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 GSGB in Year 1 and Year 2. The address-level response rate (19 percent) was lower than the target (22 percent). To mitigate the lower response rate, boost samples were included within the year 2 sample to increase the overall productive sample size. More detail on response can be found in the ‘A’ tables’ accompanying each annual report. Note that Year 1 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) |
|---|---|---|---|---|
| 1 (31 July 2023 to 19 February 2024) | 37,554 | 6,636 | 19% | 9,742 |
| 2 (15 January 2024 to 19 January 2025) | 78,866 | 13,489 | 19% | 19,714 |
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) |
|---|---|---|
| 1 (31 July 2023 to 19 February 2024) | 44% | 56% |
| 2 (15 January 2024 to 19 January 2025) | 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) |
|---|---|---|---|---|
| 1 (31 July 2023 to 19 February 2024) | 21% | 31% | 35% | 13% |
| 2 (15 January 2024 to 19 January 2025) | 22% | 31% | 36% | 12% |
Table 4 shows response rates by mode of completion for year 1 and year 2. More detail on mode response can be found in the ‘A’ tables’ accompanying each annual report.
Table 4: Response rates by mode of completion
| Survey year | Productive participants: Online completions (percentage) | Productive participants: Postal completions (percentage) |
|---|---|---|
| 1 (31 July 2023 to 19 February 2024) | 65% | 35% |
| 2 (15 January 2024 to 19 January 2025) | 66% | 34% |
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. 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) score2.
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 GB3. 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 NatCen has continued to monitor best practice developments in the area of within household selection of adults in push-to-web surveys) and still consider this the best way to select adults within households.
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 rates4. 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 post5.
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 |
|---|---|---|---|---|
| 1 | 31 July 2023 to 16 November 2023 | 6 November 2023 to 7 March 2024 | N/A | N/A |
| 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 |
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 weeks6
- Problem Gambling Severity Index (PGSI)7
- 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
- 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 activity8.
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’.
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 dataset9.
It is also important to validate GSGB data against other surveys and industry data. This process includes research into reasons why there are discrepancies 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 have added a new question to the Year 3 survey (data collection throughout 2025) to ask participants if they have registered themselves with GamStop in the past 4 weeks, which will facilitate validation against industry data related to GamStop. We also added a new question which was designed in collaboration with the Bingo Association to ask people where they play bingo, to help validate GSGB data against industry data on the number of people playing bingo in bingo clubs. In its review of the GSGB, the Office for Statistics Regulation (OSR) also recommended investigating the coherence and comparability of GSGB data with other relevant data, such as the Adult Psychiatric Morbidity Survey (published June 2025) and the Health Survey for England, due for publication at the end of 2025.
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% |
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.
Availability of datasets
Data is deposited at UK Data Service (opens in new tab) after each annual publication.
- Year 1 data (opens in new tab)
- Year 2 data (will be submitted to the archive by January 2026).
References
2Indices 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.
3In 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.
4 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.
5 Love2Shop vouchers cannot be exchanged for cash and cannot be used for gambling, so do not pose ethical problems for this survey.
6The 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.
7The 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)
8Demographic questions align to the GSS harmonisation strategy which promotes consistent definitions and question wording in data collection.
9Speeders 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: 2 October 2025
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Updated with GSGB Annual report (2024) detail.