Internet Addiction

INTERNET ADDICTION

Problematic Internet Use, Gaming, Social Media, Smartphones and the Attention Economy, the Under-16 Social Media Ban

A current 2026 review: history • diagnosis • neurobiology • ADHD • youth • treatment • prevention • platform design

Overview

The internet is now infrastructure rather than a discrete leisure activity. It contains work, education, banking, friendships, entertainment, sex, shopping, gambling, gaming, news, healthcare and social identity. That makes 'internet addiction' fundamentally different from addiction to a single substance: a person may spend many hours online without being impaired, while another may lose control over one highly reinforcing activity despite far less total screen time.

Current thinking therefore distinguishes high engagement from disorder. The key questions are not simply 'How many hours?' or 'How often do you check your phone?' but whether there is impaired control, increasing priority over other activities, persistence despite harm, repeated failed attempts to cut down, significant distress or functional impairment, and a stable pattern that cannot be better explained by another condition.

The field is also becoming more specific. Gaming disorder has formal recognition in ICD-11. Gambling disorder is already an established behavioural addiction. Problematic social media use, problematic smartphone use, compulsive sexual behaviour, online shopping and other digital behaviours overlap with addiction science but do not all have equivalent diagnostic status. The most defensible 2026 approach is therefore behaviour-specific, impairment-focused and cautious about over-pathologising ordinary digital life.

1. Where did the idea of 'internet addiction' come from?

The idea emerged almost as soon as public internet access became widespread. In 1995, psychiatrist Ivan Goldberg circulated the term 'Internet Addiction Disorder' partly satirically, borrowing the structure of substance-dependence criteria to make a point about psychiatric classification. The joke proved culturally powerful because clinicians and researchers were already encountering people who described loss of control over online use.

In the mid-1990s, psychologist Kimberly Young began systematic research on excessive internet use and proposed diagnostic-style criteria influenced by pathological gambling. Her Internet Addiction Test later became one of the most widely used screening instruments in the field. Early research tended to treat 'the Internet' itself as the addictive object. This made sense in the dial-up era, when online activity was relatively unified around chatrooms, bulletin boards, web browsing and emerging multiplayer environments.

As digital life diversified, that broad model became less satisfactory. Researchers increasingly argued that people are usually not addicted to the internet as a transmission medium; rather, the internet gives rapid, persistent and highly accessible access to specific rewards — gaming, gambling, pornography, shopping, social reassurance, novelty, information or interpersonal attention.

2. A brief history of the digital environment

3. Why the diagnosis remains controversial

The core controversy is conceptual. Is excessive internet use a distinct addiction, a family of separate behavioural addictions, a coping strategy, a symptom of another disorder, or some combination of these? Different studies use different labels, scales and thresholds, producing prevalence estimates that cannot always be compared directly.

A second problem is that many diagnostic-style scales were adapted from substance addiction. Concepts such as tolerance and withdrawal can be difficult to translate literally. Feeling irritable when disconnected is not necessarily equivalent to physiological drug withdrawal, and needing more online stimulation may reflect novelty-seeking or changing activities rather than classic pharmacological tolerance.

A third problem is circular measurement. If a questionnaire defines 'problematic use' partly by high frequency or long duration, it may identify intense but healthy users. Better contemporary models emphasise functional impairment, loss of control and persistence despite harm.

4. DSM and ICD: what is actually recognised?

WHO places gaming disorder within 'disorders due to addictive behaviours' alongside gambling disorder. Its definition centres on impaired control, increasing priority and continuation despite negative consequences, with significant functional impairment.[1,2] WHO also stresses that gaming disorder affects only a small proportion of people who game; ordinary gaming, even when frequent, should not be pathologised.[1]

5. What behaviours can become problematic online?

6. The attention economy

Many digital products are not neutral containers. Their commercial value may depend on keeping users engaged for longer, returning more often, clicking more frequently or generating more data. Design techniques include infinite scroll, autoplay, personalised recommendation, intermittent notifications, visible social metrics, streaks, countdowns, scarcity prompts and highly frictionless re-entry.

These features do not prove that a platform is 'addictive' in the medical sense, but they can amplify known learning mechanisms. Variable and unpredictable rewards are particularly powerful in maintaining repeated checking. Personalised recommender systems can also learn which topics, emotional tones or social cues are most effective at retaining a particular user.

7. Neurobiology: what do we know?

Behavioural addictions involve learning, motivation and reward systems that overlap partly with substance addictions, but the analogy should not be overstated. Digital behaviours do not introduce an external psychoactive molecule into the brain. Instead, repeated rewarding experiences recruit normal reinforcement systems involving the ventral striatum, dopamine signalling, salience processing, habit learning and prefrontal control.

Cues — a notification sound, game icon, message preview or moment of boredom — can acquire motivational value. Repeated cue-response-reward cycles become increasingly automatic. At the same time, executive-control demands rise: the user must repeatedly inhibit an immediately available reward in favour of a delayed goal such as studying, sleeping or completing work.

Neuroimaging studies report differences in reward processing, executive control and cue reactivity in groups with gaming disorder or severe problematic internet use, but findings are heterogeneous and mostly cross-sectional. They cannot establish that an observed brain difference was caused by internet use, and similar patterns occur in ADHD, depression, substance-use disorders and other conditions.

8. The role of dopamine — and the myths around it

Popular discussion often reduces digital overuse to 'dopamine addiction' or recommends a 'dopamine detox'. This is biologically misleading. Dopamine is essential for movement, learning, motivation and reinforcement; it is not a toxin that accumulates because someone watches videos or checks messages.

What matters is repeated reinforcement and cue learning. Highly salient, rapidly changing digital rewards can train attention and habits, particularly when they are available instantly and unpredictably. Reducing exposure to those cues may be useful, but not because the brain needs to be 'cleansed' of dopamine.

9. How common is problematic use?

Prevalence is difficult to state because definitions and instruments vary widely. Studies may measure 'internet addiction', problematic smartphone use, gaming disorder or problematic social media use using different cut-offs. Some screening instruments deliberately favour sensitivity and therefore should not be treated as diagnostic prevalence estimates.

A 2024 systematic review and meta-analysis of 106 articles comprising 109 studies and 97,748 participants estimated a pooled prevalence of problematic smartphone use of 37.1%, but the authors emphasised major variation by region and measurement scale.[4] That figure should therefore not be interpreted as meaning that more than one third of the population has a psychiatric addiction; it illustrates how common elevated screening scores can be under broad definitions.

Similarly, reviews of university populations frequently report high rates of problematic smartphone use, but much of the evidence is cross-sectional and based on self-report.[5] For formal gaming disorder, WHO emphasises that only a small proportion of people who game develop a clinically significant disorder.[1]

10. Young people

Adolescents are a major focus because digital social life, gaming and smartphone use are embedded in development. Reward sensitivity is high, peer evaluation matters strongly, sleep timing shifts biologically, and self-regulatory systems continue to mature. At the same time, online communities can provide genuine friendship, identity exploration, education and support — particularly for young people who are isolated offline.

The evidence linking ordinary social-media use to poor mental health is more nuanced than headlines suggest. A 2024 umbrella review concluded that social-media use carries both risks and opportunities, with effects depending on the person, the type of use and platform design.[6] A 2024 systematic review of 67 studies found that problematic social-media use was associated with depressive and anxiety symptoms, while sleep deprivation, social comparison and feedback-seeking were among important mediators.[7]

A separate 2024 systematic review and meta-analysis found weak associations between general social-media use and depression/anxiety, but stronger and more consistent associations for problematic social-media use, including poorer wellbeing and sleep problems.[8] This supports a shift away from crude screen-time limits as the sole metric.

11. ADHD and neurodevelopment

ADHD is highly relevant to problematic digital use. The same characteristics that make digital environments compelling — immediate reward, novelty, rapid feedback, multiple streams of stimulation and minimal delay — can be particularly attractive to people with difficulties in sustained attention, inhibition, task initiation or reward delay.

• Hyperfocus may also operate selectively: a person can sustain intense attention to a highly rewarding game or online interest while struggling to initiate less immediately rewarding tasks. This does not contradict ADHD; it reflects dysregulated allocation of attention rather than a simple inability to concentrate.

Clinically, excessive gaming or phone use may be a consequence, amplifier or coping strategy for ADHD rather than a separate primary disorder. Assessment should therefore examine developmental history, executive function, sleep, mood, anxiety, autism, social difficulties and substance use rather than assuming the device is the root cause.

12. Autism and digital environments

For some autistic people, online environments offer predictable structure, controllable social distance, shared-interest communities and reduced sensory or interpersonal demands. These can be protective and socially enabling. At the same time, intense interests, social isolation, difficulty switching tasks or preference for predictable digital routines may increase vulnerability to very prolonged use in some individuals.

The clinical goal should not be to remove a valued autistic interest simply because it is digital. The relevant question is whether the activity supports or undermines sleep, nutrition, education, work, relationships, movement, self-care and broader autonomy.

13. Mental health and causality

Depression, anxiety, loneliness and problematic digital use frequently occur together, but direction of causality is often unclear. Depression may lead to withdrawal into online activity; compulsive use may reduce sleep and offline activity and worsen mood; or both may be driven by common vulnerabilities.

This bidirectionality is one reason simplistic claims such as 'social media causes depression' or 'phones cause ADHD' go beyond the evidence. Longitudinal and experimental work is improving, but much of the literature remains observational.

14. Sleep: one of the clearest clinical pathways

Sleep is often the most immediate mechanism through which problematic digital use becomes harmful. Devices delay bedtime, make disengagement difficult, provide emotionally activating content and can fragment sleep through notifications or compulsive checking.

The issue is not simply blue light. Cognitive arousal, reward anticipation, social interaction and displacement of sleep opportunity may matter at least as much. Problematic social-media use has been associated with sleep problems in recent meta-analytic work.[8]

·       Protect a consistent sleep opportunity rather than relying only on total daily screen-time limits.

·       Remove high-reward apps from the bedroom when night-time loss of control is a problem.

·       Disable non-essential notifications and reduce late-evening novelty-seeking.

·       Treat coexisting insomnia, anxiety, ADHD or mood disorder rather than assuming abstinence alone will fix sleep.

15. Clinical assessment

Assessment should identify the specific online behaviour and map its antecedents, rewards and consequences. Total time remains useful context, but impairment is more important.

16. Screening tools

Common research instruments include Young’s Internet Addiction Test, the Problematic Internet Use Questionnaire, the Internet Gaming Disorder Scale, the Gaming Disorder Test, the Smartphone Addiction Scale and the Bergen Social Media Addiction Scale. These can structure assessment and monitor change, but cut-offs differ and should not substitute for clinical judgement.

17. Treatment: what actually helps?

The evidence base is strongest for psychological and behavioural approaches, particularly cognitive-behavioural strategies adapted to the specific online activity. Treatment is usually more realistic when it targets control and function rather than demanding permanent abstinence from the internet.

• · Functional analysis: identify cues, emotional states, times and environments that trigger automatic use.
• · Stimulus control: disable non-essential notifications, remove shortcuts, use app/site blockers, change device location, create friction before high-risk apps.
• · Time and task structuring: scheduled use periods, timers, planned stopping points and external prompts.
• · CBT: challenge beliefs such as 'I cannot tolerate missing out' or 'I can only relax online'; build alternative coping and reward.
• · Behavioural activation: restore exercise, face-to-face activity, hobbies, sleep routines and meaningful offline goals.
• · Relapse planning: anticipate stress, loneliness, holidays, exams, rejection or unstructured periods that previously triggered escalation.
• · Family work for younger people: collaborative rules, parental modelling, predictable boundaries and reduction of conflict-based monitoring.
• · Treat comorbidity: ADHD, depression, anxiety, trauma and sleep disorders may be maintaining the behaviour.

For gaming disorder specifically, CBT has the most established psychological evidence, although studies vary in quality, duration and outcome definition. No medication is approved specifically for general internet addiction. Pharmacological studies have often targeted comorbid depression, ADHD or other conditions rather than the digital behaviour itself.

18. Why simple abstinence often fails

Unlike alcohol or illicit drugs, complete internet abstinence is usually impossible and often undesirable. Work, banking, navigation, education, healthcare and relationships may depend on digital access. The treatment task is therefore closer to developing controlled, intentional use than eliminating the medium.

This also changes relapse concepts. Opening a social app is not necessarily a relapse; losing control and returning to a pattern of significant impairment is more clinically meaningful. Treatment should define the target behaviour clearly and measure sleep, functioning, relationships and wellbeing rather than only minutes online.

19. Digital detoxes: useful idea, misleading label

Temporary breaks can be valuable because they expose automatic habits, reduce cue-driven checking and create space for alternative activities. But the term 'detox' falsely implies removal of a toxin. Short abstinence periods are best understood as behavioural experiments.

• A planned break can answer useful questions: Which apps generate the strongest urges? What emotions appear when checking is unavailable? Does sleep improve? What fills the time? Which connections were genuinely valuable and which were habitual?

20. Platform design and regulation

The modern debate increasingly extends beyond individual self-control. If platforms optimise engagement using behavioural data, recommendation algorithms and repeated prompts, responsibility is shared between users, families, clinicians, designers, regulators and commercial organisations.

·       Age-appropriate design and stronger protection for minors.

·       More transparent recommender systems and researcher access to platform data.

·       Friction around endless feeds, autoplay and repeated notifications.

·       Meaningful user controls over recommendation and notification intensity.

·       Clearer separation of advertising from ordinary content.

·       Protection from dark patterns that exploit urgency, scarcity or repeated re-engagement.

·       Better moderation of self-harm, eating-disorder, extremist, gambling and exploitative content without assuming moderation alone can solve underlying vulnerability.

21. Children, parents and schools

Rules work best when they are predictable, proportionate and modelled by adults. Constant conflict over devices can itself become a major family problem, particularly when the young person’s social world or special interest is online.

·       Prioritise sleep, school attendance, meals, movement, relationships and safety.

·       Agree device-free contexts rather than imposing vague all-day restrictions.

·       Distinguish schoolwork and social contact from compulsive reward-seeking.

·       Avoid using removal of all digital contact as the default punishment for every problem.

• · Teach algorithm literacy: feeds are selected to hold attention, not simply to show 'what is happening'.

·       Look for bullying, exploitation, grooming, gambling, pornography exposure or coercive relationships where clinically relevant.

·       Assess ADHD, autism, depression, anxiety and family stress when use becomes persistently dysregulated.

22. When should someone seek professional help?

Professional assessment is reasonable when digital behaviour is causing persistent loss of sleep, school or work failure, relationship breakdown, severe conflict, self-neglect, financial harm, marked distress, inability to cut down, or when there is associated depression, self-harm, gambling, sexual exploitation, psychosis or substance use.

Urgency depends on the associated risk rather than the label 'internet addiction'. A young person awake gaming all night for weeks and no longer attending school may need prompt assessment even if the exact diagnostic category remains uncertain.

23. What current research is getting right

Recent research is moving away from treating all screen use as equivalent. It increasingly distinguishes active from passive use, social connection from comparison, purposeful use from compulsive checking, and content from duration. It also recognises that individual susceptibility matters: the same platform can be supportive for one person, neutral for another and highly dysregulating for a third.

The 2024 umbrella review of adolescent social-media research explicitly concluded that risks and opportunities coexist and that outcomes depend on personal characteristics, usage type and platform design.[6] This more nuanced framework is likely to dominate the next phase of research.

24. Emerging issues for 2026 and beyond

25. A practical 2026 framework

• This framework avoids both extremes: dismissing serious digital dysregulation as merely a bad habit, and medicalising ordinary modern life. The diagnosis matters, but the functional formulation matters more.

26. THE UNDER-16
SOCIAL MEDIA EXPERIMENT

Australia and the United Kingdom

Age restrictions, platform responsibility, mental health and the future of childhood online

The Under-16 Social Media Experiment: Australia and the UK

One of the most important developments in digital-health policy has been the move from advising families about children’s social-media use to placing legal responsibility directly on platforms. Australia has already implemented a national minimum-age regime, while the United Kingdom has announced plans to introduce a similar prohibition for under-16s.

These policies represent a significant shift in how governments conceptualise online risk. Instead of assuming that children and parents should simply manage exposure through better self-control, parental supervision or screen-time limits, the new approach places responsibility on technology companies to prevent access to services considered unsuitable for younger users.

Australia: the first national under-16 restriction

Australia became the first country to implement a national social-media minimum age of 16. The rules came into effect on 10 December 2025.

Under the Australian framework, age-restricted social-media platforms are required to take reasonable steps to prevent people under 16 from creating or maintaining accounts. The obligation falls primarily on the platforms rather than on children or parents.

The rules apply to major services including Facebook, Instagram, TikTok, Snapchat, X, Reddit, Twitch and YouTube, although the precise list of regulated services can change as platforms and regulatory definitions evolve.

The policy is overseen by Australia’s eSafety Commissioner. Platforms that fail to take reasonable steps to comply may face substantial financial penalties.

By January 2026, eSafety reported that social-media companies had removed, restricted or otherwise dealt with approximately 4.7 million accounts identified as belonging to Australians under the age of 16. The scale of this figure illustrates both the extent to which social media had become embedded in adolescent life and the practical challenge of enforcing a national age threshold.

Importantly, the Australian system does not criminalise children or parents for accessing social media. The regulatory burden is aimed at the companies operating the platforms.

Why did Australia introduce the ban?

The policy emerged from growing concern about the effects of social-media environments on children and adolescents, including:

·       compulsive and prolonged engagement;

·       cyberbullying and harassment;

·       exposure to self-harm, suicide and eating-disorder content;

·       pornography and sexualised material;

·       grooming and exploitation;

·       social comparison and appearance pressures;

·       sleep disruption;

·       algorithmic amplification of highly emotional or harmful content;

·       commercial profiling of minors; and

·       platform features deliberately designed to maximise engagement.

The rationale therefore extends beyond the narrow concept of “internet addiction”. It reflects a broader concern that children are being exposed to sophisticated behavioural-design systems before they have fully developed the cognitive and emotional capacity to manage them.

The United Kingdom: moving towards an under-16 social-media ban

The UK has followed a similar direction. On 15 June 2026, the UK government announced plans to prohibit social-media companies from providing social-media services to children under the age of 16.

The proposals build on the Online Safety Act and the age-assurance requirements already being implemented by Ofcom. They represent a significant escalation from requiring platforms to make services safer for children to potentially excluding younger children from social-media accounts altogether.

The government has indicated that legislation is expected before the end of 2026, with implementation anticipated during 2027. The proposed UK model is explicitly influenced by the Australian approach.

Rather than requiring parents to police individual apps, regulated platforms would be expected to establish sufficiently reliable age-assurance systems and prevent under-16s from maintaining accounts.

What would the UK restrictions cover?

The final legislative details remain subject to implementation, but the government has indicated that the policy will apply principally to social-media services rather than all online communication.

Private messaging services such as WhatsApp and Signal are not expected to be treated in exactly the same way as conventional social-media platforms.

The wider package of reforms also includes proposals for stronger protection of 16- and 17-year-olds rather than assuming that all safeguards can disappear immediately at age 16.

Measures under consideration or announced include stronger default privacy settings, restrictions on personalised recommendation systems, limits on autoplay and potentially stronger protections during overnight hours.

Age assurance: the practical challenge

An age restriction is only meaningful if platforms can determine whether a user is genuinely over the minimum age. Traditional systems asking users to enter their date of birth are easily circumvented. Governments are therefore encouraging more sophisticated forms of age assurance.

·       identity documents;

·       digital identity systems;

·       facial age estimation;

·       payment or banking information;

·       mobile-network information;

·       device-based age signals; and

·       combinations of several indicators.

• This immediately creates a second policy challenge: protecting children may require platforms to collect or process additional personal information.

Age assurance therefore has to balance two legitimate objectives — preventing children from entering inappropriate digital environments while avoiding unnecessary surveillance or retention of identity data.

The case for restricting social media before 16

Supporters argue that the policy changes the power balance between children and very large technology companies. A 13-year-old is not competing on equal terms with an algorithm that has been trained on billions of interactions to determine what will keep that individual watching, clicking or returning.

Removing access during early adolescence may reduce exposure to

·       highly personalised recommendation algorithms;

·       infinite scrolling;

·       repeated notifications;

·       social metrics such as likes and follower counts;

·       appearance comparison;

·       addictive reward schedules;

·       commercial profiling;

·       harmful viral challenges;

·       adult contact;

·       unwanted sexual material; and

·       content that promotes self-harm or disordered eating.

The strongest argument is therefore not that every adolescent becomes “addicted” to social media. It is that children are being exposed to an unusually persuasive commercial environment during a developmental period characterised by strong reward sensitivity, increasing peer influence and still-maturing executive control.

The case against a blanket ban

The evidence is not entirely one-sided. Social media also provides friendship, community, identity exploration, creativity, education and access to support. For some isolated, disabled, neurodivergent or LGBTQ+ young people, online communities can provide social opportunities that may be difficult to obtain locally.

A blanket restriction could therefore remove beneficial as well as harmful experiences. There are also practical concerns.

Young people may bypass age controls, borrow older people’s accounts, move towards unregulated platforms or use VPNs and other workarounds. If displacement occurs towards smaller services with weaker moderation, some risks could increase rather than decrease.

Another concern is that a legal age threshold can create a false sense of safety. A child reaching 16 does not suddenly become immune to manipulation, compulsive use or harmful content. The quality of the digital environment remains important after the birthday threshold has been crossed.

Does the evidence prove that banning social media will improve mental health?

Not yet. There is good evidence that problematic social-media use is associated with poorer sleep, anxiety, depression and reduced wellbeing in some young people. There is also strong evidence that harmful experiences such as cyberbullying, exploitation and exposure to self-harm content can have serious consequences.

What remains less certain is whether a population-wide prohibition will itself produce measurable improvements in mental health. Australia is therefore becoming an important natural experiment.

Researchers will be able to examine whether the legislation changes

·       depression and anxiety rates;

·       sleep;

·       bullying;

·       school attendance;

·       physical activity;

·       social isolation;

·       self-harm;

·       use of alternative platforms;

·       family conflict; and

·       overall digital behaviour.

The results are likely to influence policy far beyond Australia.

From screen time to platform design

One of the most interesting aspects of the Australian and UK approaches is that they move the debate beyond simple screen-time limits.

A child watching a two-hour educational documentary online is not having the same digital experience as a child spending two hours moving through an algorithmically personalised feed of short videos.

Similarly, an hour spent talking with close friends is different from an hour spent repeatedly checking appearance-based feedback or gambling-style reward systems.

That is a more sophisticated question than simply asking how long someone has been online.

A major shift in responsibility

Historically, advice about problematic digital use has focused heavily on individual behaviour: “Put the phone down.” “Use more self-control.” “Parents should monitor their children.”

The Australian and UK models represent a different philosophy. They acknowledge that responsibility also lies with the companies designing the environment.

If a service deliberately removes stopping cues, continuously personalises content, sends repeated re-engagement notifications and rewards users with unpredictable social feedback, it is reasonable to ask whether children should be expected to resist those systems entirely through willpower.

• This reflects a broader public-health principle: when an environment systematically shapes behaviour, prevention can involve redesigning the environment rather than simply instructing individuals to behave differently.

Australia and the UK compared

What should clinicians and families make of this?

The legislation should not replace clinical assessment. A teenager who is depressed, socially isolated, autistic, experiencing ADHD-related dysregulation or being bullied will not necessarily recover simply because an Instagram or TikTok account disappears.

The underlying reasons for problematic use still matter. Likewise, a young person whose gaming or social-media behaviour is causing major impairment should not have their difficulties dismissed simply because the platform remains legally accessible.

The most useful approach combines sensible regulation with individual assessment. Families should continue to consider sleep, relationships, school attendance, physical activity, emotional wellbeing, online safety and the specific function that digital activity serves.

A global experiment

Australia and the United Kingdom may ultimately represent the beginning of a much larger change in how societies regulate childhood online.

For two decades, children entered commercial social-media environments largely under the same fundamental model as adults, with only partial safeguards layered on top. The emerging model reverses that assumption.

Instead of asking whether a particular child can prove that social media is harming them, governments are beginning to ask whether companies should have to demonstrate that their products are sufficiently safe before exposing children to them.

Whether under-16 bans ultimately prove to be the optimal solution remains uncertain. But the policy direction is significant.

Key policy sources

Australian Government / eSafety Commissioner. Social media minimum age and age-restricted social media platform guidance. Current framework in force from 10 December 2025.

• UK Government. Growing Up in the Online World: Government Response, 2026.
• UK Government. Fact sheet: New rules to protect children online, 2026.

Ofcom. Online Safety Act implementation and age-assurance guidance.

27. The central message

The internet itself is not a drug, and high use is not automatically addiction. Yet certain online behaviours can become genuinely compulsive, difficult to control and functionally destructive. Gaming disorder is now formally recognised in ICD-11, while broader constructs such as problematic smartphone use and problematic social-media use remain active areas of research.

• The strongest contemporary approach is specific rather than moralistic: identify the behaviour, understand the reward loop, measure actual impairment, assess ADHD and other comorbidity, protect sleep and daily functioning, redesign cues and routines, and use evidence-based psychological treatment when self-management is insufficient.

References and current sources

1. World Health Organization. Inclusion of 'gaming disorder' in ICD-11. WHO; 2018.
2. World Health Organization. Gaming disorder: Frequently Asked Questions. ICD-11. Current online guidance accessed 2026.
3. American Psychiatric Association. Internet Gaming Disorder. DSM-5 Section III / condition for further study.
4. Lu X, An X, Chen S. Trends and Influencing Factors in Problematic Smartphone Use Prevalence (2012-2022): A Systematic Review and Meta-Analysis. Cyberpsychology, Behavior, and Social Networking. 2024;27(9):616-634. doi:10.1089/cyber.2023.0548.
5. Problematic smartphone usage, prevalence and patterns among university students: a systematic review. Journal of Affective Disorders Reports. 2023;14:100643.
6. Social Media Use and adolescents' mental health and well-being: An umbrella review. Computers in Human Behavior Reports. 2024;14:100404.
7. Saleem N, Young P, Yousuf S. Exploring the Relationship Between Social Media Use and Symptoms of Depression and Anxiety Among Children and Adolescents: A Systematic Narrative Review. Cyberpsychology, Behavior, and Social Networking. 2024;27(11):771-797.
8. Social media use, mental health and sleep: A systematic review with meta-analyses. Journal of Affective Disorders. 2024;367:701-712.
9. World Health Organization. Clinical descriptions and diagnostic requirements for ICD-11 mental, behavioural and neurodevelopmental disorders (CDDR). Geneva: WHO; 2024.
10. Musetti A, Floros G, Chiappedi M, et al. Gaming disorder in the ICD-11: the state of the game. BMC Psychiatry. 2025;25:1114.
11. Petry NM, Rehbein F, Ko CH, O'Brien CP. Internet Gaming Disorder in the DSM-5. Current Psychiatry Reports. 2015;17:72.
12. World Health Organization. Addictive behaviour: gaming and gambling. WHO programme resources, current through 2026.

Educational information only. This document does not replace individual medical, psychiatric, psychological or safeguarding assessment.