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. 2023 Jan 12:25:e40121.
doi: 10.2196/40121.

Internet-Based Self-Assessment for Symptoms of Internet Use Disorder-Impact of Gender, Social Aspects, and Symptom Severity: German Cross-sectional Study

Affiliations

Internet-Based Self-Assessment for Symptoms of Internet Use Disorder-Impact of Gender, Social Aspects, and Symptom Severity: German Cross-sectional Study

Jan Dieris-Hirche et al. J Med Internet Res. .

Abstract

Background: Internet use disorder (IUD) is a new type of behavioral addiction in the digital age. At the same time, internet applications and eHealth can also provide useful support in medical treatment.

Objective: The purpose of this study is to examine if an internet-based eHealth service can reach individuals with IUD. In particular, it should be investigated whether both male and female individuals with more severe IUDs can be reached.

Methods: Data were retrieved from the OMPRIS (online-based motivational intervention to reduce problematic internet use and promote treatment motivation in internet gaming disorder and internet use disorder) project (DRKS00019925), an internet-based motivational intervention to reduce problematic internet use and promote treatment motivation in internet gaming disorder and IUD. During the recruitment process (August 2020-March 2022), a total of 3007 individuals filled out the standardized scale for the assessment of internet and computer game addiction (AICA-S). The assessment was accessible via the project homepage. There was no preselection of participants at this stage of the study; however, the offer was addressed to people with hazardous internet use and IUDs. The web-based assessment was free and could be found via search engines, but attention was also drawn to the service via newspaper articles, radio reports, and podcasts.

Results: Out of 3007 who participated in the web-based self-assessment, 1033 (34.4%) are female, 1740 (57.9%) are male, 67 (2.2%) are diverse individuals, and 167 (5.5%) did not disclose their gender. The IUD symptom severity score showed a wide range between the AICA-S extreme values of 0 and 27 points. On average, the total sample (mean 8.19, SD 5.47) was in the range of hazardous IUD behavior (AICA-S cutoff>7.0). Furthermore, 561 individuals (18.7% of the total sample; mean 17.42, SD 3.38) presented severe IUD (AICA-S cutoff>13.5). Focusing on female and male participants, 20.9% (363/1740) of the men and 14.9% (151/1033) of the women scored above 13.5 points, which can be considered pathological IUD behavior (χ22,2773=16.73, P<.001, effect size: Cramér V=0.078). Unemployment, being in vocational training or studying at a university, and being male were significantly associated with high IUD symptoms.

Conclusions: Using a large sample, the study showed that both mildly and severely IUD-affected individuals can be reached via the internet. An internet-based eHealth offer can thus be a good way to reach patients with IUD where they are addicted-on the internet. In addition, eHealth services increase the likelihood of reaching female patients, who hardly ever come to specialized outpatient clinics and hospitals. Since social problems, especially unemployment, have a strong association with disease severity, the integration of social counseling into treatment seems advisable in terms of a multidisciplinary approach.

Trial registration: German Clinical Trials Register (DRKS) DRKS00019925; https://drks.de/search/de/trial/DRKS00019925.

Keywords: OMPRIS; eHealth; eHealth services; gaming disorder; internet addiction; internet use; internet use disorder; online self-assessment; self-assessment; telemedicine.

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Conflict of interest statement

Conflicts of Interest: The study was part of an RCT study titled “Online-based motivational intervention to reduce problematic internet use and promote treatment motivation in internet gaming disorder and internet use disorder” (OMPRIS) that is funded by the German Innovation Fund of Germany’s Federal Joint Committee. JDH obtained the funding. The authors declare that they do not receive any financial support from the industry, in particular the computer games industry.

Figures

Figure 1
Figure 1
Frequency of AICA-S scores among women and men. AICA-S: Assessment of Internet and Computer Game Addiction Scale.
Figure 2
Figure 2
Two-way ANOVA: main and interaction effects of gender and unemployment (left) or being in vocational training or studying (right). AICA-S: Assessment of Internet and Computer Game Addiction Scale.

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