52% Yes, a signiicant crisis 3% No, there is no crisis 7% Don't know 38% Yes, a slight crisis 38% Yes, a slight crisis 1,576 RESEARCHERS SURVEYED M ore than 70% of researchers have tried and failed to reproduce another scientist's experiments, and more than half have failed to reproduce their own experiments. Those are some of the telling figures that emerged from Nature's survey of 1,576 researchers who took a brief online questionnaire on reproducibility in research. The data reveal sometimes-contradictory attitudes towards reproduc-ibility. Although 52% of those surveyed agree that there is a significant 'crisis' of reproducibility, less than 31% think that failure to reproduce published results means that the result is probably wrong, and most say that they still trust the published literature. Data on how much of the scientific literature is reproducible are rare and generally bleak. The best-known analyses, from psychology 1 and cancer biology 2 , found rates of around 40% and 10%, respectively. Our survey respondents were more optimistic: 73% said that they think that at least half of the papers in their field can be trusted, with physicists and chemists generally showing the most confidence. The results capture a confusing snapshot of attitudes around these issues, says Arturo Casadevall, a microbiologist at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland. "At the current time there is no consensus on what reproducibility is or should be. " But just recognizing that is a step forward, he says. "The next step may be identifying what is the problem and to get a consensus. "

The COVID-19 pandemic has increased negative emotions and decreased positive emotions globally. Left unchecked, these emotional changes might have a wide array of adverse impacts. To reduce negative emotions and increase positive emotions, we tested the effectiveness of reappraisal, an emotion-regulation strategy that modifies how one thinks about a situation. Participants from 87 countries and regions (n = 21,644) were randomly assigned to one of two brief reappraisal interventions (reconstrual or repurposing) or one of two control conditions (active or passive). Results revealed that both reappraisal interventions (vesus both control conditions) consistently reduced negative emotions and increased positive emotions across different measures. Reconstrual and repurposing interventions had similar effects. Importantly, planned exploratory analyses indicated that reappraisal interventions did not reduce intentions to practice preventive health behaviours. The findings demonstrate the viability of creating scalable, low-cost interventions for use around the world.

BackgroundMobile technology gives researchers unimagined opportunities to design new interventions to increase physical activity. Unfortunately, it is still unclear which elements are useful to initiate and maintain behavior change.ObjectiveIn this meta-analysis, we investigated randomized controlled trials of physical activity interventions that were delivered via mobile phone. We analyzed which elements contributed to intervention success.MethodsAfter searching four databases and science networks for eligible studies, we entered 50 studies with N=5997 participants into a random-effects meta-analysis, controlling for baseline group differences. We also calculated meta-regressions with the most frequently used behavior change techniques (behavioral goals, general information, self-monitoring, information on where and when, and instructions on how to) as moderators.ResultsWe found a small overall effect of the Hedges g=0.29, (95% CI 0.20 to 0.37) which reduced to g=0.22 after correcting for publication bias. In the moderator analyses, behavioral goals and self-monitoring each led to more intervention success. Interventions that used neither behavioral goals nor self-monitoring had a negligible effect of g=0.01, whereas utilizing either technique increased effectiveness by Δg=0.31, but combining them did not provide additional benefits (Δg=0.36).ConclusionsOverall, mHealth interventions to increase physical activity have a small to moderate effect. However, including behavioral goals or self-monitoring can lead to greater intervention success. More research is needed to look at more behavior change techniques and their interactions. Reporting interventions in trial registrations and articles need to be structured and thorough to gain accurate insights. This can be achieved by basing the design or reporting of interventions on taxonomies of behavior change.

In this article, we provide a toolbox of recommendations and resources for those aspiring to promote the uptake of open scientific practices. Open Science encompasses a range of behaviours that aim to improve the transparency of scientific research. This paper is divided into seven sections, each devoted to different groups or institutions in the research ecosystem: colleagues, students, departments and faculties, universities, academic libraries, journals, and funders. We describe the behavioural influences and incentives for each of these stakeholders as well as changes they can make to foster Open Science. Our primary goal, however, is to suggest actions that researchers can take to promote these behaviours, inspired by simple principles of behaviour change: make it easy, social, and attractive. In isolation, a small shift in one person’s behaviour may appear to make little difference, but when combined, many shifts can radically alter shared norms and culture. We offer this toolbox to assist individuals and institutions in cultivating a more open research culture.

Just observing other people can influence what we do. Under certain conditions, it inspires us to strive for the same goal as the other person. Such goal contagion occurs, because one first automatically infers the goal and then adopts it for oneself. In a series of three experiments (overall N = 840 university students), we investigated personal goal value and the observed person’s effort as moderators of goal contagion, which is mediated by goal inference. In all three experiments, participants read a brief story about a student who either wants to earn money (target goal) or to do an internship (control) and expects to show much or little effort. In Studies 1a and b, goal inference was the dependent variable, whereas in Study 2, we considered the full moderated-mediation model and measured how strongly participants pursue the goal to earn money. We aimed at locating the moderators within this two-step process. We hypothesized that high effort increases goal inference, whereas personal goal value strengthens the relationship between goal inference and goal adoption. Across experiments, we did find evidence for explicit and spontaneous, but not for implicit goal inference. Furthermore, participants did not pursue to earn money to a different degree across conditions and different degrees of goal value. Taken together, neither the moderated-mediation process nor the basic goal contagion effect was supported. Results are discussed in the light of other published studies on goal contagion and the current Replication Crisis.