ArticleJournal of behavioral addictions2024
Genetics of gambling disorder and related phenotypes: The potential uses of polygenic and multifactorial risk models to enable early detection and improve clinical outcomes.
Article in Journal of behavioral addictions, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Parental Influence on Adolescent Gambling: the Role of Communication, Rules, and Social Support.Journal of gambling studies · 2026Article
- Chasing among older-aged gamblers: the role of mentalizing and psychological distress.Frontiers in psychiatry · 2024Article
- Transforming global approaches to chronic disease prevention and management across the lifespan: integrating genomics, behavior change, and digital health solutions.Frontiers in public health · 2023Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Gambling Disorder (GD) is an impactful behavioural addiction for which there appear to be underpinning genetic contributors. Twin studies show significant GD heritability results and intergenerational transmission show high rates of transmission. Recent developments in polygenic and multifactorial risk prediction modelling provide promising opportunities to enable early identification and intervention for at risk individuals. People with GD often have significant delays in diagnosis and subsequent help-seeking that can compromise their recovery. In this paper we advocate for more research into the utility of polygenic and multifactorial risk modelling in GD research and treatment programs and rigorous evaluation of its costs and benefits.
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