Diagnosis of<unk>  is empirically difficult. Various screening instruments have been employed to detect<unk> . Current diagnoses are faced with multiple obstacles. Difficulties Given the newness of the<unk>  and the inconsistent definition of<unk> , practical diagnosis is far from clear-cut. With the first research initiated by Kimberly S. Young in 1996, the scientific study of<unk>  addiction has merely existed for more than 20 years. A few obstacles are present in creating an applicable diagnostic method for<unk> . * Wide and extensive use of the<unk> : Diagnosing<unk>  addiction is often more complex than substance addiction as<unk>  use has largely evolved into being an integral or necessary part of human lives. The addictive or problematic use of the<unk>  is thus easily masked or justified. Also, the<unk>  is largely a pro-social, interactive, and information-driven medium, while other established addiction behaviors such as gambling are often seen as a single, antisocial behavior that has very little socially redeeming value. Many so-called<unk>  addicts do not suffer from the same damage to health and relationships that are common to established addictions. * High comorbidity:<unk>  addiction is often accompanied by other psychiatric disorders such as personality disorder and intellectual disability. It is found that<unk>  addiction is accompanied by other DSM-IV diagnosis 86% of the time. In one study conducted in South Korea, 30% of the identified<unk>  addicts have accompanying symptoms such as anxiety or depression and another 30% have a second disorder such as attention deficit hyperactivity disorder (ADHD). Another study in South Korea found an average of 1.5 other diagnoses among adolescent<unk>  addicts. Further, it is noted in the United States that many patients only resort to medical help when experiencing difficulties they attribute to other disorders. For many individuals, overuse or inappropriate use of the<unk>  is a manifestation of their depression, social anxiety disorders, impulse control disorders, or pathological gambling. It generally remains unclear from existing literature whether other psychiatric disorders is the cause or manifest of<unk>  addiction. Despite the advocacy of categorizing<unk>  addiction as an established illness, neither DSM-IV (1995) nor DSM-5 (2013) considers<unk>  addiction as a mental disorder. A subcategory of<unk> ,<unk>  gaming disorder is listed in DSM-5 as a condition that requires more research in order to be considered as a full disorder in May 2013. The WHO's draft 11th Revision of the<unk> ional Classification of Diseases (ICD-11) scheduled for publication in 2018 also include gaming disorder. There is still considerable controversy over whether<unk>  should be included in the DSM-5 and recognized as a mental disease in general. Screening instruments DSM-based instruments Most of the criteria utilized by research are adaptations of listed mental disorders (e.g., pathological gambling) in the Diagnostic and Statistical Manual of Mental Disorders (DSM) handbook. Dr. Ivan K. Goldberg, who first broached the concept of<unk>  addiction, adopted a few criteria for<unk>  on the basis of DSM-IV, including “hoping to increase time on the network” and “dreaming about the network.” By adapting the DSM-IV criteria for pathological gambling, Dr. Kimberly S. Young (1998) proposed one of the first integrated sets of criteria, Diagnostic Questionnaire (YDQ), to detect<unk>  addiction. A person who fulfills any five of the eight adapted criteria would be regarded as<unk>  addicted: # Preoccupation with the<unk> ; # A need for increased time spent online to achieve the same amount of satisfaction; # Repeated efforts to curtail<unk>  use; # Irritability, depression, or mood lability when<unk>  use is limited; # Staying online longer than anticipated; # Putting a job or relationship in jeopardy to use the<unk> ; # Lying to others about how much time is spent online; and # Using the<unk>  as a means of regulating mood. While Young's YDQ assessment for IA has the advantage of simplicity and ease of use, Keith W. Beard and Eve M. Wolf (2001) further asserted that all of the first five (in the order above) and at least one of the final three criteria (in the order above) be met to delineate<unk>  addiction in order for a more appropriate and objective assessment. Young further extended her eight-question YDQ assessment to the now most widely used<unk>  Addiction Test (IAT), which consists of 20 items with each on a five-point Likert scale. Questions included on the IAT expand upon Young's earlier eight-question assessment in greater detail and include questions such as "Do you become defensive or secretive when anyone asks you what you do online?" and "Do you find yourself anticipating when you go online again?". A complete list of questions can be found in Dr. Kimberly S. Young's 1998 book Caught in the Net: How to Recognize the Signs of<unk>  Addiction and A Winning Strategy for Recovery and Drs. Laura Widyanto and Mary McMurran's 2004 article titled The Psychometric Properties of the<unk>  Addiction Test. The Test score ranges from 20 to 100 and a higher value indicates a more problematic use of the<unk> : * 20–39 = average<unk>  users, * 40–69 = potentially problematic<unk>  users, and * 70–100 = problematic<unk>  users. Over time, a considerable number of screening instruments have been developed to diagnose<unk>  addiction, including the<unk>  Addiction Test (IAT), the<unk> -Related Addictive Behavior Inventory (IRABI), the Chinese<unk>  Addiction Inventory (CIAI), the Korean<unk>  Addiction Self-Assessment Scale (KS Scale), the Compulsive<unk>  Use Scale (CIUS), the Generalized Problematic<unk>  Use Scale (GPIUS), the<unk>  Consequences Scale (ICONS), and the Problematic<unk>  Use Scale (PIUS). Among others, the<unk>  Addiction Test (IAT) by Young (1998) exhibits good internal reliability and validity and has been used and validated worldwide as a screening instrument. Although the various screening methods are developed from diverse contexts, four dimensions manifest themselves across all instruments: * Excessive use: compulsive<unk>  use and excessive online time-use; * Withdrawal symptoms: withdrawal symptoms including feelings such as depression and anger, given restricted<unk>  use; * Tolerance: the need for better equipment, increased<unk>  use, and more applications/software; * Negative repercussions:<unk>  use caused negative consequences in various aspects, including problematic performance in social, academic, or work domains. More recently, researchers Mark D. Griffiths (2000) and Dr. Jason C. Northrup and colleagues (2015) claim that<unk>  per se is simply the medium and that the people are in effect addicted to processes facilitated by the<unk> . Based on Young's<unk>  Addiction Test (IAT), Northrup and associates further decompose the<unk>  addiction measure into four addictive processes: Online video game playing, online social networking, online sexual activity, and web surfing. The<unk>  Process Addiction Test (IPAT) is created to measure the processes to which individuals are addicted. Screening methods that heavily rely on DSM criteria have been accused of lacking consensus by some studies, finding that screening results generated from prior measures rooted in DSM criteria are inconsistent with each other. As a consequence of studies being conducted in divergent contexts, studies constantly modify scales for their own purposes, thereby imposing a further challenge to the standardization in assessing<unk> . Single-question instruments Some scholars and practitioners also attempt to define<unk>  addiction by a single question, typically the time-use of the<unk> . The extent to which<unk>  use can cause negative health consequences is, however, not clear from such a measure. The latter of which is critical to whether<unk>  should be defined as a mental disorder. Neuroimaging techniques Emergent neuroscience studies investigated the influence of problematic, compulsive use of the<unk>  on the human brain. Following anecdotal reports and the conclusion by Dr. Kimberly S. Young (1998), neuroimaging studies revealed that<unk>  contributes to structural and functional abnormalities in the human brain, similar to other behavioral and substance additions. Therefore, objective non-invasive neuroimaging can contribute to the preliminary diagnosis and treatment of<unk> . Electroencephalography-based diagnosis Using Electroencephalography (EEG) readings allows identifying abnormalities in the electrical activity of the human brain caused by<unk> . Studies revealed that individuals suffering from<unk>  predominantly demonstrate increased activity in the theta and gamma band and decreased delta, alpha, and beta activity. Following these findings, studies identified a correlation between the differences in the EEG readings and the severity of<unk> , as well as the extent of impulsivity and inattention. Classification As many scholars have pointed out, the<unk>  serves merely as a medium through which tasks of divergent nature can be accomplished. Treating disparate addictive behaviors under the same umbrella term is highly problematic. Dr. Kimberly S. Young (1999) asserts that<unk>  addiction is a broad term which can be decomposed into several subtypes of behavior and impulse control problems, namely, * Cybersexual addiction: compulsive use of adult websites for cybersex and cyberporn (see<unk>  sex addiction) * Cyber-relationship addiction: Over-involvement in online relationships * Net compulsions: Obsessive online gambling, shopping or day-trading * Information overload: Compulsive web surfing or database searches * Computer addiction: Obsessive computer game playing (see Video game addiction) For a more detailed description of related disorders please
Internet addiction disorder
Cannabis use disorder
Benzodiazepine use disorder
Pornography addiction
Benzodiazepine dependence
Polysubstance dependence
Amphetamine dependence
Stimulant use disorder