Sharing data has many benefits. However, data sharing rates remain low, for the most part well below 50%. A variety of interventions encouraging data sharing have been proposed. We focus here on editorial policies. Kidwell et al. (2016) assessed the impact of the introduction of badges in Psychological Science; Hardwicke et al. (2018) assessed the impact of Cognition’s mandatory data sharing policy. Both studies found policies to improve data sharing practices, but only assessed the impact of the policy for up to 25 months after its implementation. We examined the effect of these policies over a longer term by reusing their data and collecting a follow-up sample including articles published up until December 31st, 2019. We fit generalized additive models as these allow for a flexible assessment of the effect of time, in particular to identify non-linear changes in the trend. These models were compared to generalized linear models to examine whether the non-linearity is needed. Descriptive results and the outputs from generalized additive and linear models were coherent with previous findings: following the policies in Cognition and Psychological Science, data sharing statement rates increased immediately and continued to increase beyond the timeframes examined previously, until reaching close to 100%. In Clinical Psychological Science, data sharing statement rates started to increase only two years following the implementation of badges. Reusability rates jumped from close to 0% to around 50% but did not show changes within the pre-policy nor the post-policy timeframes. Journals that did not implement a policy showed no change in data sharing rates or reusability over time. There was variability across journals in the levels of increase, so we suggest future research should examine a larger number of policies to draw conclusions about their efficacy. We also encourage future research to investigate the barriers to data sharing specific to psychology subfields to identify the best interventions to tackle them.

The present studies were aimed at developing the Hungarian version of the Short Dark Triad questionnaire (SD3-HU). The internal structure of the translated questionnaire was examined with confirmatory factor analysis and exploratory structural equation modeling. Then the construct and concurrent validity of the Hungarian version was tested. The obtained results were based on a total of seven independent samples (NTOTAL = 2161). While the internal structure of the SD3-HU showed inconsistencies with that of the original SD3, it proved consistent with adaptations developed in other languages. The SD3-HU showed adequate construct and concurrent validity. In line with the conceptual framework of, and previous empirical findings on the Dark Triad, each dark trait showed the expected associations with broad personality dimensions, sensation seeking, character strengths, work motivation, and counterproductive work behaviors. Furthermore, self-ratings on the SD3-HU were consistent with peer ratings. In sum, the SD3-HU is a reliable and valid measure of the dark traits.