Christie A. P. auteur aut IRD Abecasis D. auteur aut IRD Adjeroud Mehdi auteur aut IRD Alonso J. C. auteur aut IRD et al. auteur aut IRD text journalArticle eng text/pdf reformatted digital access Building trust in science and evidence-based decision-making depends heavily on the credibility of studies and their findings. Researchers employ many different study designs that vary in their risk of bias to evaluate the true effect of interventions or impacts. Here, we empirically quantify, on a large scale, the prevalence of different study designs and the magnitude of bias in their estimates. Randomised designs and controlled observational designs with pre-intervention sampling were used by just 23% of intervention studies in biodiversity conservation, and 36% of intervention studies in social science. We demonstrate, through pairwise within-study comparisons across 49 environmental datasets, that these types of designs usually give less biased estimates than simpler observational designs. We propose a model-based approach to combine study estimates that may suffer from different levels of study design bias, discuss the implications for evidence synthesis, and how to facilitate the use of more credible study designs. Randomised controlled experiments are the gold standard for scientific inference, but environmental and social scientists often rely on different study designs. Here the authors analyse the use of six common study designs in the fields of biodiversity conservation and social intervention, and quantify the biases in their estimates. specialized 020 021 11 1 6377 [11 ] 2020 2041-1723 https://www.documentation.ird.fr/hor/fdi:010080491 10.1038/s41467-020-20142-y 2041-1723 [F B010080491] https://www.documentation.ird.fr/hor/fdi:010080491 https://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers21-01/010080491.pdf IRD - Base Horizon / Pleins textes 2021-02-08 2025-02-24 fdi:010080491 fre