Enhancing implicit change detection through action

Implicit change detection demonstrates how the visual system can benefit from stored information that is not immediately available to conscious awareness. We investigated the role of motor action in this context. In the first two experiments, using a one-shot implicit change-detection paradigm, participants responded to unperceived changes either with an action (jabbing the screen at the guessed location of a change) or with words (verbal report), and sat either 60 cm or 300 cm (with a laser pointer) away from the display. Our observers guessed the locations of changes at a reachable distance better with an action than with a verbal judgment. At 300 cm, beyond reach, the motor advantage disappeared. In experiment 3, this advantage was also unavailable when participants sat at a reachable distance but responded with hand-held laser pointers near their bodies. We conclude that a motor system specialized for real-time visually guided behavior has access to additional visual information. Importantly, this system is not activated by merely executing an action (experiment 2) or presenting stimuli in one's near space (experiment 3). It is activated only when both conditions are fulfilled, which implies that it is the actual contact that matters to the visual system.     

Bayesian PTSD-Trajectory Analysis with Informed Priors Based on a Systematic Literature Search and Expert Elicitation

There is a recent increase in interest of Bayesian analysis. However, little effort has been made thus far to directly incorporate background knowledge via the prior distribution into the analyses. This process might be especially useful in the context of latent growth mixture modeling when one or more of the latent groups are expected to be relatively small due to what we refer to as limited data. We argue that the use of Bayesian statistics has great advantages in limited data situations, but only if background knowledge can be incorporated into the analysis via prior distributions. We highlight these advantages through a data set including patients with burn injuries and analyze trajectories of posttraumatic stress symptoms using the Bayesian framework following the steps of the WAMBS-checklist. In the included example, we illustrate how to obtain background information using previous literature based on a systematic literature search and by using expert knowledge. Finally, we show how to translate this knowledge into prior distributions and we illustrate the importance of conducting a prior sensitivity analysis. Although our example is from the trauma field, the techniques we illustrate can be applied to any field.     

The Experience of Being a Qualified Female BME Clinical Psychologist in a National Health Service: An Interpretative Phenomenological and Repertory Grid Analysis

This study explores the lived experience of black and minority ethnic (BME) clinical psychologists employed in the U.K. National Health Service (NHS). A mixed method qualitative approach was employed using repertory grids and interpretative phenomenological analysis. Six female BME clinical psychologists took part. Four master themes emerged from the analysis, including standing out as different, negotiating cultural and professional values, sitting with uncertainty, and feeling proud to be a clinical psychologist. The repertory grid analysis supported these findings and enriched the study. Implications of the study are discussed—namely, the importance of the profession increasing the cultural competency and sensitivity of its members as well as becoming more diverse.