Boosting Understanding and Identification of Scientific Consensus Can Help to Correct False Beliefs

Stekelenburg, Aart van; Schaap, Gabi; Veling, Harm; Buijzen, Moniek

doi:10.1177/09567976211007788

Cited by 25 publications

(10 citation statements)

References 55 publications

(55 reference statements)

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“…Does high talker variability in training examples make it easier for non-native speakers to learn Mandarin tones (Dong et al, 2019)? Does informing people about the scientific consensus help correct false beliefs about climate change (Stekelenburg et al, 2021)? These research questions, drawn from across the psychological sciences, illustrate that we are often interested not only in the size of an effect, but in whether or not an effect exists at all.…”

Section: Introductionmentioning

confidence: 99%

Bayes factors for logistic (mixed effect) models

Silvey¹,

Dienes²,

Wonnacott³

2021

Preprint

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In psychology, we often want to know whether or not an effect exists. The traditional way of answering this question is to use frequentist statistics. However, a significance test against a null hypothesis of no effect cannot distinguish between two states of affairs: evidence of absence of an effect, and absence of evidence for or against an effect. Bayes factors can make this distinction; however, uptake of Bayes factors in psychology has so far been low for two reasons. Firstly, they require researchers to specify the range of effect sizes their theory predicts. Researchers are often unsure about how to do this, leading to the use of inappropriate default values which may give misleading results. Secondly, many implementations of Bayes factors have a substantial technical learning curve. We present a case study and simulations demonstrating a simple method for generating a range of plausible effect sizes based on the output from frequentist mixed-effects models. Bayes factors calculated using these estimates provide intuitively reasonable results across a range of real effect sizes. The approach provides a solution to the problem of how to come up with principled estimates of effect size, and produces comparable results to a state-of-the-art method without requiring researchers to learn novel statistical software.

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Section: Introductionmentioning

confidence: 99%

Bayes factors for logistic (mixed effect) models

Silvey¹,

Dienes²,

Wonnacott³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Moreover, many forms of skepticism seem unrelated or only very weakly related to science literacy (see Rutjens et al, 2018Rutjens et al, , 2022, and emphasizing the value of agreed upon knowledge (i.e., scientific consensus) in a particular domain is not always useful. More specifically, this has been shown to be effective in the case of genetically modified (GM) foods, but not climate change (van Stekelenburg et al, 2021). Finally, in some instances, increased knowledge and reasoning ability can even facilitate the "bending" of science information to fit the individual's ideology or worldview (e.g., Drummond & Fischhoff, 2017b;Kahan et al, 2012).…”

mentioning

confidence: 99%

Psychological Distance to Science as a Predictor of Science Skepticism Across Domains

Većkalov

Zarzeczna

McPhetres

et al. 2022

Pers Soc Psychol Bull

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This article presents and tests psychological distance to science (PSYDISC) as a domain-general predictor of science skepticism. Drawing on the concept of psychological distance, PSYDISC reflects the extent to which individuals perceive science as a tangible undertaking conducted by people similar to oneself ( social), with effects in the here ( spatial) and now ( temporal), and as useful and applicable in the real world ( hypothetical distance). In six studies (two preregistered; total N = 1,630) and two countries, we developed and established the factor structure and validity of a scale measuring PSYDISC. Crucially, higher PSYDISC predicted skepticism beyond established predictors, across science domains. A final study showed that PSYDISC shapes real-world behavior (COVID-19 vaccination uptake). This work thus provides a novel tool to predict science skepticism, as well as a construct that can help to further develop a unifying framework to understand science skepticism across domains.

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“…However, appreciating the value of scientific consensus is a sign of science literacy that partially predicts vaccination scepticism (Rutjens et al, 2018;. Pro-vaccination people can first be taught about the importance of scientific consensus (van Stekelenburg et al, 2021). Then, they could be equipped with two main messages: A message that underlines the importance of scientific consensus and another easy-to-remember messages emphasizing existing consensus on COVID-19 vaccines.…”

Section: Discussionmentioning

confidence: 99%

Science is coming closer: Manipulating psychological distance to COVID-19 vaccination

Erhan¹

2022

Preprint

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We have an effective weapon in the fight against the COVID-19 pandemic: vaccines. Despite their abundance, many people remain unvaccinated. Growing antivaccine scepticism likely contributes vaccine rejection. Previous research linked individual differences (i.e., spirituality and science literacy) to vaccination scepticism. This project moved beyond idiosyncratic factors and proposed a theory-driven and malleable predictor that can contribute to explain scepticism towards new (i.e., hypothetical vaccines adapted to fight off the variants more effectively) and existing COVID-19 vaccines in Turkey: psychological distance. We presented participants (N = 250) with one out of two statements regarding COVID-19 vaccines. The content of each statement was manipulated by utilizing psychologically close or distant terms. We found just- moderate evidence in favour of the null hypotheses that state invariance across both conditions by using Bayesian independent samples t-test. Psychological distance by itself is not a mutable and causal factor to bypass the stable factors contributing to COVID-19 vaccination scepticism in Turkey. Future studies should still consider coupling psychological distance with other measures to test its real potential.

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Boosting Understanding and Identification of Scientific Consensus Can Help to Correct False Beliefs

Cited by 25 publications

References 55 publications

Bayes factors for logistic (mixed effect) models

Bayes factors for logistic (mixed effect) models

Psychological Distance to Science as a Predictor of Science Skepticism Across Domains

Science is coming closer: Manipulating psychological distance to COVID-19 vaccination

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