Terror in time: extending culturomics to address basic terror management mechanisms

Building on Google's efforts to scan millions of books, this article introduces methodology using a database of annual word frequencies of the 40,000 most frequently occurring words in the American literature between 1800 and 2009. The current paper uses this methodology to replicate and identify terror management processes in historical context. Variation in frequencies of word usage of constructs relevant to terror management theory (e.g. death, worldview, self-esteem, relationships) are investigated over a time period of 209 years. Study 1 corroborated previous TMT findings and demonstrated that word use of constructs related to death and of constructs related to patriotism and romantic relationships significantly co-vary over time. Study 2 showed that the use of the word “death” most strongly co-varies over time with the use of medical constructs, but also co-varies with the use of constructs related to violence, relationships, religion, positive sentiment, and negative sentiment. Study 3 found that a change in the use of death related words is associated with an increase in the use of fear related words, but not in anxiety related words. Results indicate that the described methodology generates valuable insights regarding terror management theory and provide new perspectives for theoretical advances.     

Using Dynamic Panel Models to Study Age‐related Differences and Time‐related Changes in Personality

Along with an increasing interest in the plasticity and role of personality across the adult lifespan comes the need for a diverse set of innovative statistical approaches to study it. With this paper, we set out to illustrate some of the possibilities and challenges in modelling age‐related differences and time‐related changes in personality psychology by means of dynamic panel models. To this end, we first distinguish between the study of age‐related differences and time‐related changes and demonstrate how the treatment of age and time as either discrete or continuous variables implies important modelling choices. Second, we present a selection of four example cases that address the topic of age moderation in diverse matters and with different objectives. Based on our cross‐tabulation of age and time as discrete and continuous variables, the first two example cases represent fairly well‐established models (cases A and B), whereas the remaining cases are used to illustrate current developments in the field (cases C and D). We close the paper with some final remarks on current limitation and future research directions. © 2019 European Association of Personality Psychology     

A Systematic Review of Online Response Rates in Four Counseling Journals

This systematic review of articles published in 4 counseling journals found 207 articles that used online recruitment, of which 98 (47.3%) reported a response rate. These 98 studies collectively contained 22,466 individual participants. Results showed that nearly one third of all empirical articles used online recruitment, and the average response rate was 34.2% (SD = 22.6). Response rates are further described by journal, population, research methodology, and recruitment strategy. Researcher‐reported issues with online recruitment and data collection were also analyzed qualitatively, and recommendations for researchers are discussed.     

Learning to teach through video playback: student teachers confronting their own practice

The aim of this study was to examine the use of video playback with student teachers to promote teacher learning and to analyse patterns of reflection. A total of 14 student teachers video recorded their lessons in the practice setting and later confronted their performance, facing their videotaped lesson during the course of an interview with their university supervisor. The interviews were then transcribed and coded. Our results indicate that video playback facilitates student teacher learning and that the quality of reflection ranges from routine to dialogic. This suggests that further research into how to elicit higher levels of reflection is needed. The role of the supervisor in promoting deeper thinking should be further examined.     

A Monte Carlo evaluation of masked visual analysis in response‐guided versus fixed‐criteria multiple‐baseline designs

We developed masked visual analysis (MVA) as a structured complement to traditional visual analysis. The purpose of the present investigation was to compare the effects of computer‐simulated MVA of a four‐case multiple‐baseline (MB) design in which the phase lengths are determined by an ongoing visual analysis (i.e., response‐guided) versus those in which the phase lengths are established a priori (i.e., fixed criteria). We observed an acceptably low probability (less than .05) of false detection of treatment effects. The probability of correctly detecting a true effect frequently exceeded .80 and was higher when: (a) the masked visual analyst extended phases based on an ongoing visual analysis, (b) the effects were larger, (c) the effects were more immediate and abrupt, and (d) the effects of random and extraneous error factors were simpler. Our findings indicate that MVA is a valuable combined methodological and data‐analysis tool for single‐case intervention researchers.     

Estimating Incremental Validity Under Missing Data

A common form of missing data is caused by selection on an observed variable (e.g., Z). If the selection variable was measured and is available, the data are regarded as missing at random (MAR). Selection biases correlation, reliability, and effect size estimates when these estimates are computed on listwise deleted (LD) data sets. On the other hand, maximum likelihood (ML) estimates are generally unbiased and outperform LD in most situations, at least when the data are MAR. The exception is when we estimate the partial correlation. In this situation, LD estimates are unbiased when the cause of missingness is partialled out. In other words, there is no advantage of ML estimates over LD estimates in this situation. We demonstrate that under a MAR condition, even ML estimates may become biased, depending on how partial correlations are computed. Finally, we conclude with recommendations about how future researchers might estimate partial correlations even when the cause of missingness is unknown and, perhaps, unknowable.