BackgroundThe p value obtained from a significance test provides no information about the magnitude or importance of the underlying phenomenon. Therefore, additional reporting of effect size is often recommended. Effect sizes are theoretically independent from sample size. Yet this may not hold true empirically: non-independence could indicate publication bias.MethodsWe investigate whether effect size is independent from sample size in psychological research. We randomly sampled 1,000 psychological articles from all areas of psychological research. We extracted p values, effect sizes, and sample sizes of all empirical papers, and calculated the correlation between effect size and sample size, and investigated the distribution of p values.ResultsWe found a negative correlation of r = −.45 [95% CI: −.53; −.35] between effect size and sample size. In addition, we found an inordinately high number of p values just passing the boundary of significance. Additional data showed that neither implicit nor explicit power analysis could account for this pattern of findings.ConclusionThe negative correlation between effect size and samples size, and the biased distribution of p values indicate pervasive publication bias in the entire field of psychology.

Measuring user acceptance to avoid system rejection by the users in pre-prototype stage of product development is of high interest for both researchers and practitioners. This is especially true when technology uses strategies of persuasion in an emotional laden environment like the car. This paper presents the results of an online survey aiming at evaluating the acceptance of future persuasive in-car interaction approaches for a more economic driving behaviour. Five different persuasive interface concepts are presented and studied towards their acceptance. The results show an overall acceptance of the system concepts and the usefulness of the presented method. We show that individual expectations of the systems' disturbance and risk have an effect on the acceptance of technology and the behavioural intention to use.

Over-reliance on significance testing has been heavily criticized in psychology. Therefore the American Psychological Association recommended supplementing the p value with additional elements such as effect sizes, confidence intervals, and considering statistical power seriously. This article elaborates the conclusions that can be drawn when these measures accompany the p value. An analysis of over 30 summary papers (including over 6,000 articles) reveals that, if at all, only effect sizes are reported in addition to p’s (38%). Only every 10th article provides a confidence interval and statistical power is reported in only 3% of articles. An increase in reporting frequency of the supplements to p’s over time owing to stricter guidelines was found for effect sizes only. Given these practices, research faces a serious problem in the context of dichotomous statistical decision making: since significant results have a higher probability of being published (publication bias), effect sizes reported in articles may be seriously overestimated.

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

Sex differences have been reported for a variety of cognitive tasks and related to the use of different cognitive processing styles in men and women. It was recently argued that these processing styles share some characteristics across tasks, i.e. male approaches are oriented towards holistic stimulus aspects and female approaches are oriented towards stimulus details. In that respect, sex-dependent cognitive processing styles share similarities with attentional global-local processing. A direct relationship between cognitive processing and global-local processing has however not been previously established. In the present study, 49 men and 44 women completed a Navon paradigm and a Kimchi Palmer task as well as a navigation task and a verbal fluency task with the goal to relate the global advantage (GA) effect as a measure of global processing to holistic processing styles in both tasks. Indeed participants with larger GA effects displayed more holistic processing during spatial navigation and phonemic fluency. However, the relationship to cognitive processing styles was modulated by the specific condition of the Navon paradigm, as well as the sex of participants. Thus, different types of global-local processing play different roles for cognitive processing in men and women.