Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset
Science is integral to society because it can inform individual, government, corporate, and civil society decision-making on issues such as public health, new technologies or climate change. Yet, public distrust and populist sentiment challenge the relationship between science and society. To help researchers analyse the science-society nexus across different geographical and cultural contexts, we undertook a cross-sectional population survey resulting in a dataset of 71,922 participants in 68 countries. The data were collected between November 2022 and August 2023 as part of the global Many Labs study “Trust in Science and Science-Related Populism” (TISP). The questionnaire contained comprehensive measures for individuals’ trust in scientists, science-related populist attitudes, perceptions of the role of science in society, science media use and communication behaviour, attitudes to climate change and support for environmental policies, personality traits, political and religious views and demographic characteristics. Here, we describe the dataset, survey materials and psychometric properties of key variables. We encourage researchers to use this unique dataset for global comparative analyses on public perceptions of science and its role in society and policy-making.
History
Citation
Mede, N.G., Cologna, V., Berger, S. et al. Perceptions of science, science communication, and climate change attitudes in 68 countries – the TISP dataset. Sci Data 12, 114 (2025). https://doi.org/10.1038/s41597-024-04100-7Author affiliation
College of Life Sciences Psychology & Vision SciencesVersion
- VoR (Version of Record)
Published in
Scientific DataVolume
12Issue
1Pagination
114Publisher
Springer Science and Business Media LLCissn
2052-4463eissn
2052-4463Acceptance date
2024-11-08Copyright date
2025Available date
2025-03-07Publisher DOI
Spatial coverage
EnglandLanguage
enPublisher version
Deposited by
Dr Mams ElsherifDeposit date
2025-02-20Data Access Statement
All data as well as the R code, and pre-computed models underlying the analyses described in this article, and Figs. 1–4 in high resolution are available at the Open Science Framework: https://osf.io/5c3qd.Rights Retention Statement
- No