Adolescent Online Gaming Disorder, Comorbidity, Neural Mechanism and Psychotherapy of Internet Gaming Disorder
Bibliographic record
Abstract
Due to the sharp increase in the number of online game addicts, this paper systematically reviewed the neural mechanism, comorbidity, and psychotherapy of adolescent online game addicts. Online gaming disorder (IGD) is a new concept, which has been studied in many aspects in different literature. The analysis of existing research results shows that inhibition control and risk behaviors of adolescents with online gaming addiction are increased, and depression and dissociative experience is a common comorbidity of Internet game disorder. Single psychotherapy cannot effectively treat adolescents with online gaming addiction. Comprehensive psychological intervention based on cognitive behavior therapy is more effective for adolescent participants. This paper aims to analyze the existing literature, systematically review the neural mechanism, comorbidity, and psychotherapy of adolescent online game disorder, and provide guidance for future research in this emerging field. At the end of this paper, these suggestions will help scholars find problems and gaps that have not been fully explored, and these problems and gaps can become the basis for further research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".