One size does not fit all. Should gambling loss limits be based on income?
Langeland, Elias; Johnsen, Ingvild Faxvaag; Sømme, Kaja Kastrup; Morken, Arne Magnus; Erevik, Eilin K.; Kolberg, Eirin; Jonsson, Jakob; Mentzoni, Rune Aune; Pallesen, Ståle
Journal article, Peer reviewed
Published version
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https://hdl.handle.net/11250/3040662Utgivelsesdato
2022Metadata
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- Department of Psychosocial Science [885]
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Sammendrag
Background: Previous research has suggested empirically based gambling loss limits, with the goal of preventing gambling related harm in the population. However, there is a lack of studies relating gambling loss limits to individual factors such as income. The current study examines whether gambling loss limits should be income-specific.
Materials and methods: The dataset was derived from three representative cross-sectional surveys of the Norwegian population and consisted of 14,630 gamblers. Four income groups, based on a quartile approximation, were formed. Gambling related harm was measured with the Problem Gambling Severity Index (PGSI), and precision-recall (PR) analyses were used to identify loss limits for the different income groups at two levels of gambling severity: moderate-risk gambling and problem gambling.
Results: For both levels of gambling severity, we found the lowest income group to have the lowest gambling loss limits, and the highest income group to have the highest loss limits, which compared to the loss limits for the total sample, were lower and higher, respectively. Calculating the cut-offs for moderate-risk gamblers, we found a consistently ascending pattern from the lowest to the highest income group. Calculating the cut-offs for problem gamblers, we found a similar pattern except for the two middle income groups.
Conclusion: The results suggest that income moderates empirically derived gambling loss limits. Although replication is required, income-based gambling loss limits may have higher applied value for preventing gambling related harm, compared to general loss limits aimed at the entire population.