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Record W4406529940 · doi:10.2196/59740

Scrutinizing the Gateway Relationship Between Gaming and Gambling Disorder: Scoping Review With a Focus on the Southeast Asian Region

2025· review· en· W4406529940 on OpenAlexvenueno aff
Kristiana Siste, Daniel L. King, Enjeline Hanafi, Lee Thung Sen, Belinda Julivia Murtani

Bibliographic record

VenueJMIR Serious Games · 2025
Typereview
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsGateway (web page)Focus (optics)Southeast asiaPsychologyAdvertisingGeographySociologyBusinessEthnologyComputer scienceWorld Wide Web

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.173
GPT teacher head0.437
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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