Showing papers by "Jelte M. Wicherts published in 2022"
TL;DR: Understanding the prevalence of responsible research practices across disciplines and ranks, as well as their associated explanatory factors, can help to systematically address disciplinary- and academic rank-specific obstacles, and thereby facilitate responsible conduct of research.
Abstract: Background: Traditionally, research integrity studies have focused on research misbehaviors and their explanations. Over time, attention has shifted towards preventing questionable research practices and promoting responsible ones. However, data on the prevalence of responsible research practices, especially open methods, open codes and open data and their underlying associative factors, remains scarce. Methods: We conducted a web-based anonymized questionnaire, targeting all academic researchers working at or affiliated to a university or university medical center in The Netherlands, to investigate the prevalence and potential explanatory factors of 11 responsible research practices. Results: A total of 6,813 academics completed the survey, the results of which show that prevalence of responsible practices differs substantially across disciplines and ranks, with 99 percent avoiding plagiarism in their work but less than 50 percent pre-registering a research protocol. Arts and humanities scholars as well as PhD candidates and junior researchers engaged less often in responsible research practices. Publication pressure negatively affected responsible practices, while mentoring, scientific norms subscription and funding pressure stimulated them. Conclusions: Understanding the prevalence of responsible research practices across disciplines and ranks, as well as their associated explanatory factors, can help to systematically address disciplinary- and academic rank-specific obstacles, and thereby facilitate responsible conduct of research.
7 citations
TL;DR: In this paper , the authors discuss common methods based on a review of the personality traits negative affectivity and social inhibition, and apply several longitudinal measurement invariance models, univariate and multivariate latent growth curves models, and latent trait-state occasions models to data from 2625 cancer survivors.
3 citations
TL;DR: Understanding the prevalence of responsible research practices across disciplines and ranks, as well as their associated explanatory factors, can help to systematically address disciplinary- and academic rank-specific obstacles, and thereby facilitate responsible conduct of research.
Abstract: Background: Traditionally, research integrity studies have focused on research misbehaviors and their explanations. Over time, attention has shifted towards preventing questionable research practices and promoting responsible ones. However, data on the prevalence of responsible research practices, especially open methods, open codes and open data and their underlying associative factors, remains scarce. Methods: We conducted a web-based anonymized questionnaire, targeting all academic researchers working at or affiliated to a university or university medical center in The Netherlands, to investigate the prevalence and potential explanatory factors of 11 responsible research practices. Results: A total of 6,813 academics completed the survey, the results of which show that prevalence of responsible practices differs substantially across disciplines and ranks, with 99 percent avoiding plagiarism in their work but less than 50 percent pre-registering a research protocol. Arts and humanities scholars as well as PhD candidates and junior researchers engaged less often in responsible research practices. Publication pressure negatively affected responsible practices, while mentoring, scientific norms subscription and funding pressure stimulated them. Conclusions: Understanding the prevalence of responsible research practices across disciplines and ranks, as well as their associated explanatory factors, can help to systematically address disciplinary- and academic rank-specific obstacles, and thereby facilitate responsible conduct of research.
3 citations
TL;DR: In this paper , a Bayesian two-dimensional item response theory (IRT) model was applied to data obtained from two registered reports that investigated stereotype threat in mathematics, and estimated the latent correlation between underlying test strategy (here, completion factor, a proxy for working speed).
Abstract: When cognitive and educational tests are administered under time limits, tests may become speeded and this may affect the reliability and validity of the resulting test scores. Prior research has shown that time limits may create or enlarge gender gaps in cognitive and academic testing. On average, women complete fewer items than men when a test is administered with a strict time limit, whereas gender gaps are frequently reduced when time limits are relaxed. In this study, we propose that gender differences in test strategy might inflate gender gaps favoring men, and relate test strategy to stereotype threat effects under which women underperform due to the pressure of negative stereotypes about their performance. First, we applied a Bayesian two-dimensional item response theory (IRT) model to data obtained from two registered reports that investigated stereotype threat in mathematics, and estimated the latent correlation between underlying test strategy (here, completion factor, a proxy for working speed) and mathematics ability. Second, we tested the gender gap and assessed potential effects of stereotype threat on female test performance. We found a positive correlation between the completion factor and mathematics ability, such that more able participants dropped out later in the test. We did not observe a stereotype threat effect but found larger gender differences on the latent completion factor than on latent mathematical ability, suggesting that test strategies affect the gender gap in timed mathematics performance. We argue that if the effect of time limits on tests is not taken into account, this may lead to test unfairness and biased group comparisons, and urge researchers to consider these effects in either their analyses or study planning.
TL;DR: In this article , the authors present guidance for sharing research data for verification and reuse, and suggest that behavioural researchers should protect participants privacy, particularly when studying sensitive topics, and they urge researchers to mend privacy via checks of re-identification risk before sharing data.
Abstract: When sharing research data for verification and reuse, behavioural researchers should protect participants’ privacy, particularly when studying sensitive topics. Because personally identifying data remain present in many open psychology datasets, we urge researchers to mend privacy via checks of re-identification risk before sharing data. We offer guidance for sharing responsibly.