Trust in scientists and their role in society across 67 countries

Scientific information is crucial for evidence-based decision-making. Public trust in science can help decision-makers act based on the best available evidence, especially during crises such as climate change or the COVID-19 pandemic. However, in recent years the epistemic authority of science has been challenged, causing concerns about low public trust in scientists. Here we interrogated these concerns with a pre-registered 67-country survey of 71,417 respondents on all inhabited continents and find that in most countries, a majority of the public trust scientists and think that scientists should be more engaged in policymaking. We further show that there is a discrepancy between the public’s perceived and desired priorities of scientific research. Moreover, we find variations between and within countries, which we explain with individual-and country-level variables,including political orientation. While these results do not show widespread lack of trust in scientists, we cannot discount the concern that lack of trust in scientists by even a small minority may affect considerations of scientific evidence in policymaking. These findings have implications for scientists and policymakers seeking to maintain and increase trust in scientists

Trust in scientists and their role in society across 67 countries

Scientific information is crucial for evidence-based decision-making. Public trust in science can help decision-makers act based on the best available evidence, especially during crises such as climate change or the COVID-19 pandemic. However, in recent years the epistemic authority of science has been challenged, causing concerns about low public trust in scientists. Here we interrogated these concerns with a pre-registered 67-country survey of 71,417 respondents on all inhabited continents and find that in most countries, a majority of the public trust scientists and think that scientists should be more engaged in policymaking. We further show that there is a discrepancy between the public’s perceived and desired priorities of scientific research. Moreover, we find variations between and within countries, which we explain with individual-and country-level variables,including political orientation. While these results do not show widespread lack of trust in scientists, we cannot discount the concern that lack of trust in scientists by even a small minority may affect considerations of scientific evidence in policymaking. These findings have implications for scientists and policymakers seeking to maintain and increase trust in scientists

Fast Track Algorithm: How To Differentiate A “Scleroderma Pattern” From A “Non-Scleroderma Pattern”

Objectives: This study was designed to propose a simple “Fast Track algorithm” for capillaroscopists of any level of experience to differentiate “scleroderma patterns” from “non-scleroderma patterns” on capillaroscopy and to assess its inter-rater reliability. Methods: Based on existing definitions to categorise capillaroscopic images as “scleroderma patterns” and taking into account the real life variability of capillaroscopic images described standardly according to the European League Against Rheumatism (EULAR) Study Group on Microcirculation in Rheumatic Diseases, a fast track decision tree, the “Fast Track algorithm” was created by the principal expert (VS) to facilitate swift categorisation of an image as “non-scleroderma pattern (category 1)” or “scleroderma pattern (category 2)”. Mean inter-rater reliability between all raters (experts/attendees) of the 8th EULAR course on capillaroscopy in Rheumatic Diseases (Genoa, 2018) and, as external validation, of the 8th European Scleroderma Trials and Research group (EUSTAR) course on systemic sclerosis (SSc) (Nijmegen, 2019) versus the principal expert, as well as reliability between the rater pairs themselves was assessed by mean Cohen's and Light's kappa coefficients. Results: Mean Cohen's kappa was 1/0.96 (95% CI 0.95-0.98) for the 6 experts/135 attendees of the 8th EULAR capillaroscopy course and 1/0.94 (95% CI 0.92-0.96) for the 3 experts/85 attendees of the 8th EUSTAR SSc course. Light's kappa was 1/0.92 at the 8th EULAR capillaroscopy course, and 1/0.87 at the 8th EUSTAR SSc course. C Conclusion: For the first time, a clinical expert based fast track decision algorithm has been developed to differentiate a “non-scleroderma” from a “scleroderma pattern” on capillaroscopic images, demonstrating excellent reliability when applied by capillaroscopists with varying levels of expertise versus the principal expert and corroborated with external validation.Wo