Gambling consumption and harm: a systematic review of the evidence

Abstract

The total consumption model (TCM) postulates a close link between total consumption and levels of harm within the population, which has important implications for prevention. This review aimed to explore evidence relating to the application of the TCM and theoretical elements associated with it (i.e. the distribution of harms; the concentration of consumption) to gambling by reviewing evidence pertaining to the distribution of harms across the population; the concentration of gambling consumption; and evidence of the validity of the TCM in gambling. Systematic literature searches were performed using MEDLINE, PsycINFO, and Web of Science databases, restricted to publications between January 1, 2010, and March 29, 2023. The search identified seven studies examining risk curves for gambling harm, of which only two employed continuous consumption measures. This nascent literature suggests mixed evidence for the relationship between gambling consumption (e.g. losses, frequency, expenditure, and expenditure as a percentage of income) and risk of harm. Five publications found that the concentration of gambling consumption was high among those experiencing gambling harms, with some evidence that spending is more concentrated for certain games (e.g. online casinos) than for others (e.g. lotteries). Finally, four studies assessed the TCM, suggesting close association between gambling consumption and problem gambling, lending empirical support to the validity of the TCM. However, robust evidence is nascent and further research is required to assess these relationships.

Keywords:

• Total consumption model
• gambling consumption
• risk of harm
• risk curves
• concentration
• gambling expenditure
• prevention

Acknowledgments

We thank Fiona Dobbie for providing important insights at the early stages of this project, and Daria Ukhova for valuable feedback on editing of the text.

Ethical statement

The research in this paper does not require ethics board approval.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Data from Global Betting and Gaming Consultants (GBGC), owned by Regulus.

2 Note: Betting trajectory is the estimated slope coefficient of betting frequency on the amount wagered. Daily betting variability is the standard deviation of betting frequency on the amount wagered. Net outcome of gambling is the difference between total amount wagered and total winnings. Number of different types of gambling refers to ten gambling forms: Lotto, EGMs, Scratch tickets, Betting, Betting on own performance, Lottery, Poker, Other card games, Bingo, and Casino gambling. Continuous gambling types are skill-based gambling forms which have a high event frequency (e.g., EGMs). Number of gambling activities is the number of gambling types participated in (e.g., in the last month). Percent of income spent on gambling is the proportion of income spent on gambling. Frequency of gambling refers to the number of days (e.g., per month) individuals participates in gambling. Gambling expenditure is the total (e.g., weekly, monthly) expenditure on gambling.

3 Note: Problem Gambling Severity Index (PGSI), South Oaks Gambling Screen (SOGS), NORC or related DSM Screen for Gambling Problems including the Brief Biosocial Gambling Screen (NORC or related DSM Screen measures), Canadian Problem Gambling Index (CPGI), Lie/Bet Questionnaire (Lie/Bet), Problem and Pathological Gambling Measure (PPGM), Short Gambling Harm Screen (SGHS), and concentration of expenditure- top 1%, top 10%, and top 20%.

4 Based on Pareto (1896). Cours d'économie politique: professé à l'Universi̧té de Lausanne (Vol. 1 and 2). F. Rouge.

Additional information

Funding

This study was supported by the Wellcome Trust.