Who Is at Risk for Problematic Video Gaming? Risk Factors in Problematic Video Gaming in Clinically Referred Canadian Children and Adolescents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Both Internet and offline video gaming have become a normal aspect of child development, with estimates of children playing video games ranging from 90% to 97%. Research on problematic video gaming (PVG) has grown substantially in the last decade. Much of that research has focused on community samples, while research on clinically referred children and youth is lacking. The present study includes 5820 clinically referred children and youth across 44 mental health agencies, assessed using the interRAI Child and Youth Mental Health Assessment. Logistic regression analyses revealed that older age, male sex, extreme shyness, internalizing symptoms, externalizing symptoms, and poor relational strengths are all significant predictors of problematic video gaming (PVG). Further analyses suggested that, out of the internalizing symptoms, anhedonia was predictive of PVG in both males and females, but depressive symptoms and anxiety were not predictive of PVG when controlling for other variables in the model. Moreover, proactive aggression and extreme shyness were predictive of PVG in males, but not in females. The implications of these findings are discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it