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Gambling disorder and suicide risk: A meta-epidemiology study

2025· review· en· W4415679231 on OpenAlexaboutno aff
Liaoyao Wang, Xinyi Qin, Yuejie Lu, Hejing Pan, Xuanlin Li, Le Luo

Bibliographic record

VenueJournal of Psychiatric Research · 2025
Typereview
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsGambling disorderPoison controlHuman factors and ergonomicsSuicide preventionAssociation (psychology)Injury preventionOccupational safety and health

Abstract

fetched live from OpenAlex

OBJECTIVE: This meta-analysis aims to explore the relationship between gambling disorder (GD) and suicide, with a focus on the increased risk of suicidal ideation, suicide attempts, and suicide mortality in GD patients. METHODS: We systematically searched PubMed, Embase, and Cochrane databases from inception to March 2025 for observational studies examining the association between GD and suicide risk, using relevant MeSH/keywords. Study quality was assessed via the Newcastle-Ottawa Scale. Data were pooled using random-effects models in STATA 14.0, with results expressed as adjusted odds ratios (ORs) and 95 % confidence intervals (CIs). Subgroup analyses evaluated influences of study design and geographic region. RESULT: This meta-analysis included 14 high-quality observational studies, and the results of the meta-analysis were unbiased. Fourteen studies demonstrated significant associations between GD and suicide outcomes: suicidal ideation [OR = 1.58], suicide attempt [OR = 2.91], and suicide mortality [OR = 8.52]. Subgroup analysis by study design showed non-significant risk in case-control studies [OR = 1.59], but significant risk in cross-sectional [OR = 3.31] and cohort studies [OR = 4.10]. Geographically, Asian studies showed non-significant association [OR = 1.13], while significant risks were observed in Europe [OR = 4.38], North America [OR = 2.41] and Oceania [OR = 2.16]. CONCLUSION: Research shows that gambling disorders are linked to a higher risk of suicide. This association may vary across populations and contexts.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
gptMeta-epidemiology (broad)
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Meta-analysishigh
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.030
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0140.058
Bibliometrics0.0080.007
Science and technology studies0.0010.000
Scholarly communication0.0040.001
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.702
GPT teacher head0.658
Teacher spread0.044 · 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

Labeled directly by 2 models reading the full record.

Study designMeta-analysis
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

Citations3
Published2025
Admission routes1
Has abstractyes

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