A contribution to the clinical characterization of Internet addiction in a sample of treatment seekers: Validity of assessment, severity of psychopathology and type of co-morbidity
Introduction
In the last years a growing amount of literature has emerged dealing with the new phenomenon of excessive use of the Internet. It can be described as an “excessive and poorly controlled preoccupation, urge or behavior regarding the use of the computer and the Internet that leads to functional impairment and stress” [1]. As first clinical studies have demonstrated that symptoms of this kind of dysfunctional behavior are characterized by loss of control, tolerance, craving, effortless attempts to reduce Internet behavior and withdrawal, several scientists and clinicians have proposed to classify it as a new type of behavioral addiction (cf. [2], [3], [4]) calling it “Internet addiction” (IA). Neuroscientific studies on IA have supported the notion of a non-substance related addiction disorder, demonstrating that similar neurobiological circuits are involved in the process of craving (e.g. [5], [6]) and recovery from IA [7].
Epidemiological surveys have indicated that IA is a growing health problem. Community-based representative samples have found prevalence rates between 0.6% and 1.0% [8], [9]. Even increased rates of 3–15% have been reported among adolescents [10], [11]. Furthermore, addictive Internet use has been shown to cause psychosocial problems [7], [8] and is accompanied by high rates of co-morbid disorders [12] and associated psychopathological symptoms [13]. Reports have shown that IA is accompanied by social isolation and loneliness [14], difficulties in concentrating in school, university or at work [15], [10], sleep disturbances [16] and physical problems [17].
Among co-morbid disorders, depressive disorders have been most prominently related to IA [12], [18], as well as anxiety disorders, and substance-related addictions [12]. These findings have led to the proposition that IA might be regarded as a mere symptom of an underlying mental disease (e.g. [19]) rather than a diagnostic entity. However, recent studies have suggested that IA can be separated from other mental problems and therefore should be considered as an independent disorder (e.g. [11]). Based on these findings, the American Psychiatric Association (APA) has recently included Internet Gaming Disorder as a special sub-type of IA in Section 3 of the DSM-5 [20].
However, there are still uncertainties regarding diagnostic criteria of IA. While several self-report measures are available, most of them have not been validated adequately. So there is still debate on whether these instruments are reliable and valid measures to operationalize IA. While data on statistical validation are available for several self-report measures, investigations on correlations with solid external criteria are lacking (cf. [21]). Ko et al. [22], [23] proposed diagnostic criteria for IA in adolescents and young adults, based on the criteria of substance-use disorders and gambling disorder. In a first clinical validation of these criteria applied in clinical interviews they found satisfying diagnostic accuracy. Similarly, Wölfling and colleagues [24] developed a clinical interview based on six core criteria of IA (craving, withdrawal, tolerance, negative consequences, preoccupation and loss of control). In their clinical investigation on 141 IA-treatment seekers they demonstrated that these criteria led to a high diagnostic accuracy. Yet, investigations of clinical validity and accuracy of self-report measures assessing IA are still missing. This current problem in research on IA has been justly criticized (cf. [25]).
The aim of this study was to (1) conduct a first clinical validation of the Scale for the Assessment of Internet and Computer game Addiction (AICA-S) a disorder-specific self-report measure assessing IA. To that purpose sensitivity and specificity of AICA-S were determined by comparing its scoring with external clinical judgment of IA in treatment seekers. A second goal was to validate cut-offs of AICA-S derived from earlier epidemiologic surveys by conducting a ROC-analysis with external judgment on IA by therapists as an external criterion. Thirdly, we wanted to give an extensive clinical description of treatment seekers because of suspected IA. This clinical description referred to psychosocial strain, level of functioning and associated co-morbid disorders among those treatment seekers. Lastly, it was intended to present the most common sub-types of Internet addictive behavior within this clinical sample. As IA is regarded as a multifactorial construct, that can manifest itself in addictive online-gaming, shopping, searching for information or use of pornography (e.g. [26]), we wanted to quantify the frequency of those sub-types. Regarding previous findings, it was expected that addictive use of online-games will be the most prominent kind of IA (e.g. [18]).
As AICA-S has shown good psychometric properties in previous clinical (e.g. [27]) and epidemiological studies (e.g. [28], [29]), we hypothesized that there will be satisfying to good correspondence between classification of IA in patients on the basis of AICA-S-scoring and clinical rating. Concerning clinical characterization of treatment seekers, the following hypotheses were formulated: treatment seekers that fulfill the criteria for IA (according to AICA-S; IA-group) will suffer from heightened psychopathological symptoms measured by Symptom Checklist 90R [30] than those subjects that did not met criteria for IA (clinical controls; CC). Based on previous findings (e.g. [13]), it is expected that increased psychopathology will be observable in every subscale of SCL-90R. We also expect to find increased rates of co-morbid disorders in IA compared to CC (assessed by clinical interviews and by the Patient Health Questionnaire as a self-report scale [31]). With respect to the current literature [12], especially depressive and anxiety disorders are expected to be of high prevalence. Finally, we hypothesize that subjects with IA will show impairment in different areas of their life, especially decreased levels of functioning in social interactions and achievement as indicated by various studies [15], [32].
Section snippets
Recruitment, data collection and description of the sample
Between 2008 and 2013 a total of 500 persons consulted an outpatient clinic specialized for the treatment of behavioural addictions in Germany due to suspected IA. Before the diagnostic interview each patient was asked to fill out questionnaires to assess socio-demographics, pre-morbid variables, psychopathological symptoms and symptoms of IA (see chapter 2.2). Since all the data gathered in those questionnaires were not available to the diagnostician conducting the clinical interviews, he was
Internet use behaviour and clinical classification of the sample
Most of the patients reported being online every day (88.2%). On the average, 5.8 hours (SD = 3.59) were spent online on a regular weekday and 7.1 (SD = 4.31) on a weekend day or holiday. The most frequent Internet activities were doing online research (79.3% often or very often), using online games (71.4%), chatting (52.1%), mailing or instant messaging (48.2%) or using social networking sites (41.0%). Fewer patients reported surfing for pornographic material (31.8%), visiting shopping-sites
Discussion
In this clinical survey a sample of 290 treatment seekers because of signs of IA was examined regarding socio-demographic features, type of IA, psychosocial functioning, psychopathological symptoms and co-morbid disorders. A second series of analyses aimed to determine if IA assessed with a self-report measure meets diagnostic standards by showing accordance to external expert ratings on IA.
IA-patients displayed Internet gaming as the most frequent problematic Internet-related activity.
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