Scrutinizing the Gateway Relationship Between Gaming and Gambling Disorder: Scoping Review With a Focus on the Southeast Asian Region
Bibliographic record
Abstract
Background: The gaming and gambling overlap has intensified with new evidence emerging. However, the relationship between gaming and gambling in the digital space is still inconclusive, especially in resource-limited Asian countries. Objective: This study aims to review available evidence on the possible interaction and focuses specifically on the gateway interaction between gambling and gaming. Additionally, this review delves into the state of evidence from the Southeast Asian region, providing an in-depth analysis of this underexplored area. Methods: We performed a scoping review by sifting through the publications in five databases. We focused on the gateway interaction and provided a possible pathway model, while two other convergence relationships were provided for comparison. Results: The scoping review identified a total of 289 publications, with the majority being empirical (n=181), although only 12 studies used longitudinal designs. A significant proportion of the publications (n=152) concentrated on the correlation or comorbidity between gaming and gambling. Most of the evidence has originated from Global North countries, with very limited research emerging from Southeast Asia (n=8). The most commonly studied gambling-like element in video games was loot boxes (n=105). Other elements investigated included esports betting, skin betting, token wagering, gambling advertisements, and gambling-like features. Several longitudinal studies have highlighted the risk of the gateway effect associated with gamblification involvement. However, emerging evidence suggests more nuanced underlying mechanisms that drive the transition from gaming to gambling. Conclusions: Overall, there is early evidence of linkage between gambling and gaming, through shared structural and biopsychosocial characteristics. This association possibly extends beyond disparate comorbidity, as such engagement in one activity might influence the risk of partaking in the other behavior. The field requires further longitudinal data to determine the directionality and significant precipitating factors of the gateway effect, particularly evidence from Asia.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".