Gambling Harm Treatment and Support in Scotland: Current provisions and future directions

Annex 3: Exploring access to support services for gambling-related harm in at-risk populations

Author: Laura Macdonald

This report aims to map access to in-person support services for gambling-related harm across Scotland and identify populations with limited geographical access, with a particular focus on socioeconomically disadvantaged groups at elevated risk of harm. Understanding the geographic distribution of support services and their relationship to at-risk populations is critical to informing equitable service provision and policy decisions.

Methods

Data Sources

Support services for gambling-related harm were identified across 92 venues, comprising peer-led mutual aid groups (e.g., Gamblers Anonymous) and a range of third-sector organisations. Over two-thirds of venues were run by Gamblers Anonymous, suggesting that most provision reflects peer-support models rather than structured psychological therapies (e.g., Cognitive Behavioural Therapy or other talking therapies). As detailed service information was not available, variation in service type across venues could not be confirmed.

Gambling-related harm support services venue addresses (2026) were obtained from organisations that completed the survey and provided location data. Each venue was counted once regardless of multiple meetings. Venues were geocoded in ArcGIS Pro 2.7.0 using full address matching where available. Four were mapped using postcodes.

Data Zone level (N=6,976) population and Census data were obtained:

• Scottish Index of Multiple Deprivation (SIMD) – provided income domain rank (i.e., based on those receiving income-related benefits or tax credits) and employment domain rank (i.e., based on those who are unemployed or not involved in the labour market due to ill-health or disability - also categorised into quintiles where quintile 1 = most deprived 20% of areas).
• Census (2022): - provided % unemployed, % with no qualifications, % social renters, % providing unpaid care.
• 2022 Mid-year population estimates and six-fold urban/rural categorisation - Large Urban Areas, Other Urban Areas, Accessible Small Towns, Remote Small Towns, Accessible Rural and Remote Rural classifications were used to characterise settlement context
• Population-weighted centroids from Data Zone Centroids 2011 and Data Zone Boundaries 2011 – provided data zone geographic centre of population.

Note: 2011 Data Zones were used as they link to both SIMD and Census data, which capture complementary dimensions of area-level deprivation, and are associated with elevated gambling-harm risk. See supplementary Table 1 on page 86.

Accessibility and Deprivation

Drive-distance catchments around support service venues were created in ArcGIS Pro at three thresholds: ‘good’ access (<10 miles), ‘limited’ access (10-20 miles), and ‘poor’ access (>20 miles).

The 10-mile threshold was informed by feedback from service providers, who indicated that approximately 90% of their clients travelled up to 10 miles to access support. The 20-mile threshold was used for sensitivity analysis to identify the most critically underserved areas. Drive-distance rather than drive-time was used as travel time varies considerably between urban and rural contexts, whereas distance provides a more consistent measure across Scotland's diverse geography. Data zone accessibility was classified dependent on whether their population centroids fell within good, limited, or poor access catchments.

Socioeconomic and deprivation characteristics were compared between good, limited, and poor access data zones, using comparisons of mean percentages of each of the four Census variables and of the income deprivation and employment deprivation ranking (rank 1=most deprived).

Characterising At-Risk and Critical Risk Areas

Data zones were flagged as 'at-risk' (for gambling-related harm) if they met all three of the following criteria:

• Population-weighted centroid located >10 miles from at least one venue, AND
• In the most deprived quintile (quintile 1) for both SIMD income and employment domains, AND
• Above the Scotland median for at least two of four Census variables.

Data zones were flagged as 'critical risk' if they met the same criteria but with poor access (>20 miles).

Results

Drawing on both the mapped locations (see Maps 1a and 1b) and the detailed list of venue addresses provided by service providers, support services for gambling-related harm in Scotland are heavily concentrated in the Central Belt. The pattern is overwhelmingly urban and broadly mirrors population density, with provision located where most of the population resides.

The largest concentration is in Greater Glasgow and the west of Scotland, with extensive coverage across Glasgow and surrounding areas including Rutherglen, East Kilbride, Bishopbriggs, Kirkintilloch, Clydebank, Dumbarton, Paisley, Erskine and Greenock/Inverclyde. Lanarkshire is also represented (Motherwell, Hamilton, Coatbridge and Airdrie). A second concentration is centred on Edinburgh and the Lothians, with multiple sites across the city and in Musselburgh, Broxburn, Bathgate, Livingston and Whitburn. Provision extends through the Forth Valley (Falkirk, Larbert, Stirling) and into Fife (Kirkcaldy, Dunfermline), Perth and Dundee, with additional sites in Arbroath and Broughty Ferry.

Beyond the Central Belt, services are present in other regional urban centres, including Aberdeen and Peterhead in the North-East; Inverness and Elgin in the Highlands and Moray; and across Ayrshire (Kilmarnock, Ayr, Irvine, Troon, Ardrossan, West Kilbride, Girvan and Hurlford). Dumfries is represented in Dumfries & Galloway, and Kelso provides limited coverage in the Borders.

However, despite this broader spread, provision remains sparse across much of Scotland’s rural and island areas. Coverage across the Highlands is largely limited to Inverness and Elgin, with no services in the Western Isles, Orkney or Shetland, and little presence across large parts of Argyll and Bute or the wider Highland region. While Ayrshire has multiple sites, large rural areas between towns remain without local provision. Overall, the spatial pattern continues to reflect population density, with strong urban clustering and comparatively limited rural accessibility.

Accessibility and Deprivation

Most of Scotland's population (around 81%) lives within 10 miles of a support service (see Table 1). However, over one million people (around 19%) must travel more than 10 miles to access services, including 440,410 people (around 8%) who live more than 20 miles from the nearest venue.

Map 2 shows driving distance catchments around service venues. The lighter shading shows areas within 10-20 miles of a service venue (limited access), the darker shading indicates good access (< 10 miles). The geographic inequity is stark, with urban residents having multiple nearby options while those in more rural communities may face longer journeys to access in-person services.

The findings indicate that areas with good access to gambling-related support had higher percentages of populations as social renters, unemployed and unpaid carers, and were more income and employment deprived (lower ranking) compared to areas with limited or poor access (see Table 2). This suggests that populations exhibiting higher area-level risk markers generally reside within areas of good access.

Note: All between-group differences significant at p<0.001 (ANOVA). Mean and median values similar across all indicators, suggesting relatively symmetrical distributions.

However, in comparison to limited access areas, poor access areas showed slightly higher mean percentages of social renters (17.6% vs 16.3%), no qualifications (17.9% vs 16.1%), and unpaid carers (11.8% vs 11.6%), and were also more income (3877.8 vs 4097.2) and employment (3895.2 vs 4086.0) deprived, i.e. had a lower ranking.

Characterising At-Risk and Critical Risk Areas

Of all data zones, around 17% (N=1,213) were in the most deprived quintiles for income and employment combined and above the Scotland median for at least two Census variables (see Table 3). Of these, 70 data zones face compounded access and deprivation barriers: 47 data zones (32,665 people) are 'at-risk' (limited access, 10-20 miles), and 23 data zones (13,786 people) are at 'critical risk' (poor access, >20 miles).

Table 4 shows that support services are reaching some highly deprived populations, as evidenced by areas that meet deprivation criteria but have good access (<10 miles). At-risk and critical-risk areas exhibit comparable deprivation levels to these accessible areas, suggesting that poor geographic access, rather than greater deprivation, is the distinguishing barrier. However, compared to at-risk category areas, critical risk areas show slightly elevated mean percentages of social renters (49.4%), and lower income (765) and employment (762) deprivation ranks, which highlights greater deprivation (at-risk areas - social renters: 47.1%, income rank: 840, employment rank: 817).

Note: All between-group differences significant at p<0.001 (ANOVA). Mean and median values similar

across all indicators, suggesting relatively symmetrical distributions.

Urban-Rural Distribution

Around 30% of the 47 at-risk data zones were located in East Ayrshire (N=14), six in South Lanarkshire, five in Argyll and Bute, and fewer numbers in a number of other local authorities, with most located in areas classified as ‘Accessible Small Towns’ and ‘Other Urban Areas’ (see Table 5). No at-risk data zones were located in Large Urban Areas. See Map 3 for at-risk (orange) and critical risk (navy) data zones.

Critical risk data zone areas were located in the following Local Authorities: three in Argyll and Bute, seven in Dumfries and Galloway, 10 in Highland, and three in the Scottish Borders (i.e., 17 Remote Towns, three Remote Rural, and three Other Urban Areas). See supplementary Table 1 on page 84 for a list of these data zones with key information.

Discussion

This analysis reveals that, while the geographic distribution of support services for gambling-related harm generally favours more deprived areas with higher gambling-harm risk populations generally having good access to support, significant gaps remain for specific at-risk communities. Key findings include:

• Most (81%) of Scotland's population lives within 10 miles of a support service, but over 1 million people face travel distances exceeding 10 miles.
• Areas with access within 10 miles are characterised by significantly higher socioeconomic deprivation, suggesting support service placement generally aligns with need.
• However, 70 data zones, with a total population of 46,451 people, combine ‘at-risk’ socioeconomic profiles with limited or poor support service access, representing a critical service gap.
• Deprived areas at ‘critical’ risk (>20 miles) were generally in rural areas and were more income and employment-deprived than at-risk areas (10-20 miles).

Limitations

This study has several limitations that should be considered when interpreting the findings. The 10-mile and 20-mile distance thresholds may not reflect actual willingness or ability to travel, particularly given differences between urban and rural contexts. The analysis assumes private vehicle access and does not account for public transport availability or on-foot access. Population-weighted centroids represent single points rather than actual population distribution within data zones. In larger or irregularly shaped data zones, particularly in rural areas, some residents may live considerably further from the centroid, meaning accessibility could be over or underestimated for specific populations. The analysis does not account for virtual support provision (online meetings, telephone support) or other forms of gambling support beyond in-person services. Neither does the analysis distinguish between peer-support provision and clinically delivered treatment, therefore, geographic access to formal therapeutic services may be substantially more limited than suggested by venue counts alone. Finally, the use of aggregated data at data zone level means findings cannot be applied to individuals, and patterns observed at area level may not reflect the circumstances or behaviour of every person living in those areas.

Conclusion

Addressing these geographic and socioeconomic access gaps is an important equity priority in gambling-related harm reduction policy, ensuring that those at risk of harm have access to appropriate support services. While the overall pattern suggests that services are generally located in more deprived areas, the identification of 70 data zones (population 46,451) with both high deprivation and poor access (including 23 critically underserved areas) reveals specific geographic gaps requiring targeted policy intervention. Importantly, as most provision identified reflects peer-support models, access to formal, clinically delivered treatment is likely to be more limited and geographically concentrated, raising further equity considerations beyond simple venue proximity.

Acknowledgements

With thanks to the gambling support organisations for providing information on service locations.