Expert appraisal of criteria for assessing gaming disorder: an international Delphi study
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Bibliographic record
Abstract
BACKGROUND AND AIMS: Following the recognition of 'internet gaming disorder' (IGD) as a condition requiring further study by the DSM-5, 'gaming disorder' (GD) was officially included as a diagnostic entity by the World Health Organization (WHO) in the 11th revision of the International Classification of Diseases (ICD-11). However, the proposed diagnostic criteria for gaming disorder remain the subject of debate, and there has been no systematic attempt to integrate the views of different groups of experts. To achieve a more systematic agreement on this new disorder, this study employed the Delphi expert consensus method to obtain expert agreement on the diagnostic validity, clinical utility and prognostic value of the DSM-5 criteria and ICD-11 clinical guidelines for GD. METHODS: A total of 29 international experts with clinical and/or research experience in GD completed three iterative rounds of a Delphi survey. Experts rated proposed criteria in progressive rounds until a pre-determined level of agreement was achieved. RESULTS: For DSM-5 IGD criteria, there was an agreement both that a subset had high diagnostic validity, clinical utility and prognostic value and that some (e.g. tolerance, deception) had low diagnostic validity, clinical utility and prognostic value. Crucially, some DSM-5 criteria (e.g. escapism/mood regulation, tolerance) were regarded as incapable of distinguishing between problematic and non-problematic gaming. In contrast, ICD-11 diagnostic guidelines for GD (except for the criterion relating to diminished non-gaming interests) were judged as presenting high diagnostic validity, clinical utility and prognostic value. CONCLUSIONS: This Delphi survey provides a foundation for identifying the most diagnostically valid and clinically useful criteria for GD. There was expert agreement that some DSM-5 criteria were not clinically relevant and may pathologize non-problematic patterns of gaming, whereas ICD-11 diagnostic guidelines are likely to diagnose GD adequately and avoid pathologizing.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it