The Scale Shaping Gambling Policy

It began, as many international standards do, in Canada. In 2001, researchers Rachel Ferris and Harold Wynne set out to build a national tool that could measure gambling behaviour and harm across the population. Their creation, the Problem Gambling Severity Index (PGSI) would go on to become one of the most widely used instruments in gambling research worldwide.

Two decades later, this nine-question survey remains the foundation of gambling prevalence data in countries from Canada to Australia, and notably, in the United Kingdom. It is the metric that underpins official government figures on “problem gambling,” informs regulatory debate, and shapes public perceptions of gambling harm.

But as gambling has developed, particularly online, the question is not whether the PGSI should exist, but how it can be better understood, refined, and contextualised to produce fair, evidence-based insights that benefit both players and operators, ensuring gambling remains an enjoyable form of entertainment while supporting sustainable player relationships and long-term value.

The PGSI is straightforward by design. It asks respondents how often they have, in the past 12 months, bet more than they could afford to lose, felt guilt, chased losses, or been criticised by others for gambling. Each answer earns a numerical score, and the sum places respondents into one of four categories: non-problem, low-risk, moderate-risk, or problem gambler.

SCORE	CATEGORY	MEANING
0	Non-problem gambler	No negative consequences
1–2	Low-risk gambler	Minimal harm
3–7	Moderate-risk gambler	Some harm or risk
8+	Problem gambler	Significant harm likely

This simplicity is part of its success. It allows governments to track trends over time, compare data internationally, and ensure that policy debates are grounded in evidence rather than assumption. In the United Kingdom, the UK Gambling Commission uses PGSI data as the official measure of gambling harm. Its prevalence surveys show a remarkably stable picture: around 0.2 to 0.3 percent of adults are categorised as “problem gamblers,” with another 2 to 3 percent classed as “at risk.”

Such figures are often used to illustrate that, while gambling is common, severe gambling-related problems remain statistically rare. This is a reassuring conclusion for policymakers and operators alike, and one that helps frame responsible gambling within a manageable, evidence-based framework.

“It’s a blunt instrument. Useful, yes, but potentially misleading if you don’t understand what it’s actually measuring,”

However, no measure is without limitation. Researchers have identified several areas where the PGSI might be refined or better interpreted.

One recurring concern is that the index mixes behaviour and consequence. Some questions describe potential risk factors (like chasing losses), while others measure actual harm (like financial or health impacts). This blending can make it difficult to distinguish between those who gamble frequently but without detriment, and those whose gambling has led to genuine distress or loss.

Another issue lies in cut-off thresholds. The PGSI’s risk categories, low, moderate, and problem, were derived from statistical distributions, not clinical definitions. As a result, small changes in scoring can move an individual between categories, making it difficult to track meaningful trends over time.

Then there is the self-reporting challenge. Respondents must recall a year of gambling activity, often through the lens of personal emotion or social expectation. Some understate their gambling to avoid stigma; others overstate to justify loss. The data’s accuracy, therefore, depends heavily on honesty and memory.

Finally, the PGSI’s cultural origins matter. It was built around Western notions of individual responsibility and guilt, which may not align with how gambling is perceived in other cultures. Similarly, gender and generational differences affect how people interpret questions about money, criticism, or control.

These are not reasons to dismiss the PGSI, they are reasons to improve it.

What the PGSI offers, despite its imperfections, is a unified framework. It gives regulators, researchers, and operators a common language for discussing gambling-related harm. Without it, international comparisons would be nearly impossible, and policy decisions could become fragmented or politically driven, as arguably, they often are.

“The PGSI is trying to capture both why people gamble and what happens when they do. Those are related, but not the same thing,”

Yet as gambling continues to diversify, particularly online where engagement data is more detailed and dynamic, there is a growing opportunity to complement the PGSI with more sophisticated tools. Behavioural analytics, for instance, can reveal early indicators of risky play far more precisely than self-report surveys. When combined with the PGSI, such data could offer a far richer understanding of how and why harm occurs, and for whom.

A unified approach to measuring harm remains essential, but it must evolve. Future versions of the PGSI could include improved weighting of behavioural versus harm indicators, more cultural adaptability, and a clearer focus on context. Who is completing the questionnaire, and under what circumstances.

Most importantly, this should not be the domain of academics or regulators alone. The gambling industry, particularly online operators who now hold unprecedented behavioural data, should be part of the discussion. Collaboration between researchers, regulators, and industry could ensure that measurement tools are not only accurate, but also meaningful, actionable, and fair.

The Problem Gambling Severity Index brought structure to an area once dominated by speculation, and it remains the best-known benchmark for assessing gambling harm. But as with any standard, its greatest strength, simplicity, is also its greatest weakness.

A path forward is not to discard the PGSI, but to refine it, to recognise that measurement itself shapes perception, and that understanding harm is a shared responsibility.

The PGSI remains a flawed but valuable framework for assessing gambling harm at a population level. However, it is largely a retrospective tool, identifying harm only once it has occurred. Online gambling is rich in behavioural data and patterns that can be tracked in real time, so there is an opportunity to move from measuring harm after the fact to detection and prevention if it emerges.

Considering prevention is better than the cure, perhaps focus should shift to Markers of Harm. Rather than waiting for a player to self-report harm, they look at what the data already shows; changes in spending, frequency, or the rhythm of play. A player logging in more often at odd hours, or depositing larger amounts in shorter bursts, may be telling a story long before they ever fill out a questionnaire. The value lies in acting on those quiet warnings before they turn into something more serious.

By integrating such data analytics into player monitoring systems, operators can act sooner and with greater precision. The aim is not to restrict play unnecessarily, but to ensure that gambling remains what it should be, a form of entertainment. Early identification allows for timely interventions such as messages of support, temporary cooling-off options, or tailored responsible gambling tools, which protect players while maintaining trust and engagement.

This proactive approach also aligns commercial and social goals. Sustainable play enhances customer wellbeing, strengthens brand integrity, and increases player lifetime value through long-term engagement rather than short-term loss.

The relationship between the PGSI and Markers of Harm should not be seen as competitive, but collaborative. With refinement, the PGSI can assist tracking prevalence and informing public policy, while Markers of Harm bring those insights to life operationally. Together, they move the industry from measuring harm after the fact to managing risk before it happens, keeping play enjoyable, data transparent, and regulation grounded in evidence. In the end, it is balance that serves every stakeholder best.