Report
Gambling Survey for Great Britain - technical report
Gambling Survey for Great Britain: Official statistics
Methodology
Response
Table 1 outlines the issued sample and overall response for the Gambling Survey for Great Britain (GSGB) in 2023, 2024 and 2025. The address-level response rate (19 percent in 2023 and 2024, 18 percent in 2025) was lower than the target (22 percent). To mitigate the lower response rate, boost samples were included within the 2024 and 2025 samples to increase the overall productive sample size. More detail on response can be found in the ‘A’ tables accompanying each annual report. Note that 2023 comprised 6 months of fieldwork only.
Table 1: Issued sample and overall response
| Survey year | Issued sample addresses (number) | Productive addresses response (number) | Productive addresses response (percentage) | Productive participants (number) |
|---|---|---|---|---|
| 2023 (Year 1, July 2023 to February 2024) | 37,554 | 6,636 | 19% | 9,742 |
| 2024 (Year 2, January 2024 to January 2025) | 78,866 | 13,489 | 19% | 19,714 |
| 2025 (Year 3, January 2025 to January 2026) | 88,736 | 14,603 | 18% | 20,775 |
The proportion of productive participants by sex and age are outlined in Table 2 and Table 3 respectively. More detail on individual response by sex and age can be found in Table A.3 accompanying each annual report. Table A.3 also includes further information on the age distribution of the GSGB sample compared to the population. The GSGB sample is typically older than the general population aged 18 and over.
Table 2: Productive participants by sex
| Survey year | Productive participants: Male (percentage) | Productive participants: Female (percentage) |
|---|---|---|
| 2023 (Year 1, July 2023 to February 2024) | 44% | 56% |
| 2024 (Year 2, January 2024 to January 2025) | 44% | 56% |
| 2025 (Year 3, January 2025 to January 2026) | 44% | 56% |
Table 3: Productive participants by age
| Survey year | Productive participants: 18 to 34 years (percentage) | Productive participants: 35 to 54 years (percentage) | Productive participants: 55 to 74 years (percentage) | Productive participants: 75 years and over (percentage) |
|---|---|---|---|---|
| 2023 (Year 1, July 2023 to February 2024) | 21% | 31% | 35% | 13% |
| 2024 (Year 2, January 2024 to January 2025) | 22% | 31% | 36% | 12% |
| 2025 (Year 3, January 2025 to January 2026) | 21% | 31% | 35% | 14% |
Table 4 shows response rates by mode of completion for 2023, 2024 and 2025. More detail on mode response can be found in the tables accompanying each annual report, specifically A.1 to A.6.
Table 4: Response rates by mode of completion
| Survey year | Productive participants: Online completions (percentage) | Productive participants: Postal completions (percentage) |
|---|---|---|
| 2023 (Year 1, July 2023 to February 2024) | 65% | 35% |
| 2024 (Year 2, January 2024 to January 2025) | 66% | 34% |
| 2025 (Year 3, January 2025 to January 2026) | 67% | 33% |
Sampling strategy
A high-quality sample is essential for ensuring a nationally representative survey, capable of producing robust population estimates. To achieve this, a stratified random probability sample of addresses in Great Britain (GB) was used. The target population of the survey was adults aged 18 years and over, living in private households within GB.
There is no publicly available list of the GB adult population that can be used for sampling individuals. Instead, like many national surveys, the Postcode Address File (PAF) was used, since this is currently the best-available sampling frame for large-scale general population surveys5. The PAF is compiled by the Post Office and lists postal addresses (or postcode delivery points) in the United Kingdom.
To get from a list of addresses to a selection of adults within them, involves a 2-stage selection process:
- selection of addresses from the PAF
- selection of adults within addresses.
Selection of addresses from the PAF
Prior to selection, the sample frame was ordered: this can help to reduce sampling error and increase the precision of estimates, as well as ensuring representativeness with respect to the measures used. The following measures for stratification (in order) were: Country and English region; Population density at Local Authority level and overall Index of Multiple Deprivation (IMD) score6.
At each sampled address, there may have been more than 1 dwelling and/or household. However, a random selection of households is very difficult to operationalise without an interviewer and there was no control over which household opened the invitation letter. As a result, in multi-occupied addresses, no formal household selection took place and the selection of which household took part was left to chance (that is, whichever household opened the letter). The overall proportion of multi-occupied addresses for PAF samples is very small (around 1 percent), and it is therefore unlikely to lead to any systematic error (known as bias) in the responding sample.
Selection of adults within addresses
At each address, up to 2 adults (aged 18 years and over) could take part. If the household contained 3 or more adults, the instruction was that the 2 adults with the most recent birthday should complete questionnaires.
Asking a set number of adults (in the case of this survey, 2) rather than all adults from each address to complete the survey is a well-established approach for push-to-web surveys in GB7. Most residential addresses (85 percent) contain either 1 or 2 adults, meaning that exclusion of additional adults should not introduce any notable error (known as selection bias). Under this approach, it is estimated that 93 percent of the sample are the ones that would have been selected using a random approach.
While this approach leads to a degree of within-household clustering, the effect of this is lower than if all adults per household were eligible though will be higher than if just 1 adult per household was selected. Moreover, the slight inefficiency at this stage is outweighed by the higher number of productive cases achieved from asking up to 2 adults from each address to complete the survey instead of only 1.
As recommended within the Sturgis (2024) report (opens in new tab) NatCen has continued to monitor best practice developments in the area of within household selection of adults in push-to-web surveys. With the next-birthday method balancing statistical robustness with practical compliance, NatCen still considers this the best way to select adults within households8.
Mailing strategy
As a push-to-web survey using a PAF sample, the GSGB is reliant on sending invitation letters to perspective participants. The following participant engagement strategy was used; each item was sent to selected addresses in the post:
- invitation letter including a survey-specific web page and 2 sets of login details needed to access the online questionnaire
- first reminder letter (this contained similar information to the initial invitation letter)
- second reminder letter with 2 postal questionnaires and return envelopes
- third reminder letter.
The letter also contained 2 Quick Response (QR) codes which provided an alternative method for accessing the online questionnaire. This approach was tested in the experimental phase and proved to be successful in securing target response rates. Instructions on what to do if more than 2 adults lived in the household were also included in the letter. Addresses in Wales received the letter in both Welsh and English.
The invitation letter and reminders were the main levers to convince people, including those who did not gamble, to take part. Envelopes sent to participants were branded with the HM Government logo. Additionally, all letters were carefully designed following evidence-informed participant engagement guidance for online surveys published by the Office for National Statistics (ONS) Participant engagement for push-to-web social surveys – Government Analysis Function (opens in new tab).
Experience shows that most people complete a survey within a few days of receiving the request. The time between each mailing was therefore kept as short as possible, to ensure that the request was fresh in people’s mind. A gap of around 10 days between mailings was introduced, to allow removal of responding participants from the sample for the reminders. The day of the week of the mailing was varied to allow for the fact that different people may have time for survey participation on different days of the week.
A study website, freephone number and dedicated email address were set up for participants to contact with issues or queries. The use of monetary incentives in surveys has been proven to increase response rates9. A £10 completion incentive per individual questionnaire was offered. This took the form of a Love2Shop voucher. Those who responded online were emailed a Love2Shop voucher code. Those who completed the postal questionnaire received a physical Love2Shop voucher by post10.
Data collection
The aim is to achieve a sample size of 5,000 completed individual questionnaires per wave. To ensure a spread of completions throughout the data collection period, the sample for each wave is divided into 2 batches and issued at equal intervals (with minimal overlap between batches and waves).
Table 5 outlines the fieldwork dates for each wave within each survey year (the first date for each wave refers to when invitation letters were posted; the latter date refers to the final date returned postal questionnaires were accepted).
Table 5: Fieldwork dates for each wave within each survey year
| Survey year | Wave 1 | Wave 2 | Wave 3 | Wave 4 |
|---|---|---|---|---|
| 2023 (Year 1) | 31 July 2023 to 16 November 2023 | 6 November 2023 to 19 February 2024 | N/A | N/A |
| 2024 (Year 2) | 15 January 2024 to 28 April 2024 | 8 April 2024 to 21 July 2024 | 1 July 2024 to 13 October 2024 | 23 September 2024 to 19 January 2025 |
| 2025 (Year 3) | 13 January 2025 to 27 April 2025 | 7 April 2025 to 20 July 2025 | 30 June 2025 to 31 October 2025 | 22 September 2025 to 22 January 2026 |
Questionnaire content and design
The postal questionnaire was designed to be as comparable as possible to the online questionnaire. This approach was taken to minimise the low risk of differences arising in the visual presentation of the 2 questionnaires, which could lead to differences in the ways in which questions were understood and answered (known as measurement differences).
Some differences between the 2 questionnaires remain. The online questionnaire includes complex routing and dynamic adjustment of question wording that reflects the participant’s answers to earlier questions. This cannot be replicated in the postal questionnaire. Moreover, to design a postal questionnaire that participants would find straightforward to complete within the required page limit, some questions asked in the online questionnaire are omitted from the postal version.
The questionnaires contain core and modular content. The core content is asked every wave and included some of the official statistics measures. Modular questions are included in the online questionnaire and asked on a rotating basis as required by the Commission and include topical questions or those related to the development of specific policies.
Core content includes:
- leisure activities, internet access and use
- gambling activities participated in in-person and online in the last 12 months and in the past 4 weeks11
- Problem Gambling Severity Index (PGSI)12
- consequences from gambling
- reasons for gambling
- feelings towards gambling
- health and wellbeing, including general health, smoking and drinking status, impulsivity scale, Short Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) and suicidality questions.
Modular content covers (online questionnaire only), but is not limited to:
- gambling management tools and complaints
- illegal online gambling
- consumer trust in gambling
- gambling binge
- advertising and social media
- direct marketing
- attitudes towards gambling (ATGS-8).
Demographic information captured:
- sex
- gender identity
- date of birth
- age
- ethnicity
- number of adults and children in the household
- marital or registered civil partnership status
- household income
- tenure
- education level
- economic activity13.
Data processing
Data was collected from 2 sources: an online questionnaire and a postal questionnaire. The online questionnaire data in its raw form were available immediately to the research team. However, the postal questionnaire data had to be manually recorded as part of a separate process.
Data editing and coding
The online questionnaire was designed to require minimal editing with built-in routing and checks. The postal questionnaire relied on correct navigation by participants and there was no constraint on the answers they could give. As a result, these responses could include errors, so the data was manually edited. These edits included ensuring single answer questions had only 1 answer option selected, that questionnaire routing was followed, and that answers were realistic and consistent.
A small number of questions within both questionnaires allowed participants to write in a response if none of the existing answer options applied to them. These were back-coded into existing categories or remained coded as ‘other’. If any activities reported under 'other' in the gambled in the past 12 months question were not gambling (for example raffles or premium bonds), and no other gambling activities were reported, the response to the gambled in the past 12 months question was re-coded to 'No'.
Data validation
Post-fieldwork validation was carried out. This included checks that variables from the 2 data collection modes had merged correctly into 1 dataset. As up to 2 adults per household could answer demographic questions relating to the whole household (for example, household size and information about income), there was potential for differing responses between individuals. The following rules for harmonising household responses were followed, in priority order:
- taking the most common valid answer (such as excluding ‘don’t know’, refusal)
- taking the valid answer from the oldest household member: or where this was not clear, the response of the first household member to complete a questionnaire (online completions first then postal completions).
A further step involved identifying and removing duplicate responses. For this, questionnaires were checked to see if responses to up to 2 questionnaires were very likely to be from the same individual in a household (based on exact matches for the age, date of birth, sex and name provided). Suspected duplicates were removed so that only 1 completed questionnaire from that individual was retained.
Where a household had more than 2 records, any extra cases were removed according to the following rules:
- fully completed online questionnaires took priority over postal questionnaires
- fully completed postal questionnaires took priority over partially completed online questionnaires
- partially completed online questionnaires took priority over partially completed postal questionnaires.
‘Speeders’ (individuals who completed the online questionnaire in an unrealistic amount of time for them to have properly engaged with the questions) were identified and removed from the dataset14.
It is also important to compare GSGB data against other surveys and industry data. This process includes research into reasons why there are differences between the GSGB estimates and those from other surveys (see section on Caveats for interpreting estimates generated by the Problem Gambling Severity Index (PGSI)). To enhance this process, we added a new question to the 2025 survey which was designed in collaboration with the Bingo Association to ask people where they play bingo, to help compare GSGB data against industry data on the number of people playing bingo in bingo clubs. The analysis in the report Investigating the coherence and comparability of estimates from the GSGB with industry data from the Bingo Association helps to explain the difference between participation estimates from the GSGB and industry data. The analysis concludes that when GSGB participants report playing bingo in person they are referring to a much broader definition of bingo than just playing in a traditional bingo club. When those playing in other venues (for example community venues, charity events and holiday parks) were filtered out, the estimates were much more aligned.
We also added a new question to the 2025 survey asking participants if they have registered themselves with GAMSTOP in the past 4 weeks. However, this question did not work as intended, particularly since the limited timeframe restricted comparisons of GSGB responses with GAMSTOP registration figures by financial quarter. For 2026 (Year 4), the question has been changed to a two-step format: first asking whether participants are currently registered with GAMSTOP, and then asking when they registered, using a broader timeframe from 'In the past 4 weeks' up to 'More than one year ago'. This revised approach should improve data quality and enable comparison of GSGB data with industry GAMSTOP data later this year.
The Office for Statistics Regulation’s (OSR) recent recommendation for the GSGB was that work should be undertaken to assess the coherence and comparability of GSGB data with other relevant surveys, such as the Adult Psychiatric Morbidity Survey (published June 2025) (opens in new tab) and the Health Survey for England (2024 report published January 2026) (opens in new tab). To date, discussion has focused on comparing headline prevalence estimates and explaining why these differ across studies, focusing mainly on past year rates of gambling participation or Problem Gambling Severity Index scores. Relatively little attention has been given to whether these surveys reveal consistent patterns of behaviour, such as do these differing surveys tell a coherent story about gambling. This theme has been explored in more detail by the University of Glasgow and NatCen which can be read here.
Weighting
The data were then weighted to allow for comparisons with other data sources. Each publication is accompanied by a wave specific technical report, which outlines the weighting strategy used. Further details can be found alongside each publication in the latest Gambling Survey for Great Britain publications.
Table 6 provides further technical detail on each year’s overall annual weights.
Table 6: Further technical detail on each year’s overall annual weights
| Survey year | Productive sample (number) | Design effect (number) | Sample size (number) | Efficiency percentage |
|---|---|---|---|---|
| 1 (July 2023 to February 2024) | 9,742 | 1.25 | 7,820 | 80% |
| 2 (January 2024 to January 2025) | 19,714 | 1.26 | 15,600 | 79% |
| 3 (January 2025 to January 2026) | 20,775 | 1.27 | 16,296 | 78% |
2 annual weights are produced for each survey year; this includes an overall annual weight and an online only weight. The online only weight should only be used when analysing data only collected via the online questionnaire, all other analysis should be carried out using the overall weight.
Quality assurance
A number of rigorous quality assurance processes were utilised when preparing the survey data. This included checks on the survey data carried out by NatCen data managers, such as those included in the data validation above (removing duplicates and speeders and harmonisation) as well as identifying outliers and creating and double-checking derived variables used for reporting.
The survey weights were created and checked by NatCen statisticians, with 2 statisticians working together so that one would produce the weights and a second would check them.
Tables used within the report were run using NatCen’s standard tables syntax that has been developed and refined over several years. The tables syntax and outputs were run twice and cross-checked by a second member of the research team to ensure the correct input variables had been used. The excel tables were also checked by 2 researchers to ensure that bases were correct, and table information was accurate and reader friendly.
On receipt of the data, the Commission also carry out their own quality assurance of the data.
In the instance that an error is spotted in the published data this is reported to the Commission straight away and a review of processes is then carried out to understand why the error has happened. The data is corrected and resupplied to the Commission and published in line with its Revisions and corrections policy.
Correction statement
During the Year 3 (2025) Wave 1 reporting process, NatCen identified that derivations for some rebased variables based on ‘gambling activity in the past 12 months’ were not aligned with the standard approach used for all other rebased variables. A review of all derivations was conducted, and a second error was found with the ‘consequences of gambling’ derived variables (DVs).
Derived variables based on ‘gambling activity in the past 12 months’ had been created using the original rather than the backcoded input variables. The ‘other gambling activity’ variable was also incorrect for PAPI cases, which were all coded ‘No’ because the lack of a follow‑up string question had incorrectly not been accounted for.
The ‘consequences of gambling’ DVs were based on an incorrect priority order. Consequently, cases with at least one ‘Yes’ and one ‘Missing’ input were incorrectly coded as ‘Missing’ in the associated DV. The corrected ordering ensures that any ‘Yes’ input results in the DV being coded as ‘Yes’.
As a result of the derivation errors, several of the prevalence estimates and/or base sizes in the Year 1 (2023), Year 2 (2024) and wave 1 and 2 of 2025 reports and Excel files were incorrect. These have all been amended, with impact being minimal. Some PGSI scores and suicide ideation or attempts estimates have also been amended in line with the corrected base ‘Gambled in past 12 months’ DV. Most affected estimates changed by between +/- 0.1 percent and +/-1 percent with overall narrative remaining the same.
Data errors will be prevented from recurring by conducting independent code reviews, including additional QA sign‑off steps, and periodically reviewing past issues to ensure lessons are learned.
Availability of datasets
Data is deposited at UK Data Service (opens in new tab) after each annual publication.
- 2023 Year 1 data (opens in new tab)
- 2024 Year 2 data (opens in new tab)
- 2025 (Year 3 data will be submitted to the archive by November 2026.
References
5 Keyes, A., Smith, P. (2026) Working Paper 17: Enhanced sampling frames: A literature review. National Centre for Social Research, University of Southampton, UK (opens in new tab) (PDF).
6Indices of multiple deprivation (IMD) is a measure of relative deprivation for small, fixed geographic areas of the UK. Separate indices are produced for each UK country. IMD classifies these areas into 5 quintiles based on relative disadvantage, with quintile 1 being the most deprived and quintile 5 being the least deprived.
7In the Experimental Phase, the effect on data quality and selection bias of inviting a maximum of 2 or a maximum of 4 adults from each household to take part in the survey was investigated. There was no discernible experimental condition effect on household response rates, duplications nor gambling participation rates. There was evidence of significant clustering of gambling behaviours among households with three or four participants. As this can impact on the accuracy of the gambling participation data the recommendation was to invite up to two adults per household to take part going forward.
9 See for example Church, A. (1993). Estimating the effect of incentives on mail survey response rates: A meta-analysis. Public Opinion Quarterly; 57:62-79. Mercer, A., Caporaso, A., Cantor, D. and Townsend, R. (2015). How Much Gets You How Much? Monetary Incentives and Response Rates in Household Surveys. Public Opinion Quarterly 79 (1):105-29. Pengli Jia, Luis Furuya-Kanamori, Zong-Shi Qin, Peng-Yan Jia, Chang Xu, Association between response rates and monetary incentives in sample study: a systematic review and meta-analysis, Postgraduate Medical Journal, Volume 97, Issue 1150, August 2021, Pages 501–510.
10 Love2Shop vouchers cannot be exchanged for cash and cannot be used for gambling, so do not pose ethical problems for this survey.
11The PGSI consists of 9 items and each item is assessed on a four-point scale: never, sometimes, most of the time, almost always. Responses to each item are given the following scores: never = 0, sometimes = 1, most of the time = 2, almost always = 3. When scores to each item are added up, a total score ranging from 0 to 27 is possible. See Problem gambling screens (gamblingcommission.gov.uk) for full detail.
12The Commission is conducting work to develop and test a series of survey questions aimed at collecting data on the experience of consequences from gambling. Full detail on the work undertaken to date and the next steps can be found at Statistics and research series (gamblingcommission.gov.uk)
13Demographic questions align to the GSS harmonisation strategy which promotes consistent definitions and question wording in data collection.
14Speeders are identified by calculating the median time it took to answer each question among all those who answered. From this an expected time is calculated for each participant dependent on the questions that they answered. A ratio of actual time compared with expected time is produced and any statistical outliers on this ratio measure are removed.
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GSGB technical report - Data analysis and reporting
Last updated: 16 July 2026
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Updated with GSGB Annual report (2025) detail.