Bidirectional Associations Between Self-Reported Gaming Disorder and Adult Attention Deficit Hyperactivity Disorder: Evidence From a Sample of Young Swiss Men
Bibliographic record
Abstract
Background Gaming disorder (GD) has been shown to co-occur with attention deficit hyperactivity disorder (ADHD), yet few studies to date have investigated their longitudinal associations. Method The sample included 5067 young Swiss men (mean age was 20 years at wave 1 and 25 years at wave 3). Measures were the Game Addiction Scale and the Adult ADHD Self-Report Scale (6-item screener). Longitudinal associations were tested using autoregressive cross-lagged models for binary measures of GD and ADHD, as well as continuous measures for GD score and ADHD subscales of inattention and hyperactivity. Results ADHD at age 20 increased the risk for GD at age 25 (probit=.066 [.023, .109]; p=.003). GD at age 20 also increased the risk for ADHD at wave 3 (probit=.058 [.013, .102]; p=.011). Only the ADHD inattention subscale showed a bidirectional longitudinal relationship with the GD score (standardized Beta from inattention at age 20 to GD score at age 25: .090 [.056, .124]; p < .001; from GD score at age 20 to inattention at age 25: .044 [.016, .071]; p = .002), whereas associations between the hyperactivity subscale and GD were not significant. Discussion GD had bidirectional longitudinal associations with ADHD, in that ADHD increased the risk for GD and GD increased the risk for ADHD, and they may reinforce each other. These associations may be linked more to the inattention ADHD component than to the hyperactivity ADHD component. Individuals with ADHD or GD should be screened for the other disorder, and preventive measures for GD should be evaluated in individuals with ADHD.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".