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. "

Alternative classification proxies (1.5 nmol/l or 15.5% increase) are able to effectively distinguish between cortisol responders and nonresponders and should be used in future research, whenever statistical response class allocation is not feasible.

In the context of performance optimizations in multitasking, a central debate has unfolded in multitasking research around whether cognitive processes related to different tasks proceed only sequentially (one at a time), or can operate in parallel (simultaneously). This review features a discussion of theoretical considerations and empirical evidence regarding parallel versus serial task processing in multitasking. In addition, we highlight how methodological differences and theoretical conceptions determine the extent to which parallel processing in multitasking can be detected, to guide their employment in future research. Parallel and serial processing of multiple tasks are not mutually exclusive. Therefore, questions focusing exclusively on either task-processing mode are too simplified. We review empirical evidence and demonstrate that shifting between more parallel and more serial task processing critically depends on the conditions under which multiple tasks are performed. We conclude that efficient multitasking is reflected by the ability of individuals to adjust multitasking performance to environmental demands by flexibly shifting between different processing strategies of multiple task-component scheduling.