a diary at baseline predicted higher depression scores on the Beck Depression Inventory (BDI) at one-year follow-up. Similarly, Liu et al. [ 8 ] found that baseline high MP use was associated with higher incidence of depressive and anxiety symptoms measured with the BDI and the Self-Rating Anxiety Scale (SAS) after eight months. However, two studies (both moderate risk) from the LIFE cohort did not find any association between baseline general MP use and internalising symptoms recorded via the Strengths & Difficulties Questionnaire (SDQ)—parent-reported [ 50 ] and self-reported [ 49 ] at one-year follow-up. This finding is consistent with the largest longitudinal study reviewed (low risk), a cohort study that found no association between baseline texting duration and depression or anxiety measured with the self-report versions of the Clinical Interview Schedule (CIS-R) in adolescents after two years [ 56 ].

Externalising symptoms : Three out of four studies (one low risk and two moderate risk) found a significant association between general use of MP/WD and measures of externalising symptoms. The first LIFE cohort study found that more frequent baseline parent-reported MP use predicted a higher score in the parent-reported hyperactivity/inattention and conduct problems SDQ subscales of young children after one year [ 50 ]. This evidence was consistent with the findings from two other studies: one found increase in conduct disorders after 18 months measured by ecological momentary assessment (EMA) [ 45 ] and the other found increase in concentration difficulties after one year measured by a four-point single-item Likert scale [ 48 ] in adolescents’ populations, both associated with more frequent self-reported texting [ 45 , 48 ] and duration of MP calls [ 48 ]. The latter study also measured cumulative RF-EMF dose from MP/WD and far-field environmental sources and found that whole-body RF-EMF dose was associated with concentration difficulties when calculated from self-reported duration of use (duration of data traffic, cordless phones), but not when calculated from objective measures (network operator-measured data volume and call duration) [ 48 ]. The second LIFE cohort study found no significant association with baseline MP/WD usage and self-reported SDQ in adolescents at one-year follow-up [ 49 ].

Wellbeing : Two out of three studies (both moderate risk) found a significant association between general use of MP/WD and measures of wellbeing. Use of MP/WD over a school year was negatively associated with positive self-concept but not with general wellbeing in adolescents [ 55 ]. Conversely, Poulain et al. [ 49 ] found that adolescents with higher MP use at baseline reported a decrease in wellbeing measured with the health-related quality of life (HRQoL) scale by KIDSCREEN-27 at one-year follow-up. Another study (moderate risk) found that baseline duration of MP use for social communication had a positive indirect effect on children’s wellbeing measured with a bespoke scale at one and two-year follow-up, mediated through changes in social capital [ 57 ].

Cross-sectional findings

Twelve out of the 16 studies reporting cross-sectional findings included in this review examined associations between mental health outcomes and general use of MP/WD (Table 3 ). Two studies measured general use of MP and mental health, as well as problematic use of MP via specific questionnaires [ 46 , 47 ], but as they did not report direct associations between duration or frequency of MP/WD use and mental health, we do not report their findings in this section.

Internalising symptoms : Six out of nine studies found significant cross-sectional positive associations between general use of MP/WD and measures of internalising symptoms [ 10 , 11 , 13 , 15 , 16 , 52 ]. Most samples were adolescents and symptom measures varied from a single-item self-report to validated questionnaires. Overall, higher MP/WD use was associated with more anxiety or depressive symptoms, although in some studies this was limited to activities such as social networking and online chatting [ 11 , 15 ] or in females only [ 12 ]. One study reported an association in the opposite direction, reporting that adolescents experienced less anxiety and depressive symptoms measured with the Multidimensional Anxiety Scale for Children (MASC) and BDI on days when sending more text messages [ 45 ]. Two studies did not find any significant association [ 51 , 52 ].

One study also investigated the direct effect of RF-EMF on internalising symptoms [ 14 ], which showed that adolescents that used cordless phones had a higher likelihood of depressive symptoms compared to those who did not, but only true for cordless phones with frequencies ≤ 900 MHz [ 14 ].

Externalising symptoms : Three out of five cross-sectional studies found a significant positive association between general MP/WD use and measures of externalising symptoms (Table 3 ).

In particular, greater MP/WD use was related to concentration problems [ 16 , 53 ], attention problems [ 16 ], hyperactivity symptoms [ 51 ], conduct problems [ 51 ], and hostility [ 15 ]. In contrast, no association was found with externalising symptoms reported by parents or teachers in young children [ 52 ].

Wellbeing : Two cross-sectional studies reported cross-sectional associations between general MP use and measures of wellbeing. One study found that adolescents who used MP for social media had significantly lower self-esteem [ 15 ]. Using more sophisticated modelling in a large sample of adolescents, Przybylski & Weinstein [ 59 ] described an inverted-U-shape relationship between digital-screen time and mental wellbeing, such that moderate engagement with MP is not harmful and may be advantageous, and effects may differ on weekdays compared to weekends.

Bedtime use of wireless devices

Only one (low risk) out of 10 longitudinal studies included in this review examined associations between mental health outcomes and bedtime MP use, measured both at baseline and at three-year follow-up [ 60 ] (Table 4 ).

Internalising symptoms : Increased bedtime MP use from baseline to follow-up was not associated with changes in depressed mood measured with a bespoke 5-item scale, after adjusting for sleep behaviour [ 60 ].

Externalising symptoms : Increased bedtime MP use from baseline to follow-up was not associated with changes in externalizing behaviour measured with a bespoke 7-item scale, after adjusting for sleep behaviour [ 60 ].

Wellbeing : Increased bedtime MP use from baseline to follow-up was not associated with changes in coping abilities and self-esteem measured with bespoke 1 item and 3-item scales, after adjusting for sleep behaviour [ 60 ].

Four out of the 19 cross-sectional studies included in this review examined associations between mental health outcomes and bedtime MP/WD use (Table 2 ).

Internalising symptoms : All three studies investigating associations between bedtime MP use and measures of internalising symptoms found significant positive associations. In particular, more frequent and longer bedtime use was associated with higher depressive [ 58 , 61 ], anxiety symptoms [ 58 ], suicidal feelings and self-injury [ 28 ]. However, in two studies this was partially mediated through reduced sleep duration [ 58 ] and sleep difficulties [ 61 ].

Externalising symptoms : No retrieved cross-sectional study investigated the associations between bedtime MP use and measures of externalising symptoms.

Wellbeing : One cross-sectional study described that adolescents who used MP at bedtime scored less on the HRQoL scale by KIDSCREEN-52 compared to those who did not, particularly when using screen mobile devices in a dark room [ 54 ].

This systematic review evaluated the current evidence on associations between MP/WD use and mental health outcomes in children and adolescents across 25 studies published up to 2019. With regards to our objectives, firstly, we found evidence to suggest that greater use of MP/WD may be associated with poorer mental health in children and adolescents, but that the strength of the associations vary partly depending on the time and nature of MP/WD usage. Secondly, we found evidence that bedtime MP/WD duration or frequency of use in particular is associated with worse mental health. Third, based on limited available research we found no evidence supporting a direct impact of RF-EMF on mental health. Finally, more studies are needed to clarify whether the different uses of MP/WD have distinct impacts on specific psychopathology. In particular, we found that the general use of MP/WD might be associated with externalising symptoms in children and adolescents.

We found substantial between-study heterogeneity in the choice of exposures and mental health outcomes, methods of exposure assessment, scales used to assess outcomes, study design, population selection, and approaches taken to address confounding variables—limiting our ability to infer general conclusions. This combined with the fact that a large proportion of studies (16 out of 25) were rated as high risk of bias, may explain the considerable between-study discrepancies on the presence/direction of associations found. Limitations to exposure assessment (as discussed below) imply that some associations could have been missed, while lack of correction for known confounding variables and differential recall bias in studies with cross-sectional design may have inflated the magnitude of associations [ 62 ]. Our synthesis is predominantly based on cross-sectional data, with few longitudinal studies to date producing inconsistent results.

The results of the current review largely align with recent systematic reviews on aggregated electronic screen time in children and young people, which have concluded that there are positive small but significant correlations between screen time and young children’s internalizing and externalizing behaviours [ 63 , 64 ], and that longitudinal associations between screen time and depressive symptoms varied between different devices and uses [ 64 ].

MP/WD usage

The strength and direction of associations between MP/WD use and mental health outcomes appear to depend on exposure-related factors including: the type of device, the purpose and the time-pattern of use, and the method of exposure assessment. For example, significant associations between MP use and symptoms of depression are reported for general MP use, but not when only measuring texting longitudinally [ 56 ] and fewer symptoms were reported on days when adolescents sent more texts in a cross-sectional study [ 45 ]. Similarly, no association with mental health outcomes emerged from specifically examining the effect of phone call duration or frequency in adolescents [ 14 , 15 , 48 ], unless calls occurred at night-time [ 58 , 60 ]. Six studies specifically reported to be measuring smartphone use [ 11 , 12 , 15 , 51 , 57 , 59 ]. Almost all other studies reported aggregated measures from devices capable of internet use with those that are not capable, making disentangling smartphone-specific effects impossible.

Overall, our observations are consistent with previous literature on differential effects depending on modes of technology use. For example, interactive screen time such as the use of a computer has been found to be more detrimental to sleep than passive screen time such as television watching [ 24 , 65 ]. Historically, aggregated “screen time” was believed to impact health via displacing activity away from more adaptive behaviours [ 66 ], but this fails to capture the current diverse scopes of MP/WD use, from information seeking, to social interaction and entertainment [ 67 ]. Future studies should clarify how different modes of MP/WD use may have distinct psychological consequences, some of which are likely to foster resilience as well as increase vulnerability to mental health disorders.

An emerging area of the literature that holds promise explaining how the use of mobile phone use may explain variation in mental health in young people involves defining problematic mobile phone use or problematic smartphone use (PSU). This domain of behaviours has been conceptualised in a way that corresponds to the constructs of behavioural addiction. Previous studies have defined PSU through self-report scales with items with diagnostic criteria that resemble the criteria for substance use disorders (SUD), specifically symptoms of dependence such as loss of control (trouble limiting one’s smartphone use), tolerance (progressive increase in smartphone use to achieve the same psychological rewards) and withdrawal (negative symptoms on withdrawal) [ 68 ]. This approach has already shown that PSU is associated with poorer wellbeing and mental illness: a recent meta-analysis investigating psychological and behavioural dysfunctions related to smartphone use in young people has shown that PSU was associated with an increased odds of depression, anxiety, and stress; however, most research subjects within the pooled sample for depression and anxiety were over the age of 18 [ 18 ]. Furthermore, in common with other related constructs of problematic technology use associated with dysfunction (such as internet addiction and internet gaming addiction [ 69 , 70 ]), some commentators have raised concerns that diagnosing individuals with PSU who display behavioural addictive symptoms with borrowed items from the diagnostic criteria of substance addiction disorders may not improve understanding of problematic use of technology’s aetiology and psychological sequelae [ 71 , 72 ]. Nonetheless, although out the scope of this review, investigating MP/WD usage through the paradigm of PSU and addiction research with younger children, who are not yet as studied as college students, could potentially inform this field.

A major limitation in most studies was the choice of self-report measures to assess MP/WD exposure without external validation. Self-report device use is subject to measurement error such as recall difficulty and bias (e.g. call duration is considerably overestimated in adolescents populations [ 73 , 74 ]). However, as children and adolescents favour online activity over calls and use wi-fi, data from self-report questionnaires may be more reliable indicators than activity inferred from operator-reported data [ 75 ]. Some self-report methods may be more robust, for example EMA may eliminate recall bias compared to self-report questionnaires or diaries [ 9 ], but participants may selectively respond to certain EMA signals [ 76 ]. Combining different methods of assessment has so far highlighted incongruencies [ 47 , 48 ] and suggests a need for refining methodological rigour in measuring exposure. Future study-designs should confront these potential sources of bias by cross-validating different self-report instruments combined with device-recorded assessments of MP/WD use. Understanding measurement of MP/WD use and how likely exposure misclassification occurs is of critical importance. Some researchers have used duration of usage as a proxy for whether smartphone usage is problematic, i.e., is excessive and includes behaviours linked to addiction and impaired control. There is no established cut-off beyond which usage is defined as problematic, nor is usage alone sufficient for this classification without subjective distress [ 77 ]. Measures of problematic use can capture constructs that are distinct from measures of daily usage and duration, yet only with improving tracking and logging media use can the relationship between the two be understood [ 78 ].

Assessment of mental health

Assessment of outcomes also included a wide range of different instruments, hindering direct comparison and limiting conclusive generalisable data synthesis. Mental health outcomes were investigated with a variety of self-report measures including ad hoc items [ 13 , 16 , 28 , 53 , 57 ], scales [ 8 , 12 , 17 , 47 , 49 , 50 , 51 , 52 , 56 , 59 ], sections of scales [ 9 , 10 , 14 , 15 , 45 , 60 , 61 ] and the same scale was even used with different cut-off levels [ 11 , 12 , 17 , 46 , 47 , 49 , 50 , 51 , 52 , 54 , 55 ].

No study examined clinically diagnosed mental disorders and only one study used a self-report version of a structured interview: the CIS-R [ 56 ]. Given the public health relevance of this research area, we recommend use of validated instruments suitable for the general population but that have been standardised against clinical cut-offs (such as the PHQ-9, GAD-7, SDQ) and validated for younger children combined with parent-reported outcomes, such as the Common Measures for Mental Health Science [ 79 ]. Furthermore, robustness of findings would be increased by linkage with clinical data such as health records, with a view to drawing policy recommendations.

Radiofrequency-EMF

We found no clear evidence supporting a direct effect of RF-EMF on mental health in children and adolescents. Only one study from the search time period directly assessed RF-EMF exposure using dosimeters [ 48 ]. Only designs that combine measures of device usage with measurements from all local RF-EMF sources (Bluetooth, other wireless networks), can discern whether RF-EMF dosage from MP/WD is responsible for variation in mental health outcomes. Even with these measures, disentangling effects is not straightforward, since MP/WD usage often co-occurs with changes in behaviour. Schoeni, et al. [ 48 ] showed one approach to addressing these issues; alongside self-reported device usage, network operator-reported calls and data traffic, and other local RF-EMF sources, they measured types of device usage deemed negative exposure controls for RF-EMF (gaming on computers, instant messaging). They found the duration of data traffic on the mobile phone, or the number of texts sent per day were more consistently associated with symptoms of concentration difficulties than one-year cumulative RF-EMF dose, suggesting mechanisms other than RF-EMF absorption were likely to explain differences in concentration. Further research in this area must move beyond exposimeter measurement and modelling of RF-EMF exposures given their inability to accurately measure RF levels from the user’s mobile phone. 5G base stations use narrow beams aimed from base stations to the user’s device. A large proportion of RF-EMF dosage will be triggered by a user’s device demanding data from the network, resulting in high spatio-temporal variations in the RF-EMF exposure. Future studies investigating effects of RF-EMF from mobile devices may now require personal exposure monitors worn on the body to address these challenges, whilst continuing to use device-reporting software, and activity-logging mapped with spatio-temporal data [ 80 ].

The role of sleep

Consistent with previous literature, we found credible evidence that adverse outcomes may derive from MP/WD use at night. All cross-sectional studies examining bedtime use found a significant association with worse mental health, including higher levels of internalizing symptoms [ 28 , 58 , 61 ] and lower wellbeing [ 28 , 54 ].

There is good evidence that sleep may act as a mediator for the effects of MP/WD on depression symptoms. Two studies found a mediating role for sleep difficulties [ 60 , 61 ], and one found sleep duration mediated this relationship [ 58 ]. In both cases, the association between mobile phone use and depression was attenuated when conditioning on sleep and other demographic variables. This mediation could occur through the content of messages received, which could increase cognitive and emotional arousal [ 28 , 60 ]. Alternatively, sleep quality could be affected by physical mechanisms such as melatonin suppression via exposure to bright light from screens, as observed in lab research [ 81 , 82 ]; findings from Mireku et al. [ 54 ] support this as they found that young adolescents were found to have a greater likelihood of lower HRQoL when using MP/WD at night-time in the dark as opposed to with lights on. Two studies however found that the association between bedtime use and internalizing symptoms persisted even when adjusting for sleep duration [ 28 , 58 ] or sleep latency [ 28 ]. Taken together, this suggests that MP/WD is only partially mediated by sleep duration or quality [ 26 , 83 ], and may affect mental health through other mechanisms. Only one longitudinal study conditioned on sleep behaviour and found that the direct association between bedtime MP/WD and all mental health indicators was non-significant when controlling for sleep behaviour [ 60 ].

A few studies examining the effects of general MP/WD use also controlled for either sleep duration or sleep problems with mixed findings dependent on gender and purpose of device use [ 10 , 12 ]. One study using cross-lagged panel analysis identified bidirectional longitudinal associations between both MP use and mental health outcomes as well as between MP use and sleep outcomes [ 8 ], suggesting that more complex models might be needed to infer the correct causal mechanisms.

Future longitudinal research should combine measures of both general and bedtime MP/WD use with sleep behaviour assessment. Given the known relationship between sleep disorders and behavioural problems such as delinquency, drug use and sexual risk-taking [ 84 ], future research should also investigate the role of sleep variables as potential confounders or mediators of the association between MP/WD use and externalising symptoms in children and early adolescents.

Social media

We found that the association between MP and mental health outcomes was influenced by the nature and type of use, with social media more often associated with negative sequalae. Three cross-sectional studies found consistent evidence that social media use was associated with negative mental health outcomes in adolescents, in particular higher internalising symptoms including depression, anxiety, negative self-esteem and somatization [ 11 , 12 , 15 ] and also externalising symptoms [ 15 ]. More than two hours/day on social networking and online chats was associated with a higher risk of depression in Japanese adolescents, even when adjusting for sleep duration [ 11 , 12 ]. These findings suggest that the content viewed or received, or the type of interactions developed by children and adolescents using MP/WD (e.g., on social media sites) may be harmful, rather than the duration of general use of MP/WD itself. Accordingly, recent research has focussed on potential harm from either broadcasted ideals driving feelings of inadequacy or social pressure to conform [ 85 ] or from normalising, triggering and contagion of harmful behaviour, such as self-harm [ 86 ] and orthorexia [ 87 ].

The specific relationship between social media and mental health outcomes may explain a chronological trend found in our review: only studies collecting data from 2012 onwards [ 8 , 9 , 10 , 11 , 12 , 14 , 15 , 16 ] found a significant association between internalizing symptoms and general MP use in adolescents. In 2019, half the UK’s 10-year-olds own a smartphone, compared with only 18% of 8-11 s, and 62% of 12-15 s in 2012 [ 1 , 88 ]. Smartphones allow truly mobile and continuous access to the internet, including at sensitive times (bedtime) and without parental supervision, which may explain this observed trend.

These initial findings need to be replicated in longitudinal studies dissecting the mental health impact of different types of MP/WD use. None of the reviewed studies probed for specific uses of social media (e.g., interpersonal support, social comparison), nor for the time spent on each platform. Unless the specific type of data and content viewed by children and adolescents on social media (and other online activities using MP/WD) is analysed, much of the commentary on the mechanism by which usage might affect mental health remains conjecture [ 89 ]. Digital phenotyping could represent a promising avenue towards understanding these mechanisms (as well as their interaction with other factors such as sleep). By measuring mental health symptoms and device-recorded children’s digital activities at a high temporal resolution [ 90 ], future studies could understand the relationship between inter-individual heterogeneity in mental health trajectories and MP/WD messaging patterns and online usage, supported by new technologies such as screenomics, the machine-learning assisted categorisation of images and text [ 91 , 92 ]. Whilst there are ethical challenges, these could be overcome by collaborations between researchers and social media corporations (who already hold children’s social network activity data), as well as strong engagement work with young people and parents in co-producing acceptable frameworks for data capture, data protection and study design.

Socio-demographic factors

Most but not all studies controlled for socio-demographic factors [ 15 , 16 , 45 , 57 ] with considerable heterogeneity in the covariates included (e.g., age, gender, SES, parents’ education level, family composition and ethnicity). Many of these factors are known to be associated with both MP/WD use and mental health outcomes. For example, gender divides [ 93 ], and differences in households´ SES shift the use and access to information and communications technology [ 94 ], the pattern of use and how parents manage their teens’ technology use [ 95 ]. Failing to condition analyses on these variables, e.g. SES, is likely to exaggerate the relationship between MP/WD usage and mental health outcomes. Some studies reported that age and gender may modify the effect of MP/WD use on mental health, though findings were inconsistent [ 28 , 61 ].

When is MP/WD use positive for mental health?

A number of studies reported findings of a positive rather than detrimental association between MP/WD use and mental health [ 45 , 57 , 59 ]. Przybylski and Weinstein [ 59 ] describe a concave-down quadratic model that supports the Goldilocks Hypothesis, i.e. that moderate technology use is not harmful and even advantageous for wellbeing. A moderate MP/WD use for communication may strengthen social connections and provide access to support from interpersonal relationships and communities, which may, in turn, improve psychological wellbeing [ 96 , 97 , 98 ]. This is also supported by evidence that social capital mediates the effects of smartphone use for communication [ 57 ].

Understanding the positive impact of MP/WD use on children and adolescents’ mental health is crucial in the current context of the COVID-19 pandemic and related policy responses, such as physical distancing, social isolation, and school closures. Evidence from studies on online activity of adolescents from early phases of the pandemic (outside the scope of this review as they did not focus on MP/WD-specific behaviour) suggest that time fostering online connections could act as a buffer against the negative impact of isolation on mental health as online interactions are likely to mimic offline dynamics [ 99 , 100 ]. However, other studies have found opposite findings: greater time on social media during the pandemic was related to higher depressive symptoms, despite lower feelings of loneliness [ 101 ], and divergent findings depending on the purpose of use and personality [ 102 ]. Given this dramatic change in context, we re-ran our search using our original search terms with the addition of COVID-19 keywords (see Supplementary Material). We found two studies that reported epidemiological analysis of child and adolescent MP/WD use and psychological outcomes during the pandemic compared to pre-pandemic assessments, but neither identified direct associations between post-pandemic change in MP/WD use and mental health [ 103 , 104 ].

Limitations

Due to heterogeneity in exposure and outcome assessments, we were not able to conduct a meta-analysis to calculate pooled effects. Device definitions in reviewed studies were often not specific, aggregating measures from devices capable of internet use with those that are not capable, making disentangling device- and activity-specific effects challenging. We encourage future reviews to conduct meta-analyses of specific MP/WD types of activity and their effects on mental health, as Sohn et al. have conducted with PSU [ 18 ]. A further consequence of not conducting a meta-analysis is that we were not able to estimate publication bias, evidence of which has been reported in a recent systematic review into child screen time and behaviour problems [ 63 ].

Our ability to infer causal relationships between MP/WD use and mental health was limited by the small number of longitudinal studies, and for those studies further limited by the assumption of unidirectional causal relationships. It remains unknown whether evidence on the effects technology use is skewed by children and adolescents seeking support for ongoing symptoms and bidirectional causal loops may exist between MP/WD usage and mental health [ 105 , 106 ]. Indeed, a recent systematic review on longitudinal studies in this field reported the relation between screen time and subsequent depression was stronger than the reverse, i.e., depression and subsequent screen time [ 64 ].

Other limitations include: first, most evidence to date comes from high-income countries, which limits the generalizability of findings. Second, despite most of the studies controlling for SES, many studies relied on convenience samples drawn from schools instead of population-based samples and therefore may not reflect the global range of children’s social, cultural and economic environments. Third, we decided to adopt broad groupings of “internalizing symptoms”, “externalizing symptoms”, and “wellbeing” to synthesise the data, which may result in loss of important information about potential effects related to more specific disorders. Finally, although the role of cognitive function falls outside of the scope of the present review, it is well known that cognitive functioning affects emotional processing and therefore in turn mental health. This is particularly so in early adolescence when pubertal and cognitive development occur in tandem with radical changes in one’s social environment. Future research should investigate whether MP/WD use´s impact on cognitive function might mediate effects on mental health outcomes, and explore potential mechanistic pathways between MP/WD use, cognitive development and mental health.

Conclusions and future directions

This systematic review expands upon previous work synthesizing findings regarding MP/WD usage and mental health from a predominantly under 18 years population. The studies included presented heterogeneous measures of both MP/WD usage and mental health, which limits the ability to synthesise findings in a conclusive and clinically meaningful way. More robust and standardised measures of MP/WD use are strongly needed to advance this area of research. In summary, we found suggestive evidence supporting a negative impact of general MP/WD use on externalising symptoms in children and early adolescents, while findings on internalising symptoms are less consistent. Sleep disturbance due to MP/WD use appears to influence mental health outcomes but the specific role of sleep remains to be clarified. Major gaps remain, such as the need to dissect effects based on different types of MP/WD use and in relation to specific population characteristics.

Despite the fears held around wireless technologies, we believe that at this stage there is not enough evidence supporting a causal negative relationship between MP/WD use and children and adolescent’s mental health to justify particular public health interventions. It is likely that a large between-subject variability exists in how MP/WD usage may predict the development of mental health outcomes based on the interaction with a child’s psychosocial context and neurobiological factors. Future research should focus on identifying groups at-risk for intervention or behavioural modification with respect to technology use. This is of increasing importance in the context of the COVID-19 pandemic, which is accelerating digital transformations and divides, including how much adolescents use technology for learning, connection and social support.

Availability of data and material

Not applicable.

Code availability

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BGS is supported by a fellowship funded by the Koplowitz foundation. AS and the work is supported by the Medical Research Council (MRC) [grant number MR/R015732/1]. MBT is the principal investigator of the SCAMP study, which is funded by the Medical Research Council (MR/V004190/1), and which was originally commissioned by the Department of Health and Social Care via the independent Research Initiative on Health and Mobile Telecommunications—a partnership between public funders and the mobile phone industry (Secondary School Cohort Study of Mobile Phone Use and Neurocognitive and Behavioural Outcomes/091/0212). The SCAMP study was part supported by the MRC Centre for Environment and Health, which is currently funded by the MRC (MR/S019669/1, 2019–2024). The SCAMP study is part funded by the National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Exposures and Health, and the NIHR Health Protection Research Unit in Chemical and Radiation Threats and Hazards, which are partnerships between Public Health England and Imperial College London (Health Protection Research Units -2012–10141). The views expressed are those of the author(s) and not necessarily those of the MRC, NIHR, Public Health England or the Department of Health and Social Care. Infrastructure support for the Department of Epidemiology and Biostatistics was provided by the NIHR Imperial Biomedical Research Centre (BRC). MBT’s Chair and the work in this paper is supported in part by a donation from Marit Mohn to Imperial College London to support Population Child Health through the Mohn Centre for Children’s Health and Wellbeing.

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Braulio M. Girela-Serrano and Alexander D.V. Spiers are joint first authors of equal contribution.

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Division of Psychiatry, Department of Brain Sciences, Imperial College London, 7th Floor, Commonwealth Building, Du Cane Road, London, W12 0NN, UK

Braulio M. Girela-Serrano, Liu Ruotong, Shivani Gangadia & Martina Di Simplicio

Westminster Children and Adolescents Mental Health Services, Central and North West London NHS Foundation Trust, London, W9 2NW, UK

Braulio M. Girela-Serrano

MRC Centre for Environment and Health, School of Public Health, Faculty of Medicine, Imperial College London, St Mary’s Campus, Norfolk Place, London, W2 1PG, UK

Alexander D. V. Spiers & Mireille B. Toledano

NIHR Health Protection Research Unit On Chemical Radiation Threats and Hazards, School of Public Health, Faculty of Medicine, Imperial College London, St Mary’s Campus, Norfolk Place, London, W2 1PG, UK

Mohn Centre for Children’s Health and Wellbeing, School of Public Health, Faculty of Medicine, Imperial College London, St Mary’s Campus, Norfolk Place, London, W2 1PG, UK

Mireille B. Toledano

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Correspondence to Braulio M. Girela-Serrano .

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Girela-Serrano, B.M., Spiers, A.D.V., Ruotong, L. et al. Impact of mobile phones and wireless devices use on children and adolescents’ mental health: a systematic review. Eur Child Adolesc Psychiatry 33 , 1621–1651 (2024). https://doi.org/10.1007/s00787-022-02012-8

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What Your Phone Might Be Doing to Your Brain

January 5, 2023

Brain Health

Nearly three years into the COVID-19 pandemic, screen usage has increased exponentially, especially among children. The average amount of time children spend staring at screens has risen 52 percent since the beginning of the pandemic, according to a recent study published in JAMA Pediatrics .

Even before the pandemic, the average American adult spent about 3 hours and 30 minutes a day using mobile internet in 2019, an increase of about 20 minutes from a year earlier, according to measurement company Zenith. (You probably already know this if you get one of those “screen time usage” reports weekly from your phone.)

Smartphones are an integral part of our lives, but what effect does all this scrolling and staring have on our brains? What can we do to protect ourselves and our children?

Here’s what we know.

Smartphones May Affect How We Think

Although there is not yet clear evidence that smartphones have a long-term negative effect on the brain, health experts are concerned that excessive use can be harmful—especially to children whose brains are not yet fully developed.

For example, research has shown that smartphones may adversely affect cognition (but more study is needed to understand the connection). Cognition is the process of acquiring and applying knowledge through thought, experiences and the senses.

A study in the Journal of the Association for Consumer Research found that cognitive capacity was significantly reduced whenever a smartphone is within reach, even when the phone is off.

With smartphones, you no longer need to memorize a phone number or find your way around town using a map—your smartphone does these things for you. Research shows this overreliance on your phone can lead to mental laziness .

Modern connectedness also could be rewiring our brains to constantly crave instant gratification.

“Social media, in my view, provides the user with inconsistent positive reinforcement, similar to gambling . When the user posts a message, the number of likes serve as a reward, and the chance of more likes increases with one more scroll or one more message. The user is not always rewarded with likes and positive responses, but these are quite satisfying when occurring. In fact, the user may unconsciously change their views to appease friends who provide likes, and select a friend population with shared values,” says UNC Health neurologist Jorge L. Almodóvar-Suárez, MD .

Smartphones May Affect How We See

Since the beginning of the pandemic, there has been an increase in children with myopia (nearsightedness), says UNC Health neuro-ophthalmologist Maja Kostic, MD, PhD .

Nearsightedness is an eye condition in which people can view objects up close clearly, but things farther away appear blurry.

“We are currently doing studies to measure the effect of smartphone usage on children’s long-distance vision,” Dr. Kostic says. “If kids are looking at phones at a near distance for long hours without any break, then we think this could lead to more and more progression with myopia .”

Smartphones Can Impair Social and Emotional Skills

The more time you spend looking at a screen, the less time you spend interacting in person with others. This makes it more difficult to establish interpersonal connections and strong relationships, which are important for mental health and the health of the community at large.

Using screens to zone out or decompress is fine in moderation, but there can be a negative effect if excessive.

“Anything that is done out of moderation is cause for concern,” says UNC Health pediatric and adult neurosurgeon Carolyn Quinsey, MD . “For children, they are learning early in life to engage in passive activities instead of being actively engaged, which can become a habit as they grow older.”

That lack of face-to-face interaction can lead to depression . Health experts are also concerned that excessive social media use—especially among teens—can lead to depression and anxiety.

“We know that social media can be linked to depression and anxiety,” Dr. Almodóvar-Suárez says. “When we go into social media and post, we’re posting a manufactured life—picking the best pictures of ourselves or the nicest picture from our trip. We’re not showing an ugly part of the trip, like a four-hour bus ride or an unflattering picture. The problem is that when we see that from other people, we start to question why we can’t be having that same experience. We feel like something is missing.”

Concern about the long-term effects of technology and social media use on teen social and emotional development was the impetus for a new research center at the University of North Carolina at Chapel Hill that will study the impact of technology and social media on adolescent brains.

How to Protect Your Brain from Your Phone

You don’t have to swear off your phone completely to improve your brain health. The important thing is to be aware of how you use your phone and other devices and to prioritize other activities and in-person interactions whenever possible.

“The first thing adults or children can do is create some awareness around it. A lot of people aren’t aware of how much time they’re spending on a particular activity that involves a screen,” Dr. Quinsey says.

Most smartphones allow you to track your average screen time hours. Pay attention to how much time you are spending.

“If you feel like that’s a problem for you or your child, make adjustments,” Dr. Quinsey says.

“We can be more purposeful about the time that we’re using a screen, rather than it being so habitual.”

Some people find it helpful to delete social media apps from their phone or to download software that limits the time they’re permitted on a particular site. Others designate hours of the day “phone-free” to protect family time. It can be empowering to trade screen time for reading a book or working on a hobby.

As you scale back your phone time, the increase in your mental clarity or mental health might be motivation enough to keep it up.

To avoid harmful side effects of screen usage on the eyes, adults and children should practice “screen hygiene,” a set of best practices for using screens. To start, hold digital media at least 18 to 25 inches from your face.

Also, practice the 20/20/20 rule: Every 20 minutes, look up from your device at something 20 feet ahead for 20 seconds. This relaxes your eyes. For example, look out the window between rounds of Candy Crush or after a chapter or two of an e-book.

Forgoing any use of technology is not realistic, but it’s important to set boundaries and time limits—your brain will thank you.

Talk to your doctor if you have concerns about the effect your devices are having on your brain. If you need a doctor, find one near you .

Negative impacts of Mobile phones

Jul 28, 2014

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Outcomes Use key terms appropriately Explain a negative impact using examples Extend you writing using connectives. Refer to the mark scheme. Starter Watch this clip and define what the four conflict minerals are and why. Negative impacts of Mobile phones. Objectives

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Outcomes Use key terms appropriately Explain a negative impact using examples Extend you writing using connectives. Refer to the mark scheme Starter Watch this clip and define what the four conflict minerals are and why Negative impacts of Mobile phones Objectives Consolidate your knowledge about a negative aspect of mobile phones in a piece of extended writing Key Terms Congo Tungsten Human rights Conflict Tantalum Trade Militia Tin Consumer Minerals Gold • http://www.enoughproject.org/conflict_areas/eastern_congo

Who are these people and what is their link to mobile phones

Listen to this clip from the Enough! ProjectEnough! is a project who monitors human rights abuses • http://www.youtube.com/watch?v=aF-sJgcoY20&feature=player_embedded

Video Notes • Eastern Congo is experiencing the most violent conflict in the world since the second world war. Sexual Violence • Our Consumer appetites for electronic goods contributes to Congo’s violence • Tungsten (for vibration), Gold (coats wires), Tin(on circuit boards), Tantalum (stores electricity) • Conflict minerals • Eastern Congo • Mines are controlled by militias who act like a mafia • Minerals are smuggled to neighbouring countries e.g. Rwanda and Uganda • Smuggling point are also controlled by the militia. Uganda and Rwanda make money from this • Rape is used to intimidate and punish local Congolese populations to force them to continue to support the militia. Their human rights are abused • DR Congo, Uganda and Rwanda are all LEDC’s and suffer in parts from extreme Poverty • Smuggled minerals are shipped to Thailand, Malaysia, China and India for processing. • China and India dominate the mobile phone manufacturing. It is a vital trade for their development • Minerals are mixed with other minerals (smelted) and then processed and shipped to Europe and the UK • As consumers we can contact the companies such as Nokia, Sony etc and demand that they do not use conflict mineral • Nokia have a good record of corporate responsibility. Use examples of what they do to

How to write you essay Introduction What is the main issues Introduce your key words Conflict mineral Human rights abuses Militia Main What are the negative impacts? How are we as consumers and our choices adding to the conflict Who is suffering Consumer appetite Extreme Violence Dangerous conflict Control of mines Smuggling Conclusion Sum up the problem link to consumers Suggest a solution Use examples of good corporate practice Consumer choice Consumer pressure Corporate responsibility Nokia

http://www.raisehopeforcongo.org/content/initiatives/conflict-minerals http://www.raisehopeforcongo.org/content/initiatives/conflict-minerals

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Numbers, Facts and Trends Shaping Your World

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• Mobile Connectivity in Emerging Economies
• 2. Majorities say mobile phones are good for society, even amid concerns about their impact on children

Table of Contents

• 1. Use of smartphones and social media is common across most emerging economies
• 3. People say the internet brings economic and educational benefits – but some are concerned about the societal impact of social media
• Acknowledgments
• Methodology
• Appendix A: About the focus groups
• Appendix B: Compiled usage figures
• Appendix C: Detailed tables

Across the 11 countries surveyed, people’s attitudes toward mobile phones tend to be largely positive. In most of the countries, a large majority say mobile phones have been good for them personally, and many also say mobile phones positively impact education and the economy. Mobile phone users also overwhelmingly agree that their phones help them to stay in touch with faraway friends and family and keep them informed of the latest news and information.

At the same time, people’s positive attitudes are paired with concerns about the impact of mobile phones on certain aspects of society – and especially their impact on children. In eight of these countries, a majority of the public says that the increasing use of mobile phones has had a bad impact on children today. And when asked about the potential risks of mobile phone use, majorities in every country say people should be very concerned that mobile phones might expose children to harmful or inappropriate content.

I think mobile phones have made the world like a global village. MAN, 24, KENYA

Overwhelming majorities say mobile phones have been more positive than negative for them personally

In nine of the 11 countries surveyed, large majorities say mobile phones have been mostly good for them personally. In Venezuela, people are more skeptical of the role mobile phones are playing in their lives. There, 49% say mobile phones have been mostly good for them personally, while 47% say they have been mostly bad. Elsewhere, no more than 11% in any country say mobile phones have been mostly a bad thing for them.

In nine of these 11 countries, majorities also say mobile phones have had a positive impact on society. But in most countries, people report less enthusiasm about the societal impact of mobile devices than about their personal impact. For example, while 82% of Jordanians say mobile phones have mostly been good for them personally, just 53% express positive views about their societal impact. And in Colombia, Tunisia and Mexico, there is at least a 10-percentage-point difference between shares who see the personal benefits of mobile phones and those who see the society-wide benefits.

Regardless of the type of mobile phone people use – basic, feature or smart – most have similar views about how their lives and societies have been impacted by their devices. 9 Across all surveyed countries, basic or feature phone users are just as likely as smartphone users in their country to say mobile phones have mostly been a positive thing for them personally. And in all countries but Mexico, similar shares of smartphone users and those with less advanced devices say the societal impact of mobile phones has mostly been good. In Mexico, where smartphone use is relatively low compared with other countries , smartphone users are somewhat more likely than basic or feature phone users to say the impact on society has been mostly positive (77% vs. 69%).

But there are some differences between mobile phone users and those who do not use a mobile phone at all. In five of these 11 countries (India, Kenya, Lebanon, Mexico and South Africa), mobile users of any kind are more likely than non-users to say that mobile devices have had a mostly positive impact on society.

Mobile phone users have mixed views about upsides and downsides of their phones, are especially divided over whether they ‘couldn’t live without’ phones

In every country surveyed, mobile phone users are more likely to say their phone is something that frees them rather than something that ties them down. At least 63% in five countries (Kenya, Vietnam, Venezuela, South Africa and the Philippines) characterize their phone as something that frees them, whereas users in other countries are somewhat more ambivalent. For example, while 46% of Jordanian mobile phone users say their phone frees them, 25% say it ties them down, and 21% volunteer that neither statement holds true. In Lebanon, 40% of mobile phone users say their phone frees them, compared with 30% who say it ties them down.

“It’s like the mobile phones become your partner. WOMAN, 40, PHILIPPINES

Across the 11 countries surveyed, mobile phone users are somewhat more divided when it comes to whether their phone helps save them time or makes them waste time. In seven countries, larger shares say their phone helps save them time. Kenyans are especially likely to see their phone as a time saver; 84% of mobile phone users say their phone saves them time, compared with 14% who say it wastes their time. Venezuelan (71%), South African (65%), Indian (64%), Vietnamese (63%), Tunisian (54%) and Colombian (50%) phone users are also more likely to say that phones save them time rather than waste it. But mobile phone users in Jordan and the Philippines generally believe they waste more time on their phones than they save, while Mexican and Lebanese phone users are roughly evenly divided in their assessments.

Mobile phone users are even more divided when assessing their reliance or lack thereof on their mobile device. In six countries – Mexico, Colombia, India, the Philippines, Venezuela and Vietnam – around half or more see their phone as something they don’t always need. But in five others – Jordan, Lebanon, South Africa, Tunisia and Kenya – users are more inclined to say they couldn’t live without it.

In some instances, people’s perceptions of the necessity of their mobile device is not linked to their assessments of its utility in other aspects of their life. For instance, a majority of Venezuelans say their phone is something that frees them and helps them save time – but just 29% say they couldn’t live without it. Conversely, a majority of Jordanians say they couldn’t live without their phone – even as they are more likely to describe it as a time waster rather than a time saver.

Consistently, smartphone users tend to be somewhat more critical of their device than basic or feature phone users in their country. For example, in every country smartphone users are more likely than basic or feature phone users to say their phone makes them waste time. And in all countries except Lebanon, smartphone users are more likely to say their phone ties them down rather than frees them.

There are also prominent and consistent differences by age. In every country surveyed, mobile phone users ages 50 and older are significantly more likely than users ages 18 to 29 to believe their phone helps them save time. The age gap is particularly notable in Vietnam, Tunisia and Colombia, where the shares of older adults who see their phone as a time saver surpass those of younger adults by at least 27 percentage points. And, while it is true that younger adults use smartphones and social media at higher rates than older adults, in every country but India these age differences persist even when accounting for age-related differences in usage.

Users largely agree mobile phones help them maintain long-distance communication, stay informed about important issues

When asked about a variety of ways in which mobile phones might affect their day-to-day lives, users across the surveyed countries generally agree that mobile phones have mostly helped them keep in touch with people who live far away and obtain information about important issues. But there is less consensus when it comes to mobile phones’ impact on people’s ability to earn a living, concentrate and get things done, or communicate face-to-face.

In general terms, communication is much more efficient. You are more interconnected, [whether] with your relatives or with world affairs. MAN, 26, MEXICO

Large majorities say their phones have mostly helped them stay in touch with people who live far away. A median of 93% across the 11 countries surveyed express this view, whereas a median of just 1% say mobile phones have hurt their ability to stay in touch. Majorities also say their mobile phones have helped them obtain information and news about important issues, ranging from a low of 73% in Vietnam to a high of 88% in Kenya. And only small shares (from 1% to 6% of users) indicate that phones have hurt their ability to do this.

In all 11 countries, smartphone users are significantly more likely than basic or feature phone users to say their phone has helped them obtain news and information. The difference is particularly prominent in Lebanon, where 83% of smartphone users say the impact has been positive, compared with 26% of non-smartphone users. And in Jordan, smartphone users are much more likely than non-smartphone users to say their phone has mostly helped them obtain information (83% vs. 44%).

Less consensus over whether mobile phones help users earn a living, concentrate or communicate face-to-face

Across the 11 countries surveyed, there is less agreement about whether mobile phones have helped people earn a living. Majorities of users in nine countries say their phone has had a positive impact on their livelihood – ranging from 55% in Tunisia to 81% in Kenya – while Jordanians and Lebanese most commonly say that mobile phones have not had much impact either way on their ability to make a living. Still, few people see mobile phones having a negative effect. Even in Jordan and Lebanon, nearly four-in-ten say the impact has been favorable.

There is less consensus among mobile phone users that their devices have helped them to concentrate and get things done. Majorities in eight out of 11 countries say mobile phones have mostly helped them concentrate and get things done. But notable shares in the Philippines (30%), Lebanon (18%) and India (16%) say mobile phones negatively affect their concentration.

In some instances, these attitudes are related to the type of device users carry – although this relationship varies by country. Smartphone users in five out of 11 countries – Lebanon, India, Jordan, Colombia and Venezuela – are more likely than other phone users to say their phone helps them concentrate and get things done, while there are no differences based on smartphone usage in the other six countries surveyed. This pattern is particularly salient in Lebanon, Jordan and India, where smartphone users and non-smartphone users differ by at least 10 percentage points.

These findings echo the concerns raised by some focus group participants (see Appendix A for more information on how the groups were conducted). Some respondents noted how mobile phones bring distractions and shorten their attention spans, leading people to commit basic errors or not complete work because of the attention paid to their devices. In every group held in the Philippines, for example, at least one participant brought up that she had burned the rice she was making because of her focus on her phone.

Because I was busy texting my client, my rice got overcooked. WOMAN, 40, PHILIPPINES

Lastly, majorities of users in eight countries say their mobile phones have helped their ability to communicate face-to-face – but notable shares in many countries say that impact has been mostly negative. In particular, 35% of Lebanese phone users say mobile phones have hurt their ability to communicate face-to-face.

In focus groups, some lamented that more and more people prefer virtual communication enabled by mobile phones and other technologies to face-to-face interaction. A few participants across the four countries where focus groups were conducted also pointed out similar trends among children and young people.

People meet less because of their phones; people use telephones to express themselves to avoid face-to-face discussions. MAN, 23, TUNISIA

Because these questions center on people’s personal relationship with their device, they were only asked of those who own or regularly share a mobile phone. For those who reported not using a phone at all, a different set of questions were posed: How do mobile phones, in general, shape people’s ability to stay in touch with those far away, to obtain information, and so on? Broadly, non-users’ impressions of the impact of mobile phones tend to mirror the ways users feel about their own devices. The vast majority of non-users feel that mobile phones help people stay in touch with those who live far away, but smaller shares think they help people to concentrate and get things done or communicate face-to-face.

Majorities in most countries say mobile phone use has had a good impact on education, but fewer see positive impacts on children, health, morality

Publics in the 11 nations polled view mobile phones as having a range of positive and negative consequences when it comes to their broader impact on their country and its society. Most notably, a median of 67% – and around half or more in every country – say the increased use of mobile phones has had a good influence on education. Slightly smaller majorities say the increased use of mobile phones has had a good influence on the economy (58%) as well as on their local culture (56%).

Few in these countries say mobile phones have had a good impact on children today

My kid’s always on his phone, and every time I address him he just nods while on his phone. WOMAN, 46, MEXICO

Across all dimensions measured in the survey, publics in the 11 countries are most negative about the impact of mobile phones on children. Nowhere does a majority feel that mobile phones have had a good influence on children. And in eight countries, majorities of the population say that mobile phones have had a bad influence on children today. Residents of the three Middle East and North African (MENA) countries surveyed are especially downbeat about mobile phones in this regard: 90% of Jordanians, 86% of Lebanese and 81% of Tunisians say mobile phones have had a bad influence on children in their country.

People also focus on the negative impacts of mobile phones on physical health, morality

In addition to the impact of mobile phones on children, health and morality stand out as particular areas of concern. A median of 40% – and clear majorities in Lebanon (71%), Jordan (69%) and Tunisia (63%) – say the increasing use of mobile phones has had a bad influence on people’s physical health. Some focus group participants expressed similar sentiment by commenting that excessive screen time, phone “addiction” and lack of physical activities were potential health-related challenges.

Meanwhile, a median of 34% say mobile phones have had a positive impact on morality, similar to the share who say the impact has been negative. As was the case with children and health, Lebanese, Jordanians and Tunisians hold the most unfavorable views in this regard. Roughly a third or more in Colombia, Mexico, Kenya and South Africa also say mobile phones negatively affect people’s morality.

Phones also give us much more room to conceal things. MAN, 42, MEXICO

As noted above, publics in Lebanon, Jordan and Tunisia stand out in their overall negativity toward mobile phones on these aspects of society. But other countries are conspicuous for having relatively positive attitudes in this regard. Kenyans, in particular, offer especially upbeat assessments of mobile phones. Half or more Kenyans feel that mobile phones have had a positive impact on each of these aspects of society, with the exception of children today (just 28% of Kenyans say mobile phones have been good for children). South Africans and Filipinos are also relatively positive about most areas surveyed.

In most countries, there are no differences between smartphone users and non-users – nor between social media users and non-users – when it comes to people’s views about the impact of increasing mobile phone use on children. But on other questions there is more variation between users and non-users. For instance, in six out of 11 countries larger shares of social media users than non-users say the increasing use of mobile phones has had a good influence on their nation’s politics. This includes all three MENA countries in the survey. Conversely, in eight of these 11 countries larger shares of social media users than non-users say mobile phones have had a bad influence on family cohesion.

Concern is widespread about the risk that mobile phones might expose children to immoral or harmful content

Despite the perceived benefits of increased mobile adoption in areas such as education, publics express concern about an array of potential downsides of mobile phone use. The survey asked about six possible risks from mobile phone use, and respondents in every country are most concerned about children being exposed to immoral or harmful content. A median of 79% – including a majority in each country surveyed – feel people should be very concerned about this.

Meanwhile, the prospect of users losing their ability to communicate face-to-face is the item of least concern in each country. In only two countries (South Africa and Colombia) are a majority of adults very concerned about declining face-to-face communication skills as a result of mobile phone usage.

Among these 11 countries, Colombians rank in the top two most-concerned about all of these issues. Other countries that rank in the top two most-concerned on particular issues include: Mexico (identity theft and online harassment); Jordan (phone addiction and impacts on children); South Africa (exposure to false information and losing the ability to talk face-to-face); and Tunisia (phone addiction).

Beyond these country-specific differences, concerns about mobile phone use exhibit few consistent or substantial differences relating to gender, age, phone type or social media usage. Notably, concerns about children are widespread across multiple groups. In most instances, men and women, older and younger adults, and social media users and non-users express similar levels of concern about the impact of inappropriate online content on children.

Additionally, men and women in most of these countries are similarly concerned about harassment and bullying – a noteworthy contrast to the gender-related differences often seen in surveys of online harassment among Americans. For example, a 2017 Pew Research Center survey found that 70% of women in the U.S. said online harassment was a “major problem,” compared with 54% of men.

It is relatively common for mobile phone users to limit the amount of time they – as well as their children – spend on their phones

“Sometimes I try to use [my phone] less, but it only lasts for two or three days and then I come back to the daily rhythm. WOMAN, 21, TUNISIA

Amid a widespread debate over the impact of various types of screens on children and adults alike, majorities of mobile phone users in five of these 11 countries say they have ever tried to limit the time they themselves spend on their phone. This behavior is especially common in the Philippines and Mexico, but somewhat less prevalent among mobile phone owners in Jordan, Lebanon, Venezuela and Vietnam.

In all 11 countries surveyed, smartphone users are more likely than non-smartphone users to say they try to limit the time they spend on their mobile phone. These differences are especially prominent in Vietnam (where 46% of smartphone users and 24% of non-smartphone users have done this) and Colombia (66% vs. 45%). And in 10 of these countries, larger shares of mobile phone users who also use social media say they have tried to limit their phone use relative to those who do not use social media.

People’s efforts to limit screen time also extend to children. Among parents whose child has access to a mobile phone, about half or more in seven of these countries say they ever set limits on how much time their child can spend on their phone. 10

As was true of limiting their own screen time, parents’ efforts to limit the time their child spends on his or her phone also differ by the type of phone they themselves own. 11 Smartphone-owning parents whose child also uses a mobile phone are more likely than parents with more basic phones to say they have tried to limit their child’s screen time in nine of these 11 countries. Indeed, this gap reaches double digits in nine of these 11 countries – and is as high as 22 points in Vietnam and Jordan.

Parents’ efforts to limit their child’s mobile phone use are also related to their concerns about the negative impacts of mobile phone use (such as online harassment or children being exposed to immoral content). In nearly every country surveyed, parents who say they are very concerned about at least five of the six issues tested are more likely to try to limit their child’s mobile phone use relative to those who are very concerned about two or fewer of these issues. The only exception to this trend is Jordan, where similar shares of highly concerned and less-concerned parents say they try to limit their child’s mobile phone use.

“You should be the one limiting your child. It’s up to you to make ways to be able to limit the problems that you encounter. That’s why even if my child is very interested with gadgets, he is consistently in the honor rolls … I make limitations.” WOMAN, 38, PHILIPPINES

It is common for parents to monitor their child’s mobile phone use, and notable shares monitor the phone activity of their spouse or partner

In the focus group interviews conducted as part of this study, mobile phone surveillance performed by immediate family members emerged as a common theme. Some parents mentioned that mobile phones allowed them to track the whereabouts of their children and to make sure they were not exposed to harmful content. And for people in marriages or romantic relationships, mobile phone “spying” and social media “stalking” sometimes become the source of drama, jealousy and harassment.

Among parents whose child or children use a mobile phone, a median of 50% say they ever monitor what their child is looking at or doing on the screen. But some variation exists across these countries. In Jordan, Colombia and Mexico, for example, clear majorities of parents do this, compared with 37% of parents in Vietnam and 38% in India.

Parents who use a smartphone are generally more likely to say they monitor their child’s phone usage than parents who use a basic or feature phone. This trend is seen in 10 out of the 11 countries and is especially prominent in Jordan and Vietnam, where smartphone users differ from other phone users by 30 percentage points each.

Parents’ likelihood of monitoring their child’s phone use also differs by their own social media presence. Parents who use social media and messaging apps in each country are more likely than parents who do not use social media platforms to say they monitor content on their child’s phone.

Monitoring of mobile phone activity also extends to marriages and romantic relationships

In all countries surveyed, it is less common to monitor a partner’s phone activity – although notable shares of those with a spouse or partner report doing so. 12 Among those whose partner or spouse uses a mobile phone, a median of 26% say they ever monitor their partner’s phone use. In the Philippines, this behavior is somewhat more common; 38% say they monitor their partner’s phone.

In most countries surveyed, younger adults are more likely to monitor their partner’s phone than older adults in their country. This trend holds even after accounting for the fact that younger adults are generally more likely than older adults to use smartphones or social media. In 10 countries, smartphone users ages 18 to 29 are more likely to say they monitor their partner’s phone activity than smartphone users ages 50 and older.

There are also notable gender differences when it comes to monitoring the phone activity of their significant other. In five of these 11 countries (Jordan, Venezuela, Vietnam, Mexico and Tunisia), larger shares of women than men say they ever monitor what their partner does on the phone. India is the only country surveyed where men are more likely than women to say they keep an eye on their partner’s phone.

When a guy commented on my post, my husband got jealous about it. WOMAN, 27, PHILIPPINES Talking from a married point of view, I think it’s brought a lot of mistrust. If my data is on at 10 in the night and someone sends something on WhatsApp, it’s always suspect. Who’s texting at 10? My husband is often suspicious. WOMAN, 32, KENYA

• Throughout this this report, mobile phone users include those who say they own or share a mobile phone. ↩
• In the survey, questions about parents and children were asked of all respondents. The results reported here were recalculated to exclude those who volunteered that they do not have any children, and/or that their child or children do not have a mobile phone. ↩
• The survey did not ask what type of phone the respondent’s child or children use. ↩
• In the survey, questions about spouses and partners were asked of all respondents. The results reported here were recalculated to exclude those who volunteered that they do not have a spouse or partner, and/or that their partner does not have a mobile phone. ↩

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• v.192(6); 2020 Feb 10

Smartphones, social media use and youth mental health

• Evidence from a variety of cross-sectional, longitudinal and empirical studies implicate smartphone and social media use in the increase in mental distress, self-injurious behaviour and suicidality among youth; there is a dose–response relationship, and the effects appear to be greatest among girls.
• Social media can affect adolescents’ self-view and interpersonal relationships through social comparison and negative interactions, including cyberbullying; moreover, social media content often involves normalization and even promotion of self-harm and suicidality among youth.
• High proportions of youth engage in heavy smartphone use and media multitasking, with resultant chronic sleep deprivation, and negative effects on cognitive control, academic performance and socioemotional functioning.
• Clinicians can work collaboratively with youth and their families, using open, nonjudgmental and developmentally appropriate approaches to reduce potential harms from social media and smartphone use, including education and practical problem-solving.
• There is a need for public awareness campaigns and social policy initiatives that promote nurturing home and school environments that foster resilience as youth navigate the challenges of adolescence in today’s world.

In the last decade, increasing mental distress and treatment for mental health conditions among youth in North America has paralleled a steep rise in the use of smartphones and social media by children and adolescents.

In Ontario, the proportion of teenagers reporting moderate to serious mental distress increased from 24% in 2013, to 34% in 2015 and to 39% in 2017, 1 with parallel increases in health service utilization. Inpatient hospital admissions of children and adolescents for mental health reasons increased substantially across Canada between 2007 and 2014, while admissions for other medical conditions in this age group decreased by 14%. 2 Between 2009 and 2014, admissions to hospital for intentional self-harm increased by 110% in Canadian girls. 3 Suicide is now the second leading cause of death for Canadian youth. 4 A recent analysis of survey data found the 12-month prevalence of suicidal ideation, attempts and nonsuicidal self-injury to be 8.1%, 4.3% and 8.8%, respectively, among adolescents aged 14 to 17 years, with all rates being higher in girls. 5 Similarly, administrative data in the United States show that presentations to hospital for suicidal ideation or attempts among children and adolescents almost doubled between 2008 and 2015, with the highest increase for adolescent girls. 6 Self-poisoning rates among 10- to 18-year-olds, which had declined in the US since the turn of the century, increased substantially from 2011 to 2018, primarily among girls. 7 Surveys of high school students in the US have shown a similar pattern for self-reported symptoms of depression, major depressive episodes and suicidality over the last 2 decades. 8 , 9

At the same time, social media use has increased markedly. In the US, the proportion of young people between the ages of 13 and 17 years who have a smartphone has reached 89%, more than doubling over a 6-year period; moreover, 70% of teenagers use social media multiple times per day, up from a third of teens in 2012. 10 The percentage of Ontario’s teenagers who reported spending 5 or more hours a day on social media increased from 11% in 2013, to 16% in 2015 and to 20% in 2017. 1 An analysis of Australian longitudinal data found that 86% of students owned smartphones in grade 8, increasing to 93% by grade 11, with increased use of social media communication with age. 11

We review the evidence that links smartphone and social media use with mental distress and suicidality among adolescents. We do not review evidence for online gaming. Although most existing data are observational, making causality difficult to establish, findings from a few longitudinal, randomized and controlled studies suggest that social media and smartphone use may be contributing to the rising burden of mental distress among youth. We consider the clinical implications of existing evidence, to help practising clinicians to work collaboratively with youth and families to mitigate potential negative effects of social media and smartphone use on mental health.

How has use of social media been shown to affect adolescents’ sense of self?

Two cross-sectional surveys of American and German university students, respectively, 12 , 13 found that students who spent more time on the social media platform Facebook were more likely to endorse feeling envy or sensing that others in their social network were better off than they were. The term “FOMO” — fear of missing out — has been defined as “a pervasive apprehension that others might be having rewarding experiences from which one is absent,” 14 and has been associated with increased stress related to Facebook use. 15

A systematic review of 20 studies found that use of social media was associated with body image concerns and disordered eating. 16 In a randomized study, female participants reported more negative mood after just 10 minutes of browsing their Facebook account compared with those who browsed an appearance-neutral control website. 17 Moreover, participants who were high in appearance comparison tendency reported an increased desire to change the appearance of their face, hair or skin after spending time on Facebook, in comparison with those who browsed the control website. 17

The nature of social media interactions, which are arm’s length, makes negative commenting both easy and more frequent than in-person interactions with peers. An Ontario survey of middle- and high school students showed that the odds of suicidal ideation, plans and attempts were all significantly higher among those who had experienced cyberbullying, even after controlling for a range of potential confounders. 18

Does social media addiction exist and can it affect mental health?

One study of repeat survey data from 2013, 2014 and 2015 associated the extent of self-reported use of Facebook with subsequent poor self-reported mental health and life satisfaction. 19 Concerns have been raised about social media platforms having been deliberately designed — in highly sophisticated ways that use behavioural psychology, neuroscience and artificial intelligence — to promote behavioural reinforcement and behavioural addiction. 20 , 21 Several cross-sectional studies have shown that high proportions of youth appear to be addicted to their smartphones, 22 , 23 but there is no standard or agreed-upon definition of smartphone or Internet addiction; studies have used different definitions and scales, varying from those that rely on behavioural addiction criteria, to measurement of the extent of functional impairment and level of device use. 24 , 25 As such, reported prevalence rates are highly variable. 25

A systematic review identified Internet addiction as being particularly associated with self-harm or suicidal behaviour based on 7 included studies, all of which were cross-sectional school-based surveys that used validated outcome measures and were rated as high or medium to high quality. 24 A recent large prospective study of senior high school adolescent students in Taiwan found that youth classified as experiencing Internet addiction had a significantly increased risk of having newly emerged self-harm or suicidal behaviour or both when re-evaluated 1 year later. 26

Two systematic reviews have shown that media multitasking is associated with negative effects on cognitive control, academic performance and socioemotional functioning in youth. 27 , 28 Most existing studies, however, are cross-sectional, and measures are heterogenous across studies with limited attempts to consider individual and contextual differences, making it impossible to establish causality. Youth with lower impulse control may be more susceptible to deleterious effects of media multitasking. A large longitudinal study of adolescents who did not have significant symptoms of attention-deficit/hyperactivity disorder (ADHD) at baseline found that high-frequency digital media use was positively associated with emergence of symptoms meeting Diagnostic and Statistical Manual of Mental Disorders–4th Edition (DSM-IV) criteria for ADHD over a 2-year follow-up period, even after adjusting for known confounders. 29

Can social media promote self-harm?

Youth communicate thoughts of suicidality and self-harm behaviours online, including sharing images of self-inflicted injuries. Explicit depiction of self-injury — particularly cutting — on social media is common, as shown by site content studies 30 , 31 that found photographs or live videos of self-injurious behaviour, many of which had no warnings about graphic content. Of particular concern were viewers’ comments, which typically contained positive feedback or personal disclosures about self-injury experiences, and rarely offered encouragement or discussion of recovery. Such findings show the potential for mental illness romanticizing and messaging that normalizes self-harm among youth. Indeed, a systematic review that included 26 studies (using qualitative, descriptive or cross-sectional methodology) found that social media platforms included normalization of self-harm behaviour, discussions about practical issues regarding suicidality and live depictions of self-harm acts. 32 At the same time, there were also positive elements, including providing a sense of community, suggestions for seeking treatment and advice on stopping self-harm behaviour.

Do the effects of smartphones on social skills affect mental health?

An observational study showed that spending more than a few hours per week using electronic media correlated negatively with self-reported happiness, life satisfaction and self-esteem, whereas time spent on nonscreen activities (in-person social interactions, sports or exercise, print media, homework, religious services, working at a paid job) correlated positively with psychological well-being, among adolescents. 33 Other observational studies have linked spending more than 2 hours a day on social networking sites and personal electronic devices with high rates of suicidality and depressive symptoms among adolescent girls, although youth who sustained high levels of face-to-face socializing were relatively protected against the negative consequences of too much time online. 13 , 34

Youth do increasingly interact online rather than in person, and smartphones can interfere even with face-to-face interactions via what has been termed “phubbing”: attending to one’s phone when in the presence of others. 35 A recent empirical field study using experience sampling in 304 participants showed that even the mere presence of phones on a table caused participants who were randomly assigned to that condition to feel more distracted and have lower enjoyment during social interactions compared with those who were randomized to putting their phone away. 36 Phone use was also found to predict distraction, which in turn predicted greater boredom and worse overall mood. 36

Does sleep-loss associated with use of social media affect mental health?

An analysis of US annual survey data found an abrupt increase in the proportion of adolescents getting insufficient sleep after 2011–2013, with more than 40% sleeping less than 7 hours most nights in 2015. 37 The study also showed an exposure–response relationship between daily electronic media use beyond 2 or more hours per day, and insufficient sleep. 37 An analysis of survey data from Ontario found that 63.6% of 5242 students aged 11–20 years slept less than recommended, 38 also showing a significant relationship between use of social media beyond 1 hour a day and odds of insufficient duration of sleep. 38

In a 14-day, randomized, crossover experimental study under well-controlled conditions, use of electronic screens before bedtime was shown to disrupt sleep in multiple ways: longer time to fall asleep and decreased evening sleepiness, reduced melatonin secretion, circadian clock delay, reduced amount and delay in rapid eye movement sleep, and reduced next-morning alertness. 39 A systematic review and meta-analysis that included 20 studies on the association between portable screen-based media devices and sleep outcomes found that use of media at bedtime was associated with decreased duration and quality of sleep and excessive daytime sleepiness. 40 Of note, the mere presence of portable screen-based media devices in the bedroom was shown to disrupt sleep, 40 possibly related to the temptation to check media devices when they are present or owing to a conditioned response involving increased arousal.

Data from a longitudinal study of 1101 adolescents in Australia showed that poor sleep mediated the relationship between nighttime mobile phone use and subsequent depressed mood, externalizing behaviours and decline in self-esteem and coping based on various validated scales. 11 In another longitudinal study involving 2286 adolescents in Europe, magnitude of Internet use in general had a negative impact on mental health, but the most robust effects came from the consequences — in particular, lack of sleep from Internet use had a notable adverse effect on mental health on 4-month follow-up based on measures from a validated depression, anxiety and stress scale. 41

Are some individuals more susceptible to mental health effects than others?

Although population-based studies suggest a link between social media use and mental distress among youth, the impact of these technologies may vary among individuals — and some may be less susceptible to harm, as indicated by an emerging literature of experimental studies. Girls and young women tend to spend more time on social media than boys do, have more exposure to cyberbullying and show tendency to experience more mental health effects, 10 , 34 which is consistent with recent epidemiologic trends indicating that depressive symptoms, self-harm and suicidality have increased among young females in particular. 5 – 9

The context of social media use may mediate its effects. A structural equation modelling analysis of a cross-sectional survey of 910 high school students in Belgium found that, among girls, passive use of Facebook had a negative impact on mood but active use had a positive impact on perceived online social support, which in turn had a positive impact on mood. 42 However, for boys active site use had a negative effect. A systematic review of 70 studies found that while social media use was correlated with depression, anxiety and measures of well-being, effects could be both detrimental (such as from negative interactions and social comparison) and beneficial (such as through social connectedness and support) depending on the quality of interactions and individual factors. 43 Certain cognitive styles, such as those that involve rumination and brooding, appeared to exacerbate negative effects of social media. 43 Moreover, the negative impact of social media on depressive symptoms appears to be much greater for adolescents with low levels of in-person interaction; in contrast, youth with high levels of face-to-face socializing appear to be relatively protected against the negative consequences of too much time online. 34 A recent survey of 1124 college students found that while social media contact in the absence of a face-to-face relationship was associated with depressive symptoms, the proportion of social media contacts with whom participants had a close face-to-face relationship was negatively associated with depressive symptoms. 44 In addition, the challenges associated with social media may be especially risky for young people who are already experiencing mental health difficulties, as suggested by the bidirectional relationship between use of electronic media and decrease in psychological well-being. 33 Of particular concern for such vulnerable individuals is that educational or even promotional content about suicide and self-harm is readily available and widely accessed online. 30 , 31

The role of individual differences in terms of the effects of social media is a topic of active investigation. Recent experimental studies have shown relationships between individual characteristics and social media experiences. In a randomized study of 120 college students, those who scored highly on the tendency to engage in social comparison based on measures from a validated scale had poorer self-perceptions, lower self-esteem and more negative affect after browsing the Facebook profile of an acquaintance, relative to those randomized to the control conditions, an effect not seen among students who scored low on social comparison traits. 45 In another empirical study, 102 college students who were asked to take a selfie were randomized to either of 3 conditions with different numbers of “likes” (average, above average and below average); those rated as having a greater sense of purpose in life based on measures from a validated scale had lower sensitivity to feedback (based on number of “likes”) on their self-photograph posts. 46 A study that categorized participants by social comparison orientations (“ability-based” versus “opinion-based”) found that different orientations showed different emotional responses to being compared with others, which in turn was related to life satisfaction. 47 These early findings offer some insights for the individualized care of youth presenting with emotional and mental distress.

How might physicians use this evidence to inform their practice?

Despite the limitations of the evidence base at this time, clinicians may be able to use currently available knowledge in their practice, combined with evidence on effecting behavioural change in youth.

Clinicians treating youth with mental illness and those at risk of mental distress can discuss with adolescents and their families the known risks of social media and smartphone use to mental health. Clinicians may choose to advocate for a harm reduction approach, suggesting reduced use of social media and the Internet rather than abstinence for youth, given evidence that suggests prolonged use is associated with poorer mental health. A recent large systematic review found that communication with adolescents is most effective in the context of a therapeutic alliance that is open and nonjudgmental, elicits trust and emotional safety, and offers a sense of inclusion and autonomy. 48

Encouraging parents to be proactively involved in limiting children’s and teens’ use of smartphones and social media may be helpful, given that social media use appears to become problematic when it surpasses 1 to 2 hours daily. 34 , 38 Results from a recent meta-analysis suggest that while parental limits may be effective at reducing the amount of media use by younger children, open discussion focused on positive engagement and guidance might be best for reducing media-related risks for adolescents; however, only 5 of the 52 included studies pertained to social media, all of which were based on cross-sectional surveys. 49 It is also worth reminding parents that they model smartphone use with their own behaviour; a randomized study showed that heavy parental smartphone use was associated with poorer quality of interactions with their children. 50 Youth and their families can be encouraged to set boundaries for smartphone and social media use. These could include such measures as using social media only for set times, and preferably only in common living areas in the home. A further motivator may be to discuss evidence showing an adverse impact of smartphones on learning, 51 and the benefit on academic outcomes when phones are put away when studying, preferably in another room. 52

A qualitative study that collected data via focus groups with adolescent girls found that high levels of confidence, high media literacy and sound appreciation of individual differences appeared to mitigate negative effects of social media on body image. 53 The participants reported that “these characteristics were nurtured by positive parental influence and a supportive school environment.” 53 These findings underscore the importance of a nurturing home and school environment in fostering resilience as youth navigate the challenges of adolescence. An empirical study of the effect of Instagram browsing on affect in just more than 500 adolescents found that randomization to conditions that provided greater contextual awareness regarding posts by others mitigated against postbrowsing negative affect in teens who reported higher levels of negative social comparison. 54

Sleep hygiene measures specific to social media and smartphone usage are crucial, as several studies have shown that increased smartphone use can disrupt sleep and shorten sleep duration. These would include avoiding use of electronic screens within 1 to 2 hours before bedtime, and not having portable, screen-based media devices in bedrooms overnight.

The American Academy of Pediatrics provides a number of useful health and safety tips to support youth regarding the use of social media, 55 as well as a Family Media Use Plan that offers structure to the recommendations related to limiting use and having discussions regarding appropriate use. 56 Further, the American Academy of Pediatrics has partnered with Common Sense Media to produce a Family Media Toolkit that has useful information for parents. 57 Other practical strategies to mitigate negative effects from using smartphones and related media are offered by the Center for Humane Technology ( http://humanetech.com/ ), an organization developed by former technology industry members out of concern for the potential deleterious effects of new media on psychological states.

A motivational interviewing approach may be useful to help young people start to make changes in their pattern of online behaviour. Motivational interviewing is an intervention with established effectiveness for adolescents with substance use, which could be useful for youth who appear to have poor self-control in their use of social media or smartphone. 58 This approach should involve open, nonjudgmental exploration of all aspects of a youth’s digital life, including positive and negative. Some youth might benefit from habit reversal training to address compulsive use, including having daily “nonscreen time” that can be progressively increased. Sharing evidence that a randomized controlled trial found that participants assigned to not using Facebook reported significantly greater “life satisfaction” and positive emotions after 1 week, compared with controls who were told to continue using the site as usual, 59 may be helpful in effecting change. Youth might be encouraged to inform their friends that they are taking a break from, or otherwise limiting, their social media use. Talking with youth about alternative ways to connect, including meeting in person or even talking directly by phone, could help with strategies to fill the social media gap, reinforced by discussion of evidence that in-person interaction may protect mental health.

At the system level, school and community-based programs can institute limits on social media and smartphone use, along the lines of those that have recently been shown to have a positive effect on healthy behaviours. 60 However, such interventions should be developmentally appropriate and aim to respectfully ensure adolescents’ autonomy. 61 Mobile-phone policies at the school and classroom level have been implemented in several jurisdictions, with mixed results. 62 Enforcement of blanket bans is often a challenge; rather, a more productive approach involves negotiation between teacher and students, as developmentally appropriate, in the context of a relationship built on mutual trust and respect for autonomy. 63 , 64

More broadly, public awareness campaigns can provide education on the impact of problematic use of digital media and promote healthy behaviours in this regard. Various social media platforms have placed bans and restrictions on content related to self-harm. 24 A qualitative study of focus groups involving a total of 66 adolescents found that while adolescents valued freedom and privacy, they recognized a need for protection and most were in favour of automatic monitoring in situations that were beyond their control. 65 Finally, there should be public discussion about the extent to which social media companies can use features that are deliberately designed to promote behavioural reinforcement and addiction, 20 , 21 particularly on platforms used primarily by youth.

Encouragingly, youth are increasingly recognizing the negative impact of social media on their lives and starting to take steps to mitigate this. 66 According to a recent poll, 54% of teens felt they spend too much time on their cell phone, and about half reported cutting back on the time they spend on it. 67

Given the importance of engaging youth in mitigating potential harms from social media, a prohibitionist approach would be counterproductive. The American Academy of Pediatrics suggests that online relationships are part of typical adolescent development. 55 Indeed, for adolescents today, who have not known a world without social media, digital interactions are the norm, and the potential benefits of online access to productive mental health information — including media literacy, creativity, self-expression, sense of belonging and civic engagement — as well as low barriers to resources such as crisis lines and Internet-based talking therapies cannot be discounted.

However, today’s youth could benefit from proven individual and systemic interventions to help them navigate the challenges brought about by use of smartphones and social media, protect themselves from harm and use social media in a manner that safeguards their mental health, against a background of policy initiatives aimed at addressing the social, environmental and economic factors that underpin family well-being and nurture youth resilience. 68

Acknowledgements

The authors acknowledge the valuable contributions of the anonymous reviewers and journal editors.

CMAJ Podcasts: author interview at https://soundcloud.com/cmajpodcasts/190434-ana

Competing interests: None declared.

This article has been peer reviewed.

Contributors: All of the authors contributed to the conception and design of the work. Elia Abi-Jaoude and Karline Treurnicht Naylor drafted the manuscript. All authors revised the manuscript critically for important intellectual content, gave final approval of the version to be published and agreed to be accountable for all aspects of the work.

ORIGINAL RESEARCH article

Negative effects of mobile phone addiction tendency on spontaneous brain microstates: evidence from resting-state eeg.

• School of Psychology, Xinxiang Medical University, Xinxiang, China

The prevalence of mobile phone addiction (MPA) has increased rapidly in recent years, and it has had a certain negative impact on emotions (e.g., anxiety and depression) and cognitive capacities (e.g., executive control and working memory). At the level of neural circuits, the continued increase in activity in the brain regions associated with addiction leads to neural adaptations and structural changes. At present, the spontaneous brain microstates that could be negatively influenced by MPA are unclear. In this study, the temporal characteristics of four resting-state electroencephalogram (RS-EEG) microstates (MS1, MS2, MS3, and MS4) related to mobile phone addiction tendency (MPAT) were investigated using the Mobile Phone Addiction Tendency Scale (MPATS). We attempted to analyze the correlation between MPAT and corresponding microstates and provide evidence to explain the brain and behavioral changes caused by MPA. The results showed that the total score of the MPATS was positively correlated with the duration of MS1, related to phonological processing and negatively correlated with the duration of MS2, related to visual or imagery processing, and MS4, related to the attentional network; the score of the withdrawal symptoms subscale was additionally associated with duration of MS3, related to the cingulo-opercular emotional network. Based on these results, we believe that MPAT may have some negative effects on attentional networks and sensory brain networks; moreover, withdrawal symptoms may induce some negative emotions.

Introduction

With the multiple and ever-changing functions of mobile phones, internet use and mobile phone use have become closely interwoven ( Montag et al., 2015 ). In China, by the end of June 2019, the Internet penetration rate had reached 61.2%, and 99.1% of Internet users preferred to use their mobile phones to access the Internet ( CNNIC, 2019 ). Among college students in China, for instance, the penetration rate of mobile phones rose from 84.6 to 99.3% between 2012 and 2015 ( Bian, 2015 ; Long et al., 2016 ), and it is continually rising, while the prevalence of mobile phone dependence has been found to range from 4.1 to 37.9% ( Wang and Zhang, 2015 ; Chen et al., 2016 ; Long et al., 2016 ). Mobile phone addiction (MPA) refers to individuals whose mobile phone use behavior is out of control, resulting in a state of obsession, which can be categorized as a problematic behavior ( Salehan and Negahban, 2013 ). An immediate impact on college students is that a higher level of MPA leads to a decline in their academic performance ( Soyemi et al., 2015 ). Additionally, Jacobsen and Forste (2011) identified a significant negative association between the use of mobile phones and academic performance among first-year university students in the United States. MPA has become a global concern because of its negative effects on memory and interpersonal communication ( Hao et al., 2019 ; Miri et al., 2019 ), as well as its association with negative emotions (anxiety, depression, stress, and loneliness) ( Demirci et al., 2015 ; Chen et al., 2016 ; Gao et al., 2018 ).

According to current research, MPA has a significant negative impact on executive function. Addicts to certain online apps that involve communication characteristics show more social anxiety, emotional deficits, and impaired prefrontal cortex-related inhibitory control ( Dieter et al., 2017 ). A significant positive correlation was found between the number of errors in the Stroop task and the short-version Smartphone Addiction Scale score ( Kwon et al., 2013 ). These findings may reflect the exact relationship between MPA and inhibitory control processes ( Dilce et al., 2017 ). Furthermore, negative associations have been found between MPA and working memory ( Billieux et al., 2008 ), executive function ( Billieux, 2012 ), self-control, and self-monitoring ( Takao et al., 2009 ). Several neuroimaging studies have provided compelling evidence for behavioral and neurobiological similarities and correlations between different types of addictions, hypothesizing that there is a fundamentally identical neural mechanism ( Bianchi and Phillips, 2005 ; Billieux et al., 2015 ; Zhang and Liu, 2017 ). A better understanding of MPA and its underlying mechanisms may also reveal other types of addiction, and vice versa ( Billieux et al., 2015 ; Zhang and Liu, 2017 ). Individuals with behavioral addiction are often characterized as exhibiting abnormal function in brain regions that include the prefrontal cortex, anterior cingulate cortex (ACC) ( Grant et al., 2010 ), ventral striatum ( Han et al., 2012 ), insula ( Kuss and Griffiths, 2012 ), and thalamus ( Ruth et al., 2010 ). It is worth noting that altered brain morphology in these areas has also been reported in Internet addicts as well as gambling addicts ( Wang and Zhang, 2015 ). This provides morphological evidence of structural changes in the brain of individuals with MPA, for which we will further explore the corresponding functional changes through resting-state electroencephalogram (RS-EEG). At the level of neural circuits, the continued increase in the activity of brain regions associated with addiction leads to neural adaptations and structural changes ( Kuss and Griffiths, 2012 ). This process is undoubtedly slow and long-lasting. Hence, we explore the changes in brain activity caused by MPA from the perspective of mobile phone addiction tendency (MPAT).

The electroencephalogram (EEG) is a widely used non-invasive tool for measuring the electrical physiology of the brain ( Ingber and Nunez, 2011 ) that can detect and record millivolt fluctuations of cortical potential with very high temporal resolution and make it easier to assess dynamically changing mental activities ( Canuet et al., 2012 ; Mani et al., 2013 ; Nishida et al., 2013 ). RS-EEG microstates are a method that defines the states of the multichannel EEG signals by the spatial topographies of electric potentials over the electrode array ( Norbaidurah et al., 2018 ). Previous studies revealed that four prototypical microstates (MS1, MS2, MS3, and MS4) explain nearly 70–80% of the variance of EEG brain activity during wakeful rest ( Seitzman et al., 2017 ; Norbaidurah et al., 2018 ). Moreover, it has been found that these four RS-EEG microstates are related to certain brain networks. MS1 is correlated with activations primarily in the bilateral superior and middle temporal gyri, which are implicated in phonological processing and also involved in speech and auditory processing or auditory ( Britz et al., 2010 ; Seitzman et al., 2017 ). MS2 is correlated with bilateral extravasate visual areas (BA18 and BA19), which have been identified as the visual network ( Damoiseaux et al., 2006 ; Mantini et al., 2007 ). MS3 is correlated with activations in the dorsal anterior cingulate cortex (dACC), the bilateral inferior frontal cortices, and the insula, which are related to the saliency network (SN) ( Fox et al., 2006 ; Seeley et al., 2007 ) and play a critical role in switching between central executive function and the default mode ( Sridharan et al., 2008 ). MS4 is correlated with signaling in the right-lateralized dorsal and ventral areas of the frontal and parietal cortex, which are related to ventral fronto-parietal attentional networks and are associated with switching and reorientation of attention ( Corbetta and Shulman, 2002 ).

Considering the high time resolution of EEG, RS-EEG microstates can also reflect the dynamic characteristics of these brain networks, such as duration (the stability of underlying neural assemblies for a certain microstate), occurrence (neural generators that become activated for a certain microstate), coverage (the time coverage for a certain microstate relative to others), as well as the possibility of transition between any two RS-EEG microstates ( Lehmann et al., 2005 ; Khanna et al., 2015 ). Moreover, the characteristics are also associated with the altered mental states under experimental conditions. Seitzman et al. (2017) found that that the duration, coverage, and occurrence of MS4 were significantly higher during the cognitive task compared to wakeful rest, while MS3 showing significantly decreased. Furthermore, MS2 and MS3 were altered by manipulations of visual input, with increased occurrence in the eyes open condition. Zappasodi et al. (2017) also found that MS2 and MS3 were regulated by visuospatial tasks, reflecting that the contribution of MS2 significantly increased while the contribution of MS3 significantly decreased under visuospatial tasks. In addition, during the eyes open condition, MS1 and MS4 had significantly shorter durations, while MS3 had increased occurrence. MS4 had decreased coverage in the eyes open condition ( Seitzman et al., 2017 ). Croce et al. (2020) observed that as the amplitude of alpha oscillations within the subject increased, the parameters of MS2 increased, the coverage of MS4 decreased, and the frequency of MS3 increased. Research has demonstrated that task-related microstates would re-emerge during post-task periods of rest ( Murphy et al., 2018 ). In other words, the resting-state microstate will be affected by previous activity. Different microstates reflect different neural network activities and thus reflect different cognitive processes or mental states ( Croce et al., 2020 ). Microstate parameters correspond to the dynamic characteristics of microstates or brain networks ( Khanna et al., 2015 ). The microstate time series in the resting state EEG represents the rapid switch between the activities of various neurons in the brain in the resting state. Resting-state EEG microstate parameters can be used as objective neurophysiological and biological indicators to provide a method for monitoring disease or other activities ( Khanna et al., 2015 ).

In this study, based on the negative effects of MPA on executive control and emotion, we examined the influence of MPAT on the spontaneous brain activities related to executive control and the generation of emotions. The negative effects of MPAT on the temporal characteristics of the four RS-EEG microstates were investigated by using the Mobile Phone Addiction Tendency Scale (MPATS) to measure MPA. We hypothesized that MS4, related to the executive function, and MS2, related to visual processing, would be affected. Additionally, the activation of the dACC, insula, and inferior frontal gyrus has been found to increase significantly under negative emotions ( Tolle et al., 1999 ; Coen et al., 2009 ; Harlé et al., 2012 ). Meanwhile, withdrawal symptoms are defined as a negative physical or psychological reaction to not using a mobile phone and are attributed to anhedonia, whose main manifestation is mood change ( Zhang, 2006 ), such as intense anxiety. Hence, we hypothesized that withdrawal symptoms might be related to mood-related MS3.

Materials and Methods

The sample consisted of 335 undergraduate students (27.2% male) from the Xinxiang Medical University ( M = 18.3, SD = 0.84, range: 18–22 years). We screened out 53 participants who had not completed EEG experiments or had incomplete data. Participants were asked not to take the drug for several days before the experiment. All experiments were conducted with the understanding and written informed consent of each participant, which was in accordance with the Declaration of Helsinki. The protocol was approved by the Ethics Committee of the Xinxiang Medical University. Any question from the participant was clarified.

Mobile Phone Addiction Tendency Scale (MPATS)

This scale, developed by Xiong et al. (2012) , referred to the existing research results on mobile phones, and, according to the actual situation of college students, through interviews, predictions, and formal tests, a formal scale with a good representative item was finally determined. The scale consists of 16 items grouped into four factors: withdrawal symptoms (negative physical or psychological reactions to not participating in mobile phone activity), salience behavior (the use of mobile phones occupies the center of thought and action), social comfort (the role of mobile phone in interpersonal communication), and mood changes (changes in mood caused by mobile phones). Using a five-point Likert scale, the scores ranged from 1 to 5 points, i.e., “very inconsistent” to “very consistent,” respectively. The higher the total score, the more serious the addiction tendency is. The Cronbach coefficient of the total scale was 0.83, and the Cronbach coefficients of withdrawal symptoms, highlight behavior, social comfort, and mood change four factors were 0.80, 0.64, 0.68, and 0.55, respectively. In our samples, the Cronbach coefficients of the total scale were 0.87, and the Cronbach coefficients of the withdrawal symptoms, salient behaviors, social comfort, and mood changes were 0.80, 0.70, 0.82, and 0.40, respectively.

RS-EEG Data Acquisition

All participants participated in data collection in an EEG lab that required low light and quiet. The RS-EEG recording was about 6 min. During the collection process, subjects were asked to relax, close their eyes, and enter a resting state to avoid swallowing, blinking, and other activities that may cause artifacts. Data were collected using instrument Cerebus 128TM system (Cyberkinetics, United States). EEG data were recorded from 64 Ag-AgCl scalp sites according to the international 10–20 system in an elastic cap (NeuroScan Product). During recording, all electrodes were referenced to Cz and re-referenced off-line to linked mastoids. Channels for horizontal and vertical EOG were computed offline from electrodes recorded from the outer canthi of the eyes and from above and below the right eye, respectively. The impedance between the electrodes and the participant’s scalp was kept below 10 kΩ.

RS-EEG Microstate Pre-processing

The raw data files from the EGI were transformed into the MAT file format for pre-processing using the EEGLAB 1 v13.0.0 toolbox. EEG was sampled online with 500 Hz frequency DC amplifiers with a band-pass filter of 2–20 Hz ( West et al., 2008 ). Artifacts produced by blinks or eye movements were corrected by subtracting the means of ICAs ( Koenig et al., 1999 , 2002 ; Lehmann et al., 2005 ) implemented in the EEGLAB software. The artifact-free data were recomputed against the average according to previous studies ( Pascual-Marqui et al., 1995 ; Naqvi et al., 2007 ; Etkin et al., 2011 ; Harlé et al., 2012 ) and was average re-referenced. Then the data were segmented into 180 epochs with an epoch length of 2000 ms.

RS-EEG Microstates Analysis

First, the global field power (GFP) was calculated using the selected EEG epoch ( Cai et al., 2018 ). After that, based on previous studies ( Tibshirani and Walther, 2005 ), the Atomize-Agglomerate Hierarchical cluster (AAHC) were used to analyze the microstates with the polarity of each topographical map being disregarded. The AAHC was a modified k-means to provide unique clusters for microstate analysis ( Murray et al., 2008 ). Third, the cross-validation criterion is used to determine the optimal cluster number, that is, the optimal cluster number can find the least template mapping, and the global interpretation variance is the largest ( Damoiseaux et al., 2006 ; Schlegel et al., 2011 ). According to our data, four clusters were found, and the explained variance was 0.787 ± 0.033. Lehmann and his colleagues labeled them A, B, C, and D, while we used MS1,MS2, MS3, and MS4 ( Lehmann et al., 2007 ; Seitzman et al., 2017 ; Norbaidurah et al., 2018 ; Figure 1 ). Raw data were then fitted according to global map dissimilarity (GMD), and each time point was labeled as the cluster chart with the best correlation ( Gao et al., 2017 ).

Figure 1. The four microstate topographic maps are RS-EEG microstate Type A (MS1), Type B (MS2), Type C (MS3), and Type D (MS4) ( Wu et al., 2020 ).

For each microstate class, the following parameters were calculated: mean duration, i.e., the mean time (in ms) reflecting the stability of its underlying neural assemblies; mean occurrences per second across all analysis epochs; contribution, i.e., mean percentage of time covered by each microstate class across analysis epochs (summing up to 100% across all four microstate classes); and the non-random transition probabilities from each microstate to another, which are often interpreted to suggest an encoded sequential activation of the neural assemblies that generate microstates ( Lehmann et al., 2005 ; Andreou et al., 2014 ; Khanna et al., 2015 ).

Statistical Analysis

Data were analyzed using SPSS software (22.0), and the scores of each scale were described and statistically analyzed. The normality of the distributions was tested using the Shapiro–Wilk test. Some variables did not conform to the normal distribution; we normalized these variables for further statistical analysis. Pearson correlation analysis was used to explore the correlation between MPA tendency and microstate composition and transition. For the level of statistical significance, we set p ≤ 0.01. Post hoc comparisons on the unstandardized residuals were considered significant at p < 0.0125 (e.g., p < 0.05, with Bonferroni correction for comparing across the four microstates). In all of these statistical analyses, age and sex were seen as covariates.

Behavioral Results

Normalization to the four variables, such as withdrawal symptoms, salience behavior, social comfort, and mood changes, have come to nothing, but they all had kurtosis and skewness of less than 1. Therefore, we regarded them as an approximate normal distribution for further statistical analysis ( Table 1 ).

Table 1. Behavioral results of MPATS ( n = 335).

The Relationship Between Questionnaire Scores and Microstates

We did not detect correlations between coverage and the MPATS’ four dimensions or the total score. According to the correlation analysis, withdrawal symptoms were significantly positively correlated with the duration of MS1 and of MS3 ( r = 0.164, p = 0.003; r = 0.146, p = 0.007, respectively) and were significantly negatively correlated with the occurrence of MS2 and of MS4 ( r = −0.152, p = 0.005; r = 0.178, p = 0.001, respectively). The total score was also significantly positively correlated with the duration of MS1 ( r = 0.159, p = 0.003) and significantly negatively correlated with the occurrence of MS2 and of MS4 ( r = −0.153, p = 0.005; r = −0.155, p = 0.004, respectively) ( Table 2 ). No correlation was found between microstate transition and MPATS scores ( Table 3 ).

Table 2. Correlations for Microstates components and MPAT.

Table 3. Correlations for Microstates transitions and MPAT.

The purpose of this study was to use microstates to determine the relationship between college students’ MPAT and changes in brain function using RS-EEG microstates. The results showed that withdrawal symptoms are significantly positively correlated with the duration of MS3, and the total score of the MPATS is significantly negatively correlated the with the occurrence of MS2 and MS4. We unexpectedly found that the total score had a significant positive correlation with MS1.

With regard to the correlation between withdrawal symptoms and the MS3 microstate, the idea that insula dysfunction underlies drug addiction is supported by a study showing that chronic cocaine users have reduced gray:white matter ratios in the insula ( Franklin et al., 2002 ). In one case, a patient with insula injury claimed that his body had forgotten the urge to smoke ( Naqvi et al., 2007 ). It has been found that MS3 is positively BOLD related to the fronto-insular SN, including the dACC, the bilateral inferior frontal cortex, and the insula ( Fox et al., 2006 ; Seeley et al., 2007 ), which play a critical role in switching between central executive function and the default mode ( Sridharan et al., 2008 ). The experiments of Miri et al. (2019) showed that the physical and psychological effects of excessive cell phone use include headaches and memory loss, and the brain regions involved in the default mode network (MS3) include the hippocampus, which explains why memory loss occurs in addicts. From the above evidence, we may infer that the addict’s insula activity increases, leading to withdrawal. Activation of the dACC, insula, and inferior frontal gyrus has been found to increase significantly under negative emotions ( Tolle et al., 1999 ; Coen et al., 2009 ; Harlé et al., 2012 ). The dACC region is involved in the assessment and expression of negative emotions ( Etkin et al., 2011 ), such as fear ( Perlman and Pelphrey, 2010 ) and anxiety ( Afif et al., 2010 ). The dACC is closely related to the attention distribution of emotional information; that is, the more strongly a person is aware of the characteristics of his own emotional experience, the higher the degree of dACC participation in the process of emotional arousal ( McRae et al., 2008 ). The insula is also important for emotional feelings ( Gasquoine, 2014 ). Consistent with our hypothesis, we found that withdrawal symptoms are related to MS3. We can speculate that the change in MS3 reflects the sensitivity of mobile phone addicts to negative emotions or their degree of attention to negative emotional experiences.

Furthermore, the total score on the MPATS was significantly negatively correlated with the occurrence of MS4. MS4 is related to the dorsal attention functional system and is associated with switching and reorientation of attention ( Corbetta and Shulman, 2002 ). Precious topographical analyses indicated that the duration, coverage, and occurrence of MS4 were significantly higher during cognitive tasks compared to wakeful rest ( Seitzman et al., 2017 ). Although our experiment reflected occurrence only, it was consistent with decreased cognitive activity in mobile phone addicts. In addition, there is a strong link between working memory and selective attention ( Ming and Yang, 2007 ). For example, the contents of working memory are related to the orientation of selective attention, and selective attention is involved in the maintenance and updating of information in working memory ( LaBar et al., 1999 ; Awh and Jonides, 2001 ). Based on previous research, individuals with Internet addiction present deficiencies in working memory ( Zhou et al., 2015 ). The potential similarities in behavioral and neurobiological factors between MPA and Internet addiction ( Billieux et al., 2015 ; Wang et al., 2016 ), combined with our findings, suggest that both play the same role in working memory and attention. In short, our findings show deficits in attention shifting and redirecting and working memory in mobile phone addicts. It is worth mentioning that some studies have found that MPA is beneficial to cognition. For example, in a study of college students, Zhang and Liu found that the MPA group had better attention conversion and cognitive flexibility than the non-addicted group ( Zhang and Liu, 2017 ). Other researchers found that Internet addicts were more sensitive to exogenous stimuli, leading to an improvement in their attention function ( West et al., 2008 ). Some studies have shown that addicts can quickly identify visual stimuli associated with a task and divert attention from stimuli that are irrelevant, and they are better able to recover from captivity when they realize they have a clue ( Li et al., 2011 ).

Finally, the total score on the MPATS was positively correlated with the duration of MS1. Previous studies found that MS1 was negatively BOLD associated with activation of the bilateral superior and middle temporal gyri, which may imply that individuals with a short duration of MS1 possess a stronger function of phonological processing ( Damoiseaux et al., 2006 ; Britz et al., 2010 ). Research also suggests a link between the overuse of mobile phones and hearing problems ( Meo and Al-Dreess, 2005 ). Therefore, we can infer that mobile phone addicts also have worse auditory information processing and speech processing ability than healthy controls. This could be a future research direction. In our study, we found that the (auditory-associated) perception system was affected, which we did not expect. We know that perception of inter-parental conflict affects Internet addiction directly and indirectly ( Zheng and Deng, 2015 ). We can guess that mobile phone addicts show the same pattern. Our experiment also confirmed visual influence (MS2 was negatively correlated with the scale score).

However, our study has some limitations. First, the results only showed weak correlations, which may be due to the large sample size in this study. In addition, all subjects with complete data were selected for correlation analysis in this study. If we selected only high and low subgroups (for example, 27%) based on the score division, the results may be more meaningful because significant inter-group differences may be obtained. Second, our experimental results were only based on the combined analysis of existing experiments and literature, and their complete accuracy cannot be guaranteed. Third, we did not further differentiate the studies on the related brain regions of MS3 and MS4, which are relatively complex microstate types, and this should be explored in future research. Unlike what we expected, we did not find a correlation between the MPATS score and MA3. MS3 is mainly related to the SN ( Fox et al., 2006 ; Seeley et al., 2007 ). Evidence from a large number of brain imaging studies across multiple task domains suggests that the anterior insula and ACC nodes of SN respond to degrees of subjective salience, whether related to cognition, homeostasis, or mood ( Craig, 2009 ; Vinod and Uddin, 2010 ). This is because the insula is important for emotional feelings ( Gasquoine, 2014 ) and is related to withdrawal symptoms ( Franklin et al., 2002 ). In addition, other addiction studies have found that the insula structure changes in addicts ( Franklin et al., 2002 ), so at the beginning of the study, we speculated that MS3 was related to the MPATS score. But in fact, our subjects are normal college students, and there are no extreme mobile phone addicts, so there may not be significant structural changes. SN is responsible for regulating attention based on various information, such as the physical properties of the stimulus or its relevance to the task at hand, and is responsible for judging the salience of the stimulus and regulating attention ( Menon, 2015 ; Chen et al., 2017 ). However, we collected resting-state data, so no significant correlation was obtained.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics Statement

The studies involving human participants were reviewed and approved by the Ethics Committee of the Xinxiang Medical University. The participants provided their written informed consent to participate in this study.

Author Contributions

XW, JY, and HL designed the research, wrote the manuscript, and analyzed the data. FZ, MZ, and YW collected the data. All authors contributed to the article and approved the submitted version.

This work was supported by the Philosophy and Social Science Project of Henan Province (2015BJY033), the National Natural Science Foundation of China (31600927 and 81830040), the Youth Foundation of Social Science and Humanity, China Ministry of Education (19YJCZH179), the Key Scientific Research Project of Colleges and Universities in Henan Province (20A190001), and the Humanities and Social Sciences Project of Henan Provincial Department of Education (2020-ZZJH-376).

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank LetPub ( www.letpub.com ) for its linguistic assistance during the preparation of this manuscript.

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Keywords : mobile phone addiction, resting-state EEG, microstates, mobile phone addiction tendency, brain function

Citation: Li H, Yue J, Wang Y, Zou F, Zhang M and Wu X (2021) Negative Effects of Mobile Phone Addiction Tendency on Spontaneous Brain Microstates: Evidence From Resting-State EEG. Front. Hum. Neurosci. 15:636504. doi: 10.3389/fnhum.2021.636504

Received: 01 December 2020; Accepted: 26 March 2021; Published: 28 April 2021.

Reviewed by:

Copyright © 2021 Li, Yue, Wang, Zou, Zhang and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hao Li, [email protected] ; Xin Wu, [email protected]

† These authors have contributed equally to this work

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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European schools crack down on mobile phone use over health concerns

European countries are increasingly raising concerns about the excessive use of mobile phones, social media and other forms of digital communication among young people – with some moving towards banning or restricting mobile phones in schools.

Recent studies have highlighted alarming links between excessive screen time and the consequent negative impact on the mental health and academic performance of children and young people.

For example, a study by the Organization for Economic Co-operation and Development (OECD) advised limited and responsible use of mobile phones in schools.

In July, after her re-election for a second term as European Commission President, Ursula von der Leyen vowed to tackle social media addiction and cyberbullying, referring to widespread concerns about the negative impact on mental health and well-being.

“We see more and more reporting on what some call a mental health crisis,” von der Leyen said. “We will convene the first-ever European-wide enquiry on the impact of social media on the wellbeing of young people. We owe it to them,” she added.

On cyberbullying, von der Leyen said: “My heart bleeds when I read about young people harming themselves or even taking their lives because of online abuse.”

Keeping mobile devices out of sight

While the European Union has been increasingly aware of the negative effects of social media and mobile phone use among young people, there are no EU-wide rules to tackle these issues.

Instead, rules vary by country.

Some European countries are considering or have already introduced bans on mobile phones in schools or restrictions on their use during school hours.

Schools in the Netherlands enacted a complete nationwide ban on mobile phones.

In Dutch secondary school classrooms, phones have been forbidden since the beginning of the year, a measure that has now been extended to primary schools from the start of the new school year in September.

Phones may still be used in class if they are necessary for a lesson like learning about media skills or if pupils need them for medical reasons or due to a disability.

At 180 of the middle schools that French children attend between the ages of eleven and 15, a scheme is being trialled to ban the use of mobile phones during the entire school day.

The trial of the so-called “digital pause,” which encompasses more than 50,000 pupils, is being implemented ahead of a possible plan to enforce it nationwide from 2025.

Right now, pupils in French middle schools must turn off their phones. The experiment takes things further, requiring children to hand in their phones on arrival.

It is part of a move by French President Emmanuel Macron to reduce the amount of time children spend in front of screens, which the government fears is hindering their development.

In Belgium, mobile phones will be banned in classrooms of hundreds of French-speaking schools in Brussels and Wallonia starting this school year.

The plans were announced by the francophone region’s new government over the summer.

In the Dutch-speaking region of Flanders, however, there is no general ban on phones in schools, but some schools have decided to introduce prohibitions on their own.

In Greece, students are required to keep their mobile phones in their school bags at all times during lessons.

Clearly visible possession and use of mobile phones is prohibited even during breaks and a violation could lead to a one-day suspension.

Last week, Greek Prime Minister Kyriakos Mitsotakis did not rule out the possibility that students would be forced to lock their mobile phones away and collect them after school hours.

In Italy, mobile phones are banned from classrooms starting this school year, under a decree issued by Prime Minister Giorgia Meloni’s right-wing administration in July.

In several regions in Spain, bans and restrictions on mobile phones in school have already been in place, such as the Communities of Madrid, Galicia, Castilla-La Mancha, Andalusia and Extremadura.

In January, the State School Council of Spain – the highest consultative body of the government in the educational field – unanimously approved a veto on the use of mobile phones in primary education and limitations for secondary education.

In Slovenian primary and secondary schools, it is up to each individual school to restrict the use of mobile devices. Internal rules vary from school to school, but few have banned the use of mobile devices completely.

According to experts, a first step towards reducing screen use would be to set national guidelines.

In Croatia, while there are no uniform national rules, some schools have decided to prohibit the use of mobile phones by students the entire time they are at school.

These include schools in several Croatian cities: Zagreb, Split, Rijeka, Osijek, Zadar. One school in Split also introduced a ban on bringing mobile phones to school, claiming that a simple ban on using it was not enough.

The content of this article is based on reporting by AFP, AMNA, dpa, EFE, FENA, HINA, STA, and TT as part of the European Newsroom (enr) project.