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Report

Gambling participation and the prevalence of problem gambling survey: Experimental statistics stage

Gambling Commission report produced by NatCen on the experimental statistics stage of the gambling participation and the prevalence of problem gambling survey.

Survey design

Sampling

A high-quality sample is essential for meeting the Gambling Commission’s aim of creating a robust and nationally representative new survey. To achieve this, a stratified random probability sample of addresses in Great Britain was used. The target population of the survey was adults aged 18 years and over, living in private households within Great Britain, and the aim was to achieve a sample size of 10,000 individuals (6,000 for step 1 and 4,000 for step 2)5.

There is no publicly available list of adults that could be used for sampling individuals. However, the Postcode Address File (PAF), compiled by the Post Office, provides a list of postal addresses (or postcode delivery points) which can be used as a sampling frame. The sampling process had two stages:

  • selection of addresses from the PAF
  • selection of adults within addresses.

Prior to selection, the sampling frame was stratified (ordered), this can help to reduce sampling error and thus 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
  • overall Index of Multiple Deprivation (IMD) score6.

Addresses were split into two selection types (‘conditions’), which specified the maximum number of adults (aged 18 and over) to be selected – by a householder – from each address to complete the survey. In condition 1 addresses, up to two adults were selected; in condition 2 addresses, up to four adults were selected. These two experimental groups are referred to as ‘C1 (up to two adults)’ and ‘C2 (up to four adults)’ in this report. A maximum of four adults was chosen as a practical cut-off given that according to Labour Force Survey data from 2022, one percent of households in Great Britain contain five or more adults.

At each sampled address, there may have been more than one 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 one percent), and it is therefore unlikely to lead to any systematic bias in the responding sample.

Step 1

The aim was to have a total achieved sample size of 6,000 adults aged 18 years and over for step 1. Power calculations assumed that in C1 households where two adults were invited to take part, an average of 1.4 participants would do so. In C2 households where up to four adults were invited to take, an average of 1.5 would do so. The estimate of 1.4 participants per responding household was taken from the pilot survey.

The estimate of 1.5 participants per responding household was taken from the Community Life Survey 2020/21 (opens in new tab). These calculations further assumed a small amount of clustering of gambling behaviour within each participating household. This clustering reduced the effective target sample size from 6,000 to 5,714 (DEFF7 1.05) but this would be large enough to detect differences in gambling behaviour between the two conditions (C1 (up to two adults) and C2 (up to four adults)) of 4.5 percent for past year gambling prevalence covering overall gambling rates, 3.6 percent for online gambling excluding the National Lottery rates, and 4.6 percent for overall gambling excluding the National Lottery rates.

For step 1, the issued sample comprised 21,953 addresses, each randomly allocated to one of three, similar-sized groups as shown in 'Figure 1: Step 1 issued and target achieved sample sizes for experimental conditions and type of gambling-related harms question asked' as follows.

Figure 1: Step 1 issued and target achieved sample sizes for experimental conditions and type of gambling-related harms question asked.
Gambling-related harms question asked Experimental condition C1 (up to two adults)
(number)
Experimental condition C2 (up to four adults)
(number)
Total
(number)
Scaled Issued addresses: 7,305
Target achieved individuals: 1,953
Issued addresses: 7,343
Target achieved individuals: 2,094
Issued addresses: 14,648
Target achieved individuals: 4,047
Binary Issued addresses: 7,305
Target achieved individuals: 1,953
Not applicable Issued addresses: 7,305
Target achieved individuals: 1,953
Total Issued addresses: 14,610
Target achieved individuals: 3,906
Issued addresses: 7,343
Target achieved individuals: 2,094
Issued addresses: 21,953
Target achieved individuals: 6,000

Step 2

For step 2, 14,982 addresses were issued with the aim of achieving 4,000 productive individual questionnaires. The sampled addresses were randomly allocated to one of three equal sized groups. Each group had 4,994 issued addresses with the aim of achieving 1,333 productive individual questionnaires. The three groups were then asked a different set of gambling questions (a long-list approach, a hierarchical approach and a chunked-list approach).

Figure 2: Step 2 issued and target achieved sample sizes for experimental approaches to asking about gambling participation

Figure 2: Step 2 issued and target achieved sample sizes for experimental approaches to asking about gambling participation.
Sample Experimental approach: long-list
(number)
Experimental approach: hierarchical
(number)
Experimental approach: chunked-list
(number)
Issued addresses 4,994 4,994 4,994
Target achieved individuals 1,333 1,333 1,333

References

5 The target achieved sample size for step 3 of the experimental stage, the soft launch, will be 4,000 individuals.

6 Indices of Multiple Deprivation (IMD) is a measure of relative deprivation for small, fixed geographic areas of the United Kingdom (UK). Separate indices are produced for each UK country. IMD classifies these areas into five quintiles based on relative disadvantage, with quintile one being the most deprived and quintile five being the least deprived.

7 The Design Effect (DEFF) is a measure that summarises the degree of clustering that has occurred. It is the ratio of the variance between individuals in the (clustered) sample, compared with the variance that would be expected from a simple random sample.

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Questionnaire content and design
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