internet addiction research paper outline

Internet Addiction: A Brief Summary of Research and Practice

Affiliation.

• 1 reSTART Internet Addiction Recovery Program, Fall City, WA 98024.
• PMID: 23125561
• PMCID: PMC3480687
• DOI: 10.2174/157340012803520513

Problematic computer use is a growing social issue which is being debated worldwide. Internet Addiction Disorder (IAD) ruins lives by causing neurological complications, psychological disturbances, and social problems. Surveys in the United States and Europe have indicated alarming prevalence rates between 1.5 and 8.2% [1]. There are several reviews addressing the definition, classification, assessment, epidemiology, and co-morbidity of IAD [2-5], and some reviews [6-8] addressing the treatment of IAD. The aim of this paper is to give a preferably brief overview of research on IAD and theoretical considerations from a practical perspective based on years of daily work with clients suffering from Internet addiction. Furthermore, with this paper we intend to bring in practical experience in the debate about the eventual inclusion of IAD in the next version of the Diagnostic and Statistical Manual of Mental Disorders (DSM).

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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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Bickham, D.S. Current Research and Viewpoints on Internet Addiction in Adolescents. Curr Pediatr Rep 9 , 1–10 (2021). https://doi.org/10.1007/s40124-020-00236-3

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A study of internet addiction and its effects on mental health: A study based on Iranian University Students

Javad yoosefi lebni.

1 Health Education and Health Promotion, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran

Razie Toghroli

2 Social Determinants in Health Promotion Research Center, Hormozgan Health Institute, Hormozgan University of Medical Sciences, Bandar Abbas, Iran

Jaffar Abbas

3 Antai College of Economics and Management/School of Media and Communication, Shanghai Jiao Tong University, Shanghai-China

Nazila NeJhaddadgar

4 Department of Health Care Services and Health Education, School of Health, Ardabil University of Medical Science, Ardabil, Iran

Mohammad Reza Salahshoor

5 Department of Anatomical Sciences, Medical School, Kermanshah University of Medical Sciences, Kermanshah, Iran

Morteza Mansourian

6 Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran

Hadi Darvishi Gilan

Neda kianipour.

7 Students Research Committee, Kermanshah University of Medical Sciences, Kermanshah, Iran

Fakhreddin Chaboksavar

Seyyed amar azizi, arash ziapour, introduction:.

The Internet has drastically affected human behavior, and it has positive and negative effects; however, its excessive usage exposes users to internet addiction. The diagnosis of students' mental dysfunction is vital to monitor their academic progress and success by preventing this technology through proper handling of the usage addiction.

MATERIALS AND METHODS:

This descriptive-analytical study selected 447 students (232 females and 215 males) of the first and second semesters enrolled at Kermanshah University of Medical Sciences, Iran, in 2018 by using Cochrane's sample size formula and stratified random sampling. The study applied Young's Internet Addiction Test and Goldberg General Health Questionnaire 28 for data collection. The study screened the data received and analyzed valid data set through the t -test and Pearson's correlation coefficient by incorporating SPSS Statistics software version 23.0.

The results of the current study specified that the total mean score of the students for internet addiction and mental health was 3.81 ± 0.88 and 2.56 ± 0.33, correspondingly. The results revealed that internet addiction positively correlated with depression and mental health, which indicated a negative relationship ( P > 0.001). The multiple regression analysis results showed students' five significant vulnerability predictors toward internet addiction, such as the critical reason for using the Internet, faculty, depression, the central place for using the Internet, and somatic symptoms.

CONCLUSIONS:

The study findings specified that students' excessive internet usage leads to anxiety, depression, and adverse mental health, which affect their academic performance. Monitoring and controlling students' internet addiction through informative sessions on how to use the Internet adequately is useful.

Introduction

In recent years, technological advancements have taken place in the modern world. In the complexity of today's world, internet use is playing a vital role in educational institutions to attain different learning skills, which have become a necessity for university students. However, scholars have shown concerns about the excessive use of this technology and the hidden risk factors of internet users, such as physical and mental health.[ 1 , 2 ] The Internet is an easy and quick medium of interaction to gain the required information for communication with others around the world. However, a lack of control over excessive internet use can disturb individuals' living standards and relationships between family members, and it can bring instability of feelings.[ 3 , 4 ] The users of the Internet have increased incredibly worldwide, with the peak of a digital industrial revolution in progress, and new technological revolution will undoubtedly create new problems and predicaments.[ 4 , 5 ] The history of internet users goes back some decades at present. The Internet has become one of the most fast-growing and transformative technologies. Globally, the users of the Internet have increased from 414 million in 2000, 665 million in 2002, and over 4.574 billion by December 31, 2019. The US National Science Foundation specified that the internet users enabled by smartphones access would increase to 5 billion in 2020.[ 6 , 7 ] In recent years, internet users in Iran have grown dramatically. According to the reported statistics, the Iranian users of the internet have risen from 11.0 million in 2006, 33.0 million in 2002, and over 62 million by July 1, 2019. Hence, the users of the Internet in Iran have increased drastically over 25 times, and recent research conducted in Iran indicated that the young population makes up the majority of internet users.[ 8 ] Previous research specified that the Iranian users devote 35% of their time to chat rooms, 28% to online games, 30% to checking E-mails, and 25% to surfing the net on averages, while connected to the Internet. Besides, another study reported that Iranian users spend 52 min/week as an average time, while linked to the Internet.[ 9 ]

Internet addiction disorder, pathological internet use, or problematic internet use typically refers to the questionable or compulsive use of the Internet, which results in substantial impairment in the function of individuals in their different life domains over prolonged time. Internet addiction and other relationships based on the usage of digital media and mental health are vital considerable research fields, arguments, and discussions among numerous experts and researchers in various disciplines. This addictive behavior has made controversy from the areas of scientific, medical, and technological communities. Internet addiction is an interdisciplinary phenomenon, and different researchers have investigated it from different perspectives from various disciplines, such as medicine, computer science, sociology, law, and psychology.[ 10 ] Some scholars have considered internet addiction as a social crisis, and it has attracted the attention of different researchers and experts. This phenomenon is a biological, psychological, social, economic, and cultural problem, which is impossible to be taken into account as a simple matter because different factors influence it.[ 11 ] The excessive and pathological use of the Internet refers to internet addiction.[ 6 ] Therefore, with the growing number of internet users and its widespread psychological and sociological implications, it is necessary to determine and recognize the contribution of predictive factors in internet addiction. By conducting pathological studies about internet addiction to judge the addictive behaviors, it would enable us to utilize this technology with a balanced approach better and more usefully.[ 12 ] Internet addiction generally refers to a type of applying the Internet, which leads to psychological, social, educational, or occupational problems in a person's life.[ 13 , 14 ] Scholars have described this phenomenon as internet addiction dysfunction[ 15 ] and the problematic application of the Internet,[ 16 ] or habitual use of the Internet,[ 17 ] which determines it as one of the forms of behavioral addiction.[ 18 ] Researchers have also described internet addiction as “the modern addiction.” In practice, this type of addiction is true dependency, like drug addiction and other kinds of dependency. Although this kind of dependency does not have the somatic problems of chemical addiction, its resultant social problems are like other types of addiction.[ 1 ] In the 2015 World Statistics report, the number of internet users and the population of countries were specified; it was reported that the total world population was 7,264,623,793, of which 3,079,339,857 were using the Internet, and the young made up the majority of users.[ 8 ] While taking into account many points of proper and practical use of the Internet and prevention of mental illness, these reported statistics underscore the importance of the Internet and social networks. Internet addiction is an etymological process of using the Internet that creates a psychological state in which the user's behavior is disturbed, thereby leading to a dysfunction in his/her cognitive status.[ 19 ] Mental health is one of the main pillars of healthy human societies, which plays a vital role in ensuring the dynamism and efficiency of any society. As university students are among the most prestigious layers of societies, they present future builders in any country, and newly arrived students in universities from far-away cities are the first who fall victim to internet addiction. The mental health of the students is essential for raising their learning and scientific awareness.[ 19 ] Mental health is a concept that reflects our thinking, feelings, and functioning in dealing with various life situations.[ 20 ] In this modern world, the disease patterns are shifting toward no communicable diseases, and the rising rate of mental dysfunction and the resultant costs imposed on societies have attracted the attention of health promotion specialists.[ 8 ] In this regard, the Global Burden of Disease statistics has introduced mental illnesses as one of the three primary causes of lost years of life due to disability.[ 21 ] According to the WHO, mental health is defined as one's ability to communicate with others harmoniously; modify the personal and social environment; and resolve conflicts and personal preferences logically, fairly, and appropriately.[ 22 ] Besides, the statistics announced by the WHO reported that 52 million people of different age groups suffer from severe illnesses worldwide and 250 million have mild mental dysfunction. In Iran, these statistics are not lower than those in other countries.[ 23 ] The results of the epidemiological studies conducted to examine psychiatric dysfunction in Iran are indicative of the variability of the prevalence of dysfunction between 11.9% and 30.2%.[ 24 , 25 ]

Concerning internet addiction, addressing the problems of individuals' mental health is of great importance. An earlier study conducted by Fallah reported that depression was more prevailing among internet users with addictive behavior as compared with average internet users. The finding specified that individuals having internet addiction showed anxious behavior and their mental health was more exposed to higher risks.[ 23 ] Lashgarara et al . described that 34% of university students had addictive behavior to the Internet based on the Young's categorization.[ 26 ]

In a previous study, Fonia et al . reported that students' mental health and internet addiction showed a negative relationship, and their internet addictive behavior was not significant. It was different from the students' gender and marital status variables.[ 27 ] Another study of Nastizai claimed that students' internet addiction developed a higher risk of mental health than ordinary users of the Internet.[ 28 ] Fonia et al . reported that there was a significant difference between internet addiction among male and female students.[ 27 ] Similarly, the relationship between internet addiction and users' mental health received more considerable attention, and previous studies have emphasized this matter, such as the investigations of Fallah Mehneh,[ 29 ] Alavi et al .,[ 30 ] Mirzaian et al .,[ 31 ] and Taheri Mobarakeh et al .[ 32 ] The tendency of using the Internet among students is higher, and they are more vulnerable to the risk of internet addiction. Thus, more attention to students' mental health needs should be considerable paid for their future as well as the development of the nation.[ 22 , 25 ] Universities need to pay attention to boosting students' mental health, personal growth, and well-being. Because internet addiction prevails worldwide, it also exists in Iran for several years, and young individuals have shown greater engagement toward internet use, while students make up the majority of internet users. The excessive use of the Internet leads to psychological injury, mental health damage, and other health problems. Experts have suggested necessary measures to prevent internet addiction among students and treat disorders and health problems where appropriate.[ 33 ] The present research emphasized investigating internet addiction and its effects on the mental health of medical students at Kermanshah University of Medical Sciences, and its findings provide valuable insights.

Materials and Methods

This descriptive-analytical study selected 447 students (232 females and 215 males) of the first and second semesters enrolled at Kermanshah University of Medical Sciences, in 2018 (May 2017–October 2018) by applying Cochrane's sample size formula and stratified random sampling methods. This method draws the statistical population according to the hierarchy of the types of population units. The study applied Young's Internet Addiction Test (IAT) and Goldberg General Health Questionnaire (GHQ-28) for data collection. The study screened the data received and analyzed valid data set through the t -test and Pearson's correlation coefficient by incorporating SPSS Statistics software version 24.0. Hence, the authors randomly selected nine faculties (medicine, dentistry, pharmaceutical medicine, nursing and midwifery, paramedics, public health, nutrition sciences, and food industries, and self-governing college). In the next step, we selected majors and classes from each faculty (as many as the number of research samples) and evaluated the data. The inclusion criterion was the right to choose the courses freely, and the investigators have excluded incomplete questionnaires from the study. Besides, we assured participants about the confidentiality of the collected information and lack of disclosure of their personal information. Besides, the ethical principles employed in the present study included critical steps, such as obtaining the necessary permits, retaining the right for the schools under investigation to either accept or reject to participate in the research study, and ensuring confidentiality and nondisclosure of agreement. The investigators distributed the questionnaires among the target respondents. The authors explained the objectives of the present study to the target individuals and obtained informed consent from all participants before to execute the research. Not to mention, the exclusion criteria were the sample's disinterest in participating in the study and handing over incomplete questionnaires.

Demographic questionnaire

The first section of the self-administered instrument contained the demographics and comprised questions on gender, age, marital status, place of residence, faculty, education, having a personal computer, central location, and time of using the Internet, and the primary reason for using the Internet.

Internet Addiction Test

Young developed this 20-item scale for measuring the internet addiction, which affects a variety of aspects in users' lives.[ 17 ] The study applied the Persian translation of Young's IAT developed by Alavi et al .[ 30 ] The questions showed the scores on a selected 5-point Likert scale (5 = always, 4 = usually, 3 = most of the time, 2 = sometimes, and 1 = seldom). The ranges of minimum and maximum scores showed 20–100. The scores divided internet users into the following three groups: typical users indicating a score of 20–49; at-risk users, specifying a score of 50–79; and the internet users having an addiction with a score of 80–100. The highest scores represent the highest levels of students' dependency on the Internet, which leads to addictive behavior. Recent studies evidenced that a score of 50 or above shows internet addiction. Besides, this study confirmed the questionnaire's validity from three experts by applying the content validity index (0.84), while the survey confirmed reliability through the t -test (0.88). The Cronbach's alpha provided a satisfactory value (0.87) with a sample of twenty medical students within 2-week process of data collection. The findings of the reliability and validity of this instrument/tool are consistent with the results of previous studies, which indicated over 90%.[ 34 , 35 , 36 , 37 , 38 ]

The General Health Questionnaire

This prospective study used GHQ-28 for gathering data.[ 39 ] The study screened the data received and analyzed valid data set through the t -test and Pearson's correlation coefficient by using the SPSS Statistics software version 24.0. The self-reported Goldberg's 28-item questionnaire examines the individual's mental health in the recent month and includes symptoms such as abnormal thoughts and feelings and aspects of visible behavior. This questionnaire consists of the following four subscales: somatic symptoms (questions 1–7), anxiety (questions 8–14), social dysfunction (questions 15–21), and depression (questions 22–28). Each subscale contains seven questions that measure the various aspects of mental health, ranging from somatic to psychological dysfunction.[ 39 ] The questions presented scores with a 4-point Likert scale (0 = not at all, 1 = average, 2 = more than average, and 3 = far more than average). The minimum and maximum ranges illustrated 0–84, which showed categories into four levels of mental health, for instance, normal (0–22), weak (21–40), balanced (41–60), and severe (61–84). The highest ratings/scores represented the lowest level of students' mental health status. The study examined and confirmed the questionnaire's reliability for each section by using content validity (0.80). The sought the opinion from three experts by using the content validity index (0.80) and confirmed reliability through several tests, such as test-retest (0.87). The study calculated the Cronbach's alpha (0.93) value from the sample of twenty medical students. The results derived from the tests of reliability and validity of this instrument are in line with the findings of previous global studies, which specified the same results.[ 9 , 40 , 41 , 42 ]

The study applied descriptive statistics (percentage, mean, and standard deviation) and inferential statistics ( t -test and Pearson's correlation coefficient) to analyze the data received by using the SPSS Statistics software (version 23.0, SPSS Inc., Chicago, IL, USA), and applied required analysis at the statistical significance level of 0.05 ( P < 0.01).

Ethical consideration

This study is the part of the research project (IR.KUMS.REC.1397.108, No. 97056) sponsored by the Deputy of Research and Technology from Kermanshah University of Medical Sciences, Iran. The authors maintained all the protocols before performing all the procedures engaged in this study involving human participants in accordance with the ethical standards of the institutional research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

The total population comprised of 447 participants in the present study, including 215 male (48.1%) and 232 female (51.9%) students. The average age of the respondents under investigation was 23.47 ± 4.58 years, and the majority of respondents' age ranged between 19 and 24 years (69.6%). Concerning the marital status, there were 360 single participants (80.50%) in this population. The second majority of the study indicated bachelor's degree students (202 students or 45.20%), and the majority of the discipline was a school of medicine (71 students or 15.90%). The majority of the dormitory students comprised 48.30% (216/447). The study findings specified that 356 students possessed their computers (356/447 = 79.60%), and the number of students using the Internet at their dormitories comprised 205 respondents (205/447 = 45.90%). The results indicated that the majority of the students used the Internet either in the morning or in the evening (367/447 = 82.10%).

The main reason for using the internet application was chatting with friends and family members. The mean and standard deviation of students with internet addiction was 3.81 ± 0.88. Besides, the mean and standard deviation of students' mental health was 2.56 ± 0.33, which stated that the general mental health of students was not in good condition. Regarding the mental health of the students' sample, the study results indicated that the highest and lowest rates showed linkage to depression with a mean and standard deviation of 2.84 ± 0.21 and somatic dysfunction with a mean and standard deviation of 2.16 ± 0.79, respectively, as indicated in Table 1 . This specific study applied the Pearson's correlation coefficient to determine the relationship between the students' internet addiction and mental health. The results of the correlation matrix demonstrated that they did not statistically significantly correlate with each other ( P < 0.001, r = 0.052). The study results specified that students' depression and somatic symptoms had the highest ( P = 0.001, r = 0.166) and lowest ( P > 0.001, r = 0.006) relationships with internet addiction, as indicated in Table 2 .

Internet addiction and mental health scores for different genders

The results of Pearson’s correlation coefficient between internet addiction and mental health among students

**Correlation was significant at the 0.01 level (two tailed)

The present study aimed to investigate internet addiction and its effects on the mental health of medical students at Kermanshah University of Medical Sciences. The results of the present study demonstrated that 45.5% of students at Kermanshah University of Medical Sciences were addicted to the Internet. This finding was concurrent with the results of studies conducted by Farhadinia et al .,[ 43 ] Sepehrian and Jokar,[ 44 ] Fonia et al .,[ 27 ] and Dargahi and Razavi.[ 45 ] Those who use the Internet more than others can replace stronger relationships in real life with low-quality social relationships, thereby resulting in more loneliness and depression. To further explicate the matter, the Internet may serve as a substitute for lives without vitality. Loneliness and isolation may cause people to spend more time on the Internet, thereby decreasing the quality of their social relationships.

As for the demographic characteristics, the results demonstrated that there was a significant difference between male and female students in terms of internet addiction. In addition, 23% of male students were internet addicts, which exceeded that of female students by 22.4%. In this study, male students should be given priority in prevention programs for internet addiction. These results were consistent with the results of studies conducted by Alavi et al .,[ 30 ] Orsal et al .,[ 46 ] and Fonia et al .,[ 27 ] whereas inconsistent with the results of studies performed by Atashpour et al .[ 47 ] and Shahbazirad and Mirderikvand.[ 48 ] Male students seem to have more internet addiction than girls. In fact, the present research, in line with the findings of previous studies, shows that men are more exposed to internet addiction, not because of biological differences between the two genders, but due to different social and environmental factors to which each gender is exposed. According to the results, it seems that this finding can be an alarm at the increase in this disorder among students, and it is better that proper planning be done in this area in cooperation with university officials.

Based on the results of the present study, the mean score of male students' mental health was higher than that of female students, and no significant difference was seen between gender and mental health. However, the finding of the present study was consistent with the results of studies conducted by Taji and Verdinejad,[ 49 ] Namdar et al .,[ 50 ] and Imani et al .[ 51 ] In studies done by Asadi et al .,[ 52 ] Gorgich et al .,[ 9 ] Fonia et al .,[ 27 ] and Xu and Liu,[ 23 ] it was expressed that female students had more mental disorders than male students, which was inconsistent with the results of the present study. It should be noted that the mean score of male students' mental health was higher than that of female students, possibly due to men's ability to communicate with others in the society and university, the ability to deal with problems and difficulties, and the ability to earn money, as well as women's excessive emotional dependency on their families and lack of social security in the society.

The results of this study revealed that half of the students had poor mental health, and there was a significant difference between the mean scores of depression and internet addiction. These results were consistent with the results of studies done by Nastizai,[ 28 ] Anderson et al .,[ 12 ] and Chung and Wong.[ 53 ] In a study done by Abdollahi on nursing students at Tehran University of Medical Sciences, it was shown that 32.1% of students had suspected mental disorders, which was 29.7% in women and 34.3% in men.[ 54 ] In addition, Rafiei and Mosavipour showed that 67.9% of students at Arak University of Medical Sciences had symptoms of mental disorders, and only 32.1% of them had normal mental health.[ 55 ] Similarly, Masoudi et al . concluded that 52.4% of students at Tehran University of Medical Sciences were suffering from mental health disorders.[ 56 ] Similarly, in a study done by Yavarian et al . on students at Uromia University of Medical Sciences, it was demonstrated that 45.8% of students had different degrees of mental health disorders. In their study, it was also revealed that 10%, 0.5%, and 3.2% of students had severe disorders in terms of somatic symptoms, anxiety and insomnia, and depression, respectively. This finding was concurrent with the results of the present study.[ 57 ] It seems that the different prevalence of psychiatric disorders in various studies can be attributed to several factors, including the differences in groups under study.

The results revealed that internet addiction and mental health were negatively related, which was consistent with the results of studies conducted by Shahbazirad and Mirderikvand,[ 48 ] Fallah Mehneh,[ 58 ] and Mousavomoghadam et al .[ 59 ] Hosseini et al . showed that 4.2% of students at Payam Noor University of Charm had severe addiction to the Internet. In addition, a significant relationship was observed between internet addiction and mental health.[ 60 ] Similarly, in a study performed by Farhadinia et al ., it was demonstrated that internet addiction and mental health significantly correlated among the students of Lorestan University of Medical Sciences,[ 43 ] which seems to lay the groundwork for the internet addicts. Some people resort to the Internet to reduce their depression. In this case, the Internet may provide a substitute for the joyless lives of depressed people, or they may get depressed as a result of internet addiction. In other words, the internet addicts will experience the negative consequences, such as depression.

In justifying the relationship between depression and internet addiction, it can be expressed that the excessive use of the Internet can lead to social isolation and depression through reducing familial, social, and local connection. Therefore, depression may occur as a result of internet addiction, and in this case, the internet addicts experience the resultant negative consequences, such as depression.[ 28 ]

The results revealed that the five major predictors of vulnerability to internet addiction in university students were as follows: the key reason for using the Internet, faculty, depression, the main place for using the Internet, and somatic symptoms.

Limitations of the study

Concerning the limitations, this study evaluated medical students in the classrooms based on different groups. The discussions among students could present bias in their feedback. There was no face-to-face interview session, and the data set reported on a self-reported questionnaire, which increases the risk of social desirability biases among medical students of medicine, dentistry, and pharmaceutical departments at self-governing Education Incubator of Kermanshah, Iran. The limitations of the current study specify that researchers can consider a large sample size based on medical students as well as other departments to execute their investigations in western part of Iran. Scholars can find experimental and longitudinal methods with larger samples to examine different results.

Conclusions

According to the findings of the present study, it can be concluded that students' excessive use of the Internet leads to depression, anxiety, and reduced mental health, thereby affecting their academic performance. Hence, it is suggested that further monitoring and control be exercised on how the Internet is used by university students, and they should be informed of the detrimental effects of this technology in the case of misuse or overuse. The findings of the present study are also indicative of the significance of preventative measures in the form of educational and counseling programs for students regarding the proper and practical use of the Internet. In addition, addressing the issues and problems relating to communication technologies, such as the Internet, can lay the groundwork for proper education and instigate parents' and families' further attention to proper and effective use of the Internet.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

Acknowledgments

The authors hereby bestow their gratitude to the students in the for-profit Schools of Medicine, Dentistry, Paramedics, Nursing and Midwifery, Paramedicine, Nutrition Sciences and Food Industries, Public Health and Self-Governing College in Kermanshah University of Medical Sciences for their participation in the present study.