Attention Deficit Hyperactivity Disorder : what are the relationships with Gaming Disorder Symptoms and the motivations to play?
Bibliographic record
Abstract
Abstract Objectives: This study aim to evaluate the relationship between ADHD and Gaming Disorder symptoms (GDs) in an adult sample, taking inattention, hyperactivity and impulsivity dimensions into account. Secondly, this study explores the motivations for playing among gamers with a potential diagnosis of ADHD compared to non-ADHD gamers.Method: 178 participants from the general population completed an online survey. They completed the Game Addiction Scale (GAS), Game Play Motivations (GPM) and the WHO Adult ADHD Self-Report Scale (ASRS).Results: 57 participants (32%) had a probable diagnosis of ADHD, 55.1% (n = 98) had GD, including 40 with comorbid ADHD (40.8%). The inattention and impulsivity dimensions of ADHD predicted GDs. In the ADHD sample, the game mechanics and escapism motivations predicted GDs.Conclusions: ADHD and GD are strongly related in our sample, and escapism predict GDs in both the ADHD and non-ADHD samples. Implications for prevention, psychotherapy and future directions are discussed.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".