Official Statistics

Participation Survey 2024 to 2025 Annual Technical Report

Published 30 July 2025

Applies to England

DCMS Participation Survey 2024/25

Annual Technical Note

April 2024 to March 2025

© Verian [2025]

1. Introduction

1.1 Background to the survey

In 2021, the Department for Culture, Media and Sport (DCMS) commissioned Verian to design and deliver a new, nationally representative ‘push-to-web’ survey to assess adult participation in DCMS sectors across England. The survey served as a successor to the Taking Part Survey, which ran for 16 years as a continuous face to face survey.

The scope of the survey is to deliver a nationally representative sample of adults (aged 16 years and over) and to assess adult participation in DCMS sectors across England. The data collection model for the Participation Survey is based on ABOS (Address-Based Online Surveying), a type of ‘push-to-web’ survey method. Respondents take part either online or by completing a paper questionnaire. In 2024/25, the target respondent sample size was reduced to 33,000, in line with the targets set for the 2021/22 and 2022/23 survey years. The increase to 175,000 respondents in 2023/24 reflected a one-year expansion, driven by strategic priorities and data needs identified through a joint commissioning arrangement between DCMS and Arts Council England (ACE).

The fieldwork period for the annual 2024/25 survey was divided into four quarters.

• Quarter one: Fieldwork conducted between 8th April 2024 and 1st July 2024.

• Quarter two: Fieldwork conducted between 3rd July 2024 and 2nd October 2024.

• Quarter three: Fieldwork conducted between 2nd October 2024 and 31st December 2024.

• Quarter four: Fieldwork conducted between 8th January 2025 and 4th April 2025.

1.2 Survey objectives

The key objectives of the 2024/25 Participation Survey were:

• To inform and monitor government policy and programmes in DCMS and other government departments (OGDs) on adult engagement with the DCMS and digital sectors (^{[footnote 1]}). The survey will also gather information on demographics (for example, age, ethnicity, education).

• To assess the variation in engagement with cultural activities across DCMS sectors in England, and the differences in social-demographics such as location, age and education.

1.3 Survey design

The 2024/25 Participation Survey was conducted via an online and paper questionnaire using Address Based Online Surveying (ABOS), an affordable method of surveying the general population that still employs random sampling techniques. ABOS is also sometimes referred to as “push to web” surveying.

The basic ABOS design is simple: a stratified random sample of addresses is drawn from the Royal Mail’s postcode address file (PAF) and an invitation letter is sent to each one, containing username(s) and password(s) plus the URL of the survey website. Sampled individuals can log on using this information and complete the survey as they might any other web survey. Once the questionnaire is complete, the specific username and password cannot be used again, ensuring data confidentiality from others with access to this information.

It is usual for at least one reminder to be sent to each sampled address and it is also usual for an alternative mode (usually a paper questionnaire) to be offered to those who need it or would prefer it. It is typical for this alternative mode to be available only on request at first. However, after nonresponse to one or more web survey reminders, this alternative mode may be given more prominence.

Paper questionnaires ensure coverage of the offline population and are especially effective with sub-populations that respond to online surveys at lower-than-average levels. However, paper questionnaires have measurement limitations that constrain the design of the questionnaire and also add considerably to overall cost. For the Participation Survey, paper questionnaires are used in a limited and targeted way, to optimise rather than maximise response.

2. Questionnaire

2.1 Questionnaire development

The majority of the survey content remained consistent with previous years, ensuring that key trends could continue to be tracked over time. However, a small number of topics were removed, and new areas of interest were introduced for the 2024/25 Participation Survey. Details of these changes can be found in Section 2.3: Questionnaire changes.

Given the limited nature of the modifications and the absence of substantial changes to question wording or structure, cognitive testing was not required for the 2024/25 survey year. Furthermore, many of the questions, such as those relating to archives, had previously been included in DCMS’s Taking Part survey, the predecessor to the Participation Survey.

2.2 2024/25 Participation Questionnaire

The online questionnaire was designed to take an average of 30 minutes to complete. A modular design was used with around half of the questionnaire made up of a core set of questions asked of the full sample. The remaining questions were split into three separate modules, randomly allocated to a subset of the sample.

The postal version of the questionnaire included the same set of core questions asked online, but the modular questions were omitted to avoid overly burdening respondents who complete the survey on paper, and to encourage response. Copies of the online and paper questionnaires are available online.

2.3 Questionnaire changes

As a result of a partnership between Arts Council England (ACE) and DCMS during the 2023/24 survey year, the Participation Survey was boosted to enable meaningful estimates at the Local Authority (LA) level. The 2024/25 survey was not boosted; however, ACE plans to implement a LA boost every three years . As a result, the following questions, primarily included to meet ACE’s needs, were removed from the 2024/25 Participation Survey:

• Environment, which included questions on mode of transport taken while travelling to an arts and cultural event, distance travelled, and reason(s) for transportation choice.

• Social prescribing, which included questions on the respondent’s experience with social prescribing, and the types of activities they were referred to.

• Further questions on arts and culture engagement, which included questions on the types of classes’ and clubs’ respondents have taken part in, the frequency and reasons(s) for their involvement, the impact/benefits of participating, and for non-participants, the reason for not participating.

• Pride in local area, which included questions on respondents’ sense of belonging and pride in their local area, the role culture plays in choosing where to live, and the current arts and culture scene in their local area.

Questions on the following topics of interest were added to the 2024/25 Participation Survey, as requested by DCMS:

• Archives, which assessed respondents’ use of archives or record offices in England, including the frequency and type of use (in-person or online), activities undertaken, and reasons for not using these services.

• A question was added to the Heritage section to determine whether the respondent made a voluntary donation during their last visit to a heritage site.

• A question was added to the Museums and Cultural Property section on reported knowledge and familiarity with the codes of practice related to metal detecting and mudlarking activities.

• A question was added to the Digital Skills and Infrastructure section to capture where respondents found information about smart device security features before buying.

• Further questions were added to the Mobile Internet section, on current access to mobile connectivity at home and, for those without access, how much they would be willing to pay for it per month.

• A question was added to the Data section to measure comfort with public sector organisations using data for patterns, trends, and decision-making.

• A question was added on awareness of government plans to commemorate and remember the impacts of the Covid-19 pandemic through various initiatives.

• A question was added measuring satisfaction with the quality of cultural activities near the respondent’s home.

Some minor changes were made to the sports participation section in the 2024/25 questionnaire in Quarter 2 see Section 2.3.1 for more details. No further questionnaire changes were required in Quarters 3 and 4.

2.3.1 Quarter 2 questionnaire changes

The following changes were made to the 24/25 questionnaire in Quarter 2:

• From July onwards, the wording for the sports event attendance question was updated as was the question variable name (CSPOLIVE to CSPOLIVE2). The update included changing ‘in the last 6 months’ to ‘in the last 12 months’ and ‘watched’ to ‘attended’, so that the question now reads:

CSPOLIVE2

In the last 12 months, have you attended any live sporting events?

1.         Yes

2.         No

• The wording for the frequency of sport event attendance was also updated as was the corresponding question variable name (CSPONUM to CSPONUM2). The new wording involved changing ‘in the last 6 months’ to ‘in the last 12 months’, so the updated question reads as follows:

CSPONUM2NEW

How many live sporting events have you attended in the last 12 months?

If you don’t know, please give your best estimate.

1.         1

2.         2-4

3.         5-9

4.         10-14

5.         15 or more

999      Don’t know *Fixed *Exclusive

• The response options for the type of sports event attended question were expanded to include “horse racing”. The variable name was revised from CSPOSPEC to CSPOSPEC2, and the question wording was updated from ‘in the last 6 months’ to ‘in the last 12 months’.

CSPOSPEC2

Which live sporting [IF CSPONUM2 = 1: event and SINGLE CODE] [EVERYONE ELSE: events] have you attended in person in the last 12 months?

Select all that apply

1.         Men’s football

2.         Women’s football

3.         Rugby

4.         Tennis

5.         Cricket

6.         Athletics

7.         Snooker

8.         Swimming

9.         Gymnastics

10.       Golf

11.       Horse racing

12.       Some other type of sport (please type in)

• The routing for both professional sports payment questions (CSPOPROF and CSPROPROFB) was updated to align with the revised variable name in the preceding sports participation question (CSPONUM2).

• The live sporting events non-attendance reasons question was updated, including its variable name (changed from NOSPORT to NOSPORT2). The update involved revising the timeframe from ‘in the last 6 months’ to ‘in the last 12 months’, so the question now reads:

NOSPORT2

What are the reasons you haven’t personally attended live sporting events in person in the last 12 months?

Select all that apply

1.         I cannot afford it

2.         It is not value for money

3.         I’m not interested

4.         I don’t have time

5.         I have a health problem or disability

6.         They are difficult to get to

7.         I don’t know what is available

8.         I would feel out of place

9.         I don’t have anyone to go with

11.       Some other reason (please type in)

12.       No reason in particular

• The response options for the type of sports event watched on TV question were expanded to include “horse racing”. The variable name was updated from SSSPOWHI to SSSPOWHI2, and the question wording was revised from ‘in the last 6 months’ to ‘in the last 12 months’.

SSSPOWHI2

In the last 12 months, which live sports have you watched on TV?

Select all that apply

1.         Men’s football

2.         Women’s football

3.         Rugby

4.         Tennis

5.         Cricket

6.         Athletics

7.         Snooker

8.         Swimming

9.         Gymnastics

10.       Golf

11.       Horse racing

12.       Some other type of sport (please type in)

13.       None of these

3. Sampling

3.1 Sample design: addresses

The address sample design is intrinsically linked to the data collection design (see ‘Details of the data collection model’ below) and was designed to yield a respondent sample that is representative with respect to neighbourhood deprivation level, and age group within each of the 33 ITL2 areas ^{[footnote 2]} in England. This approach limits the role of weights in the production of unbiased survey estimates, narrowing confidence intervals compared with other designs.

The design sought a minimum four-quarter respondent sample size of 900 for each ITL2 area. Although there were no specific targets per quarter, the sample selection process was designed to ensure that the respondent sample size per ITL2 area was approximately the same per quarter.

As a first step, a stratified master sample of 231,000 addresses in England was drawn from the Postcode Address File (PAF) ‘small user’ subframe. Before sampling, the PAF was disproportionately stratified by ITL2 area (33 strata) and, within area, sorted by (i) lower tier local authority, (ii) neighbourhood deprivation level (five groups, each of a similar scale at the national level), (iii) super output area, and finally (iv) by postcode. This ensured that the master sample of addresses was geodemographically representative within each stratum.

This master sample of addresses was then augmented by data supplier CACI. For each address in the master sample, CACI added the expected number of resident adults in each ten-year age band. Although this auxiliary data will have been imperfect, investigations by Verian have shown that it is highly effective at identifying households that are mostly young or mostly old. Once this data was attached, the master sample  was additionally stratified by expected household age structure based on the CACI data (^{[footnote 3]}):

• all aged 35 or younger (19% of the total)
• all aged 65 or older (21% of the total)
• all other addresses (61% of the total)

The conditional sampling probability in each stratum was varied to compensate for (expected) residual variation in response rate that could not be ‘designed out’, given the constraints of budget and timescale. The underlying assumptions for this procedure were derived from empirical evidence obtained from the 2023/24 Participation Survey.

Verian drew a stratified random sample of 116,894 addresses from the master sample of 231,000 and systematically allocated them with equal probability to 48 equal-sized ‘replicates’, each with the same profile and scale (2,435 to 2,436 addresses). The expectation was that only the first 32 replicates would be issued (that is, 77,934 addresses), with the remaining 16 kept back in reserve.

There were eight issue points across the full 2024/25 survey period: two per quarter, so the expectation was that the next four available replicates in each stratum (ITL2 area) would be activated at each issue point (so, eight per quarter; 32 in the whole survey period). The intention was to carry out a stratum level review towards the end of each quarter to inform the selection of replicates for the following quarter.

Sample productivity was reviewed each quarter, with alterations made to the sample issue for the subsequent quarter. There was also a final review before the release of the final (eighth) replicate. This review was carried out at ITL2 area level, leading to some differences between what was planned at the start of the year and what was issued in practice.

In total, 82,513 addresses were issued: 4,579 more than planned (+6%). These were distributed as follows: 19,488 were issued in quarter one, 20,631 in quarter two, 19,242 in quarter three, and 23,152 in quarter four.

Table 1 shows the combined quarters one, two, three and four issued sample  structure with respect to the major ‘design’ strata: neighbourhood deprivation level and expected household age structure.

Table 1: Address issue by area deprivation quintile group and expected household age structure.

Expected household age structure	Most deprived	2nd	3rd	4th	Least deprived
All <=35	4,536	4,805	3,380	2,992	1,883
Other	11,036	11,813	10,296	9,202	7,735
All >=65	2,528	2,725	3,440	3,230	2,912

3.2 Sample design: individuals within sampled addresses

All resident adults aged 16+ were invited to complete the survey. In this way, the Participation Survey avoided the complexity and risk of selection error associated with remote random sampling within households.

However, for practical reasons, the number of logins provided in the invitation letter was limited. The number of logins was varied between two and four, with this total adjusted in reminder letters to reflect household data provided by prior respondent(s). Addresses that CACI data predicted contained only one adult were allocated two logins; addresses predicted to contain two adults were allocated three logins; and other addresses were allocated four logins. The mean number of logins per address was 2.7. Paper questionnaires were available to those who are offline, not confident online, or unwilling to complete the survey this way.

3.3 Details of the data collection model

Table 2 summarises the data collection design within each principal stratum, showing the number of mailings and type of each mailing: push-to-web (W) or mailing with paper questionnaires (P). For example, ‘WWP’ means two push-to-web mailings and a third mailing with paper questionnaires included alongside the web survey login information. In general, there was a two-week gap between mailings. For the very final issue point (the second sample issue of quarter four), the fourth ‘W’ contact was removed for addresses that had a default four-contact design (either ‘WWWW’ or ‘WWPW’) as the target respondent sample size for the 2024/25 survey year had already been achieved.

Table 2: Data collection design by principal stratum.

Expected household age structure	Most deprived	2nd	3rd	4th	Least deprived
All <=35	WWPW	WWWW	WWWW	WWW	WWW
Other	WWPW	WWW	WWW	WWW	WWW
All >=65	WWPW	WWPW	WWP	WWP	WWP

4. Fieldwork

Fieldwork for the 2024/25 Participation Survey was conducted between April 2024 and March 2025, with samples issued on a quarterly basis. Each quarter’s sample was split into two issue points, the first of which was issued at the start of the quarter, and the second four to five weeks later. The specific fieldwork dates for each quarter are shown below in Table 3.

Table 3: Fieldwork dates.

Quarter	Batch	Fieldwork start	Fieldwork end
Quarter one	1	8th April 2024	3rd June 2024
	2	8th May 2024	1st July 2024
Quarter two	1	3rd July 2024	28th August 2024
	2	7th August 2024	2nd October 2024
Quarter three	1	2nd October 2024	27th November 2024
	2	30th October 2024	31st December 2024
Quarter four	1	8th January 2025	5th March 2025
	2	5th February 2025	4th April 2025

The paper questionnaire was made available to sampled individuals in seven of the fifteen principal strata at the second reminder stage as shown in Table 2 of Section 3.3: Details of the data collection model. The paper questionnaire was also available on request to all respondents who preferred to complete the survey on paper or who were unable to complete online.

4.1 Contact procedures

All sampled addresses were sent an initial invitation letter containing the following information:

• A brief description of the survey

• The URL of survey website (used to access the online script)

• A QR code that can be scanned to access the online survey

• Log-in details for the required number of household members

• An explanation that participants will receive a £10 shopping voucher

• Information about how to contact Verian in case of any queries

The reverse of the letter featured responses to a series of Frequently Asked Questions

All non-responding addresses were sent two reminder letters, at the end of the second and fourth weeks of fieldwork respectively. A pre-selected subset of non-responding addresses (see Table 2) was sent a third reminder letter at the end of the sixth week of fieldwork. The information contained in the reminder letters was similar to the invitation letters, with slightly modified messaging to reflect each reminder stage.

As well as the online survey, respondents were given the option to complete a paper questionnaire, which consisted of an abridged version of the online survey. Each letter informed respondents that they could request a paper questionnaire by contacting Verian using the email address or freephone telephone number provided, and a cut-off date for paper questionnaire requests was also included on the letters.

In addition, some addresses received up to two paper questionnaires with the second reminder letter. This targeted approach was developed based on historical data Verian has collected through other studies, which suggests that proactive provision of paper questionnaires to all addresses can actually displace online responses in some strata. Paper questionnaires were proactively provided to (i) sampled addresses in the most deprived quintile group, and (ii) sampled addresses where it was expected that every resident would be aged 65 or older (based on CACI data).

4.2 Confidentiality

Each of the letters assured the respondent of confidentiality, by answering the question “Is the survey confidential?” with the following:

Yes, the information that is collected will only be used for research and statistical purposes. Your contact details will be kept separate from your answers and will not be passed on to any organisation outside of Verian or supplier organisations who assist in running the survey.

Data from the survey will be shared with DCMS and DSIT for the purpose of producing and publishing statistics. The data shared won’t contain your name or contact details, and no individual or household will be identifiable from the results.

For more information about how we keep your data safe, you can access the privacy policies of the involved organisations.  

4.3 Fieldwork performance

When discussing fieldwork figures in this section, response rates are referred to in two different ways:

Household response rate – This is the percentage of households contacted as part of the survey in which at least one questionnaire was completed.

Individual response rate – This is the estimated response rate amongst all adults that were eligible to complete the survey.

Overall, the target number of interviews was 33,000 post validation checks, equating to 8,250 per quarter.

In total 82,513 addresses were sampled, from which 36,074 respondents completed the survey – 31,596 via the online survey and 4,478 by returning a paper questionnaire. Following data quality checks (see Section 5: Data processing for details), 1,696 respondents were removed (1,684 web and 12 paper), leaving 34,378 respondents in the final dataset. The majority of participants took part online (87%), while 13% completed a paper questionnaire.

This constitutes a 0.42 conversion rate (responses/sampled addresses), a 29% household-level response rate, and an individual-level response rate of 24% (^{[footnote 4]}).

The full breakdown of the fieldwork figures and response rates by quarter are available in Table 4.

Table 4: Combined online and paper fieldwork figures by quarter.

Quarter	No. of sampled addresses	Completes achieved – online and paper	No. households completed	Household response rate	Individual response rate
Quarter one	19,488	8,401	5,372	30%	25%
Quarter two	20,631	8,791	5,739	30%	25%
Quarter three	19,242	7,640	5,010	28%	23%
Quarter four	23,152	9,546	6,118	29%	24%
Total	82,513	34,378	22,239	29%	24%

4.4 Incentive system

All respondents that completed the Participation Survey were given a £10 voucher as a thank you for taking part.

Online incentives

Participants completing the survey online were provided with details of how to claim their voucher at the end of the survey and were directed to the voucher website, where they could select from a range of different vouchers, including electronic vouchers sent via email and gift cards sent in the post.

Paper incentives

Respondents who returned the paper questionnaire were also provided with a £10 voucher. This voucher was sent in the post and can be used at a variety of high street stores.

4.5 Survey length

For the online survey, the median completion time was 27 minutes and 23 seconds, and the average completion time was 29 minutes and 24 seconds(^{[footnote 5]}).

5. Data processing

5.1 Data management

Due to the different structures of the online and paper questionnaires, data management was handled separately for each mode. Online questionnaire data was collected via the web script and, as such, was much more easily accessible. By contrast, paper questionnaires were scanned and converted into an accessible format.

For the final outputs, both sets of interview data were converted into IBM SPSS Statistics, with the online questionnaire structure as a base. The paper questionnaire data was converted to the same structure as the online data so that data from both sources could be combined into a single SPSS file.

5.2 Partial completes

Online respondents can exit the survey at any time, and while they can return to complete the survey at a later date some chose not to do so.

Equally respondents completing the paper question occasionally leave part of the questionnaire blank, for example if they do not wish to answer a particular question or section of the questionnaire.

Partial data can still be useful, providing respondents have answered the substantive questions in the survey. These cases are referred to as usable partial interviews.

Survey responses were checked at several stages to ensure that only usable partial interviews were included. Upon receipt of receiving returned paper questionnaire, the booking in team removed obviously blank paper questionnaires. Following this, during data processing, rules were set for the paper and online surveys to ensure that respondents had provided sufficient data. For the online survey, respondents had to reach a certain point in the questionnaire for their data to count as valid (just before the second set of demographic questions). Paper data was judged complete if they answered at least 50% of the questions and reached at least as far as Q60 in the questionnaire.

5.3 Validation

Initial checks were carried out to ensure that paper questionnaire data had been correctly scanned and converted to the online questionnaire data structure. For questions common to both questionnaires, the SPSS output was compared to check for any notable differences in distribution and data setup.

Once any structural issues had been corrected, further quality checks were carried out to identify and remove any invalid interviews. The specific checks were as follows:

1. Selecting complete interviews: Any test serials in the dataset (used by researchers prior to survey launch) were removed. Cases were also removed if the respondent did not answer the declaration statement (online: QFraud; paper: Q88).

2. Duplicate serials check: If any individual serial had been returned in the data multiple times, responses were examined to determine whether this was due to the same person completing multiple times or due to a processing error. If they were found to be valid interviews, a new unique serial number was created, and the data was included in the data file. If the interview was deemed to be a ‘true’ duplicate, the more complete or earlier interview was retained.

3. Duplicate emails check: If multiple interviews used the same contact email address, responses were examined to determine if they were the same person or multiple people using the same email. If the interviews were found to be from the same person, only the most recent interview was retained. In these cases, online completes were prioritised over paper completes due to the higher data quality.

4. Interview quality checks: A set of checks on the data were undertaken to check that the questionnaire was completed in good faith and to a reasonable quality. Several parameters were used:

• Interview length (online check only).
• Number of people in household reported in interview(s) vs number of total interviews from household.
• Whether key questions have valid answers.
• Whether respondents have habitually selected the same response to all items in a grid question (commonly known as ‘flatlining’) where selecting the same responses would not make sense. *How many multi-response questions were answered with only one option ticked.

Following the removal of invalid cases, 34,378 valid cases were left in the final dataset.

5.4 Standard paper questionnaire edits

Upon completion of the general quality checks described above, more detailed data checks were carried out to ensure that the right questions had been answered according to questionnaire routing. This is generally all correct for all online completes, as routing is programmed into the scripting software, but for paper completes, data edits were required.

There were two main types of data edits, both affecting the paper questionnaire data:

1. Single-response question edits: If a paper questionnaire respondent had mistakenly answered a question that they weren’t supposed to, their response in the data was changed to “-3: Not Applicable”. If a paper questionnaire respondent had neglected to answer a question that they should have, they were assigned a response in the data of “-4: Not answered but should have (paper)”. If a paper questionnaire respondent had tick more than one box for a single response question they were assigned a response in the data of “-5: Multi-selected for single response (paper)”.

2. Multiple response question edits: If a paper questionnaire respondent had mistakenly answered a question that they weren’t supposed to, their response was set to “-3: Not Applicable”. If a paper questionnaire respondent had neglected to answer a question that they should have, they were assigned a response in the data of “-4: Not answered but should have (paper)”. Where the respondent had selected both valid answers and an exclusive code such as “None of these”, any valid codes were retained and the exclusive code response was set to “0”.

5.5. Questionnaire specific paper questionnaire edits

Other, more specific data edits were also made, as described below:

1. Additional edits to library questions: The question CLIBRARY1 was formatted differently in the online script and paper questionnaire. In the online script it was set up as one multiple-response question, while in the paper questionnaire it consisted of two separate questions (Q21 and Q25). During data checking, it was found that many paper questionnaire respondents followed the instructions to move on from Q21 and Q25 without ticking the “No” response. To account for this, the following data edits were made:

• If CFRELIB12 and CPARLI12B was not answered and CNLIWHYA was answered, set CLIBRARY1_001 was set to 0 if it was left blank.

• If CFRELIDIG and CDIGLI12 was not answered and CNLIWHYAD was answered, CLIBRARY1_002 was set to 0 if it was left blank.

• CLIBRARY1_003 and CLIBRARY1_004 was set to 0 for all paper questionnaire respondents.

1. Additional edits to grid questions: Due to the way the paper questionnaire was set up, additional edits were needed for the following linked grid questions: CARTS1/CARTS1A, CARTS2/CARTS2A, CARTS3/CARTS3A, CARTS4/CARTS4A, ARTPART12/ARTPART12A.

Figure 1 shows an example of a section in the paper questionnaire asking about attendance at arts events.

Figure 1: Example of the CARTS1 and CARTS1A section in the paper questionnaire .

Marking the option “Not in the last 12 months” on the paper questionnaire was equivalent to the code “0: Have not done this” at CARTS1 in the online script. As such, leaving this option blank in the questionnaire would result in CARTS1 being given a default value of “1” in the final dataset. In cases where a paper questionnaire respondent had neglected to select any of the options in a given row, CARTS1 was recoded from “1” to “0”.

If the paper questionnaire respondent did not tick any of the boxes on the page, they were recoded to “-4: Not answered but should have (paper)”.

5.6 Coding

Post-interview coding was undertaken by members of the Verian (formerly Kantar Public) coding department. The coding department coded verbatim responses, recorded for ‘other specify’ questions.

For example, if a respondent selected “Other” at CARTS1 and wrote text that said they went to some type of live music event, in the data they would be back-coded as having attended a “a live music event” at CARTS1_006.

For the sets CASRT1/CARTS1A/CARTS1B, CASRT2/CARTS2A/CARTS2B and CHERVIS12/CFREHER12/CVOLHER data edits were made to move responses coded to “Other” to the correct response code, if the answer could be back coded to an existing response code.

5.7 Data outputs

Once the checks were complete, a final SPSS data file was created that only contained valid interviews and edited data. Five data sets were made available

• Quarter one data

• Quarter two data

• Quarter three data

• Quarter four data

• A combined annual dataset

A set of Microsoft Excel data tables, containing headline measures were produced alongside each data set. The data tables also display confidence intervals. Confidence intervals should be considered when analysing the Participation Survey data set, especially when conducting sub-group analysis. A figure with a wide confidence interval may not be as robust as one with a narrow confidence interval. Confidence intervals vary for each measure and each demographic breakdown and will vary from year to year and should be calculated using a statistical package which takes account of design effects.

5.8 Derived variables 

The headline-derived variables for the 2024/25 year survey are outlined below. While the underlying variables used to produce the headline variables in the time series tables have varied in their derivation across years due to changes in the questionnaire, the methodology and intended outputs have remained consistent.

CARTSPDOR_NET - In the last 12 months, engaged with the arts physically OR digitally at least once. The variable counts how many respondents have engaged with the arts physically and digitally (CARTS_NET & CARTS4_NET). And excludes respondents who have not provided any answer to the question CARTS_NET or CARTS4_NET.

CARTS_NET - In the last 12 months, engaged (attended OR participated) with the arts physically. The variable counts the number of respondents who have attended/participated with the arts physically. And excludes respondents who have not provided any answer to the questions CARTS1 and CARTS2.

CARTS4_NET - In the last 12 months, engaged with the arts digitally at least once. The variable counts how many respondents have engaged with the arts digitally (CARTS4). And excludes respondents who have not the question CARTS4.

CLIBRARY1OR_NET - In the last 12 months, engaged with library services physically OR digitally at least once. The variable counts how many respondents have engaged with library services physically OR digitally. And excludes respondents who have not provided any answer to the questions CLIBRARY1_INP and CLIBDIG_DV.

CLIBRARY1_INP (23/24, 24/25) : CLIBRARY1_001 (21/22, 22/23) - In the last 12 months, engaged with library services in-person at least once. The variable counts how many respondents have engaged with library services in person. And excludes respondents who have not provided any answer to the question CLIBRARY1.

CLIBDIG_DV (23/24, 24/25) : CLIBDIG_NET (21/22, 22/23) - In the last 12 months, accessed library services digitally or online. The variable counts how many respondents have engaged with library services digitally or online. And excludes respondents who have not provided any answer to the question CLIBDIG.

ARCHUSEOR_NET (New to 24/25) - In the last 12 months, engaged with archives or record office services physically OR digitally at least once. The variable counts how many respondents have engaged with archive services physically OR digitally. And excludes any respondents who haven’t answered ARCHUSE.

ARCHUSE_INP (New to 24/25) - In the last 12 months, engaged with archives or record office services physically. The variable counts how many respondents have engaged with archive services physically. And excludes any respondents who have not provided an answer.

ARCHUSE_DIG (New to 24/25) - In the last 12 months, engaged with archives or record office services digitally. The variable counts how many respondents have engaged with archive services digitally. And excludes any respondents who have not provided an answer.

CHERVISDIGOR_NET (23/24, 24/25) : CHERVISDIGOR_SEP (21/22, 22/23) - In the last 12 months, engaged with heritage physically OR digitally. The variable counts how many respondents have engaged with heritage physically OR digitally (CHERVIS12 & CDIGHER12). And excludes respondents who have not provided any answer to the questions CHERVIS12 and CDIGHER12.

CHERVIS12_NET - In the last 12 months, have you visited a heritage site at least once (in your own time, academic study and voluntary)? The variable counts how many respondents have visited heritage sites (CHERVIS12). And excludes respondents who haven’t answered CHERVIS12.

CDIGHER12_NET (23/24, 24/25) : CDIGHER12_HDS_NET (21/22, 22/23) - In the last 12 months, have you engaged with heritage sector digitally at least once. The variable counts how many respondents have engaged with heritage sites digitally (CDIGHER12). And excludes respondents who haven’t answered CDIGHER12.

CMUSVISDIGOR_NET - In the last 12 months, engaged with museum or gallery physically OR digitally. The variable counts how many respondents have engaged with museums or galleries physically OR digitally (CMUSONL & CMUSVIS_001). And excludes any respondents who haven’t answered CMUSONL and CMUSVIS_001.

CMUSONLDIG (23/24, 24/25) : CDIGHER12_MDS (21/22, 22/23) - In the last 12 months, engaged with museum or gallery digitally. The variable counts how many respondents have engaged with museums or galleries digitally (CMUSONL). And excludes respondents who haven’t answered CMUSONL.

5.9 Standard errors

The standard error is useful as a means to calculate confidence intervals.

Survey results are subject to various sources of error that can be divided into two types: systematic and random error.

Systematic error

Systematic error or bias covers those sources of error that will not average to zero over repeats of the survey. Bias may occur, for example, if a part of the population is excluded from the sampling frame or because respondents to the survey are different from non-respondents with respect to the survey variables. It may also occur if the instrument used to measure a population characteristic is imperfect.  Substantial efforts have been made to avoid such systematic errors. For example, the sample has been drawn at random from a comprehensive frame, two modes and multiple reminders have been used to encourage response, and all elements of the questionnaire were thoroughly tested before being used.

Random error

Random error is always present to some extent in survey measurement. If a survey is repeated multiple times minor differences will be present each time due to chance. Over multiple repeats of the same survey these errors will average to zero. The most important component of random error is sampling error, which is the error that arises because the estimate is based on a random sample rather than a full census of the population. The results obtained for a single sample may by chance vary from the true values for the population, but the error would be expected to average to zero over a large number of samples. The amount of between-sample variation depends on both the size of the sample and the sample design. The impact of this random variation is reflected in the confidence intervals presented in the data tables for headline measures.

Random error may also follow from other sources such as variations in respondents’ interpretation of the questions, or variations in the way different interviewers ask questions.

Standard errors for complex sample designs

The Participation Survey employs a systematic sample design, and the data is both clustered by address and weighted to compensate for non-response bias. These features will impact upon the standard errors for each survey estimate in a unique way. Generally speaking, systematic sampling will reduce standard errors while data clustering and weighting will increase them. If the complex sample design is ignored, the standard errors will be wrong and usually too narrow.

The confidence intervals published in the annual data tables have been estimated using the svyciprop function of the R survey library, using the “logit” method.

Data considerations

Confidence intervals are important to consider when it comes to analysing the Participation Survey data, especially when drawing out inferences from the data.

Confidence intervals vary for each measure and each demographic breakdown and will vary from year to year.

5.10 Missing data

Due to changes in the questionnaire from Q2 onwards (see Section 2.3.1 for details) several sporting events questions were revised to reference activity “in the last 12 months” instead of “in the last 6 months”. The list below notes the affected variables and derived variables. Variables using the 6-month reference period contain data for Q1 but are missing for Q2 to Q4, while those using the 12-month reference contain data for Q2 to Q4 but are missing for Q1.

• CSPOLIVE -> CSPOLIVE2
• CSPONUM -> CSPONUM2
• CSPOSPEC -> CSPOSPEC2
• CSPOSPEC_FOOT -> CSPOSPEC2_FOOT
• CSPOSPEC_011DV -> CSPOSPEC2_012DV
• NOSPORT -> NOSPORT2
• SSSPOWHI -> SSSPOWHI2
• SSSPOWHI_FOOT -> SSSPOWHI2_FOOT
• SSSPOWHI_DV -> SSSPOWHI2_DV
• SSSPOWHI_011DV -> SSSPOWHI2_012DV

6. Weighting

Each quarter, a three-step weighting process was used to compensate for differences in both sampling probability and response probability:

1. An address design weight was created equal to one divided by the sampling probability; this also served as the individual-level design weight because all resident adults could respond.

2. The expected number of responses per address was modelled as a function of data available at the neighbourhood and address levels. The step two weight was equal to one divided by the predicted number of responses.

3. The product of the first two steps was used as the input for the final step to calibrate the sample. The responding sample was calibrated to the latest available Labour Force Survey (LFS)^{[footnote 6]} with respect to (i) gender by age, (ii) educational level by age, (iii) ethnic group, (iv) housing tenure, (v) ITL2 area, (vi) employment status by age, (vii) household size, (viii) presence of children, and (ix) internet use by age.

The sum of these ‘grossing’ weights equals the population of England aged 16+. An additional standardised weight was produced that was the same but scaled so the weights sum to the respondent sample size.

Equivalent weights were also produced for the (majority) subset of respondents who completed the survey by web. This weight was needed because some questionnaire items were included in the web questionnaire but not the paper questionnaire.

For the annual dataset (quarters 1, 2, 3 and 4), the ‘grossing’ weights were re-scaled and new standardised weights produced to ensure that each quarter would contribute equally to estimates based on the annual dataset.

After this, the whole annual dataset was re-calibrated using the average of the population totals used for calibrating each quarterly dataset. In addition (as part of the same process), new population totals were included in the calibration matrix: for each of the 33 ITL2 areas, the (adjusted) mid-2023 population estimates for six groups: men aged 16-34, men aged 35-64, men aged 65+, women aged 16-34, women aged 35-64, women aged 65+. The published mid-2023 population estimates were adjusted very slightly to ensure no conflict with the national sex/age population totals – based on the Labour Force Survey – that were also included in the calibration matrix.

The final weight variables in the quarters one, two, three and four datasets are:

• ‘Finalweight’ – to be used when analysing data available from both the web and paper questionnaires.

• ‘Finalweightweb’ – to be used when analysing data available only from the web questionnaire.

The final weight variables in the annual dataset are:

• ‘Y4SampleSizeWeight’ – to be used when analysing data available from both the web and paper questionnaires.

• ‘Y4SampleSizeWeight_WebOnly’ – to be used when analysing data available only from the web questionnaire.

It should be noted that the weighting only corrects for observed bias (for the set of variables included in the weighting matrix) and there is a risk of unobserved bias. Furthermore, the raking algorithm used for the weighting only ensures that the sample margins match the population margins. There is no guarantee that the weights will correct for bias in the relationships between the variables.

7. Appendix

7.1 Invitation letter

7.2 Reminder letter 1

7.2.1 Partial response

7.2.2 No response

7.3 Reminder letter 2

7.3.1 Partial response with paper questionnaires included

7.3.2 Partial response with no paper questionnaires included

7.3.3 No response with paper questionnaires included

7.3.4 No response with no paper questionnaires included

7.4 Reminder letter 3

7.4.1 Partial response

7.4.2 No response

7.5 FAQs printed on the reverse of all survey invitation and reminder letters

7.6 Ad hoc paper questionnaire request letter

7.7 Postal incentive letter

1. In February 2023, there was a Machinery of Government (MoG) change and responsibility for digital policy now sits within the Department for Science, Innovation and Technology (DSIT). This MoG change did not affect the contents of the Participation Survey for 2024/25 – digital questions are still part of this survey year. ↩

2. International Territorial Level (ITL) is a geocode standard for referencing the subdivisions of the United Kingdom for statistical purposes, used by the Office for National Statistics (ONS). Since 1 January 2021, the ONS has encouraged the use of ITL as a replacement to Nomenclature of Territorial Units for Statistics (NUTS), with lookups between NUTS and ITL maintained and published until 2023. ↩

3. Due to rounding, the percentage figures per segment may sum to slightly more than 100%. ↩

4. Response rates (RR) were calculated via the standard ABOS method. An estimated 8% of ‘small user’ PAF addresses in England are assumed to be non-residential (derived from interviewer administered surveys). The average number of adults aged 16 or over per residential household, based on the Labour Force Survey, is 1.89. Thus, the response rate formula: Household RR = number of responding households / (number of issued addresses×0.92); Individual RR = number of responses / (number of issued addresses×0.92×1.89). The conversion rate is the ratio of the number of responses to the number of issued addresses. ↩

5. Interview lengths under 2 minutes are removed, and they are capped at the 97th percentile. If interviews are under 10 minutes, they are flagged in the system for the research team to evaluate; if they are flagged for other validation checks, then those interviews are removed. ↩

6. January-March 2024 for quarter one, April-June 2024 for quarter two, July-September 2024 for quarter three, and October-December 2024 for quarter four. ↩