Author:
Kimberly S. Young
Kimberly S. Young
Center for Internet Addiction, St. Bonaventure University, St. Bonaventure, NY, 14778, USA
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Abstract
Background and Aims
Internet Gaming Disorder, a subtype of Internet Addiction, is now classified in Section 3 of the DSM-5. Cognitive behavioral therapy (CBT) has been suggested in treating Internet addiction as this modality has been shown to be an effective treatment for similar impulse control disorders. Given the daily and necessary use of the Internet and technology in general compared to other compulsive syndromes, a specialized form of CBT has been developed called Cognitive-Behavioral Therapy for Internet Addiction (CBT-IA). CBT-IA is a comprehensive three phase approach that includes behavior modification to control compulsive Internet use, cognitive restructuring to identify, challenge, and modify cognitive distortions that lead to addictive use, and harm reduction techniques to address and treat co-morbid issues associated with the disorder.
Methods
As the first model of its kind, this study examines 128 clients to measure treatment outcomes using CBT-IA. Clients were evaluated using the Internet Addiction Test (IAT) to classify subjects and were administered twelve weekly sessions of CBT-IA. Treatment outcomes were measured at the end of the twelve weeks, one-month, three months and at six month post-treatment.
Results
Results showed that over 95% of clients were able to manage symptoms at the end of the twelve weeks and 78% sustained recovery six months following treatment.
Discussion and Conclusions
Results found that CBT-IA was effective at ameliorating symptoms associated with Internet addiction after twelve weekly sessions and consistently over one-month, three months, and six months after therapy. Further research implications such as investigating long-term outcome effects of the model with larger client populations and treatment differences among the subtypes of Internet addiction or with other cultural populations using CBT-IA are discussed.
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| 2022 | |
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| Web of Science | |
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5713 |
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Psychiatry (SCIE) 18/155 |
| Impact Factor without Journal Self Cites |
7.2 |
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8.9 |
| Journal Citation Indicator | 1.42 |
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Psychiatry 35/264 |
| Scimago | |
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69 |
| Scimago Journal Rank |
1.918 |
| Scimago Quartile Score | Clinical Psychology Q1 Medicine (miscellaneous) Q1 Psychiatry and Mental Health Q1 |
| Scopus | |
| Scopus Cite Score |
11.1 |
| Scopus Cite Score Rank |
Clinical Psychology 10/292 (96th PCTL) Psychiatry and Mental Health 30/531 (94th PCTL) Medicine (miscellaneous) 25/309 (92th PCTL) |
| Scopus SNIP |
1.966 |
| 2021 | |
|---|---|
| Web of Science | |
| Total Cites WoS |
5223 |
| Journal Impact Factor | 7,772 |
| Rank by Impact Factor | Psychiatry SCIE 26/155 Psychiatry SSCI 19/142 |
| Impact Factor without Journal Self Cites |
7,130 |
| 5 Year Impact Factor |
9,026 |
| Journal Citation Indicator | 1,39 |
| Rank by Journal Citation Indicator |
Psychiatry 34/257 |
| Scimago | |
| Scimago H-index |
56 |
| Scimago Journal Rank |
1,951 |
| Scimago Quartile Score | Clinical Psychology (Q1) Medicine (miscellaneous) (Q1) Psychiatry and Mental Health (Q1) |
| Scopus | |
| Scopus Cite Score |
11,5 |
| Scopus CIte Score Rank |
Clinical Psychology 5/292 (D1) Psychiatry and Mental Health 20/529 (D1) Medicine (miscellaneous) 17/276 (D1) |
| Scopus SNIP |
2,184 |
| 2020 | |
| Total Cites | 4024 |
| WoS | |
| Journal Impact Factor |
6,756 |
| Rank by | Psychiatry (SSCI) 12/143 (Q1) |
| Impact Factor | Psychiatry 19/156 (Q1) |
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| without | |
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| Items | |
| Total | 74 |
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| Total | 12 |
| Reviews | |
| Scimago | 47 |
| H-index | |
| Scimago | 2,265 |
| Journal Rank | |
| Scimago | Clinical Psychology Q1 |
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| Scopus | 3593/367=9,8 |
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| Scopus | 2,026 |
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| 2019 | |
|---|---|
| Total Cites WoS |
2 184 |
| Impact Factor | 5,143 |
| Impact Factor without Journal Self Cites |
4,346 |
| 5 Year Impact Factor |
5,758 |
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0,587 |
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| Total Reviews |
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