Article
The iBikE Smart Learner – an interactive web-based learning tool to specifically address statistical misconceptions
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Authors
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Sophie K. Piper
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Ralph Schilling
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Oliver Schweizerhof
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Anne Pohrt
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Dörte Huscher
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Uwe Schöneberg
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
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Ulrike Grittner
- Insitute of Biometry and Clinical Epidemiology, Charité Universitaetsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany
| Published: | February 26, 2021 |
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Outline
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Background: Statistics is often not a popular subject for medical students and researchers. However, methodological skills are essential for the quality of research and for the correct interpretation of research results. Understanding statistical concepts in particular plays a central role. In standard medical training, relatively little attention is paid to the development of these competencies, so that researching physicians (from students to professors) often have deficits and misconceptions.
The most typical example is the incorrect interpretation of the p-value. Misconceptions lead to misinterpretations of what statistics can do and where certain methods reach their limits. As a consequence, methods are misused and/or results are misinterpreted, which in turn can have consequences for further research and ultimately for patients.
Methods: We developed a learning tool called the “iBikE Smart learner” – an interactive, web-based teaching program analogous to the AMBOSS learning software for medical students. It addresses common misconceptions in statistics in a targeted manner and adapted to the individual knowledge of the user.
Specifically, we were able to complete the content of the first module “Statistical misconceptions about the p-value”. The module consists of a self-contained set of multiple choice, which directly address common misconceptions on the basis of typical examples in medical research.
In addition, we obtained ethics approval in January 2020 for a randomized controlled trial to evaluate the interactive web-based learning program. We will start recruitment as soon as the Corona pandemic has been pushed back. We also plan to make a poll among participants of the GMDS&CEN conference 2020.
Results: A first (beta) version of the “iBikE Smart Learner” was available at the end of October 2019 and has been tested internally by experienced staff members of our institute. We plan promote the tool and to show results of the evaluation study.
Conclusion: We developed a first module of a web-based teaching tool addressing common misconceptions about the p-value which will be promoted at the GMDS&CEN conference 2020.
The authors declare that they have no competing interests.
The authors declare that a positive ethics committee vote has been obtained.
