Subjective,physiological, and behavioural responses towards evaluatively conditioned stimuli

Evaluative Conditioning (EC) is commonly defined as the change in liking of a stimulus (conditioned stimulus, CS) due to its pairings with an affective unconditioned stimulus (US). In Experiment 1, we investigated effects of repeated stimulus pairings on affective responses, i.e. valence and arousal ratings, pupil size, and duration estimation. After repeatedly pairing the CSs with affective USs, a consistent pattern of affective responses emerged: The CS_negative was rated as being more negative and more arousing, resulted in larger pupils, and was temporally overestimated compared to the CS_neutral. In Experiment 2, the influence of a mere instruction about the contingency between a CS and US on affective responses was examined. After mere instruction about upcoming pairings between the CS and US, subjective ratings also changed, but there was neither evidence for differential pupillary responses nor for differential temporal processing. The results indicate that EC via pairings or instructions can change the affective responses towards formerly neutral stimuli and introduce pupil size as a physiological measure in EC research. However, Experiment 2 suggests that there might be moderating factors based on the type of EC procedure involved.     

Object-Tool-Actor Interaction: Object Information Drives Intended Action

Tool use is typically explored via actor-tool interactions. However, the target-object (that which is being acted on) may influence perceived action possibilities and thereby guide action. Three different tool-target-object pairings were tested (Experiment 1). The hammering action demonstrated the greatest sensitivity and therefore subsequently used to further investigate target-object pairings. The hammer was removed as an option and instructions were provided using pictorial (Experiment 2), written (Experiment 3), and both pictorial and written formats (Experiment 4). The designed tool is chosen when available (Experiment 1) and when removed as a choice (i.e., the hammer), participants perform the same action associated with the designed tool (i.e., hammering) regardless of instruction method (Experiments 2, 3, and 4).     

反应抑制的训练:内容、效果与机制

近期的研究发现,个体的反应抑制能力具有一定的可塑性。研究者多采用双盲随机对照实验设计,训练的对象包括儿童、成人和特殊群体,研究者通过Go/Nogo、Stop-signal等任务进行为期1周至3周,45至7200试次不等的抑制控制能力训练,并结合行为、脑电以及脑成像等技术对训练效果进行评估,研究结果发现,接受了抑制控制训练的个体其抑制能力得到提升,并伴随脑神经活动的变化。另外,研究者发现,抑制控制能力的训练效果还可以迁移至个体日常生活中的表现。但是,也有些研究并未发现抑制控制训练的效果。训练任务的设置,评估任务的选择以及被试反应策略的差异等因素可能会影响训练的效果。抑制控制训练引发行为与大脑活动的变化可能是由于训练导致了个体建立了自上而下有意识的抑制控制模式和自下而上的自动抑制模式。反应抑制和冲突抑制可塑性的比较,儿童与老年人抑制功能的训练以及训练效果的追踪研究将成为该领域日后研究的重点问题。     

The Wished‐For Always Wins Until the Winner Was Inevitable All Along: Motivated Reasoning and Belief Bias Regulate Emotion During Elections

How do biases affect political information processing? A variant of the Wason selection task, which tests for confirmation bias, was used to characterize how the dynamics of the recent U.S. presidential election affected how people reasoned about political information. Participants were asked to evaluate pundit‐style conditional claims like “The incumbent always wins in a year when unemployment drops” either immediately before or immediately after the 2012 presidential election. A three‐way interaction between ideology, predicted winner (whether the proposition predicted that Obama or Romney would win), and the time of test indicated complex effects of bias on reasoning. Before the election, there was partial evidence of motivated reasoning—liberals performed especially well at looking for falsifying information when the pundit's claim predicted Romney would win. After the election, once the outcome was known, there was evidence of a belief bias—people sought to falsify claims that were inconsistent with the real‐world outcome rather than their ideology. These results suggest that people seek to implicitly regulate emotion when reasoning about political predictions. Before elections, people like to think their preferred candidate will win. After elections, people like to think the winner was inevitable all along.     

The Situational Test of Emotional Management – Brief (STEM-B): Development and validation using item response theory and latent class analysis

This study uses a 3-Parameter Logistic item response theory (IRT) model to develop an 18-item short-form of the Situational Test of Emotion Management (STEM). In a sample of 900 people, the short form showed acceptable reliability (reliability index = .87; Cronbach’s alpha = .84) and a meaningful correlation with another indicator of emotional intelligence (i.e., r = .30 with the Situational Test of Emotional Understanding). Latent class analysis of the short-form detected two classes. For all items, participants in Class 2 had a higher probability of selecting the best option than Class 1. When response options were coded to represent different emotion regulation strategies, Class 2 had a higher probability of endorsing “situation modification” and Class 1 had a higher probability of endorsing “no regulation”. These results provide validity evidence for the STEM-B as an assessment of emotion regulation.     

Development and Initial Validation of a Scale Measuring the Beliefs of Educators Regarding Response to Intervention

This article presents information on the development and initial validation of the 16-item Response to Intervention (RTI) Beliefs Scale. The scale is designed to measure the extent to which educators working in schools hold beliefs consistent with the tenets of RTI. The authors administered the instrument to 2,430 educators in 62 elementary schools in the fall of 2007 and 2,443 educators in 68 elementary schools in the spring of 2008. Exploratory, single-level confirmatory, and multilevel confirmatory factor analysis procedures were used to examine construct validity. Results supported a correlated 3-factor model (Academic Abilities and Performance of Students with Disabilities, Data-Based Decision Making, and Functions of Core and Supplemental Instruction) at both the school and educator levels of analysis. Furthermore, the factor scores derived from the model demonstrated significant, positive relations to RTI implementation. Reliability estimates for two of the three factor scores exceeded.70. Implications for research on educator beliefs and implementation of RTI as well as implications for school psychologists supporting RTI implementation are discussed.