Cultured meat acceptance among young Polish consumers (18–34): Survey data on intentions, benefits, barriers, and normative fit

This dataset contains responses from an online survey on cultured meat (CM) acceptance conducted among young Polish consumers aged 18–34. Data were collected between May 2024 and June 2025 via the SurvGo.com platform, using a quota sampling procedure stratified by gender and education. The final sample comprises N = 406 respondents (63.1% female) who completed the full questionnaire.
The survey instrument consisted of 44 items organised into the following sections: (1) CM awareness and dietary background (Q1–Q5); (2) meat purchase motives (Q7.1–Q7.8; displayed only to meat-consuming respondents, resulting in 59 structurally missing values); (3) willingness to replace meat with alternatives (Q9); (4) perceived benefits of CM on a 7-point Likert scale, including safety, nutrition, taste, environment, animal welfare, and food security (Q10–Q16); (5) intention toward CM on a 5-point Likert scale, capturing two dimensions: Private Acceptance (Q17.1–Q17.3: willingness to try, purchase, and pay more) and Social Diffusion Readiness (Q17.4–Q17.5: willingness to prepare for others and to try upon recommendation) (Q17.1–Q17.5); (6) affective-ontological barriers on a 5-point Likert scale, including health concerns, food novelty distrust, technological and CM-specific unnaturalness, and long-term health concerns (Q18.1–Q18.5), plus a single-item 7-point disgust measure (Q13); (7) normative fit on a 5-point Likert scale, assessing perceived need, superiority over traditional meat, and alignment with personal standards (Q19–Q21); (8) demographic variables: gender (Q22), age (Q23), education (Q24), place of residence (Q25), employment status (Q26), parental status (Q27), and household income (Q28); and (9) additional intention measures, including a binary willingness-to-try item (Q31).

The file (FullDataPoland_recoded.csv) is a semicolon-separated CSV with UTF-8 encoding. Barrier items Q18.1–Q18.5 have been reverse-coded so that higher scores indicate stronger barriers. All item wordings, response scales, and source references are provided in the Supplementary Material (Table S1) of the associated article.

The dataset supports analyses reported in the related publication, including confirmatory factor analysis (WLSMV), hierarchical OLS regression, gradient boosting machine prediction with SHAP explainability, and moderation analysis. The study was classified as exempt from ethics committee review by the Institutional Review Board of the Poznań University of Life Sciences (April 2024). All data are fully anonymised; no personally identifiable information was collected