Sample

8,000 interviews were conducted online with adults aged 18+ using proprietary online panels. These panellists are recruited and agree to receive surveys periodically. Invitations for individual surveys are sent out according to the quota targets to control the sample profile, and respondents receive a small financial incentive (e.g. £0.50-£1.00 per five minutes of survey time). Fieldwork took place across 11-21 July 2025.

Quotas targets were set on region, age and gender (interlocked within region) and ethnicity to ensure that the sample reflects the known profile of the UK population on these demographic criteria. Minor shortfalls in achieving quota targets were addressed using RIM weighting post hoc, including additional weighting applied to socioeconomic group to ensure the correct profile according to the UK population.

Providers

The research was led by Icaro, a Market Research Society (MRS) Company Partner. Survey fieldwork was executed by Deltapoll, who are a member of the British Polling Council and abide by its rules.

Survey design

Survey questionnaires went through several rounds of iteration between Icaro and the CaSE team. Quantitative opinion data is always subject to a number of possible biases, most importantly a tendency for participants to agree with statements or “satisfice”. To counteract this, the survey was designed to vary the types of questions shown, and incorporate binary choice scales and multi-select questions as well as agree-disagree Likert-style questions. Attention was also given to the potential for sequencing bias and priming, with questions about awareness of the term R&D, for example, appearing early in the questionnaire.

Reaching the sample

Participants were recruited through online proprietary panel providers, where individuals register their interest in taking part in online research in return for incentives. By their nature, online samples exclude those with low levels of digital access, however they enable strong control over the demographic make-up of the final sample. The sample is targeted to be representative of the UK public according to the chosen quotas. All surveys are subject to some level of recruitment bias, where those who are interested in taking part may represent a more “engaged” group of people than if the selection was truly random. By reaching the sample through online panels, incentives can be tailored to meet specific groups to encourage the participation of those who are less likely to volunteer.

The survey also features attentional checks for inattentive responding, both in the form of trap questions where participants are instructed to select a specific answer option in order to proceed, and open-response questions which are retrospectively assessed for “nonsense” responding. All surveys also feature “reCAPTCHA” checks for bots, to prevent surveys being flooded by scripted responses, with a second check for such problems during analysis of any open responses.

Analysis

Full access to the data tables is provided from CaSE’s website (see Download the Data), broken down by demographic groups. We have adopted a convention that sample sizes of less than 300 are too small for meaningful analysis or to adequately represent the sub-group, and so they are avoided throughout our analysis.

All survey results are subject to margins of error (because a sample has been surveyed, unlike in a Census where everyone answers). Statistical tests have been undertaken to the 99% confidence level (i.e. 99 times out of 100 the observed difference will be real vs. 1 time out of 100 it will have happened by chance).

For this survey with a sample of 8,000, the maximum margin of error in the results is ±1.4% (i.e. if the survey result is 50% then the real result if everyone in the UK was interviewed would be in the range 48.6% – 51.4%). When comparing the results from this survey with previous surveys undertaken by CaSE of an equivalent sample size, the maximum margin of error between waves is ±2.0% (i.e. an increase from 50% to 53% would be statistically significant, but an increase from 50% to 52% would not).

NB. Statistical tests are only valid when the survey method has used random probability sampling. While the market research industry routinely applies the same logic to non-probability samples, like this survey, this must be done with appropriate caveats – including an acknowledgement that confidence limits are, technically speaking, not possible to calculate. Any reference in this report to statistically significant differences should be used to accurately guide the interpretation of trends and differences in the data, rather than be taken to be objective statistical fact.

CaSE’s 2025 tracker survey explored the following areas, with results described in detail on the CaSE Public Attitudes to R&D 2025 results page.

• • Priorities and outlooks
  • Awareness and understanding of R&D
  • Benefits of R&D
  • R&D and place
  • Investing in R&D
  • Engagement and involvement in R&D
  • Trust

The qualitative research involved three elements of work

Eight focus groups involving 64 participants
Follow up in depth interviews with 10 of the focus group participants (undertaken online)
Follow up video interviews with 12 of the focus group participants, using a smartphone app called Indeemo (which is similar to Instagram)

a) Focus groups

The focus groups involved UK adults, selected to meet certain demographic or attitudinal criteria, participating in a facilitated discussion led by a moderator.

These groups were held face to face in eight different locations across the UK: Belfast, Cardiff, Clacton, Edinburgh, London (Sutton/Croydon), Middlesbrough, Nottingham and Taunton. These locations were selected by Icaro and CaSE to reflect: (a) representation of the four UK nations and English region; (b) political representation in terms of how the areas voted in the 2024 UK General Election, (c) a mix of cities and towns (including coastal towns), and (d) a mix of levels of R&D activity happening in each locality. One group was conducted in each location.

Focus groups are useful for understanding – in people’s own words – why they hold the views they do. They are particularly useful in unpicking views and providing granularity about the ‘how’ and ‘why’ that sits behind headline survey findings. However, the resulting data necessarily comes from a small sample size, so it is conveyed in terms of key discussion themes (and supporting quotes) and never in the form of statistics. We avoid drawing conclusions about the “proportion” who hold views and instead focus on exploring broad themes. Words such as ‘most’ or ‘only some’ are sometimes used to distinguish overtly majority or minority positions, but it was

not the intention of the groups to establish consensus, nor dismiss positions held by only some in the group (since they may reflect a wider audience outside of the confines of a group of eight individuals).

Recruitment

Once the locations for the groups were determined, recruitment of participants from that locality was undertaken according to a recruitment questionnaire. This performs two roles: the first to screen out participants who work in certain industries (e.g. market research) or have undertaken more than a certain number of focus groups in the past six months; the second to set quotas to guide the composition of the sample. The following quota variables were used:

Gender (50:50 split)
Age (a mix of ages from 21-70)
Socioeconomic grade (a mix across AB, C1, C2, DE)
Ethnicity (representation of White and BAME groups, flexed to locality)
Vote intention at the next UK General Election (minimum 2 Centre Left; 2 Conservative; 2 Reform)
Pre-existing interest in science (from a long list of subjects of interest): minimum two; maximum four

Discussion guides and moderating groups

Moderators who facilitate the focus groups follow a discussion guide, which establishes the key questions to be answered throughout the group, with ample space for discussion to deviate if new topics or discussion points arise. The role of the moderator is to ensure:

Everyone in the group is given opportunity to express their views.
The conversation is not derailed by arguments between participants, or by individual participants dominating the conversation.
The conversation remains on topic. This is particularly important when the discussion covers broad or abstract areas like R&D.
That, where possible, relevant points made by participants are explored in more detail by prompting with follow-up questions.

Analysis

Analysis of qualitative data is normally carried out through detailed readings of the transcripts, identifying broad themes and language used by the participants, and looking for patterns in how participants respond to the specific questions. In our analysis we have aimed to demonstrate both where the broad findings of the quantitative research have been supported by qualitative data and where it has been challenged. We have aimed to present any quotations from the qualitative work with as much context as possible, to ensure these can be reliably interpreted.

b) In depth interviews

Following on from the focus groups, a smaller number of participants from the original groups (10) were recontacted to take part in an interview. Interviews were 30 minutes in length and conducted online, in the form of a semi-structured discussion with one of the focus group moderators. They took place from 25 – 29 September 2025.

The purpose of the interviews was to three-fold: a) to follow up in more detail some of the themes covered in the groups (e.g. benefits of R&D); (b) to capture views towards some themes that were not possible to cover adequately in the groups (e.g. views on what a researcher is like / who they are); and (c) to capture any further reflections they’d had since the groups (e.g. had they given RD& any more thought, or discussed it with friends/family).

c) Video interviews (via Indeemo)

In parallel to the depth interviews, 12 participants from the focus groups were recontacted and invited to take part in a follow on phase that involved answering questions through selfie videos, using a dedicated ‘in the moment’ research app called Indeemo.

Six questions were pre-determined and – like the depth interviews – they covered a mix of territory from the focus groups as well as new topics (e.g. how can the R&D sector ensure it connects more with the public?). The main difference to the depth interviews (other than some differences in thematic coverage) is that there is no moderator present and the process is self-guided. The outputs are also different and primarily take the form of video clips or video reels to convey what respondents think in their own words (in a highly engaging and visual way). They took place from 27 – 30 September 2025.

Quotes in the report

Quotes are used throughout the report to illustrate the points being discussed and help ‘bring the findings to life’. Each quote is tagged with some basic information about the participant (i.e. gender, age band, location, socioeconomic group). In addition, the last element of the tag indicates where the quote originated from (either ‘focus groups’, ‘depth interview’ or ‘Indeemo’).

The quantitative research carried out as part of this project included five surveys run online with a UK sample of adults aged 18 and over. Public First is a member of the British Polling Council (BPC) and a company partner of the Market Research Society (MRS) and abides by their rules. 

Survey design

Survey questionnaires went through several rounds of iteration. Quantitative opinion data is always subject to a number of possible biases, most importantly a tendency for participants to agree with statements or “satisfice”. To counteract this, we design the survey to vary the types of questions shown, and incorporate binary choice scales and multi-select questions as well as agree-disagree likert-style questions.

Reaching the sample

Participants were recruited through online proprietary panel providers, where individuals register their interest in taking part in online research in return for incentives. By their nature, online samples exclude those with low levels of digital access, however they enable strong control over the demographic make-up of the final sample. The sample is targeted to be representative of the UK public, along interlocked age and gender, regional and socio-economic grade lines. All surveys are subject to some level of recruitment bias, where those who are interested in taking part may represent a more “engaged” group of people than if the selection was truly random. By reaching the sample through online panels, incentives can be tailored to meet specific groups to encourage the participation of those who are less likely to volunteer.

The survey also features attentional checks for inattentive responding, both in the form of trap questions where participants are instructed to select a specific answer option in order to proceed, and open-response questions which are retrospectively assessed for “nonsense” responding. All surveys also feature “reCAPTCHA” checks for bots, to prevent surveys being flooded by scripted responses, with a second check for such problems during analysis of any open responses.

Analysis

Our section – Download the Data – provides access to the full data tables, broken down by demographic groups. In general, sample sizes of less than 100 are considered too small for statistical analysis, and are avoided throughout our analysis. For a sample of over 8,000 the margin of error is +/- 1%, meaning we can be 95% confident that the real proportion lies within 1% of the reported statistic at the top level.

When samples are split, either through different message testing, or crossbreaks, this margin of error will increase. As a rough guide, the margin of error for different samples sizes are:

• • 4,000 sample size: 2%
  • 2,000 sample size: 2%
  • 1,000 sample size: 3%
  • 500 sample size: 4%
  • 100 sample size: 10%

CaSE commissioned a poll to explore public attitudes to R&D and the Government’s missions, following the election of the Labour Government.

• Attitudes to the Government missions and the UK’s economic situation
• Attitudes to R&D-based approaches to the Government missions: Do the public think investing in R&D is an effective approach to achieving the missions, and how do R&D approaches affect how people feel about the missions?
• Perceived importance of R&D in achieving mission-based objectives: How much of a priority are objectives relating to the missions, and how important a role does the public feel R&D has to play in achieving these objectives?
• Competing priorities and clarity on R&D’s role in the missions: Should R&D approaches be taken over other approaches, what R&D solutions support the missions, and how clear is R&D’s role in helping achieve the missions?
• Attitudes to R&D and national security: Do the public think investing in R&D is a clear and effective approach to improve national security, and how appropriate are R&D spending levels on defence?
• Attitudes of the Labour party’s ‘target voters’ towards R&D and the missions: Do the attitudes of the voter groups that the Labour party is expected to be focusing on ahead of the next election align more closely with attitudes of Labour-leaning individuals or with the attitudes of those intending to vote for the alternative parties key voters are considering?

The qualitative research carried out as part of this project consisted of focus groups. This involves participants, selected to meet certain demographic or attitudinal criteria, participating in a facilitated discussion led by a moderator.

These groups were held online. Since the pandemic, much qualitative research which would have traditionally been conducted in-person has migrated online. This offers increased accessibility for participants who no longer have to travel for the group, and allows participation to more easily fit around other commitments. We have also found it encourages more participants to express their views, as participants tend to take turns to speak more than they would in a physical setting. The challenges of an online setting are mainly infrequent technical difficulties, accessibility for those who are digitally excluded, and the risk of distractions within the home.

Focus groups are useful for understanding – in people’s own words – why they hold the views they do. However, the resulting data necessarily comes from a small sample size, so it is primarily conveyed via quotes rather than statistics. We avoid drawing conclusions about the “proportion” who hold views on the basis of qualitative work, and instead focus on exploring broad themes.

Recruitment

Recruitment is typically done on a geographical basis, focussing on a specific area such as a city, parliamentary constituency or broad region. This research involved groups in:

• Hendon: The Conservative 2019 target voter subgroup, who swung from voting Conservative in 2019 to Labour in 2024
• Kingston-Upon-Hull East: A smaller group of those who voted Reform UK in 2024 and are considering voting Labour in future.

Discussion Guides and running groups

Moderators who facilitate the focus groups follow a discussion guide, which establishes the key questions to be answered throughout the group, with ample space for discussion to deviate if new topics or discussion points arise. For copies of the discussion guides used in our groups, please contact Rebecca Hill.

The role of the moderator is to ensure:

• Everyone in the group is given opportunity to express their views
• The conversation is not derailed by arguments between participants, or by individual participants dominating the conversation.
• The conversation remains on topic. This is particularly important when the discussion covers broad or abstract areas like R&D.
• That, where possible, relevant points made by participants are explored in more detail by prompting with follow-up questions.

Analysis

Analysis of qualitative data is normally carried out through detailed readings of the transcripts, identifying broad themes and language used by the participants, and looking for patterns in how participants respond to the specific questions. In our analysis we have aimed to demonstrate both where the broad findings of the quantitative research have been supported by qualitative data and where it has been challenged. We have aimed to present any quotations from the qualitative work with as much context as possible, to ensure these can be reliably interpreted.

The quantitative research carried out as part of this project included five surveys run online with a UK sample of adults aged 18 and over. Public First is a member of the British Polling Council (BPC) and a company partner of the Market Research Society (MRS) and abides by their rules. 

Survey design

Survey questionnaires went through several rounds of iteration. Quantitative opinion data is always subject to a number of possible biases, most importantly a tendency for participants to agree with statements or “satisfice”. To counteract this, we design the survey to vary the types of questions shown, and incorporate binary choice scales and multi-select questions as well as agree-disagree likert-style questions.

Reaching the sample

Participants were recruited through online proprietary panel providers, where individuals register their interest in taking part in online research in return for incentives. By their nature, online samples exclude those with low levels of digital access, however they enable strong control over the demographic make-up of the final sample. The sample is targeted to be representative of the UK public, along interlocked age and gender, regional and socio-economic grade lines. All surveys are subject to some level of recruitment bias, where those who are interested in taking part may represent a more “engaged” group of people than if the selection was truly random. By reaching the sample through online panels, incentives can be tailored to meet specific groups to encourage the participation of those who are less likely to volunteer.

The survey also features attentional checks for inattentive responding, both in the form of trap questions where participants are instructed to select a specific answer option in order to proceed, and open-response questions which are retrospectively assessed for “nonsense” responding. All surveys also feature “reCAPTCHA” checks for bots, to prevent surveys being flooded by scripted responses, with a second check for such problems during analysis of any open responses.

Analysis

Our section – Download the Data – provides access to the full data tables, broken down by demographic groups. In general, sample sizes of less than 100 are considered too small for statistical analysis, and are avoided throughout our analysis. For a sample of over 8,000 the margin of error is +/- 1%, meaning we can be 95% confident that the real proportion lies within 1% of the reported statistic at the top level.

When samples are split, either through different message testing, or crossbreaks, this margin of error will increase. As a rough guide, the margin of error for different samples sizes are:

• • 4,000 sample size: 2%
  • 2,000 sample size: 2%
  • 1,000 sample size: 3%
  • 500 sample size: 4%
  • 100 sample size: 10%

CaSE commissioned a poll to explore public attitudes to global-facing R&D, which is research carried out in the UK that has benefits elsewhere. It explored:

• Attitudes to issues facing the UK and the world
• The UK’s role in global problems, including whose responsibility it is to tackle global problems, the UK’s role and how it compares with other countries
• The role of R&D in tackling global problems, including exploration of cooperation between countries, the investment of UK funds, priority research areas and benefits of UK-based R&D on global issues
• The most effective or convincing messaging about R&D and who are trusted messengers
• Attitudes to UK-based research infrastructure and centres

The qualitative research carried out as part of this project consisted of focus groups. This involves participants, selected to meet certain demographic or attitudinal criteria, participating in a facilitated discussion led by a moderator.

These groups were held online. Since the pandemic, much qualitative research which would have traditionally been conducted in-person has migrated online. This offers increased accessibility for participants who no longer have to travel for the group, and allows participation to more easily fit around other commitments. We have also found it encourages more participants to express their views, as participants tend to take turns to speak more than they would in a physical setting. The challenges of an online setting are mainly infrequent technical difficulties, accessibility for those who are digitally excluded, and the risk of distractions within the home.

Focus groups are useful for understanding – in people’s own words – why they hold the views they do. However, the resulting data necessarily comes from a small sample size, so it is primarily conveyed via quotes rather than statistics. We avoid drawing conclusions about the “proportion” who hold views on the basis of qualitative work, and instead focus on exploring broad themes.

Recruitment

Recruitment is typically done on a geographical basis, focussing on a specific area such as a city, parliamentary constituency or broad region. This research involved groups in Leeds and Coventry, with participants selected by whether they recently donated to charity.

Discussion Guides and running groups

Moderators who facilitate the focus groups follow a discussion guide, which establishes the key questions to be answered throughout the group, with ample space for discussion to deviate if new topics or discussion points arise. For copies of the discussion guides used in our groups, please contact Rebecca Hill.

The role of the moderator is to ensure:

• Everyone in the group is given opportunity to express their views
• The conversation is not derailed by arguments between participants, or by individual participants dominating the conversation.
• The conversation remains on topic. This is particularly important when the discussion covers broad or abstract areas like R&D.
• That, where possible, relevant points made by participants are explored in more detail by prompting with follow-up questions.

Analysis

Analysis of qualitative data is normally carried out through detailed readings of the transcripts, identifying broad themes and language used by the participants, and looking for patterns in how participants respond to the specific questions. In our analysis we have aimed to demonstrate both where the broad findings of the quantitative research have been supported by qualitative data and where it has been challenged. We have aimed to present any quotations from the qualitative work with as much context as possible, to ensure these can be reliably interpreted.

The quantitative research carried out as part of this project included five surveys run online with a UK sample of adults aged 18 and over. Public First is a member of the British Polling Council (BPC) and a company partner of the Market Research Society (MRS) and abides by their rules. 

Survey design

Survey questionnaires went through several rounds of iteration. Quantitative opinion data is always subject to a number of possible biases, most importantly a tendency for participants to agree with statements or “satisfice”. To counteract this, we design the survey to vary the types of questions shown, and incorporate binary choice scales and multi-select questions as well as agree-disagree likert-style questions.

Reaching the sample

Participants were recruited through online proprietary panel providers, where individuals register their interest in taking part in online research in return for incentives. By their nature, online samples exclude those with low levels of digital access, however they enable strong control over the demographic make-up of the final sample. The sample is targeted to be representative of the UK public, along interlocked age and gender, regional and socio-economic grade lines. All surveys are subject to some level of recruitment bias, where those who are interested in taking part may represent a more “engaged” group of people than if the selection was truly random. By reaching the sample through online panels, incentives can be tailored to meet specific groups to encourage the participation of those who are less likely to volunteer.

The survey also features attentional checks for inattentive responding, both in the form of trap questions where participants are instructed to select a specific answer option in order to proceed, and open-response questions which are retrospectively assessed for “nonsense” responding. All surveys also feature “reCAPTCHA” checks for bots, to prevent surveys being flooded by scripted responses, with a second check for such problems during analysis of any open responses.

Analysis

Our section – Download the Data – provides access to the full data tables, broken down by demographic groups. In general, sample sizes of less than 100 are considered too small for statistical analysis, and are avoided throughout our analysis. For a sample of over 8,000 the margin of error is +/- 1%, meaning we can be 95% confident that the real proportion lies within 1% of the reported statistic at the top level.

When samples are split, either through different message testing, or crossbreaks, this margin of error will increase. As a rough guide, the margin of error for different samples sizes are:

• • 4,000 sample size: 2%
  • 2,000 sample size: 2%
  • 1,000 sample size: 3%
  • 500 sample size: 4%
  • 100 sample size: 10%

CaSE commissioned two polls ahead of the General Election 2024. This first poll explored:

• Economic growth: Do the public feel confident in their understanding of economic terms, and do they associate R&D with economic growth?
• Jobs: What types of jobs do the public want the Government to priorities, and qualities do the public link to R&D jobs?
• Local actions related to R&D: Do the public want to see their next MP taking action to support R&D?
• Trust: Do the public trust scientists to talk about R&D?
• Tracking questions: Exploring how attitudes to R&D, its benefits and engagement opportunities have changed since previous polling

The second poll ahead of the General Election explored:

• Priority issues for the public and political parties: What are the public’s main concerns, which issues should political parties focus on, and what areas have got better or worse in the past 10 years?
• Attitudes to R&D breakthroughs and priority topics: How do the public feel about potential R&D breakthroughs, and what areas do they think should be prioritised?
• Attitudes to actions to support R&D for the next Government: How do the public feel about R&D-related actions the next Government could take, and who should advise next Government?
• Attitudes to UK universities and international students and researchers: Do the public see benefits of UK universities, and efforts to attract international researchers?

Public First worked with Electoral Calculus to produce a Multi-Level Regression with Poststratification (MRP) analysis of these results, modelling the expected attitudes at a constituency level.

Using the demographic information provided by the participants, multi-level regression models are fit to assess the relationship between demographics and views on R&D in 13 questions.

This enables us to make predictions as to how individuals who fill specific demographic categories (e.g. male, 18-24, white British…) would respond to each question.

These predictions are then “post-stratified” – using known proportions of people in these demographic categories in each Westminster constituency so that we can predict the likely outcome of asking the question in that local area.

NB due to the size of sample in Northern Ireland and the unique political correlates, models do not include projections for these constituencies
The results of this process are shown on the Results tab.

Important Notes:

• These results are modeled predictions; assuming that the relationships we find between R&D attitudes and demographic hold up in all areas, this is how this question would likely pan out at the constituency level.
• This means that hyper-local context or factors cannot be taken into account. For example, a controversy surrounding a specific local candidate for Parliament would not be picked up by this process.