The DOI matches its Crossref record; 136 of the 136 references it cites were found in a registry or an index.
Measuring Risk Literacy: The Berlin Numeracy Test
Open accessAbstract
We introduce the Berlin Numeracy Test, a new psychometrically sound instrument that quickly assesses statistical numeracy and risk literacy. We present 21 studies (n=5336) showing robust psychometric discriminability across 15 countries (e.g., Germany, Pakistan, Japan, USA) and diverse samples (e.g., medical professionals, general populations, Mechanical Turk web panels). Analyses demonstrate desirable patterns of convergent validity (e.g., numeracy, general cognitive abilities), discriminant validity (e.g., personality, motivation), and criterion validity (e.g., numerical and non-numerical questions about risk). The Berlin Numeracy Test was found to be the strongest predictor of comprehension of everyday risks (e.g., evaluating claims about products and treatments; interpreting forecasts), doubling the predictive power of other numeracy instruments and accounting for unique variance beyond other cognitive tests (e.g., cognitive reflection, working memory, intelligence). The Berlin Numeracy Test typically takes about three minutes to complete and is available in multiple languages and formats, including a computer adaptive test that automatically scores and reports data to researchers (http://www.riskliteracy.org). The online forum also provides interactive content for public outreach and education, and offers a recommendation system for test format selection. Discussion centers on construct validity of numeracy for risk literacy, underlying cognitive mechanisms, and applications in adaptive decision support.
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1 retracted
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Cited by
Susceptibility to misinformation about COVID-19 around the world
Roozenbeek, J., Schneider, C. R., Dryhurst, S., Kerr, J., Freeman, A. L. J., Recchia, G., van der Bles, A. M., & van der Linden, S. (2020) · Royal Society Open Science · doi:10.1098/rsos.201199 · Cited by 1,447
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ChatGPT in medical school: how successful is AI in progress testing?
Friederichs, H., Friederichs, W. J., & März, M. (2023) · Medical Education Online · doi:10.1080/10872981.2023.2220920 · Cited by 122
Metadata
- Authors
- Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R.
- Venue
- Judgment and Decision Making
- Publisher
- Cambridge University Press (CUP)
- Published
- 2012-01
- Volume
- 7
- Issue
- 1
- Pages
- 25-47
- ISSN
- 1930-2975 (ISSN-L)
- OpenAlex
- W2142604507
- Cited by
- 745
- References
- 136
- FWCI
- 31.54
- Type
- journal article
- Language
- en
- Open access
- gold
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