purpose of internet addiction essay

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Current Research and Viewpoints on Internet Addiction in Adolescents

• Adolescent Medicine (M Goldstein, Section Editor)
• Published: 09 January 2021
• Volume 9 , pages 1–10, ( 2021 )

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• David S. Bickham   ORCID: orcid.org/0000-0002-2139-6804 1  

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Purpose of Review

This review describes recent research findings and contemporary viewpoints regarding internet addiction in adolescents including its nomenclature, prevalence, potential determinants, comorbid disorders, and treatment.

Recent Findings

Prevalence studies show findings that are disparate by location and vary widely by definitions being used. Impulsivity, aggression, and neuroticism potentially predispose youth to internet addiction. Cognitive behavioral therapy and medications that treat commonly co-occurring mental health problems including depression and ADHD hold considerable clinical promise for internet addiction.

The inclusion of internet gaming disorder in the DSM-5 and the ICD-11 has prompted considerable work demonstrating the validity of these diagnostic approaches. However, there is also a movement for a conceptualization of the disorder that captures a broader range of media-use behaviors beyond only gaming. Efforts to resolve these approaches are necessary in order to standardize definitions and clinical approaches. Future work should focus on clinical investigations of treatments, especially in the USA, and longitudinal studies of the disorder’s etiology.

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Introduction

Every day we carry with us a tool that provides unlimited social, creative, and entertainment possibilities. Activities facilitated by our smartphones have always been central to the developmental goals of adolescents—as young people move toward their peers as their primary social support system, their phones provide constant connection to their friends as well as access to the popular media that often defines and shapes youth culture. Considering young people’s continued use of more venerable forms of entertainment screen media (e.g., television, video games, computers), it is not surprising that adolescents spend more time using media than they do sleeping or in school—an average of 7 h 22 min a day [ 1 ]. While the majority of young media users adequately integrate it into their otherwise rich lives, an undeniable subset suffers from what has been termed by some as internet addiction [ 2 ] but, as discussed below, has been referred to by many different names. While overuse of technology and its impact has been of concern since the days of television, the constantly changing media landscape as well as advances in our understanding of the issue requires regular updates of what is known. The purpose of this review is to provide an understanding of this issue grounded in the established evidence of the field but primarily informed by work published between 2015 and 2020 and, in doing so, address the following questions: What is internet addiction and is this the best term for the problem? What is its prevalence among adolescents around the world? What individual characteristics predispose young people to internet addiction and what are the common comorbidities? And, finally, what treatment strategies are being use and which have been found to be effective?

Defining the Issue

To answer any of these questions, first we must define the problem at hand. Unfortunately, this is a difficult task as recent publications use a wide variety of terms to reference this problem. Video game addiction, problematic internet use, problematic internet gaming, internet addiction, problematic video gaming, and numerous other terms have been used to identify this problem in the last 5 years. Such terms all have limitations. Focusing on a specific behavior, such as internet gaming, does not capture the variety of media use problems experienced by young people. Even the term “internet” may not be especially precise or consistent in meaning as online functionality is now seamless and permeates all activities on a phone, computer, tablet, game system, or television. In order to focus the nomenclature on the variety of behaviors that cross devices and avoid the term addiction which may unnecessarily stigmatize game players and impede their seeking help, my colleagues and I have suggested the use of the term problematic interactive media use (PIMU) [ 3 , 4 , 5 , 6 ]. The term PIMU attempts to capture the broad spectrum of potential media use behaviors seen in clinical settings including gaming, information seeking, pornography use, and social media use without naming a specific behavior or type of media which could position the term for obsolescence [ 3 •].

A Focus on Gaming

Another approach to defining this issue has been to focus on internet games as they are seen as having unique features and elevated harm through excessive use [ 7 ]. In 2013 the American Psychiatric Association described internet gaming disorder (IGD) in its updated Diagnostic and Statistical Manual of Mental Disorders (DSM-5) as a condition needing further research in order to classify as a unique mental disorder [ 8 ]. The proposed clinical diagnosis of IGD includes persistent use of the internet to play games with associated distress or life impairment as well as endorsement of at least 5 of 9 symptoms including preoccupation with games, increased need to spend more time gaming, inability to reduce game time, lying to others about the amount of gaming, and using gaming to reduce negative mood [ 8 ]. Following suit, the World Health Organization included gaming disorder (GD) in its 11th revision of the International Classification of Diseases (ICD-11) [ 9 ]. These two diagnostic approaches both characterize problematic gaming as repetitive, persistent, lasting at least a year, and resulting in significant impairments of daily life [ 10 ]. While there is considerable overlap in the identified clinical symptoms (e.g., loss of control over gaming and continued use of gaming even when after negative consequences), the GD diagnosis does seem to focus on more severe levels of problematic use and worse functional impairment [ 10 ]. The inclusion of IGD and GD in these major diagnostic manuals have been seen as an opportunity for unification in the field around the conceptualization, and measurement of problematic gaming and resulting discussions have, to some extent, indicated increasing agreement [ 7 ].

However, in the years following the definition of IGD, numerous authors took umbrage with these diagnostic criteria pointing out limitations of the defined symptoms and calling into question the idea that there is consensus in the field around this diagnosis [ 11 ••]. For example, preoccupation with gaming, they argue, could represent a form of engagement similar to other types of engrossing activities rather than something pathological [ 11 ••]. Similarly, using gaming to avoid adverse moods is unlikely to differentiate problematic from casual gamers. The use of the term “internet” in the name of the condition was also met with resistance considering that it assumes that video games accessed through the internet are different from other video games in terms of their addictive qualities [ 11 ••]. Some argue that the field is lacking the unified definitions and extensive, foundational research necessary that must precede a diagnosis [ 12 ]. Finally, by focusing on gaming, IGD does not account for other potentially addictive online behaviors. There appears, however, not to be an easy solution to this concern. A broader conceptualization of the disorder has been seen as too general by some, but it seems untenable to create new diagnostic criteria for each specific online behavior. This complexity is evident even within the APA’s description of IGD when the manual states that “Internet gaming disorder” is “also commonly referred to as Internet use disorder, Internet addiction, or gaming addiction [ 8 ].”

Scales and Assessment

Building effective igd scales.

As evidence that much of the field is accepting IGD as a unifying conceptualization of problematic media use, numerous clinicians and scientist have investigated the DSM-5 criteria by designing and testing new scales or applying existing scales to this new framework. Some early testing utilized an interview procedure to confirm a 5-symptom cutoff for IGD, although a cutoff of 4 was adequate for differentiating between those suffering from IGD and healthy controls [ 13 ]. Scales such as the Internet Gaming Disorder Scale and its short form as well as the Internet Gaming Disorder Test (IGDT-10) have been designed and tested demonstrating that fairly short (e.g., 9 or 10 items) assessments can demonstrate strong psychometric properties, support the defined cutoff of 5 symptoms, and successfully measure a single construct [ 14 , 15 , 16 , 17 ]. Testing has been done on other assessment tools that are aligned with the IGD criteria including the Clinical Video Game Addiction Test which provided further support for the 5-item cutoff diagnosis [ 18 ] and the Chen Internet Addiction Scale—Gaming Version which identified its own cutoff [ 19 ]. This abundance of screeners and other instruments demonstrates how, as a result of the inclusion of IGD in the DSM-5, researchers and clinicians have access to numerous well-designed and tested assessments for problematic game play. On the other hand, the profusion of scales may also indicate that the field is still far from one regularly stated goal: a universal and standardized measurement tool.

Internet Addiction Scales

To further expand the assessment landscape, researchers and clinicians who prefer a broader conceptualization of this disorder, one more aligned with internet addiction rather than gaming disorder, have also created scales for research and clinical settings. The Chen Internet Addiction Scale is one of the earliest and most utilized scales [ 20 ]. Developed by applying established concepts from substance abuse and impulse control, it and its revised form have established internal reliability and criterion validity [ 21 ]. The designers of the 20-item Internet Addiction Test (IAT) used the criteria for pathological gambling as the basis of the test and designed it specifically to differentiate between casual and compulsive internet users [ 2 ]. The IAT has high internal reliability [ 22 ], a consistent factor structure across age categories [ 23 ], and is associated with expected comorbidities including depression [ 22 ] and attention-deficit disorders [ 24 ]. The 18-item Problematic and Risky Internet Use Screening Scale (PRIUSS) has three subscales—social consequences, emotional consequences, and risky/impulsive internet use—and a 3-item version was created that used one question from each subscale [ 25 , 26 ]. The strong psychometric properties of both versions of this scale are indicative of their value as tools for identifying adolescents and young adults struggling with their technology use.

Much like the measures of IGD, these internet addiction scales are more similar than dissimilar. They all assess a diverse array of experiences and consequences related to PIMU including its impact on social relationships, sleep, and aspects of mental health. In fact, some items from the different scales are almost identical. For example, the IAT asks, “Do you choose to spend more time online over going out with others?” the PRIUSS asks, “Do you choose to socialize online instead of in person?” and the CIAS asks how much this statement matches your experiences: “I find myself going online instead of spending time with friends.” The scales share an overall approach of asking about internet use in general rather than about specific online activities. While this allows the instruments to focus on the impulsive and risky aspects of internet use in general, it requires young people to differentiate between online and offline activities, a distinction that may no longer be relevant. Scales using this approach should continually be tested and revised as technology develops.

Considering the similarities of the scales, a researcher or clinician would likely be well served by any of them. However, even though the IAT and the CIAS both have identified diagnostic cutoffs, the availability of a 3-item pre-screener for the PRIUSS makes this instrument especially useful for inclusion in a battery of in-office measures. The PRIUSS does, however, require the adolescent or young adult patient to endorse behaviors that are worded in such a way that might activate feelings of judgment or reactance. For example, the question “Do you neglect your responsibilities because of the internet?” puts the onus directly on the user with little room for rationalizing an external cause. That said, the consistently high performance of this scale indicates the set of questions as a whole are successful at classifying problematic internet users.

Because the field lacks standardized language, reporting on the current prevalence of this issue requires the use of work that employs different definitions. However, the similarities across measures likely result in reasonably comparable prevalence rates. In a systematic review focusing on problematic gaming, reported rates varied from 0.6 (in Norway) to 50% (in Korea) with a median prevalence rate of 5.5% across all included studies and 2.0% for population-based studies [ 27 ]. A meta-analyses using data across multiple decades found a pooled prevalence of 4.6% with a range of .6 to 19.9% with higher frequencies in studies performed in the 1990s (12.1%), those with samples under 1000 (8.6%), those that utilized concepts based of psychological gambling (9.5%), and those performed in Asia (9.9%) and North America (9.4%) [ 28 ••].

Recent studies reinforce the variability of prevalence in different regions of the world. In a study of 7 European countries with a representative sample of 12,938, the prevalence of IGD was 1.6% with 5.1% being considered “at-risk” for IGD with little variation among countries [ 29 ]. In studies of individual countries, prevalence of IGD in Germany ranged from 1.16 [ 30 ] to 3.5% [ 31 ]. In Italy, 12.1% were classified as having problematic use and .4% as having internet addiction [ 32 ].

Countries in Asia showed similar disparities. In a review of 38 studies from countries defined by the authors as Southeast Asia (with most being from India), prevalence of internet addiction ranged from 0 to 47.4% [ 33 ]. Among middle and high school students in Japan, prevalence was 7.9% for problematic internet use and 15.9% for adaptive internet use, a lower cutoff of the diagnostic questionnaire [ 34 ]. In rural Thailand, 5.4% reached the cutoff for IGD [ 35 ], and in Taiwan 3.1% met that threshold [ 17 ]. Among 2666 urban middle school children in China, prevalence of IGD was 13.0% [ 36 ]. Finally, in rural South Korea, the prevalence of PIU was 21.6% among a sample of 1168 13- to 18-year-olds [ 37 ].

With such disparate findings from around the world, it seems that PIMU prevalence varies considerably from county to country and region to region. While this may be the case, summary findings from two large reviews do have similar final estimates—5.5% [ 27 ] and 4.6% [ 28 •• ]. This rate is also similar to the prevalence of youth “at-risk” for IGD across Europe (5.1%) [ 29 ] and for full IGD in rural Thailand (5.4%) [ 35 ]. While far from definitive, 5% might be our strongest general prevalence estimate given the evidence. There are some sample and study characteristics that seem to result in a higher prevalence. Unsurprisingly, rates are higher when less restrictive definitions of the disorder are used. There is also some evidence that rates are lower in Europe and higher in North America and Asia, but these results were not universal. If we accept a prevalence of approximately 5% in the USA, that would translate to approximately 1.5 million adolescents experiencing significant life consequences as a result of their struggles with digital technology. Understanding who is most at risk and how best to treat this problem is essential for comprehensive, contemporary adolescent medicine.

Potential Determinants of PIMU

Individual characteristics, demographic features, and psychosocial traits have all been identified as possible determinants of PIMU. Perhaps the most widely documented risk factor is being male. Prevalence among boys and young men has been found to be 2 [ 38 ], 3 [ 28 ••], or even 5 [ 27 ] times higher than among girls and young women. Throughout early adolescence PIMU increases with age, but peaks around 15–16 [ 39 ]. Indicators of lower socioeconomic status including less maternal education and a single parent household have been shown to increase the risk for PIMU [ 36 ].

Family Functioning

Young people’s family functioning also seems to play a role in their development of PIMU. Risk factors seem to include lower levels of family cohesion, more family conflict, and poorer family relationships [ 40 ]. The most frequent finding in a recent systematic review was that a worse parent-child relationship was associated with more problematic gaming [ 41 ]. Less time with parents, less affection from parents, more hostility from parents, and lower quality parenting were all family characteristics potentially indicated in the development of gaming problems [ 41 ]. Game play and other online social activities may serve as solace from difficult family lives as adolescents seeking treatment for gaming addiction report that they are motived to play in part by escapism and the draw of virtual friendships [ 42 ]. At the other end of the spectrum, positive parent-child relationships may be protective against the development of problematic gaming [ 41 ]. Additionally, parental monitoring of adolescents’ internet use can also reduce PIMU which, in turn, improves parent-child relationships [ 43 ]. Parents, it seems, have some prevention tools available to them which could improve their family functioning overall. Fathers appear to have a particularly influential role as their relationships with adolescents has been shown to be especially protective [ 41 , 43 ].

Personality Traits

Certain individual personality traits appear to be common among adolescents with media use issues potentially indicating that young people with these traits are predisposed to develop PIMU. PIMU sufferers regularly demonstrate limitations in areas related to self-control including higher levels of impulsivity. In two studies examining problematic smartphone use, one identified dysfunctional impulsivity and low self-control as two key risk factors [ 44 ] and the other found impulsivity to predict this behavior in their female participants [ 45 ]. Patients diagnosed with IGD also demonstrated higher levels of impulsivity than healthy controls [ 46 ]. A systematic review of research examining the personality traits predictive of IGD concludes that impulsivity plays a role in IGD and that certain aspects of this trait, such as high levels of urgency, are especially potent risk factors. [ 47 •].

In addition to impulsivity, behavior traits related to aggression and hostility are common among adolescents with media use problems. Aggressive tendencies were identified as a predictor of IGD by multiple studies in a recent review of the research [ 47 •]. In a large European survey study, adolescents who reported IGD had higher scores on rule-breaking and aggressive behaviors scales [ 29 ]. While it may seem that aggression findings are simply indicative of the observed gender differences, models that include gender as well as other traits that predict PIMU found that hostility was independently associated with problematic smartphone use [ 48 ] and conduct problems were predictive of problematic internet use [ 49 ].

Neuroticism, the tendency to feel nervous and to worry, has been identified as a potential predisposing factor for PIMU. Using the Big Five model of personality to investigate commonalities among young people with IGD, the authors of a recent review highlighted multiple studies linking neuroticism with PIMU and concluded that this work demonstrates a clear and consistent link [ 47 •]. Some of the strongest evidence comes from clinical samples in which young people seeking care for IGD showed higher levels of neuroticism than healthy controls [ 50 ]. Additionally, neuroticism may be an important trait that differentiates game players who have problematic use versus those who are simply heavily engaged with the games [ 51 ] perhaps in part because the control provided by video games is especially appealing to those with neurotic tendencies [ 50 ]. Neuroticism is a common element of internalizing mood disorders including anxiety and depression [ 52 ], which, as described below, are frequently comorbid with PIMU.

While it is clear that some traits are common among PIMU sufferers (and there are others not covered above), we must stop short of claiming a defining personality profile. Young people experiencing PIMU are likely to have as much diversity as they do similarity in their psychological and personality characteristics. Some of the most conclusive findings originate from clinical samples, but, because of limited specialized care opportunities, this work has been almost entirely conducted outside of the USA. Seeing as culture plays an important role in the development of personality, investigations are necessary to determine if our current knowledge is generalizable to the USA.

Neurobiology and Brain Function

Apart from individual characteristics and family functioning, there appear to be some neurobiological dysfunction that may characterize PIMU sufferers. Working from models based on the brain functioning in gambling and substance use addicts, researchers have looked for similarities with these disorders. Sussman and colleagues call attention to the viewpoint that people are not actually addicted to a substance or a behavior itself but rather to the brain’s response to the drug or activity [ 53 ••]. This perspective opens the door for digital entertainment obsession to be compared to substance use and gambling disorder. Video games and certain types of internet use have been shown to release dopamine at a rapid rate leading to immediate gratification and the potential for a repetitive response that can include compulsive behaviors and increased tolerance [ 53 ••]. In a simultaneous test of reward processing and inhibitory control, both behavioral and electroencephalography findings indicate adolescents with IGD demonstrate irregularities in both systems [ 54 • ]. Additionally, fMRI studies have documented neurobiological explanations for dysregulated reward processing, diminished impulse control, and other behavioral and cognitive patterns in IGD sufferers that are similar to those from people with gambling disorders [ 55 ]. Imaging studies have demonstrated that the brains of adolescents with internet addiction share at least one structural abnormality with brains of those with substance use disorder, namely, reduced thickness in the orbitofrontal cortex [ 56 ]. The evidence at hand seems to indicate that PIMU shares similarities in neural functioning and potentially some brain structures with other compulsive behaviors as well as substance use. However, there are still many fewer neuroimaging studies of PIMU sufferers than of substance users, and many of the existing studies are hindered by small, heterogeneous samples and lack of attention to comorbid conditions [ 55 ].

The observed similarities between PIMU and substance use disorder do not necessarily signify that compulsive technology use should be characterized as a behavioral addiction. In fact, there are strong reasons to consider other conceptualizations for this set of behaviors. Excessive use may be indicative of maladaptive coping [ 57 ] or the manifestation of existing self-regulatory problems [ 58 •]. Rather than being a novel disorder, PIMU behaviors may be symptoms of existing psychiatric problems being expressed within the digital environment [ 3 •]. If these underlying disorders are appropriate explanations for these behaviors, then, some argue, we should not classify the set of symptoms as a behavioral addiction [ 59 ]. Furthermore, there is limited evidence that stopping use results in serious withdrawal symptoms which is a key factor in some diagnostic tools [ 60 ].The term addiction may also convey a sense of stigma and potentially interfere with one’s likelihood for seeking help or leading to incorrect treatment [ 3 , 61 ]. A consistent set of observed, troublesome, comorbid disorders may support the possibility that existing problems drive problematic media use rather than the behavior indicating a uniquely diagnosable behavioral addiction.

Comorbidities

A core set of mental health problems comorbid with PIMU have been identified and include depression, attention deficit hyperactivity disorder (ADHD), anxiety, and autism [ 62 •]. As most of the research in this area is cross-sectional, the exact explanation for the association between PIMU and these other disorders is unknown and could include a one directional relationship (in either direction), a bi-directional relationship, or a common factor causing both issues [ 62 •]. Bearing in mind the complex etiology of these severe mental health issues, PIMU may very well arise from pre-existing mental health problems. The behaviors and environment afforded by excessive game play and internet use may also exacerbate certain symptoms of these disorders. The associations likely differ by unique co-occurring disorder as well as by the specific behaviors evident in an individual’s experience of PIMU. Longitudinal representative research along with additional clinical investigations examining different presentations of PIMU (especially using samples from the USA) is needed to fully understand this relationship.

Depression and Anxiety

Regardless of the specifics of the relationships, identifying the most common mental health issues that are comorbid with PIMU can help illuminate the disorder. Depression is consistently found to be predictive of problematic video game, internet, and smartphone use [ 63 , 64 , 65 ]. In a study comparing multiple predictors of the Internet Addiction Scale, level of depression had the strongest association even when considering demographics, personality traits, and future time perspective (i.e., the ability to envision and pursue future goals) [ 22 ]. Considering anxiety is closely related to depression, it is not surprising that it too has been shown to be linked to PIMU. Young people’s use of technology to cope with depression and anxiety likely explains at least some of these observed relationships, but a reciprocal relationship between PIMU and depression or anxiety is likely most realistic [ 64 , 66 ].

Seeing as impulsivity is a common trait of adolescents suffering from PIMU, it follows that ADHD is one of its most common comorbidities. In a recent review, 87% of the included studies found significant relationships between ADHD symptoms and PIMU [ 62 •]. Findings from a meta-analysis align with these results with studies consistently showing that PIMU is present at higher rates among those with ADHD from those without [ 67 ]. Furthermore, adolescents with ADHD show more severe symptoms of PIMU and are less likely to respond to treatment [ 67 , 68 ]. Ease of boredom, poor self-control, and other typical symptoms of ADHD are likely driving this association [ 67 ].

PIMU was shown to be prevalence in 45.5% of a small clinical sample of youth with Autism Spectrum Disorder (ASD) [ 69 ]. Youth with ASD have higher levels of compulsive internet use and video game play compared to healthy peers [ 70 ]. Online communication platforms especially those that occur within the well-defined ruleset of multiplayer games may be seen as less threatening and thereby particularly attractive to youth with ASD who desire connection but tend to lack well-developed social skills [ 4 ]. The coexistence of ADHD and ASD is an especially predictive combination with PIMU observed in 12.5% of patients with ADHD, 10.8% of those with ASD, and 20.0% of those with both disorders [ 71 ].

For clinicians hoping to better discriminate between adolescents who are heavily engaged with screen media and those who are experiencing problematic use, it is likely effective to attend carefully to young people with mental health issues commonly comorbid to PIMU. To inform on this effort, my colleagues and I have proposed the acronym A-SAD (ADHD, social anxiety, ASD,depression) to remember these key disorders [ 5 •]. While this suggestion is consistent with current evidence, research testing this approach is still necessary in order to understand its overall effectiveness in clinical settings.

Even though there is continued debate about the nomenclature around this issue and the appropriateness of labeling the problem an addiction or its own mental health diagnosis, adolescents around the world are seeking treatment to overcome their disordered media use and its consequences. As of yet, there is not an agreed upon approach for treating PIMU resulting in resourceful and skilled clinicians applying and adapting multiple approaches known to be effective to similar issues to this newer problem. For many years, there were few systematic investigations of these treatments, but recently the number of clinical trials has increased.

Cognitive Behavioral Therapy

With rigorous research in this field becoming more common, a recent review was able to rely more heavily on randomized clinical trials in reaching its conclusions [ 72 •]. This work identified 3 treatment possibilities as most heavily researched—cognitive behavioral therapy (CBT), pharmacological, and group/family therapies—however, approaches in all three were only classified as experimental [ 72 •]. CBT seeks to change problematic thought patterns and their resulting behaviors especially in terms of coping with psychological problems in healthy, direct ways. The approach of using CBT to address the cognitions of problematic users was proposed almost two decades ago and has been applied and adjusted to numerous populations and settings [ 73 ]. In a prototypical study, patients identified as having internet addiction and a comorbid disorder received CBT for 10 sessions and showed improvement in both internet use and anxiety [ 74 •]. Pooled effect sizes from studies of this treatment have demonstrated that overall, CBT is successful at reducing symptoms of depression and of IGD and slightly less so for anxiety [ 75 ••]. Although there is less evidence for CBT’s effectiveness at reducing game play, such a goal is less central as gaming is not inherently problematic [ 75 ••]. Dialectical behavior therapy, which is based on CBT but addresses emotions along with thoughts and behaviors, has also been applied to PIMU and seems to offer promise for future treatment [ 6 ].

Pharmacological Treatment

Other treatments including pharmacological and group and family therapies have not been the subject of as many research investigations as CBT, but findings from these areas do show encouraging effects. The general approach of pharmacological treatment has been to use medications to treat comorbid conditions or underlying pathologies of PIMU including depression [ 76 ], ADHD [ 77 ], obsessive-compulsive disorder (OCD) [ 78 ], and others. In an exemplar RCT of 114 adolescents and adults with IGD, the effectiveness of two antidepressants (escitalopram and bupropion) were investigated [ 79 ••]. Both were effective at reducing IGD, but bupropion also improved impulsivity, inattention, and mood problems which is consistent with its reported use as a treatment for ADHD [ 79 ••]. Following a similar protocol, researchers compared the effectiveness of two ADHD medications, a stimulant (methylphenidate) and non-stimulant (atomoxetine), on symptoms of both ADHD and IGD [ 80 ]. Both medications successfully reduced symptoms of IGD seemingly through their ability to regulate impulsivity [ 80 ]. Other studies reveal similar effects resulting in an overall conclusion that a pharmacological approach can be successful in reducing symptoms of both PIMU and comorbid disorders [ 81 ].

Group and Family Therapies

Group and family therapies are also being used to address PIMU. While group-based interventions that are 8-weeks or longer and include 9–12 people appear most effective [ 82 ], these approaches vary greatly making it difficult to determine which other aspects of the approach contribute to any observed successes. A systematic review describes four studies using single-family groups, multi-family groups, and school-based groups and implementing CBT-based approaches, novel psychotherapy approaches designed specifically for PIMU sufferers, and traditional family therapy approaches [ 81 ]. Group interventions have also been designed to prevent PIMU among adolescents although the effectiveness of this approach is still unknown [ 83 ]. Investigations of these treatments do show some promise. For example, a study of using multi-family group therapy found 20 out of 21 adolescent participants were no longer considered addicted to the internet following the six, 2-h sessions [ 84 ]. While the approach as a whole is based on strategies known to be effective in substance use and other adolescent problems, the heterogeneity of the therapies makes it difficult to draw any final conclusions.

There has been much advancement in identifying and treating PIMU over the last 5 years. The inclusion of IGD in the DSM-5 and of GD in the WHO’s ICD-11 has been the impetus for a growing consensus around terminology and approach. Considerable research has demonstrated that IGD can be assessed reliably and that the defined cutoffs effectively differentiate between those with and without the disorder. However, a large debate continues about whether the terminology and subsequent conceptual and clinical approaches should be based on a specific activity or broader set of behaviors. A framework that describes and addresses a multitude of behaviors that share certain determinants, comorbidities, and expressions can avoid the unsustainable situation of developing a new term and tactic for every problematic media behavior.

Additional research is necessary to more fully develop our clinical understanding and treatment approach to PIMU. Foundational, longitudinal work would help disentangle the direction of association between mental health problems and PIMU, and clinical investigations could continue to determine how therapy and medication can most effectively treat the condition. Clinical work investigating patient samples from the USA are very rare and are necessary to build awareness and increase resources available to treat the problem. Additionally, new research should explore the impact of the COVID-19 pandemic on PIMU. As screens have been relied upon for essential purposes including education, communication, and social connectedness, use has inevitably risen, and youth previously balancing media use and other activities may find themselves struggling. While our knowledge has grown substantially in this area, there are still questions that need to be answered before we can effectively treat this modern facet of adolescent health.

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Internet Addiction Disorder

Submitted: 30 April 2016 Reviewed: 16 November 2016 Published: 24 May 2017

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Internet addiction (IA) was introduced as a new disorder in mid-1990s. Since then, there is growing concern about the addictive nature of the Internet. This chapter is a comprehensive review of published seminal, research and review papers, meta-analyses and book chapters/books on IA in adolescents. The conceptualization of IA, epidemiology, phenomenology, screening, diagnoses, treatment and prevention are discussed with relevant references. The concept of IA is at fetal level with no consensus on definition, norms or clinical criteria. Asian countries such as China and South Korea are affected most. A multination meta-analysis estimated an overall prevalence of 6% for IA. Most of the research identifies IA in gaming, gambling, social networking and cybersex. A few assessment tools have been used with no comparability or cultural sensitivity. Diagnostic criteria are proposed based on those used for substance abuse and pathological gambling. The treatments are mainly psychological with a lot of emphasis on cognitive behavior therapy. The Internet is a very versatile and useful tool for children and adolescents, and it is not advisable to ban it totally. The review highlights education of them on sensible Internet use and supports inclusion of IA in international disease classifications.

• Internet addiction
• children and adolescents
• epidemiology

Author Information

Pabasari ginige *.

• Department of Psychiatry, Faculty of Medicine, University of Peradeniya, Peradeniya, Sri Lanka

*Address all correspondence to: [email protected]

1. Introduction

The Internet evolved from early 1980s to the modern day revolutionizing the broadcasting, information sharing and connecting individuals worldwide. Today, it has become an in-built part of daily lives of people including children and adolescents. The Internet can be used for many purposes: educational such as teaching, learning and research; business, such as monetary/document exchanges and conference meetings; recreational such as games, online gambling and watching sexually explicit material, and as a mode of connecting people via texting, calling, social websites, chat applications and e-mails. Research has found increasing number of students are using the Internet for their academic activities, for example, one US study showed an increase in the Internet use among students from 24.5% in 1996 to 79.5% in 2001 [ 1 ]. However, together with the many benefits come the risks that are inevitably intertwined due to the innate qualities of the Internet.

There is growing concern about the addictive quality of the Internet, and pioneering researchers have introduced the concept of addiction (IA) in mid-1990s [ 2 , 3 ]. IA has attracted the attention of media and general public increasingly, with the speedy growth in computer use and the Internet access [ 4 ]. The Internet today has reached not only the computer, but also the mobile phone and even the wristwatch with many more sophisticated high-tech apparatus with the Internet facility being introduced to the world, incessantly. It is common to find children and adolescents coming from a reasonable socioeconomical background, around the globe, using a personal digital devise like a smart phone, tablet or a laptop with the Internet. It is important to look into how it is like to grow up with such a vast degree of stimulating and inviting attractions from the cyber world on the developing brain.

This chapter explores the conceptualization of IA as an evolving novel theme [ 3 , 5 ], describes the types of Internet addiction disorders (IAD) and looks into available epidemiology and etiology. Then, a proposal of a neurobiological basis for IA in the developing brain is introduced based on the current knowledge on more established dependences of substances/behaviors such as gambling of the maturing brain. Identification of high-risk children and adolescents and association of IA with other psychiatric disorders such as depression are discussed next followed by an account of the symptoms and signs of varying clinical presentations of IA and diagnosis. Then a review of treatment modalities, proposed so far, and prognosis of and finally prevention strategies for this, most probably, a fastest growing addiction disorder of the world is discussed.

2. The concept of Internet addiction and its controversies

IA was introduced as a disorder by Young in her seminal paper “Internet Addiction: The emergence of a new clinical disorder” in 1996 [ 2 ]. She proposed diagnostic criteria for IA based on the existing Diagnostic and Statistical Manual of Mental Disorders 4th edition (DSM-4) criteria for substance dependence [ 6 ]. In 1999, David Greenfield too proposed IA to be a form of addictive disorder [ 7 ]. These researchers highlighted that the tolerance and withdrawal symptoms of Internet use and those of substance use have similar features. There are others who suggest that IA is an impulse control disorder or even an obsessive-compulsive disorder. But the symptom overlap with substance and known behavioral addictions supports the notion that IA is an addiction—a behavioral one—for that matter.

An increasing incidence of IA together with its high cooccurrence with other established psychiatric disorders was pointed out later [ 8 ]. The proposal to include “Internet addiction disorder” in the 5th edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5) was brought forward. DSM-5 acknowledged the growing concern about the Internet use and related problems, but they claimed there is “insufficient peer-reviewed evidence to establish the diagnostic criteria and course descriptions” to identify the behavior as a mental disorder.

However, DSM-5 has introduced the condition Internet gaming disorder with some proposed criteria under “Emerging Measures and Models” heading for future study. The DSM-5 work group has reviewed many articles about online gaming, and they found some behavioral similarities of Internet gaming to other addiction behaviors which are established as disorders, namely gambling disorder and substance use disorders. The proposed criteria for Internet gaming disorder focus on preoccupation and behaviors, which mainly consume most aspects of life, withdrawal, tolerance, lack of control of use and marked deterioration of the function. The criteria are mostly as proposed by early researches on Internet addiction disorder [ 2 ].

Lack of consensus on a definition for IA, which is even blurred subcategory of Internet use (i.e., gaming, social media, cybersex, etc.), makes it difficult to derive prevalence data. Also, there is little or no knowledge of natural histories of cases. Thus, limited scientific research from around the globe has hindered IA earning a place as a disorder in DSM-5 [ 6 ].

However, in parts of the world where Internet gaming has an apparent high prevalence, relevant governments such as Chinese have accepted Internet gaming as an established “addiction” and South Korea have identified IA as a problem at governmental level and declared it a serious public health hazard [ 8 ]. Such highly affected Asian countries have developed separate treatment units for Internet gaming addiction, in hospitals (e.g., China, Korea). There are an increasing number of researchers looking into the diagnosis of IA, and many researchers agree that the criteria to identify Internet addiction are like in any addiction with craving and compulsion to use despite the knowledge of the harm, loss of control in terms of initiation, continuation and conclusion of the use and withdrawal features such as mood symptoms and distress. In the case of children, however, the knowledge of harm may not be relevant due to the level of cognitive development. For example, a Taiwanese study has proposed diagnosis criteria for Internet addiction and when tested on a group of adolescents found them to be of high specificity and sensitivity [ 9 ]. The criteria of Ko et al. are more organized than what is introduced by Young in 1998 [ 10 ] with the former following the pattern of International Classification of Diseases 10th version (ICD 10) by World Health Organization (WHO) [ 11 ]. However, we need larger multicenter international collaborative studies to understand the prevalence, etiology and the course of IA before we adopt criteria proposed based on local studies as the validity and reliability of the diagnostic criteria have to be ensured. Mental healthcare professionals in many countries particularly in Asia and Europe are increasingly urging the authorities such as World Health Organization to identify IA as an independent disorder [ 12 ].

3. Controversies

The Internet is undoubtedly a very useful commodity. Can we consider liberal use of the Internet as an illness at all? Is it unwanted pathologization of changing times? A disadvantage of such a labeling could be the stigmatization of the Internet, which has many important and versatile uses. One may wonder whether there is any underlying pharmaceutical company agenda in pushing this as a diagnosis!

One controversial view is based on the argument that there is no “chemical substance” as such, to get addicted to. However, American Society of Addiction Medicine (ASAM) has defined addiction as a chronic brain disorder, which is not limited to substance use [ 13 ].

A strong argument against an independent disorder of IA is brought up by some researchers who believe existing and well-established disorders such as depression or social anxiety are the root causes of driving people to misuse the Internet [ 14 , 15 ]. They argue that IA therefore is not a new disorder but a consequence of a more primary problem in mental health. Others (e.g., Some Forensic Psychiatrists) suggest that we should consider problematic Internet use, and the same way we consider the online gamblers as gamblers but not as Internet addicts [ 16 ].

More and more younger age groups are using the Internet with wider prevalence of the availability of the Internet. It is wondered how young is too young for children to go online. Some question the demarcation between passionate high involvement and problematic use or addiction [ 17 ]. Some experts in the field bring the argument whether we are pathologizing a common behavior [ 18 , 19 ]. It is also relevant to keep in mind the discrepancies in cultural beliefs and attitudes toward the Internet use in different parts of the world. In southeast Asia, for example, parents appear to believe any behavior that takes time away from family or educational pursuits as abnormal [ 20 ]. This may partly explain the highly inflated prevalence rates of IA in countries such as Taiwan and South Korea [ 21 ].

4. Terminology in Internet addiction

Currently, some have settled into a less controversial term for the problem of IA, the “problematic Internet use” (PIU) [ 22 , 23 ]. A large European Union-funded multicountry study used the terms Internet addictive behavior (IAB) for IA and dysfunctional Internet behavior (DIB) for problematic use of the Internet [ 24 ]. Compulsive Internet use (CIU) is another term used [ 25 ]. A more recent European study involving 11 countries has adopted the terms pathological Internet use (PtIU) and maladaptive Internet use (MIU) [ 26 ]. The salient features of addiction and problem use are more or less the same though the terminology used by different researchers is different. Addiction to the Internet basically implied a craving for the Internet use for uncontrollably long periods with impairment of functionality in the absence of any other disorders accounting for the condition and problem use was when one not meeting addictive features but nevertheless there are problems in bio psychosocial aspects in life. This chapter uses the terms IA and problem use for simplicity and clarity.

5. Types of Internet addiction disorders

One very common online activity among adolescents is recognized as online gaming. Many attractive single- and multiplayer games are being marketed among the youth worldwide. (e.g., World of Warcraft Clash of Clans, Slither.io, Clash Royale, Pokemon). Virtual communities created by some of the games could be more appealing for an adolescent than the real communities; the gamer can become an avatar of anybody he or she wishes; some games are designed in such a way gamers can buy cars and mansions and have a virtual second life. People spend/invest a whole lot in the second life at the cost of a deteriorating real life. Author, going by her clinical experience, wonders whether the adolescents with low self-esteem who are not recognized in real life might gain a lot of recognition from other fellow gamers in the online community as great warriors. However, this hypothesis needs to be explored through proper research. A US study has found Internet gaming to be associated with alcohol and recreational drug abuse and poor interpersonal relationships with no gender differences [ 27 ]. Research has found online gaming addiction to be associated with aggression, low sociability and self‐efficacy, and a lower satisfaction with life [ 24 ]. The gamers with these risk factors engage in intense use and are of all age groups. It should be interesting to see the nature of these associations, whether these negative characteristics in the adolescents lead to IA or IA results in these traits. Such knowledge can provide us with interventions in terms of prevention of IA. No clear answer is evident from available data at present.

Another type of internet use, which is popular among adolescents, is social networking using applications such as viber, whatsapp, instagram, facebook, twitter, my space etc. and chat rooms/e-mail. A child or an adolescent will be very much overwhelmed by the amount of online connections he or she can have through these connecting apps. Notifications popping up will invariably distract the youth from homework or any other academic activity. Being connected with around the world friends 24 × 7 could be an around the clock distraction and disturbance. Author recalls one of her patients, a 16-year-old schoolgirl who receives 14,000+ text messages via Viber per day. Her life revolved around receiving and sending texts to her boyfriend and friends and would become aggressive toward family and property when the parents attempted to limit the Internet time. Another grave risk involved in social media sites is children and adolescents getting exposed to unknown adults who may abuse the “online friendship” and bring harm on the young.

Cybersex is also an attractive type of Internet activity among adolescents. Premature exposure to various aspects of sexuality and exposure to adverse sexual activity may hinder the healthy psychosexual development in children and adolescents. Problem use of Internet pornography by adolescents has been associated with alcohol, illicit drugs, greater number of sexual partners, poor interpersonal real-life relationships with partners and poor self-worth [ 27 ].

Online gambling is the most studied type of IA. It is found to be highly addictive among adults, yet there are not enough studies to know the situation among adolescents. However, it is reasonable to state that going by available data and author’ s clinical experience, social networking and gaming are strongly associated with problem use of the Internet.

Watching videos/movies was not related to problem use of the Internet according to one study [ 24 ]. Yet the evidence is not conclusive to derive a definite idea about this type of Internet activity.

Males are found to have been engaging in gaming significantly more compared to females, whereas more females tend to spend time in social media at a significantly higher rate than males. Children and adolescents tend to indulge in these online attractions at the expense of their school work and real-life relationships with friends/family and sports. Researchers have found that IA or problem use can arise from involvement in a range of online activities [ 2 , 23 , 28 – 30 ].

6. Epidemiology of Internet addiction

Researchers have looked into the prevalence of IA. As discussed above, being an evolving concept there are very few empirical studies and even fewer meta-analyses on IA. Further, it is difficult to compare and contrast available studies due to the vast differences in the methodology as a result of the ill-defined and poor consensual concept of IA. The considerable lack of unanimity in terminology is apparent in studies, and prevalence rates mentioned here are from studies that use many different terms for IA.

IA is reported more commonly in Asian countries and in males aged 12–20. The available research on game addiction centers mostly on young males worldwide. There is some evidence to believe that the onset of IA is probably in late childhood/early adolescence [ 31 ]. There are many reports in countries such as China and South Korea. A few European and American studies are also available. The researchers who make an effort to educate the authorities and public in USA claim that IA is a silent epidemic in United States, at present. There are a fewer African studies mainly from South Africa that indicate a lower prevalence estimate compared to other countries of the world. One study reported the figure as 1.67–5.29% [ 32 ]. A meta-analysis from 31 nations from seven world regions (North America, Oceania, North & West Europe, South & East Europe, Middle East, Asia and South America) revealed an overall prevalence estimate of 6% in IA. The results showed that the adverse real-life living conditions such as poor satisfaction with life, greater overall pollution, lower national income and greater time spent in traffic were directly proportional to the IA. Middle East had the highest individual world region prevalence estimate of IA, the figure being 10.9% [ 33 ].

The far eastern countries such as China report 10.2% of moderate users and 0.6% of severely addicted [ 34 ]: South Korea have found 1.6% [ 35 ], 3.5% [ 36 ], 4.3% [ 37 ], 10.7% [ 38 ] and 20.3% [ 39 ] of adolescents with IA. In Taiwan, 17.9% of students were found to be addicted to the Internet [ 40 ].

A European Union‐funded research project was carried on among adolescents in Greece, Germany, the Netherlands, Iceland, Poland, Romania and Spain [ 24 ]. The Internet addiction was detected in 1.2% of the total sample, and 13.9% have been found to have problematic Internet use. Less affluent countries of the sample, Spain, Romania and Poland, have showed a higher prevalence of problem use, while Germany and Iceland have shown the lowest. The problem use was associated more commonly with boys, older adolescents and those who had parents with low level of education. The problem users have shown lower psychosocial well‐being.

A more recent research on the prevalence of Internet addiction on a large number of adolescents from 11 European countries has showed that the overall prevalence of problematic Internet use was 4.4%, and rates were higher in males than in females (5.2% versus 3.8%) and differed between countries (χ(2) = 309.98; d.f. = 20; P < 0.001). A significant correlation between problem use and mean hours online and male gender were found [ 26 ].

The Indian subcontinent is seemingly overtaking other nations with 53% of Indians connected to the Internet every waking hour according to a recent study conducted in 10 countries by a global management consulting firm AT Kearney Global Research based in London. India has made several attempts to contribute to available knowledge base on IA and related problems in adolescents. One 2013 cross-sectional study conducted among 987 adolescents in Mumbai has revealed 74.5% as moderate users, 24.8% as possible addicts and 0.7% as addicts. Males in comparison with females were significantly more addicted [ 41 ]. Many such local researches are available online, yet a national figure on prevalence of IA or problem use is not yet available in India where one of the leading and fastest growing information technology industries prevails.

A preliminary survey was conducted on the Internet use in a convenient sample of 179 adolescents from schools in central Sri Lanka by author and her team to derive a general idea about the Internet use among adolescents and the views of their significant adults on the Internet [ 42 ]. Sri Lanka is a middle-income developing country in South Asia where the Internet is promoted at large scale by multinational companies for competitive prices. No published studies are available on the Internet use among children and adolescents in Sri Lanka. The survey found that 91.06% of the sample was using the Internet with no sex difference; 2.79% of parents and 3.3% of teachers liked students using the Internet; and 45% of each adult group had a neutral view ( Table 1 ). This is interesting as for some parents and teachers in Sri Lanka believe the Internet is a bad influence on the young that entices them into pornography and risky relationships. The Internet is not affordable to many young Sri Lankans yet, but mobile phone packages with Internet facility are coming up increasingly enabling the children and adolescents to use the Internet unsupervised by adults. Out of the sample, 68.7% used the Internet for social media and 55.6% was watching films and videos ( Table 2 ).

Table 1.

View of the parents and teachers about Internet usage of students [ 42 ].

Table 2.

Purpose of Internet usage (out of 163 Internet users) [ 42 ].

7. Etiology

Many children and adolescents are engaging in the Internet use for academic pursuits as well as recreation. But not all will end up being addicted to or problem users of the Internet. The pertinent question what makes a particular adolescent becomes a victim of IA is the question we should try and find an answer. However, like the etiology of any other mental and psychosomatic disorder in psychiatry, the answer is not that simple. After reviewing the attempts made by researchers to come up with a model to understand IA and its management, the author believes that the well-known biopsychosocial model of disease is a feasible and logical explanation for IA, too.

The genetic factors play a part in addictions, and therefore, biological vulnerability is considered to contribute for IA too. The psychological component with cognitive errors, negative effects and personality traits also accounts for the condition. Here, it is noteworthy that personality is again determined by the genetic composition of the individual. Finally, the social factors such as affordability and availability of the devices and networks, the attitudes of the parents and schools about the Internet and the nature of the education system (i.e., whether students are requested to use a lot of online activities for school work as in most high schools in North America) and the inert qualities of the Internet itself that attract youngsters are also contributing for IA.

Researchers have wondered whether different types of Internet addictions (i.e., cybersex, social networking, gaming, etc.) have same underlying mechanisms or not. Apparently, all the types have common features of the well-established signs and symptoms of addiction, pleasure generating quality and the ability to go anonymous if necessary. Yet it is only speculation until scientific evidence is available on underlying pathophysiology.

8. The neurobiological basis of the Internet addiction

It is known that the developing brains of children and adolescents are more vulnerable to get addicted to rewarding activities. Adolescent period is a period of heightened neuroplasticity that makes this age more susceptible to the effects of addictive drugs [ 43 ]. Internet addiction and other similar addictive behaviors too can reasonably be considered to have the same effect as drugs on these vulnerable brains. Based on the available knowledge of neurobiology of addiction, scientists have proposed a neurobiological theory for Internet addiction. The “reward center” or “pleasure pathway” of the brain is responsible for the pleasure experienced by an individual. Neurochemicals associated with pleasure such as dopamine, morphine, like endorphins, and others are released when the brain areas such as nucleus accumbens of the pleasure pathway are activated [ 44 , 45 ]. Substances of addiction or similar behaviors of addictions are found to activate the pleasure pathway. The receptors involved gets affected when exposed to the chemicals over time, and tolerance and withdrawal develop like in any addiction, needing more and more online input to achieve the same stimulation or “kick” together with continuous engagement in the behavior to avoid withdrawal features [ 46 ]. Some activists working on education of public against hazards of the Internet argue, in the genetically vulnerable adolescent or child, lack of love care and affection by the significant adults in his or her life leads to no or minimal activation of pleasure pathways. The children are left alone to fill the emptiness from outside pleasures such as the Internet. That is a theory worth more research as it can be utilized to prevent Internet addiction.

The Internet offers a strong reinforcement for addiction like any other addiction as depicted in Dr. Kimberly Young’s Hand Book on Internet Addiction [ 47 ]. In gambling, as psychologists found through their extensive research, a variable ratio reinforcement schedule (VRRS) operates giving the gambler the suspension of unpredictability and varying rewards. It is proposed what happens in Internet addiction is also the same. The computer applications are increasingly developed to engage the user fully and incessantly. The coupling of the online activity with pleasure generating themes (sex, sense of connection through social networks, etc.) will heighten the reinforcement leading to more severe addictions [ 48 ].

9. High-risk groups for Internet addiction

Qualitative research has reported how the adolescence itself is a risk factor [ 49 ].

The developing brain of adolescents has an innate quality of curiosity and a drive for adventures with risk taking. The Internet also gives answers to almost any query they have, keeps them connected and can be a load of never-ending fun at mere finger tips.

However, certain adolescents are more vulnerable to the addictive quality of the Internet than others. One with deficient real-life social skills may find it easy to have online relationships as there is no pressure of real-life eye-to-eye contacts, gestures and human touch. They may find it boosting to be liked and praised online. They may tend to overuse virtual realities offered by attractions in the Internet to fill the voids of boredom and loneliness of real life. At the press of a key, an “emoticon” expressing the due feeling could be far less distressing and comforting than all the “hard work” of trying to express emotions in real-life relationships for the shy adolescent.

Adolescents who are lacking emotional and psychological support are found to be at highest risk and so are the adolescents with identified emotional and behavioral disorders [ 31 ].

It is worth exploring the fact whether the adolescents who face tremendous academic pressure in real life tend to find temporary solace in stress-free virtual reality of being online. This may explain the high prevalence of gaming reported in Asian cultures those give priority to the education of the children even at the expense of the psychological well-being of the children. However, this theory needs empirical support.

It is found that living in metropolitan areas was associated with problem use of the Internet. It is not clear whether it is due to wider availability of the Internet by way of free WiFi in cafes, shops and malls in metropolitan area. Poor adult supervision seems a key element in high-risk adolescents. Students not living with a biological parent, low parental involvement and parental unemployment have shown the highest relative risks of both problem use and addiction of Internet.

Availability of one or several devices to log into the Internet such as smart phones, tablets and even wrist watches at present with wide spread availability of the Internet paves way for increase in the risk of IA.

The Internet-based treatment programs are trialed and used in the management of individuals with autism spectrum disorders. However, there is some concern that, despite its benefits, the Internet has the risk of addictive use in this special group of people [ 50 ].

It has been found that doing homework/research was negatively associated with problematic Internet use [ 24 ]. A positive correlation was found between Internet use for academic purposes and greater self-esteem, better relationship with parents and less use of substances of abuse [ 27 ]. Maybe the studious adolescent does not possess some of the risk factors leading to problem use of Internet to begin with, and it could be the reason for positive findings. This needs more exploration as it may lead us to understand preventive measures.

10. The association of Internet addiction with psychiatric conditions

Several authors have reported a significant comorbidity of IA and mental health disorders. Particularly, depression and anxiety disorders among adolescents may increase the vulnerability of an IA. The affected adolescents may find online activities distracting them from real life low or anxious mood and distressing cognitions [ 51 ]. Attention deficit hyperactivity disorder (ADHD) is another behavioral disorder IA is associated with making the affected children and adolescents more vulnerable to IA [ 52 ].

But some work brings about the notion whether the depressive and anxiety symptoms experienced by problem or addicted Internet users are more a consequence rather than a cause or co-occurrence [ 53 ].

A cross-sectional survey among a sample of 175 university undergraduates in Peradeniya, Sri Lanka, reported IA was positively correlated with depression, loneliness and time spent on the Internet, while it negatively correlated with healthy lifestyle [ 54 ].

11. Clinical features and diagnosis

A good detailed history from is paramount for the diagnosis of IA. The adults bring the affected child or adolescent, usually. Mostly, it is the parents who notice the changes in behavior. The clinical picture may be subtle or marked. In subtle cases, the parents or teachers may complain of a drop in school work, disinterest in extracurricular activities previously interested in and lying about the Internet usage—both about the time spent and the particular online activity (e.g., “No…. I did not spend one hour it was just a half an hour!!!!“ or “No…. I was not playing Clash of Clans but just checking up something for my home work!!!!”). Denial and concealment of the extent of the Internet use are quite often seen in the clinical practice, and they complicate matters as help is then sought very late into the problem. Problem use leads to irritabilities, arguments with parents and sleepiness in daytime. However, if the condition is not intervened early, there may be a risk of the adolescent engaging in the behavior openly and resisting adult interventions more aggressively.

Dramatic or marked presentations around the Internet use may also occur. The adolescent may be caught engaging in cybersex during school hours or at home, and the school or devastated parents will bring him or her to a psychiatrist.

In some other cases, a teenager may be engaging in online gaming for excessive hours. Going by the DSM-5 proposed criteria, clinicians can have some directives in order to diagnose Internet gaming disorder. An adolescent who is sitting at a device with the Internet and spends 8–10 h or more per day and at least 30 h per week, in gaming neglecting not only academic activities but also food or sleep, may be diagnosed as a victim of Internet gaming disorder [ 6 ]. They typically get angry and agitated if parents try to prevent the addicted behavior.

Clinicians should keep in mind the close association the IA or problem use has with the mental health of the adolescent. It should be the rule to look for features of comorbid, consequent or causative psychiatric disorders such as depression or anxiety. A thorough history and a mental state examination are warranted.

Extreme cases were reported in mostly Asian countries. The world was shocked to hear the news of the young adult couple from Seoul, South Korea, neglecting their infant daughter to death in order to raise a virtual baby called Animus in a gaming community. There are many news items of individuals including teenagers dying after excessive game playing from China, Taiwan, Hong Kong and South Korea. In these extreme cases, the online game is usually a highly addictive role-playing fantasy game.

Young states not only psychological but also physical problems such as back pain, eye strain and carpal tunnel syndrome can be caused by long hours (more than 18 h a day) online [ 10 ]. It is reported that cardiopulmonary-related deaths have also occurred in addicts in Internet cafes [ 55 ]. Therefore, it is important to look for any associated physical problems.

In the absence of any DSM or ICD 10 criteria for diagnosis of IA, reader is directed to two criteria commonly used to arrive at a diagnosis of IA: Young’s diagnostic questionnaire for Internet addiction [ 10 ] and Ko et al. ’s proposed diagnostic criteria for Internet addiction [ 9 ].

12. Assessment tools for Internet addiction

Despite the lack of consensus in diagnostic criteria, many tools of screening and assessing the degree of the Internet-related problems have been developed and used in research around the globe. Internet addiction disorder diagnostic criteria (IAD–DC) by Goldberg in 1995 [ 56 ] is the first scale on IA, found in literature. Later a widely used 20-item, quantitative, assessment scale Internet addiction test (IAT) was developed: Young’s Internet addiction test [ 57 ]. Many researchers are using IAT up-to-date due to its high reliability. Internet addiction disorder scale by Goldberg in 2000 is a qualitative 11-item scale. Readers are directed to the critical review of existing scales and their psychometric properties by Laconi et al. published in 2014, which is freely available online in the journal, Computers in Human Behaviour, for a more comprehensive in-depth review of the subject [ 58 ]. (One of the many advantages of the Internet!)

However, the assessment tools will only substantiate the clinical assessment through history and mental state in diagnosing IA.

13. Management of Internet addiction

It is understandable that there are no definitive treatments laid down for IA in light of the knowledge it is not an accepted disorder at present. However, while world health authorities are being cautious about the fundamental existence of a disorder of IA, children, adolescents and adults are increasingly reported to be facing adversities related to the Internet. Some states (e.g., China, South Korea) have gone ahead and started their own diagnoses and management systems, as they cannot afford to wait till the disease classification systems give them a label to start. Internet addiction can be detrimental to the affected individual adolescent and his or her family, and if one such adolescent walks into the clinical practice of a mental health professional, he or she should be armed with best available options of treatment.

It is important to keep in mind that it is very easy to place restrictions on a child not to use the Internet by adults, parents, teachers and therapists themselves, who grew up in a pen and paper era! The new technology evolves and societies have to keep abreast with the development for successful survival. Therefore, total banning of an adolescent from using the Internet is not the answer. In other words, total abstinence should not be the goal [ 59 ]. Instead, controlled/safe/balanced or more preferably sensible Internet usage should be the goal. Both the treating clinician and the affected individual should come to a consensus about the details of sensible use depending on the age, educational demands, cultural value system, etc.

14. Assessment of Internet addiction

The first step has to be a detailed history and mental state examination as in the case of any other mental health disorder.

A suitably validated assessment scale such as Young’s Internet addiction test (IAT) [ 10 ] can be utilized to substantiate clinical diagnosis but not to replace it, as the gold standard in diagnosing any mental and behavioral disorder, including behavioral addictions such as IA, is the clinical diagnosis. However, the cultural differences should be considered when using a tool developed in another sociocultural background.

Comorbidities should be considered, actively looked for and intervened. For example, a social phobic or a depressed adolescent may be masking his affective status by engaging in the Internet activities that make him happy and gives the feeling of being in control. In such cases, where the IA is only secondary, treating the underlying mental health disorder should be the priority. In mild cases of secondary IA, treating the root condition itself may help the individual to refrain from misusing the Internet.

15. Treatment of Internet addiction

According to a 2011 systematic review and consort evaluation on clinical trials of Internet addiction treatment by King and his team, we are unable to come up with definitive treatment modules for Internet addiction. The evidence base available for treatment is defective with conclusions coming from anecdotal reports, small-uncontrolled studies with no randomization [ 60 ].

15.1. Psychological treatments

The clinicians and therapists have attempted to have some direction from existing treatment types mainly extrapolating methods used for more known addictions such as substance addictions. Many methods such as boot camp-style treatments, cognitive behavior therapy (CBT), family therapy, group therapy, behavior therapies such as social skills training and counseling have being used worldwide [ 60 ].

Most of the psychological treatments employed had sprung from CBT [ 61 ]. This is probably due to the fact that CBT has proven to be efficacious in many other behavioral addictions such as gambling disorder and impulse control disorder.

Dr. Young the pioneering researcher on IA in her book “Internet Addiction: Symptoms, Evaluation, and Treatment” [ 62 ] and in her study [ 63 ] offers some practical treatment strategies based on CBT. Though the clinical evidence for the efficacy of the methods is not stated, they offer some important directions in managing the individual patient until more evidence to establish them or replace them arrives. The suggestions are mainly based on practical behavioral techniques that are agreed upon by the user. The reader is referred to Dr. Young’s book for a detailed account on those treatment strategies. The user’s consent, willingness and high motivation are important in order to practice the suggested treatment strategies. In the case of children and adolescents, they may not be very agreeable to the suggestions as their cognitive development is not complete to understand the adverse aspect of the Internet.

A randomized controlled study used eight sessions of multimodal school-based group CBT or no treatment on 56 adolescents aged 12–17 years randomly allocated into treatment and no treatment [ 64 ]. The Internet use has decreased in both groups, while actively treated group has additionally improved in some other general constructs.

Many other investigators have found CBT-based treatment approaches being effective on the sample of adolescents they studied [ 65 – 67 ].

Cash and his colleagues in their summary on Internet addiction mention the importance of utilizing motivational interviewing (MI) a client-centered technique used to change adverse behaviors, as a component in treatment plans for IA (19). MI has not been used so far in the treatment of Internet addiction according to available information.

Since any problem in children and adolescence is closely associated with the family, it is warranted to consider family-based therapies for IA. Though there is not enough evidence to support for efficacy of such interventions, overall improvement in communication in the family and better monitoring of the Internet use are some of the benefits noticed [ 68 , 69 ].

Many enthusiastic and innovative therapies based on behavior therapy have been put to practice to bring about a positive change in Internet addictive behaviors, such as Reality therapy (RT) [ 70 ] and Acceptance & Commitment Therapy (ACT) [ 71 ] with varying results.

Simple educational programs for children in real life or ironically online are considered to combat problem use of the Internet. One such online program follows the 12 steps self-help treatment approach used for alcoholic anonymous [ 60 ].

Some suggests that there is an important place for physical exercise in helping adolescents to reduce the use of the Internet. Sports believed to be compensating for the reduced dopamine levels in brain resulted in the decreased online use. Further, sports can be a part of CBT programs [ 72 ].

15.2. Pharmacological treatments

A few types of medications have been used, and there are some studies looking into the effectiveness of them. However, there are no adequate randomized controlled trials to derive definitive guidance to treatments.

There are several reports on the use of selective serotonin-reuptake inhibitors (SSRIs) particularly when Internet addiction is comorbid with depression and anxiety for which SSRIs have an established place as an effective treatment [ 73 , 74 ]. The SSRI, escitalopram [ 75 ], non-tricyclic antidepressants, bupropion [ 76 ], psycho-stimulant, methylphenidate [ 77 ], mood stabilizers [ 22 ], antipsychotic, quetiapine [ 78 ] and opioid receptor antagonist and naltrexone [ 79 ] have been trialed as treatments. However, most of these studies were quite short term and some are case reports. Hence, no pharmacological medication can be recommended for IA per se in children and adolescents at present.

15.3. Multimodal treatments

IA being a complicated phenomenon involving many aspects of life as biological, psychological and sociocultural, a combined or a multimodal treatment approach is increasingly considered by the concerned scientific community. There are reports on group CBT, parental training, teacher education, family therapy, medication, case management and brief intervention therapies, which are combined according to the necessity [ 80 – 85 ]. A widely inclusive IA recovery program with mindfulness-based relapse prevention, digital detoxification and animal-assisted therapy among many other different multidisciplinary approaches is proposed in 2012 [ 86 ].

16. Tips on sensible Internet use

Author suggests, after reviewing available solutions on the Internet (You tube, Ted Talks, etc.) by activists as well as scientific reports, some simple techniques based on behavior therapy with or without cognitive component that can be utilized to use the Internet sensibly ( Box 1 ).

Having a prior discussion and an agreement on Internet use before a family purchase Internet facility. (healthy digital diet and digital nutrition)

All in the household following through the plan. (Modeling by the adults)

Setting aside devices at family/friends gatherings and meal times. (Disconnect to reconnect)

Having a family Internet-free day probably on a Sunday so that education or work/business is not affected. (Digital Detox)

When at studies or assignments switching of the notifications of chat sites or social networks just the way people place mobile phones on silent mode or switch them off.

Have an assigned time for socializing on the net (by using an alarm) and setting limits on checking on social media responses, for example, only three times per day or once a week. (Checking on checking)

Internet times to be replaced by more attractive offline activities (not offline studies!) such as getting together with friends in real life, competitive or recreational sports, aerobics, etc. (Doing it in real)

Reward for being off Internet as planned, for example, by having a vacation every 3 months or weekend movie/dinner out. (Celebrate)

Box 1. Tips on sensible Internet use.

17. Clinical course and prognosis

Not much is known about the natural history of the condition as the concept of IA itself is at a very preliminary level. We need follow-up studies.

The experience from highly affected countries suggests that the problem of IA is quite a complex one. With the ubiquity of the Internet and its innate qualities of urging individuals to misuse despite harm, the course of IA is seemingly long term and resistant to treatment.

Prognosis of the highly addicted adolescent seems poor in general given the available information. However, clinicians should not be pessimistic in attempting to treat IA of an affected individual patient as multimodal treatment approached though not tested adequately offers some hope.

18. Prevention

IA is considered at different intensity by different countries depending on how affected their population by it. Asian countries are undoubtedly most affected and hence have come up with most solutions too.

Most of the Internet-based activities are promoted among children and adolescents. Case is particularly so in online gaming which seemingly is the most prevalent type of Internet addiction disorder that could even reach DSM-5 at least at a warning stage.

A mass awareness program on the concept of IA is important. It has to be carefully planned and implemented as a total aversion from the Internet even before it reaches most of the children and adolescents in some parts of the world would be a shame given the unbeatable wonderful positive aspects of the Internet on education, business and recreation. The reader is also reminded at this point, of the accusation by some, that a normal phenomenon is being pathologized by introducing the concept of Internet addiction.

Primary prevention is encouraged by developing a sensible Internet culture starting from the individual household. Adults should set living examples and have controlled access to the Internet following a discussion and agreement in the family upon the way of the Internet use ( Box 1 ).

Secondary and tertiary prevention may call for drastic methods if a nation is seriously affected. For example, total ban of the Internet in certain time of the day for under 18-year-olds, developing a system to slow down the Internet if played more than a certain number of hours (South Korea) [ 8 ], restricting Internet gaming among youth by demanding a “game fatigue system” from the game operators (China) [ 8 ].

19. Summary

The Internet use is increasingly becoming an integral part of day-to-day life of all age groups around the world. The concept of “Internet addiction” remains controversial and at a fetal stage waiting to be evolved into maturity with better quality research. While IA has not reached DSM-5 or probably the future ICD 11, we cannot ignore the numbers or the seriousness of cases reported in Asian countries, neither can we ignore the individual families seeking help for problematic Internet users, children and adolescents. An internationally consensual multicenter attempt to define the concept, look into etiology, develop valid and reliable diagnostic criteria and come up with effective management strategies that involve prevention is warranted. We are gifted with the technology of Internet, and it has come to stay and will expand in new horizons we may only see in science fictions today. The children should be taught to use it with respect in a moderated and controlled but positive way. Such an approach only will win the cooperation of today’s children and adolescents who are growing up with the Internet as a daily commodity.

20. Acknowledgments

Dr. Sampath Tennakoon, Senior Lecturer, Department of Community Medicine, Faculty of Medicine, University of Peradeniya, Sri Lanka.

Dr. Helani Alahakoon, Temporary Lecturer, Department of Psychiatry, Faculty of Medicine, University of Peradeniya, Sri Lanka.

Dr. Rangana Kuruwita, Temporary Lecturer, Department of Psychiatry, Faculty of Medicine, University of Peradeniya, Sri Lanka.

Miss. H.G Devika Malkanthi, Temporary Lecturer, Department of Psychiatry, Faculty of Medicine, University of Peradeniya, Sri Lanka.

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© 2017 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 3.0 License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Essay on Internet Addiction

Students are often asked to write an essay on Internet Addiction in their schools and colleges. And if you’re also looking for the same, we have created 100-word, 250-word, and 500-word essays on the topic.

Let’s take a look…

100 Words Essay on Internet Addiction

Introduction.

Internet addiction is a growing problem globally. It refers to excessive use of the internet, leading to negative impacts on a person’s life.

The main cause of internet addiction is the desire for online social interaction and entertainment. Online games, social media, and websites can be very engaging.

Internet addiction can lead to poor academic performance, lack of social skills, and health issues like eye strain and obesity due to physical inactivity.

It’s important to balance internet usage with other activities. Parents and teachers can help by setting limits and promoting healthy habits.

250 Words Essay on Internet Addiction

The advent of the internet has revolutionized human existence, providing limitless opportunities for learning, communication, and entertainment. However, this unprecedented access to information and connectivity has birthed a new form of dependency – internet addiction.

Understanding Internet Addiction

Internet addiction, also known as compulsive internet use, is characterized by excessive or poorly controlled preoccupations, urges, or behaviors regarding computer use and internet access. It is a psychological disorder that can lead to severe stress, anxiety, and a variety of other mental health problems.

Causes and Effects

The causes of internet addiction are multifaceted, ranging from the need for social interaction, escapism, or the thrill of exploring virtual realities. The effects, however, can be detrimental, leading to academic failure, job loss, and the breakdown of personal relationships.

Prevention and Treatment

Prevention is always better than cure. Encouraging healthy internet usage habits, promoting physical activities, and fostering real-life social interactions can help prevent this addiction. However, once addicted, professional help may be necessary. Cognitive-behavioral therapy has proven effective in treating internet addiction by helping individuals to identify and change patterns of thought that lead to compulsive behaviors.

In conclusion, while the internet has undoubtedly brought about vast benefits, it has also introduced new challenges. Internet addiction is a growing concern that requires our attention. By understanding its causes and effects, we can develop strategies to prevent and treat this modern-day affliction.

500 Words Essay on Internet Addiction

Internet addiction is characterized by an individual’s inability to control their use of the internet, which eventually interferes with their daily life, work, and relationships. It is not merely about the amount of time spent online but the obsession with internet activities to the point where it affects mental and physical health, personal relationships, and productivity.

Causes and Symptoms

The causes of internet addiction can be multifaceted. It can be a symptom of other underlying mental health issues like depression, anxiety, and stress disorders. The anonymity, ease of access, and perceived environment of acceptance and escape the internet offers can also contribute to its addictive potential. Symptoms may include preoccupation with the internet, inability to control online use, neglect of personal life, and emotional changes such as restlessness or irritability when internet use is limited.

Impacts of Internet Addiction

Preventing internet addiction involves promoting healthy internet use. This can be achieved by setting time limits, taking regular breaks, and promoting a balanced lifestyle with physical activities and offline social interactions. Treatment for those already addicted often involves cognitive-behavioral therapy, which helps individuals identify problematic behaviors and develop coping strategies. In severe cases, medication may also be used under professional supervision.

In conclusion, internet addiction is a growing concern that requires attention. As we continue to embrace digital technology, it is crucial to promote healthy internet use and provide help for those struggling with addiction. It’s a call to action for researchers, mental health professionals, and society as a whole to understand and address this modern-day issue effectively.

If you’re looking for more, here are essays on other interesting topics:

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Essay on Internet Addiction | Internet Addiction Essay for Students and Children in English

February 14, 2024 by Prasanna

Essay on Internet Addiction: The origins of the Internet can be traced back to the 1960s. Over the last 60 years, technology has improved in such strides that it seems virtually unrecognizable today to what it was when it started. No other invention has evolved at a pace as fast as this. The Internet gives us access to the entire world for anything and everything. If one has access to the Internet and enough money, there can be no need for any individual to step out of the house whatsoever. As much as it has connected us to the world, it has also isolated us.

What’s worse is that now there exists a phenomenon of ‘internet addiction.’ Which is an unhealthy addition to a world already struggling with addictions as it is. And just like any other addiction, it has its fair share of negative consequences and problems that can affect a person physically and mentally.

You can also find more  Essay Writing  articles on events, persons, sports, technology and many more.

Long and Short Essays on Internet Addiction for Students and Kids in English

As of recently, internet addiction has become a global problem among people of all ages. Not just the youth but also children. They sit in front of the screen on social media, chatting, or video games. Using the Internet in excess can be destructive for the person and even fatal.

While the Internet is a great tool and can be used to make life easier, it is essential to check how much time we spend. It is harmful when individuals make their whole lives revolve around the Internet.

The Internet is also filled with dangerous people, and it can therefore cause people to get isolated from their family and friends and influence individuals to make wrong decisions. It is crucial to regulate internet usage, and parents and guardians must be careful and aware of their children so that they don’t develop an over-dependence on the Internet.

Short Essay on Internet Addiction 350 Words in English

Short Essay on Internet Addiction is usually given to classes 1, 2, 3, 4, 5, and 6.

Internet addiction has become a new age addiction that has gripped people around the world. People belonging to different age groups suffer from this addiction, though it’s more prevalent among the youth. People access the Internet to kill boredom, find a way out of loneliness, or simply to have some fun in their lives. However, before they know it, they are hooked to it.

The Internet is a massive entertainment and engagement source, and it’s hard to resist the addictive things it offers. However, it’s essential to regulate internet use to ensure that it has not become an addiction. Like any other addiction, this one too has grave consequences. It can have a severe impact on a person’s neurological functioning. People can lose their sense of time and bearing and neglect their family, friends, and even their work and responsibilities.

Many internet addicts develop anxiety issues and depression. This hampers their personal and professional growth. Their physical health also deteriorates. They can incur health problems like obesity, heart condition, and hypertension. To live a balanced life, it is essential to be careful of one’s internet usage and to have the self-control not to let it take over your life.

Introduction

The number of internet users worldwide is increasing drastically, and with every passing day, the number of internet addicts is also rising. The Internet can be a very alluring place. Video games, chat rooms, social media platforms, entertainment videos, engrossing web series, and interesting blogs can keep an individual hooked for hours. People begin to use the Internet to beat loneliness and tedium and end up attached to it within no time.

Smart Phones and Internet Addiction

Around a decade ago, when the Internet could only be accessed on the desktop or a laptop, web usage was limited. Many were still excessively using it, but it was not as bad as it is now. The introduction of smartphones has given the rates of internet addiction a boost. People are seen glued to their screens wherever they go. This becomes worse as work is done on screen as well. And in these times, you need this technology for getting an education as well.

Internet addicts forget to eat, complete essential tasks, and ignore their loved ones. All they need is a high-speed internet connection and a tool to access it. This is more than enough to consume all their attention throughout the day.

Internet addiction is a severe disorder that affects a person’s ability to think rationally. Even though internet addicts often know the harmful consequences of this addiction, they do not make much effort to beat it. This often results in severe problems like depression, anxiety, and other psychological disorders.

Read More: Social Media Essay 250 Words

Internet Addiction Essay 400 Words in English

The Internet is one of the world’s most important sources of data that is used worldwide. People from across the globe communicate with one another through the Internet. Whether it’s watching a movie or catching up with an old friend, the Internet has made everything easier. It has also made us more productive and has made life so much easier.

It is hard to pinpoint precisely what causes internet addiction. But it is known that it can be easily compared to other types of addictions with the sort of dependency it causes. Internet addiction is a more recent phenomenon, and the causes can vary with gender, age, and personality.

Causes of internet addiction

Social circles play a critical role in causing behavioral issues like addiction. Internet addiction is no exception, as constant internet surfing has become commonplace among the youth. There is even an encouragement to seek friends online while playing online games, chat rooms, or just on social media.

The Internet can also become a coping-mechanism for self-soothing and as an escape for those who are suffering from mental health issues and such. The same way that people who suffer from depression or anxiety use alcohol and drugs to self-medicate, the Internet can be a distraction. Be it by playing video games, watching shows, or merely surfing forums.

An addition to the last point is that emotions and thought patterns have a huge role to play when it comes to addictions being developed. Those that desire an evasion from real life or a distraction from problems go to the Internet for emotional support. When an individual finds this sort of support only on the Internet and not in real life, it becomes an addiction. Introverts or are shy and do not have social skills can also develop an internet addiction. They find that it is easier to interact with people online than in person. It is also that easy for people to fabricate their identities and scam people like those who are naïve.

People get addicted due to the dopamine high that internet surfing can give. A person who receives this only from the Internet and nowhere else can very quickly be addicted. All of us need to be careful with our internet usage and dependency. Regulation or completely cutting it off can sometimes be the answer.

Long Essay on Internet Addiction 800 Words in English

Long Essay on Internet Addiction is usually given to classes 7, 8, 9, and 10.

People around the world are now having the issue of compulsive internet usage. They spend hours and hours on end on the Internet knowing that it does not benefit and is simply a waste of time. They make no effort to change this even though they know that it is harmful and can become an addiction. This lack of self-control can be hazardous, just as any other addiction is. People who are addicted to the internet face mental and physical issues, which can end up being fatal and end a person’s life prematurely.

Internet Addiction and the Youth

Internet addiction is more prevalent among youngsters. They end up scrolling on social media or forums or other websites, watching videos, shows, chatting, or shopping online. Time on the Internet may have begun as very minimal but ends up taking hours and hours of a person’s day as the usage increases. As they grow addicted, other responsibilities at home or studying are neglected. This can affect a person’s education and even inhibit their social growth.

When social skills are not allowed to be built, they do not know how to function in society anymore. They are unable to interact with people in real life normally due to this. They can also develop social anxiety. They prefer friends online who can very easily be dangerous individuals scamming them and negatively influencing them. They can be groomed inappropriately or end up stealing and losing money. When their education is affected, it hampers their future, and they spend no time developing skills that can build their careers. Spending all the time online can cause health issues if they do not exercise or go out.

It is also regrettable that parents hand their children iPads to distract them. From a young age, the children begin to develop a dependency on the Internet. Even while eating, the children gravitate towards the screen to watch something. Another sad development is the fact that now smartphones and laptops are essential for education. Notes, lectures, and all resources can be found online. If all a student’s time studying and relaxing is spent online, there is no time to be present in real life.

In the same manner, many young working professionals also fall prey to the same problem. Their time is wasted on the Internet when they should concentrate on furthering their careers and networking. Internet addiction has an adverse effect on young people today and presents a genuine danger for their future.

Consequences 

Internet addiction can have extremely harmful consequences. It can deteriorate one’s ability to function normally in society and affect them physically and mentally. It can cause various types of disorders and problems. Here are some examples of the same.

Mental Health

Constant use of the Internet reduces the brain’s capacity to grasp and understand new things. It drastically affects one’s attention span. The addicts have a continual desire to get back on the screen and surf regardless of what work is pending. It affects productivity and can cause behavioral issues.

It can also induce mental disorders such as anxiety and depression. An excellent example of this is anxiety caused by doomscrolling. It can also cause paranoia.

Social well-being

As mentioned before, individuals spend more time online than offline, which hampers social skills growth. Individuals no longer know how to interact and function normally in society. And the lack of such skills results in more avoidance, which furthers the problem and does nothing to solve it. It can lead to a feeling of isolation and even depression.

Physical Health

When all of a person’s time is spent on the Internet, and no time is spent walking around and going out, they develop an unhealthy sedentary lifestyle. This can cause obesity and cardiac issues. They can even become overweight, putting them at risk for stroke, diabetes, and such illnesses.

Withdrawal Symptoms

An obvious indication that spending time on the Internet is becoming an addiction is withdrawal symptoms. Individuals begin to feel restless, angry, and irritated when offline. The Internet becomes a crutch that they cannot live without. This causes stress and anxiety, and the emotional outburst caused by not accessing the Internet can be disturbing. It can be harmful to people around as there have been incidents where people had murdered family members when the internet connection was cut off.

Internet Addiction Essay Conclusion

People must be careful not to let internet usage get this bad and get help if it does develop into an addiction. It should not be taken lightly, and we must be careful so that we can lead healthy lives.

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• Published: 20 February 2024

Risks and protection: a qualitative study on the factors for internet addiction among elderly residents in Southwest China communities

• Dan Wang 1 ,
• Xinyi Liu 1 ,
• Kun Chen 1 ,
• Chunyan Gu 2 ,
• Hongyan Zhao 3 ,
• Yong Zhang 2 &

BMC Public Health volume  24 , Article number:  531 ( 2024 ) Cite this article

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Metrics details

In the global trend of actively promoting the participation of older adults in the digital age, the relevant negative issues featuring potential Internet Addiction (IA) among them has risen to be a new challenge facing the global public health. However, there is a severe lack of related research. This study aimed to gain a comprehensive understanding of the phenomenon and process of IA among the elderly. The purpose of this paper is to introduce factors that may influence IA in the demographic.

This study employed qualitative descriptive research methods to investigate older adults’ perceptions and experiences of IA. Semi-structured in-depth personal interviews were conducted between March and June 2023 with 36 senior citizens from urban communities in Chongqing, Southwest China. Data were analyzed via inductive content analysis methods.

Through data analysis, 2 main categories concerning IA in older adults were identified: risk factors and protective factors. The risk factor categories include 5 individual factors (e.g., Internet as the major avenue for pursuing personal hobbies and interests, etc.), 3 family factors (e.g., household WIFI increasing the risk of prolonged Internet use indoors, etc.), 2 peer factors (e.g., peer recommendation and guidance as catalysts for intensified Internet engagement, etc.), 2 socio-environmental factors (e.g., the widespread daily Internet use spurs offline intolerance, etc.), and 3 Internet platform factors (e.g., the plenitude of online content triggers endless viewing/browsing behaviors, etc.). The category of protective factors encompasses 2 individual factors (e.g., a higher level of perceived risk regarding internet health hazards, etc.) and 2 family factors (e.g., more family commitment, etc.).

Conclusions

Older adults’ Internet addictive behaviors are shaped by multiple and complex internal and external factors. A higher level of online health risk perception is a key protective factor to effectively avoid the occurrence and deterioration of IA among the aged, a distinct finding from this study. It is believed that the “individual-family-peer-community” synergy strategy is expected to become an essential direction for IA intervention for older adults, in order to promote healthy Internet use among older adults.

Peer Review reports

The convergence of digitization and aging has become an important trend in the current international community. Internet usage among older adults has increased dramatically in recent years. For example, the internet usage rate among elderly individuals in the United States has risen from 12% in 2000 to 77.5% in 2018 [ 1 ]. Similarly, in Switzerland, it has also climbed from 10% in 2000 to 73% in 2017 [ 1 ]. In China, one of Internet giants with the largest number of Internet users in Asia and the world, the Internet use by seniors aged 60 and above has reached nearly 160 million by the end of 2022 [ 2 , 3 ]. Against this backdrop, the potential negative problems related to IA among the elderly are also gradually posing a looming threat to global public health [ 4 ].

Consensus on the terminology and definitions related to IA has yet to be reached internationally. Concepts such as “Problematic Internet Use,” “Pathological Internet Use,” “Internet Use Disorders,” and “Excessive Internet Use” differ in their emphasis [ 5 ]. For instance, some scholars emphasize the negative consequences or harm resulting from internet usage when defining IA [ 6 , 7 ], whereas other researchers highlight key behavioral characteristics of IA such as withdrawal symptoms, tolerance, and impulse control disorders [ 8 , 9 ]. This study preliminarily delineates the concept of IA by integrating these various focuses: the negative impact on physical, psychological, and social aspects due to internet usage; or an inability to disengage from the internet or discomfort when away from it (withdrawal symptoms); or a need for increasingly more time spent online to satisfy the urge (tolerance); or an inability to resist the impulse to use the internet, despite the severe personal consequences that may ensue (impulse control disorders). Furthermore, in tandem with a more measured and controlled engagement with the internet, a broader segment of the populace might encounter adverse or problematic effects [ 10 ], suggesting an increasing normalization and prevalence of IA across individuals [ 11 ].

Recent systematic reviews and meta-analyses indicate that the overall prevalence rate of IA amongst the general population, predominately composed of adolescents, university students, healthcare professionals, and medical students, is approximately 14% [ 12 ]. Although there is a current lack of reported prevalence rates specifically pertaining to the elderly demographic, the emerging issues of IA among the cohort have been reported by several countries in recent years [ 1 , 13 , 14 , 15 , 16 ], and shown to be associated with various negative health outcomes, such as lower levels of well-being, feelings of loneliness, depression, anxiety, psychological distress, social isolation, reduced social support, impaired sleep, and compromised daily functioning [ 1 , 17 , 18 , 19 , 20 , 21 ]. Meanwhile, in Chinese society, there has been an endless influx of news reports regarding the detrimental effects of elderly addicted to the internet, including compromised physical health, disrupted daily routines, distorted perception of online information, and falling victim to Internet scams. Additionally, the South Korean government has recognized older adults as a high-risk and potentially risky group associated with smartphone addiction in 2019 [ 18 ]. That being said, the necessity and urgency of conducting research on IA among older adults require no further explanation.

However, existing research on IA has predominantly focused on younger populations such as children and adolescents, leaving a significant gap in our understanding of IA among older adults. Limited research on IA among older adults has been scattered across various factors influencing IA [ 13 , 18 , 20 , 22 ]. Additionally, these studies have primarily used assessment tools designed for younger generations, which may not accurately reflect the characteristics and levels of IA among older adults. Unlike younger generations who grew up in the digital age, older adults experienced the advent of the digital era in adulthood, resulting in different patterns of digital use. For example, the high usage rates of smartphones among older adults cannot be directly compared to those of younger populations [ 23 ]. This highlights the need for specifical research focused on IA among older adults.

Previous studies have primarily focused on exploring the association between IA and personality traits, as well as the psychological factors involved [ 24 ]. These personality traits include low self-esteem, impulsivity, and neuroticism, while negative emotions such as depression, anxiety, loneliness, and escapism have also been examined. Additionally, comorbidities with mental disorders, such as attention-deficit/hyperactivity disorder (ADHD), suicidal or self-harm tendencies, risky behaviors, and eating disorders, have been investigated in relation to IA [ 24 ]. In addition, other risk factors include socio-environmental dimensions like problematic peer relationships, poor parental relationships, and family functioning [ 25 ]. In comparison, research on protective factors for IA is very limited. A recent scoping review identified three elements to prevent or mitigate IA, namely social support, level of engagement, and Internet self-efficacy [ 26 ]. However, currently, there is still a lack of clarity regarding the factors associated with IA among the elderly population.

Qualitative research plays a crucial role in describing addictive phenomena, identifying the process of addiction, and elucidating the perspectives of individuals with addiction [ 27 ]. Therefore, the objective of this research was to explore the phenomenon and process of IA among the elderly. This study generated content related to the influencing factors, behavioral characteristics, attitudes, and suggestions for improvement strategy associated with the phenomenon. However, the primary objective of this paper is to elucidate the factors influencing IA among older adults. This will provide a better understanding of IA behaviors among the elderly and serve as a foundation and reference for government authorities and professionals in developing scientifically sound assessment and intervention strategies for IA in the elderly population.

This research adopted a qualitative descriptive design, appropriate for elucidating the complexities of participants’ experiential narratives and for delving into the myriad factors associated with specific phenomena, and has been widely used in the fields of health care and nursing [ 28 ]. The study employed one-on-one semi-structured in-depth interviews and adhered to the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist [ 29 ].

Participants

This study employed a purposive sampling technique to identify and select participants who met the inclusion criteria. Purposive sampling allows for the inclusion of participants with diverse characteristics such as gender, education, and age, facilitating a comprehensive understanding and obtaining rich data [ 28 ]. The study primarily recruited Internet users among the elderly from the Shuangbei community, which is situated in the city center of Chongqing, the largest municipality in Southwest China. The internet penetration rate in Chongqing Municipality has exceeded 70%, which is comparable to the national average [ 30 ]. And as of the year 2020, the population aged 65 years and above accounted for 17.08% of the total population, which is higher than the average level of 13.5% in China [ 31 ]. The Shuangbei Community Health Service Center served as our educational collaborative community for this study. Prior to conducting interviews, the researchers contacted the person in charge at the community health service center and obtained their informed consent. The research plan and recruitment posters were provided to the individuals concerned to recruit sufficient participants. The inclusion criteria for the research participants were as follows: residents of the main urban area of Chongqing for at least 1 year, aged 60 years or older; engaged in various forms of Internet activities using internet-related devices such as smartphones, desktops/laptops, tablets, and internet-enabled televisions for a duration of at least 6 months; and willing to voluntarily participate in this study after giving informed consent. The exclusion criteria included: suffering from severe physical illnesses or being in an acute phase of illness; severe mental or psychological disorders; difficulty or lack of lucidity in language expression, or hearing impairment; and withdrawal from the study before completion.

Data collection

Recruitment of participants and data collection were conducted from March to June in 2023. A semi-structured interview guide was designed and revised based on literature review, group discussions, and pre-interviews. The respondents were asked questions regarding the following areas: basic information about their Internet usage; their experiences and perceptions of using the internet; and their understanding of IA among older adults. (See more details in Table  1 )

The interviews were conducted by a female doctoral student who had received training in qualitative research and refrained from providing any personal information to the participants. Consensus on the definition of IA used in this study was established with the participants prior to the interviews. Each face-to-face interview lasted approximately 30 to 60 min and took place in private and comfortable environments, such as the office of the community health service center or the participants’ homes, with only the interviewer and the interviewee present. With the informed consent of the participants, the interviews were audio-recorded synchronously with a mobile phone and voice recorder. The interviewer also performed field observations and documented non-verbal cues such as facial expressions, emotions, and body language exhibited by the interviewees to ensure the accuracy and reliability of the data. The number of participants in the study was determined based on the point of information saturation, which implies that interviews concluded when no new insights or perspectives regarding the interview topic and questions were obtained [ 32 ]. Data saturation was achieved in this study after interviewing the 36th participant. To confirm saturation and establish an adequate sample size, an additional two interviews were conducted, which corroborated that no new information was forthcoming. Consequently, the study proceeded with data analysis using a sample of 36 participants.

Data analysis

Within 48 h after each interview, the audio recordings were manually transcribed into text. The transcriptions were then cross-referenced and supplemented with field notes and verification from the interviewees. Inductive content analysis was employed for data analysis in this study, a method especially suitable for exploratory research that does not aim to test theory [ 33 ]. The data analysis process consisted of four major stages [ 33 ]: (1) Sense of Whole, where four researchers (DW, XL, KC, YZ) read the interview data repeatedly to become thoroughly familiar with the overall content. (2) Open Coding, where two researchers (DW, XL) independently read the written material and recorded as many headings as necessary in the margins to describe all aspects of the content, generating categories freely at this stage. (3) Category Creation, where similar or related codes were compared and categorized, forming sub-categories. (4) Abstraction, which involved combining the sub-categories with similar contents into generic categories, such as individual, family, and peer factors, etc., which were subsequently combined into two main categories: risk and protective factors for IA in older adults. The resulting categories and corresponding quotes were independently translated into English by two bilingual researchers. Any discrepancies were discussed and resolved with the other bilingual researcher.

Validity and reliability

This study employed various measures to enhance the credibility, transferability, dependability, and confirmability of the research. Firstly, all four researchers had received training in qualitative research methodologies during their university education and possessed experience in conducting interviews. They actively participated in the process of data analysis and interpretation. Secondly, in the interviews, the researchers thoroughly explained the research purpose to the participants and established rapport, aiming to obtain their full comprehension and trust. Thirdly, regular research team meetings were held to address any discrepancies arising from the data analysis process, until a consensus was reached on the main categories, generic categories, sub-categories, and corresponding quotes (representative statements from the interviewees). Lastly, to validate the authenticity of the findings, the researchers conducted discussions and cross-checks with the participants, comparing the interview data and results collected.

This study included interviews with a total of 36 elderly individuals, comprising 15 male participants (41.67%) and 21 female participants (58.33%). The average age among them was 68.64 years, ranging from 60 to 82 years. Among the participants, 26 had various chronic diseases, including coronary heart disease, diabetes, hypertension, cataracts, emphysema, etc. However, these conditions did not affect their cognitive abilities. The main online activities engaged by the participants included following online news, watching or creating short videos, online shopping, searching for health-related information, chatting and sharing on WeChat, online payments, mobile banking, reading online novels, playing online games (such as card and board games or Match & Eliminate game), and stock trading. The specific demographic information can be seen in Table  2 .

The study extracted two main categories related to IA among elderly individuals: risk factors (including individual, family, peer, socio-environmental, and online platform factors) and protective factors (including individual and family factors). Please refer to Table  3 for a detailed analysis of the categories.

Main category 1 - risk factors for IA in older adults

The respondents shared their experiences and feelings about their IA, as well as their understanding and perspectives on the causes of IA. Based on this, we conducted a deductive analysis and identified potential factors contributing to IA across five dimensions: individual, family, peer, social environment, and online platform.

Individual factors

Internet as the major avenue for pursuing personal hobbies and interests.

The Internet provides older individuals with better avenues and platforms to expand and fulfill their personal interests and hobbies. They engage in maintaining and developing their interests and hobbies through various online platforms such as social media and Douyin (a popular Chinese video-sharing platform, also known as Tik Tok). It is considered that this may also increase the risk of long-term addiction to the internet.

N17: “I enjoy staying active in the WeChat group of our dance troupe on my smartphone, where we share information and updates. I also spend time watching dance videos on Douyin, as dance performance is my passion. It’s something I can’t seem to get enough of and engage in throughout the day.”

Excessive reliance on the pleasure and enjoyment derived from internet use

Elderly individuals express a deep love for the online world. They thoroughly enjoy the pleasure that comes with being online and may even consider it as a manifestation of the meaning of life. This excessive enjoyment of being online can easily lead to excessive Internet use.

N06: “I enjoy being online as it provides me with a sense of enjoyment. I don’t care about any drawbacks; I’m gonna keep enjoying being online! It’s what gives my life meaning, you know!”

Utilization of the internet as the main pastime in an otherwise mundane life

The majority of respondents believe that, unlike the desire of young people for Internet use, IA among older adults tends to be more of a pastime in response to a mundane life.

N20: “Unlike addiction among young people, I believe that addiction among older adults is a result of boredom. The use of smartphones to pass the time serves as a form of escapism, providing a sense of liberation.”

Loneliness and psychological emptiness leading to overuse of the internet

Some elderly individuals, particularly those who live alone or have less involvement in family affairs, lack various avenues for communication and social interaction. As a result, they have more free time to utilize the Internet as a means to alleviate feelings of loneliness and spiritual emptiness.

N16: “Due to loneliness and a lack of alternative means of communication, some elderly individuals may feel reluctant to engage in social interaction out of fear of being misunderstood. As a result, they turn to using smartphones as a means to pass the time and alleviate their feelings of solitude.” (A solitary elderly individual responded.)

Habitual prolonged internet use during instances of poor sleep quality

Due to insomnia or early awakening, some elderly individuals tend to spend longer periods of time on the Internet during the night or early morning.

N08: “I usually spend the most time on my smartphone in the wee hours, from around 2 AM to 5 AM. That’s because I often struggle with sleep issues and tend to wake up during that time. Playing on my smartphone has become a common activity for me during those hours.”

Family factors

Household wifi increasing the risk of prolonged internet use indoors.

Most of the respondents expressed a preference for using the Internet in the comfort of their homes due to the availability of free wireless internet. Consequently, when outside, they opt for alternative forms of entertainment such as browsing or chatting, considering the limitations of mobile data usage. Some individuals even develop a habit of staying at home or instinctively going online whenever they are home, driven by the desire to access the internet.

N03: “On a daily basis, I find myself engrossed in using my smartphone at home where WiFi is readily available and free of charge. However, when I venture outdoors, I am cautious about utilizing mobile data as it tends to deplete rapidly. Consequently, instead of indulging in smartphone activities, I tend to prioritize engaging in conversations with others outside of my home.”

Spousal Internet activities used as justification for one’s own Internet usage

Many of the respondents, when describing their Internet usage patterns, also subconsciously mentioned their spouses, asserting that they often independently engage with their smartphones at home. Their tone and demeanor revealed a sense of psychological comfort derived from the fact that their partners also use the internet, which appears to justify their own online activities.

N11: “At home, my spouse and I each indulge in our own online games. He enjoys playing ‘Chaos Chambers’ (a specific online game), while I prefer ‘Match and Eliminate’ (another online game).”

N12: “At home, it’s just my spouse and me. Like everyone else, he is constantly attached to his smartphone. He’s even juggling two smartphones simultaneously!”

Negative family dynamics leading to a predominantly Internet-centered lifestyle

Elderly individuals exhibiting clear signs of IA often express that their children rarely visit them. Furthermore, they maintain a long-standing marital pattern of sleeping in separate rooms and avoiding interference in each other’s lives. Communication and interaction are minimal, making Internet usage a significant source of companionship in their lives.

N06: “The children visit home only after long intervals, and my spouse and I have very little communication. We each indulge in our own smartphones, even after dinner. He sleeps in one room, and I sleep in another. It has been this way for more than a decade or two.”

Peer factors

Peer recommendation and guidance as catalysts for intensified internet engagement.

Respondents indicated that they were introduced to and learned some online activities by their peers and gradually became addicted to them in the process of using them.

N01: “A good friend of mine, whom I have been friends with for many years, added me to a WeChat group where they sell products through live streaming. As a result, I find myself completely absorbed in watching these live streams every day.”

N02: “It was not my family who taught me, but my peers who showed me how to use smartphones and shop online. I usually spend my time on platforms like WeChat and Douyin, and the more I watch, the more interesting it becomes. However, this extensive screen time has resulted in my vision deteriorating and developing myopia.”

Approval from peers regarding proficiency in Internet usage

Some respondents expressed that even though they spend a significant amount of time and effort online, engaging in activities they enjoy and find valuable, receiving recognition from friends boosts their confidence in continuing to use the Internet and improving their online skills.

N27: “I believe I might be developing an addiction to the internet, primarily due to my involvement in tasks such as photo editing, video editing, and posting on TikTok. When I share these online activities with my friends, they seem to appreciate them. This makes me feel somewhat different from others and suggests that I might have room for improvement, even if it may simultaneously have some negative impacts on me.”

Socio-environmental factors

The widespread daily internet use spurs offline intolerance.

Some respondents expressed that smartphones and the Internet have become essential tools in modern society. They have become so reliant on their smartphones that they cannot imagine being without them, and the thought of losing their smartphone and the associated access to the Internet is difficult to accept.

N30: “Smartphones have taken the top priority in our lives. Without a smartphone, it feels like entering a “no man’s land”—a lifestyle that no one would rather prefer to be! We have become so accustomed to having smartphones that if they were suddenly taken away from us, it would be worse than losing our lives, and uncomfortable to go about our daily lives.”

Internet’s facilitation of social interaction raises dependency risks

The internet breaks through spatial barriers and helps older people establish broader relationship networks and expand their social circles, holding a significant position in their lives. This may result in the elderly becoming overly reliant on online socialization, thereby neglecting face-to-face interactions offline.

N18: Smartphones are quite important for me. I can’t seem to get enough of it! Through platforms like Douyin, I have been able to reconnect with classmates whom I haven’t seen in decades. I have also made new friends. Those who share the interest of using Douyin have become close companions, almost like sisters. Without smartphones, we would have gone our separate ways and lost contact with each other after all these years.

Internet platform factors

The plenitude of online content triggers endless viewing/browsing behaviors.

The rich and diverse content available on the internet can cater to the various needs of older people, to the extent that they may find it difficult to disengage from spending extended periods of time online.

N17: “I feel that online content is incredibly abundant! That’s why I carry a smartphone with me every day. I can’t stay disconnected even if it’s just for an hour.”

Incentive mechanisms of online platforms

Some online software or activities use incentives such as economic rewards, preference identification, and personalized recommendations to encourage older adults to engage in relevant online activities, which may lead to addiction.

N27: “My friends say that they see a few videos I post on Douyin every day because the app sends me timely reminders to upload content. Perhaps because I post frequently, I receive two reminders every day.”

Internet activities associated with addiction risks

During this interview, it was found that activities that can potentially lead older adults to become addicted to the internet primarily include participating in online live streaming WeChat groups, being enthusiastic about inexpensive online shopping, and having a preference for online novels. Additionally, some respondents raised concerns about the risks of addiction to online gaming and gambling. Below are a few representative examples:

N03: “I have a daily habit of buying discounted and reduced-price items on Douyin and Pinduoduo. For my strong addiction to shopping, my spouse scolds me, saying that I buy too much for the house!”

N27: “I used to be addicted to the internet mainly because of reading novels. Sometimes I would feel that videos strain my eyes, but I would wipe away my tears (from eyestrain) and continue watching. I would stay up until two or three in the morning, and even when I lay down in bed, my mind would still be consumed by thoughts of novels. The next morning, I would immediately pick up where I left off. As a result, my spouse and I would bicker over it at home.”

Main category 2 - protective factors for IA in older adults

The interviewee discussed their reasons for not getting addicted to the internet and how they made a determined effort to improve addictive behavior after realizing its negative impact. Based on this, we can deduce and analyze the potential protective factors against IA among older adults, which primarily encompass two levels: personal and familial factors.

A higher level of perceived risk regarding internet health hazards

The majority of the respondents expressed that due to their prioritization of personal health, they consciously avoided excessive internet usage. Moreover, upon experiencing health risks associated with internet usage, they exhibited determination to engage in self-improvement. Their commitment to maintaining good health triumphed over their desire for internet use.

N12: “Since I developed cervical spondylosis and experienced the pain, I have been able to rein in internet usage.”

N24: “There is no need to indulge in the internet every day. Life is rich and colorful, beyond just smartphones. Health is undoubtedly important, as it belongs solely to oneself.”

A stronger sense of self-control

Some older adults believed that their ability to avoid addiction stemmed from possessing a stronger sense of self-discipline. Moreover, they were able to quickly implement self-control measures upon experiencing negative consequences of IA.

N24: “I am not addicted since I have strong self-discipline. Most people cannot stick to the routine of going to bed at 10 PM and waking up at 7 AM, but I have consistently adhered to this schedule for several years.”

N25: “I have a strong determination. For instance, if I stayed up until midnight using my smartphone yesterday, I make it a point to limit my usage to no later than 10 PM or 10:30 PM today. I firmly decide to turn off my phone and prioritize rest in order to avoid any disruption to my sleep.”

More family commitment

Some respondents indicated that their tight schedules involving numerous family responsibilities provided them with limited opportunities and circumstances for becoming addicted to the internet. Moreover, they possessed a strong sense of familial duty, often exercising self-restraint in order to prioritize completing their family obligations over excessive internet usage.

N22: “Many factors prevent me from getting addicted because I believe in being responsible for my family. I consider addiction to be a dull and immature behavior.”

Supervision and influence in multigenerational households

Family members’ reminders can assist elderly individuals in recognizing their harmful internet usage habits and behavior. This is especially true for older people living in multigenerational households who are concerned about how their internet activities may impact their grandchildren’s academic performance or serve as negative behavioral examples. As a result, they impose constraints on their own internet usage.

N17: “My family members often remind me not to use my mobile phone excessively, especially in the evenings. Moreover, my grandson keeps an eye on my activities as well.”

N22: “At our current stage in life, which primarily revolves around taking care of our grandchildren, I realize that excessive phone use is not beneficial for them. Therefore, I now exercise control over my smartphone usage and refrain from excessive indulgence.”

For all the substantial research on IA among young people, qualitative research in this area is limited. Furthermore, to our knowledge, there is currently no qualitative research specifically focused on IA among the elderly population. The primary objective of this research was to comprehensively understand the phenomenon and process of IA among the elderly by examining their perceptions and understanding of this burgeoning issue. This article aims to elucidate the factors of IA in the elderly. The findings of this study comprehensively elucidate the potential risk factors and protective factors associated with IA among the elderly, at various levels including individual, familial, peer, social, and online platform perspectives.

Risk factors for IA in older adults

At the individual level, this study reveals that most older individuals with addictive tendencies enjoy using the internet because it allows them to explore and engage with content that aligns with their interests and hobbies. This finding is similar to a survey on IA among college students, where they identified the main purpose of internet usage as “fulfilling hobbies or specific needs” [ 34 ]. Internet services provide opportunities for older individuals to pursue an active and independent lifestyle, especially with the accessibility and affordability of user-friendly electronic applications and devices such as smartphones and tablets, which further broaden their engagement in online activities [ 35 ].

Additionally, some older individuals expressed a strong fondness for the internet and thoroughly enjoyed the pleasure it brings. This phenomenon may embody the psychological construct of flow experience [ 36 ], implying that profound enjoyment could potentially evolve into compulsive and/or addictive behaviors [ 37 , 38 ]. However, compared to the fluctuating emotional experiences of enjoyment and pleasure, most participants mentioned that their motivation and experience of internet usage were more inclined towards leisurely pastimes in their daily mundane lives. This is consistent with the findings of other studies on younger demographics, including adolescents and college students [ 11 , 39 , 40 ]. With more leisure time, older individuals have access to vast resources on social media and other online platforms to seek entertainment and pass the time [ 41 ], helping them cope with or alleviate feelings of boredom. Furthermore, this study also demonstrates that loneliness is a potential cause of IA among older individuals, which aligns with other findings [ 17 , 42 , 43 ]. Due to reduced physical functioning and weakened social networks, older individuals are more susceptible to experiencing negative emotions such as loneliness [ 17 ], making them inclined to seek social interactions or entertainment through the internet to alleviate their loneliness.

Apart from emotional factors, the majority of the participants reported using the internet during sleep disturbances (insomnia or early awakening), leading to prolonged nighttime internet usage. This aligns with the limited existing research showing that sleep problems are predictors of IA [ 44 , 45 ]. Additionally, a large-scale survey among older individuals confirmed a link between pre-sleep electronic device use and poor sleep quality [ 15 ]. Considering that older individuals are more likely to experience sleep disturbances or related disorders, many of them may choose to use the internet to fill the time when they struggle to fall asleep, but this, in turn, can exacerbate their sleep problems.

This finding suggested that the IA behavior of older adults is influenced by their spouse’s internet usage. Similarly, recent research has found that parental IA is a significant predictor of adolescent IA [ 46 , 47 ]. Similar to the role parents play in the lives of adolescents, spouses also play a crucial role in the lives of older adults. Therefore, the spouse’s internet usage issues can explain the relevant problems among older adults. This study also found that problematic family relationships could be a risk factor for IA among older adults, which is consistent with most other studies [ 47 , 48 , 49 , 50 ]. Additionally, this study revealed a new finding that goes beyond traditional research results, suggesting that having a WiFi-covered home environment may increase the risk of IA among older adults. Due to their tendency to be frugal, older adults perceive internet usage at home as more cost-effective and convenient, while being concerned about data usage costs outside. Within the permissible boundaries of both physiological and psychological health conditions, prompting older adults to eschew extended periods of domestic confinement and to engage suitably in extramural social events, as well as other indoor activities, may serve as an efficacious strategy for the prevention of IA within this demographic group.

Previous studies have primarily explored the relationship between negative peer relationships, such as deviant peer associations [ 51 ], peer bullying [ 52 ], and peer pressure [ 53 ], and IA. In contrast, this study proposes that the interest sparked in older adults through peer recommendations and guided learning of the internet may be a potential contributing factor to IA, highlighting the role of “positive peer relationships” in the process of internet use. We attribute this positive peer relationship effect among older adults to the explanation of the “collective clustering phenomenon,” where individuals with IA are more likely to communicate with like-minded individuals and may influence their friends in daily life to become internet-dependent [ 54 ]. Additionally, as “digital immigrants” who did not grow up in the internet era, older adults generally face digital skill deficiencies. Older adults who are relatively proficient in internet usage may be more susceptible to peer praise, leading to a sense of “digital superiority” and potentially disregarding negative consequences in their continued internet use, which may ultimately contribute to IA.

Participants expressed the significant role that smartphones, as the primary tool for internet use, play in their social lives. On one hand, smartphones have become a necessity that provides convenience in daily life to the extent that participants feel they cannot be without internet access. On the other hand, smartphones offer older adults easier and broader access to online socialization. This phenomenon is closely tied to the widespread adoption of smartphones globally, as they surpass other information and communication technology devices (including desktop computers, laptops, and tablets, etc.) in terms of portability, immediacy, and convenience [ 55 , 56 ]. Consequently, smartphones have become the primary medium for accessing the internet and an integral component of contemporary life [ 55 ]. The increasing use of smartphones among the elderly is emerging as a common trend [ 57 ]. Diminished social roles and the deterioration of offline relationships may lead to greater reliance on smartphones among the older population, potentially resulting in addiction to these devices [ 55 ]. This bears many similarities to IA and promises to become a social issue of concern [ 55 ]. Furthermore, it is believed that this trend to some extent reflects the prevalent modern phenomenon known as “nomophobia,” which refers to the concern or fear of being unable to use or connect with others through smartphones [ 58 ]. As evidenced by participants using statements like “not having a smartphone is worse than losing one’s life” to describe the importance of smartphones to them. Of course, our research mainly reflects the attitude tendencies of older adults towards nomophobia. However, as older adults increasingly adopt and become proficient in using smartphones, their emotional gain from smartphones may increase, thereby increasing the risk of nomophobia [ 23 ]. Therefore, future research should specifically examine the characteristics related to nomophobia among older adults to obtain a more accurate analysis of the causes of IA in this cohort.

The majority of participants indicated that the abundant content available on the internet meets their diverse needs to such an extent that they find it difficult to stop using the internet even after prolonged periods, which is a major cause of IA. Moreover, online platforms incentivize older adults to continuously engage in related online activities, thereby leading to addiction. These findings are consistent with the findings of other studies explaining IA from a technical level [ 38 , 59 ]. Online platforms, particularly short video platforms, with their user-friendly interfaces, captivating content, the opportunities for interaction with content creators and more precise and personalized content recommendations are likely to fully immerse elderly users and contribute to their endless consumption of online content [ 38 , 59 ]. Additionally, future research should focus on the various subtypes of IA among the elderly, including health-related live streaming WeChat groups, online shopping, reading online novels, internet gaming and gambling.

Protective factors for IA in older adults

The study obtained surprising and unique findings, which revealed that a higher level of perceived health risks associated with internet use may be more conducive to prevent or mitigate IA among elderly individuals. To the best of our knowledge, previous research has not explored the association between IA and the perception of health risks. However, a substantial body of evidence suggests that lower perception of smoking-related health risks is associated with higher initiation rates, longer duration of smoking, and fewer attempts to quit smoking [ 60 , 61 , 62 , 63 ]. Conversely, higher health risk cognition promotes the initiation or maintenance of positive health behaviors or the avoidance of negative health behaviors [ 64 ]. Kim et al. further confirmed that younger individuals are more prone to underestimating health risks [ 65 ]. Reasonable risk perception may increase with maturity due to increased exposure to health issues [ 66 ]. Based on these perspectives, we can hypothesize that elderly individuals, who have experienced more health problems, are more concerned about their physical well-being and are more likely to perceive the health risks associated with internet use or the negative health consequences of IA. However, this assumption is contingent upon elderly individuals understanding IA and being accurately aware of its negative consequences. Therefore, actively promoting health education related to IA can help elderly individuals enhance their awareness of the health risks associated with the internet, thereby preventing IA or prompting those inclined towards or experiencing IA to take timely measures.

However, merely being aware of the dangers of IA is not sufficient to avoid problematic internet use, individuals must also possess self-control. This finding is consistent with the majority of other studies [ 23 , 42 , 59 , 67 , 68 ]. Users with higher self-control are capable of avoiding or regulating the extent of their engagement in internet addiction-related behaviors. Elderly individuals generally exhibit higher levels of self-control [ 23 ], making them more likely to resist the urge to excessively use the internet or less likely to experience impulses or cravings related to the internet [ 42 ].

Our research indicates that elderly individuals who have more family commitment are less prone to develop IA or are better able to control their addictive behaviors. This finding has not been previously reported in existing studies. However, this phenomenon can be understood and speculated from the perspective of “time management”. We believe that elderly individuals with higher levels of involvement in family affairs have less leisure time available, as they spend their days engaged in fulfilling activities without the need to rely on internet usage for time-passing purposes. Conversely, increased availability of leisure time and its inadequate management may contribute to excessive internet use [ 69 , 70 ]. For elderly individuals, the increase in available time for internet usage, combined with their heightened sense of family responsibility, fosters a situation in which family members may actively engage in the development of suitable plans for familial matters. Such collaboration can be tailored to correspond with the preferences of the elderly, thus aiding in the enrichment of their quality of life and augmenting their perceived sense of worth.

Another protective factor is the supervision and influence of family members on the internet usage of elderly individuals. Consistent with previous research, certain studies have demonstrated the positive protective effect of parental involvement in family supervision against IA among children and adolescents [ 42 ]. However, this study emphasizes the significant role of multigenerational cohabitation in the family environment in preventing excessive internet use among elderly individuals. Specifically, elderly individuals, due to concerns about their online behaviors negatively influencing and demonstrating poor online conduct to their grandchildren, proactively restrict their own internet usage. Additionally, the supervision from grandchildren tends to be more effective in encouraging them to prevent or address their own problematic internet use, compared to the advice from their immediate children. This suggests that providing intergenerational support in a multigenerational cohabitation family environment may serve as an important strategy for preventing and intervening in IA among elderly individuals.

Strengths and limitations

The potential misuse of the internet and the issue of IA among elderly individuals is becoming a new challenge for global public health. To the best of our knowledge, this is the first qualitative study specifically focusing on IA among the elderly population. This approach allows for a more authentic and comprehensive understanding of the existing issues related to internet use among the elderly and provides insights into the phenomenon of IA in this cohort. Moreover, it is aimed to raise awareness among elderly individuals about this emerging issue and promote healthy internet use through this study. Furthermore, the factors of IA among the elderly in detail from both risk and protective perspectives have been examined. Previous research has mainly focused on triggers and negative consequences.

However, this study has certain limitations. Firstly, the study participants were elderly individuals from Chongqing, a municipality in southwestern China. Due to differences in socio-cultural and economic development, some findings may differ from other countries. Secondly, our study does not draw definitive conclusions regarding the identification of IA in the elderly population. Therefore, following the development of a scientifically validated assessment tool for elderly IA, further investigative research should be conducted on individuals who meet the IA assessment criteria. Furthermore, given that the prevalence of IA among participants included in this study may be relatively low, future research should aim to enhance and refine our understanding by ensuring a balanced representation of both IA and non-IA elderly individuals and facilitating comparative analysis of interview data. Thirdly, the scope of the survey was somewhat limited. Future studies should aim to expand research areas and emphasize enhancing the transferability of findings to populations with experiences not sufficiently captured in the present study. Despite these limitations, we believe that this study is valuable as it enhances our understanding of the emerging phenomenon of IA among the elderly.

This study employed a qualitative descriptive research approach to thoroughly investigate the factors associated with IA among elderly individuals. The behavior of IA in the elderly is influenced by multiple complex factors, including individuals, families, peers, social environments, and online platforms. One prominent innovative finding of this study is that having a higher level of perceived risk regarding internet health may be an important protective factor in effectively preventing and mitigating IA among the elderly. Additionally, strong self-control, more family commitment, and supervision and influence from multigenerational cohabitation households also play a preventive and buffering role in elderly individuals’ IA behavior. Based on these findings, it is well-justified that the “individual-family-peer-community” synergy strategy holds promise as an important direction for intervention in IA among elderly individuals. By implementing comprehensive prevention measures from multiple dimensions, we can effectively prevent the occurrence of IA among the elderly and promote healthy internet use.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

• Internet addiction

Attention-deficit/hyperactivity disorder

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Acknowledgements

We acknowledge those interviewees who participated in the study.

This research is funded by the Chongqing Natural Science Fund (Grant No. CSTB2023NSCQ-MSX0489).

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Study conception and design: YL. Data collection: DW, CG, HZ. Data analysis: DW, XL, KC, YZ.Drafting of the article: DW. Critical revision of the article: YL. The author(s) read and approved the final manuscript.

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Wang, D., Liu, X., Chen, K. et al. Risks and protection: a qualitative study on the factors for internet addiction among elderly residents in Southwest China communities. BMC Public Health 24 , 531 (2024). https://doi.org/10.1186/s12889-024-17980-6

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The food addiction clinical treatment (fact) manual: a harm reduction treatment approach.

1. Introduction

2. fact manual, 2.1. fact manual goals.

• To understand the symptoms of food addiction within a harm-reduction context;
• To identify individualized triggers (e.g., people, places, things, emotions, situations, etc.) that play a role in the consumption of high-risk hyperpalatable foods;
• To identify foods that are personally higher-risk and learn how to reduce harm of identified foods;
• To improve awareness of mindless eating patterns, cravings for high-risk foods, and how to employ mindful eating approaches to reduce harm;
• To gain skills related to: eating/preparing foods that are lower-risk for addictive processes, meal planning, coping with cravings for high-risk foods, and coping with negative emotions and stress without food
• To develop a personalized post-treatment plan, regarding high-risk processed and low-risk naturally occurring foods, that is either moderation or abstinence-based, depending on the participant ’s goals and preference

2.2. FACT Manual Session Structure

• Check-in and homework discussion: Individuals are invited to share their current emotional status and difficulties/successes they experienced related to food addiction since the last session. Homework from the past week is reviewed and participants are provided with feedback.
• Psychoeducation: Individuals are provided with research-informed weekly didactics related to food addiction and skill implementation for the treatment of addiction and disordered eating behaviors.
• Group or buddy exercises: Skills taught in each session are practiced with peers in the group or amongst the group as a whole.
• Homework assignment: Individuals are asked to complete weekly journaling exercises and handouts for continued skill development prior to the next treatment session.

2.3. FACT Manual Content

3. pilot study methods, 3.1. procedure, 3.1.1. recruitment and enrollment, 3.1.2. quantitative data, 3.1.3. qualitative data, 3.1.4. fact manual treatment approach, 4.1. participants, 4.2. qualitative data, 4.2.1. personalized, harm reduction treatment approach, 4.2.2. fact manual content: helpful content.

Through my years of addictive eating I had realized that sometimes my favorite (unhealthy foods) didn’t always live up to my expectations. I often thought, why am I eating this, it’s not worth the calories today. It was like I thought the next bite was going to be awesome and the way I remembered it. Food preparation (taste) is inconsistent. This brought it to the forefront and, hopefully, I’ll think it through more before indulging.

4.2.3. Weight Loss Goals

4.2.4. concurrent treatments, 4.2.5. expertise of clinician, 4.2.6. treatment tolerance and progress, 4.3. quantitative data, 5. discussion, 5.1. fact manual, 5.2. participant outcomes, 5.3. limitations and future directions, supplementary materials, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Share and Cite

O’Hea, E.L.; Edwards-Hampton, S.A.; Beall Brown, D.L.; Sonneville, K.R.; Ziedonis, D.M.; Gearhardt, A.N. The Food Addiction Clinical Treatment (FACT) Manual: A Harm Reduction Treatment Approach. Behav. Sci. 2024 , 14 , 557. https://doi.org/10.3390/bs14070557

O’Hea EL, Edwards-Hampton SA, Beall Brown DL, Sonneville KR, Ziedonis DM, Gearhardt AN. The Food Addiction Clinical Treatment (FACT) Manual: A Harm Reduction Treatment Approach. Behavioral Sciences . 2024; 14(7):557. https://doi.org/10.3390/bs14070557

O’Hea, Erin L., Shenelle A. Edwards-Hampton, Dana L. Beall Brown, Kendrin R. Sonneville, Douglas M. Ziedonis, and Ashley N. Gearhardt. 2024. "The Food Addiction Clinical Treatment (FACT) Manual: A Harm Reduction Treatment Approach" Behavioral Sciences 14, no. 7: 557. https://doi.org/10.3390/bs14070557

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• J Behav Addict
• v.5(4); 2016 Dec 1

Prevention of Internet addiction: A systematic review

Petra vondráčková.

1 Department of Addictology, First Faculty of Medicine, Charles University in Prague, and General University Hospital in Prague, Prague, Czech Republic

Roman Gabrhelík

Background and aims.

Out of a large number of studies on Internet addiction, only a few have been published on the prevention of Internet addiction. The aim of this study is provide a systematic review of scientific articles regarding the prevention of Internet addiction and to identify the relevant topics published in this area of interest.

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were adopted. The EBSCO, ProQuest Central, and PubMed databases were searched for texts published in English and Spanish between January 1995 and April 2016. A total of 179 original texts were obtained. After de-duplication and topic-relevance review, 108 texts were systematically classified and subjected to descriptive analysis and subsequent content analysis.

The results of the content analysis yielded the following thematic areas: (a) target groups, (b) the improvement of specific skills, (c) program characteristics, and (d) environmental interventions.

Discussion and conclusion

Literature on the prevention of Internet addiction is scarce. There is an urgent need to introduce and implement new interventions for different at-risk populations, conduct well-designed research, and publish data on the effectiveness of these interventions. Developing prevention interventions should primarily target children and adolescents at risk of Internet addiction but also parents, teachers, peers, and others who are part of the formative environment of children and adolescents at risk of Internet addiction. Newly designed interventions focused on Internet addiction should be rigorously evaluated and the results published.

Introduction

Internet addiction can be defined as overuse of the Internet leading to impairment of an individual’s psychological state (both mental and emotional), as well as their scholastic or occupational and social interactions ( Beard & Wolf, 2001 ). Since its emergence in the scientific literature, this phenomenon has been accompanied by controversy concerning its definition and conceptualization. There is considerable discussion as to whether people are addicted to the Internet itself or on the Internet, specifically to the activities realized in the Internet environment, and whether to use the term Internet addiction or addictions to specific online activities such as online gambling, online gaming, or cybersex addiction ( Davis, 2001 ; Griffiths, Kuss, Billieux, & Pontes, 2016 ; Pontes, Kuss, & Griffiths, 2015 ; Starcevic, 2013 ). In this paper, we use the term Internet addiction to denote excessive use of the Internet and addictive behavior related to the Internet.

In studies using representative general population samples, the prevalence rates range from 1% in Germany ( Rumpf et al., 2014 ) to 3.4% in the Czech Republic ( Šmahel, Vondráčková, Blinka, & Godoy-Etcheverry, 2009 ). Internet addiction prevalence rates among adolescents tend to be the highest, ranging from 0.8% in Italy to 26.7% in Hong Kong ( Kuss, Griffiths, Karila, & Billieux, 2014 ). These numbers are rather indicative because Internet addiction rates vary according to which definitions of Internet addiction, assessment tool, and cut-off are used ( Douglas et al., 2008 ; Kuss, Griffiths, et al., 2014 ; Vondráčková, 2015 ; Vondráčková & Šmahel, 2015 ).

The attention of researchers has focused on the treatment of Internet addiction and some treatment studies have been published in recent years; however, the majority of them are of rather poor quality ( King, Delfabbro, Griffiths, & Gradisar, 2011 ). Very few studies report on the prevention of Internet addiction and this area has only recently started to receive more attention from researchers. Clinicians, educators, and policymakers agree that treatment strategies for tackling the Internet addiction problem need to be accompanied by prevention strategies that address risk factors before addiction evolves into a more serious form ( Kwon, 2011 ; Yu & Shek, 2013 ).

Prevention science represents a systematic transdisciplinary approach to the study of (a) etiology and epidemiology of various preventable health and social problems and (b) intervention and research designs, efficiency and effectiveness, implementation of effective interventions at the individual, social and societal systems of the family, education, workplace, community, in the areas of social welfare, planning, environment, urban design, and (fiscal) policy ( Gabrhelík, 2016 ; SPAN, 2015 ; SPR, n.d. ). This definition is framing the general scope of scientific approach to prevention that is further specified by other key terms and concepts (e.g., levels of prevention; universal, selective, indicated, early diagnostics and intervention; specific target groups; prevention models, etc.)

The objectives of this study were to review relevant literature on the prevention of Internet addiction published between January 1995 and April 2016 and to perform content analysis in order to identify relevant topics which are discussed in this context in the literature utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The unique contribution of this paper lies in the fact that this is, to the best of our knowledge, the first review focused on the prevention of Internet addiction.

A systematic search of research texts was conducted following the PRISMA recommendations ( Higgins & Green, 2011 ; Moher, Liberati, Tetzlaff, Altman, & The PRISMA Group, 2009 ). The protocol for this review was not previously registered.

Eligibility criteria

In this systematic review, all relevant papers having the prevention of Internet addiction as a main topic or as at least partially topic were included. Further criteria adopted were (a) publication between January 1995 and April 2016, (b) written in English or Spanish language, and (c) published as journal articles, book chapters, and original manuscripts. Additionally, the texts where prevention was only a general topic were excluded.

Information sources and search

Studies were identified by searching relevant papers via EBSCO, ProQuest Central, and PubMed databases, employing the following search terms: “prevent*,” “interven*,” “program*,” “parent*,” “school*,” “family*,” “peer*,” “communit*” in combination with “Internet addiction,” “gaming addiction,” “online gambling,” “cybersex addiction,” “online sex addiction,” “Internet sex addiction,” “Facebook addiction,” “social network addiction,” “compulsive Internet use,” “excessive Internet use,” “problem Internet use,” and “pathological Internet use.”

Selection and data collection process

Using the above criteria, a total of 179 original texts (see Figure  1 ) were obtained. After de-duplication and topic-relevance review of all the abstracts, 145 texts were selected for further analysis. Finally, the texts where prevention was only a general topic were excluded. The remaining 108 texts were further systematically classified and subjected to descriptive analysis. The texts included in this study were divided into two categories. In the first category, we analyzed all of the 100 texts that had the prevention of Internet addiction as a partial topic. The majority of them focused on research in some areas of Internet addiction, for example, prevalence or correlates of Internet addiction ( Ang, Chong, Chye, & Huan, 2012 ; Huang et al., 2009 ; Park, Kim, & Cho, 2008 ). Typical recommendations regarding the prevention of Internet addiction were based on their specific results, such as “These findings emphasize the importance of prevention and early intervention work with early adolescents and their parents with respect to adolescent loneliness and generalized problematic Internet use ( Ang et al., 2012 ).” These were often part of the abstract, discussion, or conclusion sections. The remaining texts were reviews or theoretical papers, again with general recommendations for the prevention of Internet addiction. For the purpose of this study, we included these recommendations regarding Internet addiction prevention in the analysis.

The PRISMA flow diagram of the selection process

In the second category, we analyzed eight texts that had the prevention of Internet addiction as their main topic. Six of them (Table  1 ) described and/or evaluated specific prevention interventions ( Busch, de Leeuw, & Schrijvers, 2013 ; de Leeuw, de Bruijn, de Weert-van Oene, & Schrijvers, 2010 ; Korkmaz & Kiran-Esen, 2012 ; Shek, Ma, & Sun, 2011 ; Turel, Mouttapa, & Donato, 2015 ; Walther, Hanewinkel, & Morgenstern, 2014 ). For the purpose of the study, were extracted data relevant to these areas: (a) country in which were data collected, (b) key characteristics of the participants (sample size and segment of the population assessed), (c) intervention characteristic, (d) risk of bias in individual studies, and (e) methodological features (objectives, assessment methods, type of study, and design).

Texts describing prevention interventions

Note . CIUS: Compulsive Internet Use Scale; IUHS: Internet Use Habit Scale; IAS: Internet Addiction Scale; KFN-CSAS-II: Video Game Dependency Scale; n.a.: not available.

For assessing risk of bias was used the Cochrane Collaboration´s tool for assessing risk of bias ( Higgins & Green, 2011 ). The following risks of bias were observed: (a) selection bias (sequence generation and allocation sequence concealment), (b) performance bias (blinding of participants and personnel), (c) detection bias (blinding of outcome assessment), (d) attrition bias (incomplete outcome data), and (e) reporting bias (selective outcome reporting).

The subsequent content analysis of all texts was focused on the identification of relevant thematic areas and their content. One reviewer (PV) screened the titles/abstracts and analyzed the full texts of the identified texts.

This article does not contain any studies with human participants or animals performed by any of the authors.

On the basis of the content analysis of these 108 texts, we identified four basic areas of interest: (a) target groups, (b) the improvement of specific skills, (c) program characteristics, and (d) environmental interventions.

Target groups

The target groups in our texts are defined on the levels of (a) universal prevention and (b) selective and indicated prevention.

Universal prevention

On the level of universal prevention, we identified four main target groups for prevention interventions: (a) children and adolescents, (b) college students, (c) parents and those close to them, and (d) gambling employees and employees with regular access to the Internet.

The majority of researchers (e.g.,  Jang & Ji, 2012 ; Lan & Lee, 2013 ) are in agreement that preventive interventions should focus mainly on children and adolescents. Children and adolescents are in their formative years, when values and standards develop, and they have the highest prevalence rates of Internet addiction ( Šmahel et al., 2009 ). For this reason, prevention programs should be implemented in the school environment, especially in elementary school settings that are often on the front line of the identification of potentially life-threatening behaviors ( Jang & Ji, 2012 ; Lan & Lee, 2013 ). The South Korean government launched its plan for Internet addiction prevention and treatment with components starting with prevention interventions even with preschool children ( Romano, 2014 ). College students are the second group on which Internet addiction prevention interventions should be focused ( Lin, Ko, & Wu, 2011 ) because of the high prevalence rates (e.g.,  Chou & Hsiao, 2000 ; Huang et al., 2009 ; Lin et al., 2011 ) and easy accessibility ( Anwar & Seemamunaf, 2015 ). In addition to children, adolescents, and college students, attention should also be paid to their close formative surroundings, especially the family, the school environment, and extracurricular activities (e.g.,  Lin & Gau, 2013 ; Park et al, 2008 ). Young ( 2010 ), on the other hand, stresses the potential for the prevention of Internet addiction at work for employees with regular access to the Internet because regular access to the Internet may be a risk factor in the development of Internet addiction. Gray, Tom, Laplante, and Shaffer ( 2015 ) describe responsible gambling training programs, which train online gambling employees about gambling and gambling-related problems.

Selective and indicated prevention

At the level of selective and indicated prevention, there are at-higher-risk individuals because of the presence of specific biopsychosocial factors and factors related to Internet use patterns. The risk factors (or characteristics) found in the literature relate to: (a)  psychopathological factors : ADHD, depressive and anxiety disorders, and social phobia (e.g.,  Alavi et al., 2012 ; Ang et al., 2012 ; Ko, Yen, Chen, Yeh, & Yen, 2009 ; Lin et al., 2011 ; Oh, 2003 ; Yen et al., 2008 ), substance use ( Ko, Yen, Yen, Chen, & Chen, 2012 ), or obsessive compulsive symptoms ( Jang, Hwang, & Choi, 2008 ); (b)  personality characteristics : hyperactivity and impulsivity ( Wu et al., 2013 ), high novelty seeking and low reward dependence ( Dalbudak et al., 2015 ; Ko et al., 2006 ), introversion, low conscientiousness and agreeableness and high neuroticism/low emotional stability ( Kuss, Shorter, van Rooij, van de Mheen, & Griffiths, 2014 ; Kuss, van Rooij, Shorter, Griffiths, & van de Mheen, 2013 ), hostility (e.g.,  Alavi et al., 2012 ; Ang et al., 2012 ; Ko et al., 2009 ; Lin et al., 2011 ; Oh, 2003 ; Yen et al., 2008 ), or a low level of self-control and self-regulation ( Blachnio & Przepiorka, 2015 ); (c)  physiological characteristics : stronger blood volume pulse and respiratory response and a weaker peripheral temperature ( Lu, Wang, & Huang, 2010 ); (d)  patterns of Internet use : a large number of hours spent online ( Kuss et al., 2013 ), engagement in different video games ( Donati, Chiesi, Ammannato, & Primi, 2015 ), or excessive weekend Internet use ( Xu, Shen, et al., 2012 ); (e)  sociodemographic factors such as gender ( Ha & Hwang, 2014 ; Shek & Yu, 2016 ) or family economic disadvantage ( Shek & Yu, 2016 ); and (f) the current situation : loneliness and stress ( Alavi et al., 2012 ; Ang et al., 2012 ; Ko et al., 2009 ; Lin et al., 2011 ; Oh, 2003 ; Yen et al., 2008 ) or affiliation with peers who have lower levels of social acceptance or young people situated in a class with higher levels of Internet addiction ( Zhou & Fang, 2015 ).

Interventions focusing on improvement of specific skills

Researchers recommend counselors, teachers, or employers to focus on the development of specific skills in (a) individuals who are at risk of Internet addiction, but also in (b) their significant others, particularly parents, teachers, and peers.

Individuals at risk of Internet addiction

The specific skills for preventing Internet addiction can be divided into four basic areas: (a)  skills associated with Internet use , such as the reduction of the positive outcome expectancy of Internet use, self-control, self-efficacy, or abstinence from addictive online applications (e.g.,  Echeburúa & de Corral, 2010 ; Kim, Namkoong, Ku, & Kim, 2008 ; Li, Wang, & Wang, 2009 ; Lin, Ko, & Wu, 2008 ; Lin et al., 2011 ; Oh, 2003 ; Wang, Wu, & Lau, 2016 ), and the ability to identify the maladaptive thoughts connected with addictive behavior ( Peng & Liu, 2010 ); (b)  skills associated with coping with stress and emotions : particularly the development of individual coping strategies (e.g.,  Li et al., 2009 ; Rehbein & Baier, 2013 ), improvement of the capacity to regulate and process emotions ( Lin et al., 2008 , 2011 ), diminution of hostility ( Ko, Yen, Yen, Lin, & Yang, 2007 ), encouragement of positive personality traits ( Yu & Shek, 2013 ), and the enhancement of self-esteem ( Ko et al., 2007 ); (c)  skills associated with interpersonal situations : the diminution of interpersonal sensitivity ( Ko et al., 2007 ), reinforcement of emotional intelligence ( García del Castillo, García del Castillo-López, Gázquez Pertusa, & Marzo Campos, 2013 ), strengthening of social competence in order to reinforce the rules of fairness and tolerance within the class group in schools ( Rehbein & Baier, 2013 ), and the ability to communicate face to face and carry out group activities and free-time activities with peers ( Echeburúa & de Corral, 2010 ; Yang, Zhu, Chen, Song, & Wang, 2016 ); and (d)  skills associated with one’s daily regime and use of free time : keeping a sleep schedule ( Lin & Gau, 2013 ), carrying out group activities and free-time activities ( Echeburúa & de Corral, 2010 ), and encouraging participation in creative, exploratory, and exciting healthy activities ( Ko et al., 2007 ).

Significant others

Some researchers also point out the presence of certain factors or parenting styles that promote the development of Internet addiction and they stress the need to work not only with vulnerable individuals but also with their loved ones, especially their parents. Most of the recommendations in the literature are focused on the parents of children at risk. Some of them are focused on peers, teachers, and employers ( Gray et al., 2015 ; Chen, Lee, & Yuan, 2013 ; Zhou & Fang, 2015 ).

In contact with the loved ones of vulnerable individuals, experts primarily recommend focusing on two basic skills: (a)  skills encouraging closer relationships , in particular the improvement of parent–child communication, the amount of time spent with their children, understanding their child’s needs, and the improvement of parental mental health (e.g.,  Echeburúa & de Corral, 2010 ; Ko et al., 2007 ; Lam, 2015 ; Lin & Gau, 2013 ). In companies with a regular Internet connection, Young ( 2010 ) recommends supporting employees’ responsibility and ethical integrity; (b)  skills connected with the monitoring of Internet use , such as understanding their child’s needs regarding Internet usage ( Kalmus, Blinka, & Ólafsson, 2013 ; Wu et al., 2013 ), knowledge and awareness of their child’s online activities ( Ang et al., 2012 ), and monitoring of the child’s Internet use ( Li, Li, & Newman, 2013 ). This may be done, for example, by establishing rules regulating the content of online activities and/or by criticizing excessive Internet use but without setting strict time limits for Internet use ( van den Eijnden, Spijkerman, Vermulst, van Rooij, & Engels, 2010 ), by the mediation of Internet use to children in the form of discussions and joint Internet use together with them ( Xiuqin et al., 2010 ), and by the use of restrictive strategies with regard to Internet use ( Kalmus et al., 2013 ; Xiuqin et al., 2010 ). Liu, Fang, Deng, and Zhang ( 2012 ) also point to the adoption of adaptive norms of Internet use and consistent adherence to them among parents. Indirectly, the literature also indicated work with teachers on how to conduct effective prevention interventions ( Walther et al., 2014 ). Regarding employees, Young ( 2010 ) encourages company management to teach employees how to detect the first signs of Internet addiction and factors that contribute to its development early on. In this context, Frangos and Sotiropoulos ( 2010 ) recommend the organization of educational seminars and the monitoring of Internet use by employers.

The skills introduced above were found to be relevant in the prevention of other risk behaviors. These skills and their role in the prevention of Internet addiction were not specifically studied and thus are not evidence-based. Only Xu, Turel, and Yuan ( 2012 ) monitored the impact of six prevention factors/specific skills (switching attention to other beneficial activities, the perceived financial cost of online gaming, dissuasion by others, rationalization/education, parental monitoring, and regulation and restriction of resources, such as money or equipment) in preventing online game playing and addiction on the basis of the self-reports of 623 adolescents in China. The data suggest that switching attention had a significant negative impact on game playing and addiction. Rationalization/education and the perceived cost had a significant negative influence on game playing but not on online game addiction and parental monitoring had a negative influence on online game addiction. Surprisingly, the adolescents reported that dissuasion was positively associated with game playing and addiction, and the regulation and restriction of resources correlated positively with online game addiction.

Program characteristics

In the texts published on Internet addiction prevention interventions, we identified the following three dimensions: (a) information-providing versus interactive interventions, (b) single versus complex interventions, and (c) empirical studies of Internet addiction prevention.

Information-providing versus interactive interventions

The most widespread form of the prevention of Internet addiction is based on providing basic information regarding Internet addiction, with an emphasis on factual information concerning its adverse consequences ( Alavi et al., 2012 ; Kwon, 2011 ). Educators usually invite experts to give a presentation to students about Internet addiction and provide some advice on how to control Internet use. Furthermore, these interventions may be a part of media education at primary and secondary schools.

Recently, four Internet addiction prevention interventions based on providing information have been published. Korkmaz and Kiran-Esen ( 2012 ) investigated the effect of a peer program on control and experimental groups of 825 students who attended the 6th to 8th grades in two primary schools in Turkey. Future peer activists attended a 10-hr educational program to learn how to inform their peers in two 40-min lectures about the Internet, Internet addiction, and types of online applications with safe and risk potential. According to the results of the study, the peer program was beneficial for the students who attended the lecture. Their Internet use was influenced in a positive manner in comparison to the members of the control group. The second publication introduced a program aimed at increasing media literacy among 2,303 German children aged 11–13 years, who were divided into experimental and control groups. The program consisted of four lectures regarding Internet use in general, online communication, and online gaming and gambling, and was implemented by trained teachers during class time. The effectiveness of the program was monitored in 1,843 respondents 12 months after the delivery of the intervention. The results revealed a significant effect of the intervention in terms of a smaller increase in their self-reported gaming frequency and gaming time and a smaller proportion of excessive gamers in the intervention group ( Walther et al., 2014 ). de Leeuw et al. ( 2010 ) describe a health promotion program delivered to 367 children aged 11–16 years; the intervention focused on education on health issues (Internet and gaming behavior was among the seven health behaviors addressed) and delivered in blocks of 2 hr a week within three school years (the authors did not present the total number of hours). The results were rather inconsistent. The time spent on the Internet (hours/day) and the number of pathological Internet users increased during the study. The number of game users decreased but heavy game use increased. Turel et al. ( 2015 ) conducted an empirical test of an Internet addiction intervention based on two short video interventions (one educational and informative and the other less informative and more humorous and surprising). A sample of 233 university students was exposed to one of the two videos. The researchers measured Internet addiction and attitudes toward reducing their use of the Internet in three waves (one week before the intervention, immediately after the intervention, and one week after the intervention). The intervention was efficacious in improving viewers’ attitudes toward reducing their Internet use.

Single versus complex interventions

Single interventions focus on a single type of risk behavior, for example, Internet addiction.

On the other hand, complex interventions focus either on: (a) different types of risk behaviors simultaneously, or (b) different types of environments that are relevant to Internet addiction. The multi-risk-behavior-focused programs also aim, besides Internet addiction, at other types of risk behaviors, mostly substance use (e.g.,  Gong et al., 2009 ; Ko et al., 2008 ; Yen, Yen, Chen, Chen, & Ko, 2007 ; Jie et al., 2009 ). The assumption that the reduction of risk behavior in one area may reduce risk behavior in other areas has been confirmed by numerous studies (e.g.,  Cuijpers, 2002 ; Miovský, Šťastná, Gabrhelík, & Jurystová, 2011 ). Regarding multiple environments or settings, we identified the following environments that such a preventive intervention should aim at: the individual, the family, peers, school, work, and the community ( Frangos & Sotiropoulos, 2010 ; Hur, 2006 ; Jang et al., 2008 ).

Busch et al. ( 2013 ) introduced a pilot version of a school intervention aimed at promoting health (healthy nutrition, physical exercise, sexual health, reducing alcohol and drug use, smoking, bullying behaviors, excessive sedentary behavior – watching television and computer use – and excessive Internet use, including online gaming) in primary schools in the Netherlands. Data were collected from 336 students aged 15–16 years, who were divided into experimental and control groups. Individual interventions were carried out on the following four levels: (a) application of healthy school policies (no smoking or use of drugs and alcoholic beverages), (b) parental activities with children and their participation in creating a healthy school environment, (c) the active development of life skills in students, and (d) addressing local health experts to provide teachers with basic information about the areas that were monitored. The intervention successfully changed the health behaviors of the students in many areas (smoking, excessive use of alcohol and drugs, sedentary behavior, and bullying) but had no effect on excessive Internet use, including online gaming. This intervention fulfilled both aspects of complexity, that is, a focus on various types of risk behavior (healthy nutrition, physical exercise, sexual health, reducing alcohol and drug use, smoking, bullying behaviors, excessive sedentary behavior – watching television and computer use – and excessive Internet use, including online gaming) and on four types of setting (the individual, family, community levels). Shek et al. ( 2011 ) present the curriculum of a positive youth development program (Project P.A.T.H.S.) which consists of 120 teaching units designed with reference to the 15 positive youth development constructs identified in successful positive youth development programs. In the extension phase of the project, a new curriculum with an additional 60 teaching units was developed with specific reference to five major adolescent developmental issues (substance abuse, the issue of sexuality, Internet addiction, bullying, and money and success issues). Besides the students, families (e.g., encouraging parental involvement) and schools (e.g., school improvement and reorganization initiatives) were also targeted.

Empirical studies of Internet addiction prevention

We identified five empirical studies describing the implementation and/or evaluation of preventive intervention (see Table  1 ). Majority of studies ( Busch et al., 2013 ; Korkmaz & Kiran-Esen, 2012 ; de Leeuw et al., 2010 ; Walther et al., 2014 ) were carried out in Europe (the Netherlands, Germany, and Turkey), only one in the USA ( Turel et al., 2015 ). Majority of studies ( Busch et al., 2013 ; Korkmaz & Kiran-Esen, 2012 ; de Leeuw et al., 2010 ; Walther et al., 2014 ) were focused on the change of Internet addiction behavior among secondary school students 11- to 16-year-olds and only one ( Turel et al., 2015 ) targeted on university students aged 18–49 years. Only Busch et al. ( 2013 ) targeted beside students their families, school environment and teachers in their preventive interventions. The rest of studies intervened in students’ population. Two studies were conducted as pilot studies with assessments ( Busch et al., 2013 ; de Leeuw et al., 2010 ) and the rest used the randomized trial with baseline and two follow ups ( Korkmaz & Kiran-Esen, 2012 ; Turel et al., 2015 ; Walther et al., 2014 ).

In terms of risk of bias in individual studies (Table  2 ), most studies ( Busch et al., 2013 ; Korkmaz & Kiran-Esen, 2012 ; de Leeuw et al., 2010 ; Turel et al., 2015 ) were assessed as high risk in the first four categories (selection bias, performance bias, detection bias, and attrition bias) and low risk in the reporting bias category. Walther et al. ( 2014 ) was assessed “high risk” bias only in the selection and attrition categories. We applied strict criteria in the assessment. However, it must be noted that the performance bias (due to knowledge of the allocated interventions by participants and personnel during the study; Higgins & Green, 2011 ) and detection bias (due to knowledge of the allocated interventions by outcome assessors; Higgins & Green, 2011 ) are, in general, not controlled for in prevention studies. Regarding the overall quality of methodology, we assess the study conducted by Walther et al. ( 2014 ) as high compared to the remaining studies.

Assessment of risk of bias in individual studies

Note. H: high risk of bias; L: low risk of bias; U: unclear bias. We applied strict criteria in the assessment. However, it must be noted that, for example, performance and detection biases are, in general, rather uncommon in these types of studies. Perhaps, in these studies, U could also be used for performance and detection biases.

Environmental interventions

Countries in which Internet addiction is considered a serious health problem are starting to introduce Internet addiction prevention interventions on the environmental level, particularly regulations related to Internet addiction. For example, the Chinese government has implemented tighter control mechanisms on Internet cafés and an anti-addiction or fatigue system. The regulations, for example, state that no Internet café is allowed within 200 meters of an elementary or middle school or that the business hours of Internet cafés must be limited to between 8 a.m. and midnight ( Guosong, 2010 ). An anti-addiction or fatigue system is a monitoring system that watches the number of hours a user spends on online game playing and the user’s game character will lose power and experience points after the limit on game playing has been exceeded ( Hsu, Wen, & Wu, 2009 ). In this context, Yani-de-Soriano, Javed, and Yousafzai ( 2012 ) urge policymakers and regulators to become more involved in the corporate social responsibility practices of online gambling companies that are aimed at preventing or minimizing the harm associated with their activities.

In the review, we focused on four basic areas regarding the prevention of Internet addiction: (a) the target groups, (b) the improvement of specific skills, (c) the program characteristics, and (d) environmental interventions.

The target group is usually split into two subgroups, using a population criterion: the universal level of prevention and the selective and indicated level of prevention. At the level of universal prevention four main subgroups were identified: (a) children and adolescents, (b) university students, (c) parents and others close to the member of the target group, and (d) gambling employees and employees with regular access to the Internet. Currently, most attention is paid to children and adolescents, who are responsive to positive influences on their values and beliefs ( Bém & Kalina, 2003 ) and easily accessible in the school environment. The prevention of Internet addiction in adults and seniors, as well as the unemployed and mothers on parental leave, who are endangered to a great extent by Internet addiction ( Müller, Glaesmer, Brähler, Woelfling, & Beutel, 2013 ; Young, 1998 ), has received very little or no attention. These are not yet mentioned in the literature on preventive interventions because such populations are difficult to access or, for example, Internet addiction might be hidden among other problematic behaviors such as workaholism ( Quinones, Griffiths, & Kakabadse, 2016 ). To address the needs of these groups, the type and extent of their problems and developing appropriate interventions for them represent more of a challenge for the future.

Regarding selective and indicated prevention, we identified six sub-groups with specific biopsychosocial risk factors: (a) psychopathological factors, (b) personality characteristics, (c) physiological characteristics, (d) patterns of Internet use, (e) sociodemographic factors, and (f) the current situation. Only factors on the individual level were mentioned in the prevention literature; factors on the environmental level, such as the family, peer, school, and community level, are missing ( Charvát & Nevoralová, 2012 ). Therefore, future studies should focus on identifying at-risk groups on the environmental level.

Future prevention interventions should also focus on people who are part of the formative environment of children and adolescents who are at risk of Internet addiction: parents, teachers, peers, and others close to them. Literature describing any specific Internet addiction prevention interventions focused on those close to potential Internet addicts is scarce ( Busch et al., 2013 ).

The development of prevention interventions that increase specific (life) skills in specific subgroups is recommended for: (a) individuals who are at risk of Internet addiction (skills associated with Internet use, with coping with stress and emotions, with interpersonal situations, and with one’s daily regime and use of free time), and also for (b) those close to them (skills encouraging closer relationships and skills connected with the monitoring of Internet use). All these skills fall into the category of life skills, which are defined as a group of psychosocial competencies and interpersonal skills that help people make informed decisions, solve problems, think critically and creatively, communicate effectively, build healthy relationships, empathize with others, and cope with and manage their lives in a healthy and productive manner ( WHO, 2003 ). In general, the adoption of relevant life skills leads to healthy lifestyles and the prevention of risk behaviors or other mental and somatic health problems ( Manee, Khouiee, & Zaree, 2011 ; Pharaoh, Frantz, & Smith, 2011 ). Although we can find many recommendations in the literature on how specific skills should be developed to prevent Internet addiction, there is only one study ( Xu, Turel, et al., 2012 ) that evaluated the impact of some specific skills in the prevention of Internet addiction. Therefore, researchers should design, conduct, and publish scientifically rigorous evaluations of specific skills that are relevant in the prevention of Internet addiction.

In Internet addiction prevention interventions, we identified three basic dimensions: (a) programs aimed at providing information versus interactive interventions, (b) single versus complex interventions, and (c) empirical studies of Internet addiction prevention. According to the literature, the general recommendations that should lead to the intended effective prevention outcomes are: (a) the mere provision of information about the negative consequences of risk behavior is ineffective and it needs to be complemented by interactive interventions aimed at changing attitudes and the development of selected skills for life ( Soole, Mazerolle, & Rombouts, 2008 ) and (b) the effective prevention interventions should be complex and focused on Internet addiction and other forms of risk behavior ( Gong et al., 2009 ) and should be a combination of interventions targeting vulnerable people with an Internet addiction, their parents and other loved ones, and the community, school, or work environment ( Frangos & Sotiropoulos, 2010 ). In our search, we found only five studies describing and evaluating prevention interventions for Internet addiction. A comparison of the results from these Internet addiction prevention interventions ( Busch et al., 2013 ; Korkmaz & Kiran-Esen, 2012 ; de Leeuw et al., 2010 ; Turel et al., 2015 ; Walther et al., 2014 ) suggests that the findings are not fully in line with the current school-based prevention recommendations based on evidence (e.g.,  Cuijpers, 2002 ; Miovský et al., 2011 ; Soole et al., 2008 ). The study of Busch et al. ( 2013 ) was complex in both dimensions but had limited effectiveness in terms of its effect on Internet addiction; the studies of Korkmaz and Kiran-Esen ( 2012 ), Turel et al. ( 2015 ), and Walther et al. ( 2014 ) used informative single-type interventions but were effective. Only the study results of de Leeuw et al. ( 2010 ) were rather inconsistent. This contradiction may be caused by the limited number of studies (five), the sample size, short-term follow ups, the different instruments used for the measurement of Internet addiction, high risk of bias in individual studies, and the emphasis on the nature of the outcome rather than the specificity of the topic of Internet addiction.

To illuminate the reasons for these contradictory findings, it is necessary to carry out more studies of the effectiveness of prevention programs focused on Internet addiction.

The above-mentioned six interventions are examples of universal prevention programs. The authors found no evidence of studies describing prevention interventions that fell within the area of selective and indicated prevention, even though in the scientific literature there are specific recommendations for the prevention of Internet addiction, especially in the area of indicated and selective prevention (e.g.,  Echeburúa & de Corral, 2010 ; Ko et al., 2007 ; Lin & Gau, 2013 ). Therefore, we recommend researchers, consultants, and educators who are planning the creation and evaluation of specific programs of selective or indicated prevention to draw inspiration from the prevention of other risk behaviors (e.g., the prevention of substance use).

We would also like to comment on the environmental interventions. Environmental interventions can be induced by providers [e.g., the owners of Internet cafés ( Guosong, 2010 ) or online gambling companies ( Hsu et al., 2009 ; Yani-de-Soriano et al., 2012 )]. Very few countries implement such interventions in practice. No efficacy or effectiveness studies have been conducted and no results published. We encourage policymakers and researchers to implement and study interventions on the environmental level.

The strength of this review is that it is (to the authors’ best knowledge) the first review focused on the prevention of Internet addiction and that also included texts written not only in English but also in Spanish. Several limitations are worth noting: first, the majority of the texts had the prevention of Internet addiction as a partial topic, while only eight texts (seven studies and one theoretical chapter) had it as the main topic; second, each of the records included in our study used different conceptualization and different measures of Internet addiction, and had different objectives; therefore, this study is more descriptive than comparative.

To the best of our knowledge, this is the first detailed review on the prevention of Internet addiction. Our findings showed that the literature on research into the prevention of Internet addiction is scarce. There is an urgent need to introduce and implement new interventions for different at-risk populations, conduct well-designed research, and publish data on the effectiveness (or lack thereof) of these interventions.

Developing prevention interventions should primarily target children and adolescents at risk of Internet addiction but also parents, teachers, peers, and others who are part of the formative environment of children and adolescents at risk of Internet addiction. These interventions should cover all three levels of prevention: universal, selective, and indicated, and should address risk factors on the family, peer, school, community, and environmental levels that contribute to the onset and development of Internet addiction. Newly designed interventions focused on Internet addiction should be rigorously evaluated and the results published.

Authors’ contribution

PV designed the study and wrote the protocol, conducted the literature searches and analyses of the records, and performed the initial drafting of the manuscript. RG contributed to the writing and finalization of the manuscript. Both authors contributed to and have approved the final manuscript. PV is the guarantor of the work.

Conflict of interest

The authors declare that they have no conflict of interest.

Funding Statement

Funding sources: This study was supported by the Czech Science Foundation (Grant no. 16-15771S) and Charles University, Prague (PRVOUK-P03/LF1/9).

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