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. "

Visual analogue scales (VASs) have shown superior measurement qualities in comparison to traditional Likerttype response scales in previous studies. The present study expands the comparison of response scales to properties of Internet-based personality scales in a within-subjects design. A sample of 879 participants filled out an online questionnaire measuring Conscientiousness, Excitement Seeking, and Narcissism. The questionnaire contained all instruments in both answer scale versions in a counterbalanced design. Results show comparable reliabilities, means, and SDs for the VAS versions of the original scales, in comparison to Likert-type scales. To assess the validity of the measurements, age and gender were used as criteria, because all three constructs have shown non-zero correlations with age and gender in previous research. Both response scales showed a high overlap and the proposed relationships with age and gender. The associations were largely identical, with the exception of an increase in explained variance when predicting age from the VAS version of Excitement Seeking (B 10 =1318.95, ΔR 2 =.025). VASs showed similar properties to Likert-type response scales in most cases.

Background: In order to improve the transition from an intention to a change in health behaviour, action planning is a frequently used behavioural change method. The quality of action plans in terms of instrumentality and specificity is important in terms of supporting a successful change in health behaviour. Until now, little has been known about the predictors of action plan generation and the predictors of high quality action plans and, therefore, the current study investigates these predictors.

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Smartphone usage is increasing around the globe—in daily life and as a research device in behavioral science. Smartphones offer the possibility to gather longitudinal data at little cost to researchers and participants. They provide the option to verify self-report data with data from sensors built into most smartphones. How accurate this sensor data is when gathered via different smartphone devices, e.g., in a typical experience sampling framework, has not been investigated systematically. With the present study, we investigated the accuracy of orientation data about the spatial position of smartphones via a newly invented measurement device, the RollPitcher. Objective status of pitch (vertical orientation) and roll (horizontal orientation) of the smartphone was compared to data gathered from the sensors via web browsers and native apps. Bayesian ANOVAs confirmed that the deviations in pitch and roll differed between smartphone models, with mean inaccuracies per device of up to 2.1° and 6.6°, respectively. The inaccuracies for measurements of roll were higher than for pitch, d = .28, p < .001. Our results confirm the presence of heterogeneities when gathering orientation data from different smartphone devices. In most cases, measurement via a web browser was identical to measurement via a native app, but this was not true for all smartphone devices. As a solution to lack of sensor accuracy, we recommend the development and implementation of a coherent research framework and also discuss the implications of the heterogeneities in orientation data for different research designs.