Towards a Pan‐cultural Personality Structure: Input from 11 Psycholexical Studies

The purpose of the present study is to find the common kernel of different trait taxonomic studies and find out how the individual structures relate to this common kernel. Trait terms from 11 psycholexically based taxonomies were all translated into English. On the basis of the commonalities in English, the 11 matrices were merged into a joint matrix with 7104 subjects and 1993 trait terms. Untranslatable terms produced large areas with missing data. To arrive at the kernel structure of the joint matrix, a simultaneous component analysis was applied. In addition, the kernel structures were compared with the individual taxonomy trait structures, obtained via principal component analysis. The findings provide evidence of a structure consisting of three components to stand out as the core of the taxonomies included in this study; those components were named dynamism, affiliation, and order. Moreover, the relations between these three kernel components and those of a six‐component solution (completing the six‐factor model) are provided. Copyright © 2014 European Association of Personality Psychology     

Symptoms of Meares-Irlen/Visual Stress Syndrome in subjects diagnosed with Chronic Fatigue Syndrome

Several diagnostic symptoms of the visual-processing deficit Meares-Irlen/Visual Stress Syndrome are remarkably similar to symptom manifestations reported by individuals with chronic fatigue syndrome (CFS). We surveyed the specific incidences of nine widely-recognised symptoms of visual stress (VS) in a group of subjects (n = 20) previously diagnosed with CFS. The presence of each symptom of VS in the CFS group was compared to its respective presence in both an age and sex matched healthy comparison group (n = 46), and an age and sex matched group comprised of individuals (n = 14) diagnosed with VS. Results showed the frequencies of all nine VS symptoms in the CFS-diagnosed group to be significantly higher (p = .032 – p < .0005) than in the comparison group, with only two symptoms being statistically less frequent in the CFS group than in the VS-diagnosed group. The average number of VS symptoms reported by the CFS group was also significantly higher than the comparison group, yet not significantly different from the VS group. Thus, the occurrence of VS symptoms in subjects diagnosed with CFS appears to be far greater than previously reported, which in turn may indicate the interplay of some yet to be identified underlying factor(s) common to both conditions.     

Invisible Stimuli,Implicit Thresholds: Why Invisibility Judgments Cannot be Interpreted in Isolation

Some studies of unconscious cognition rely on judgments of participants stating that they have “not seen” the critical stimulus (e.g., in a masked-priming experiment). Trials in which participants gave invisibility judgments are then treated as those where the critical stimulus was “subliminal” or “unconscious,” as opposed to trials with higher visibility ratings. Sometimes, only these trials are further analyzed, for instance, for unconscious priming effects. Here I argue that this practice requires implicit assumptions about subjective measures of awareness incompatible with basic models of categorization under uncertainty (e.g., modern signal-detection and threshold theories). Most importantly, it ignores the potential effects of response bias. Instead of taking invisibility judgments literally, they would better be employed in parametric experiments where stimulus visibility is manipulated systematically, not accidentally. This would allow studying qualitative and double dissociations between measures of awareness and of stimulus processing per se.     

Evidence for Mixed Processes in Normal/Mirror Discrimination of Rotated Letters: A Bayesian Model Comparison Between Single- and Mixed-Distribution Models1

When determining whether a rotated letter is normal or mirrored, an observer mentally rotates the letter to its canonical orientation. To account for patterns of response times (RTs) for the normal/mirror discrimination of rotated letters, previous research formulated a model that postulated a mixture of trials with and without mental rotation. While this model could explain the curvilinear relationship that has been found between averaged RT and letter orientations, the curved RT function is still open to alternative explanations without assuming mixed processes. To address this issue and test the mixed-process hypothesis more directly, we analyzed trial-by-trial RT data instead of averaged RTs by employing a Bayesian model comparison technique. If rotation and non-rotation trials are mixed, trial-by-trial RTs for letters in a particular orientation should not follow a single distribution but a mixed one formed from the superposition of two separate distributions, one for rotation and one for non-rotation trials. In the present study, we compared single- and mixed-distribution models. Bayes-factor analysis showed decisive support for the mixed-distribution model over the single-distribution model. In addition, using the widely applicable information criterion (WAIC), the predictive accuracy of the mixed-distribution model was found to be as high as that of the single-distribution model. These results indicated the involvement of mixed processes in normal/mirror discrimination of rotated letters. The usefulness of statistical modeling in psychological study and necessary precautions to take in the interpretation of the parameters of unconfirmed models are also discussed.     

语言经验对概率词切分的影响

概率词切分指个体利用音节间的转换概率切分语流、发现词语边界的过程。经典的概率词切分研究多采用“学习-测试”范式, 首先要求被试切分一段无意义人工语言, 随后对切分效果进行测试。近年来, 研究者逐渐关注语言经验对概率词切分的影响, 具体包括语音经验和被试掌握的语言知识两方面。今后的研究, 一方面可以更多地关注普通话母语者的语言经验如何作用于概率词切分过程; 另一方面还可以在语言经验的分类上进行拓展, 细分群体语言经验和个体语言经验的影响。     

双模态情感分析的弹幕网络视频平台营销策略

随着互联网飞跃发展, 弹幕视频应运而生。这种新型的用户与视频交互方式具有新特性, 如用户情感表达实时动态性、情感分布多峰性。同时, 新特性也给实际研究工作带来挑战, 如用户画像刻画难度增大, 视频推荐和广告推送所需精度提高。现有研究尚未对弹幕视频的新特性进行深入分析, 也没有充分挖掘其本身所蕴含的学术研究价值。本文利用深度学习、自然语言处理技术、系统动力学方法, 结合心理学、市场营销学等多学科交叉前沿知识, 从数据驱动角度对弹幕视频数据进行分析和建模, 深度挖掘视频大数据潜在的商业价值。重点研究弹幕与视频双模态融合的情感识别方法; 构建带有用户情感特征的动态用户画像, 并建立基于用户画像的网络视频粘性营销机制; 分析用户情感与视频广告插播方式的相关性, 提出视频广告动态插播策略。丰富现有研究的同时, 为网络视频企业准确定位与分析用户需求, 创建高品质的智能营销平台供理论与决策支持。     

Therapists’ Thought-Action Fusion Beliefs Predict Utilization of Exposure in Obsessive-Compulsive Disorder

Although exposure and response prevention (ERP) is considered the gold standard for the treatment of obsessive-compulsive disorder (OCD), it is rarely used in clinical practice. Therapists’ beliefs about ERP affect its utilization, as previous research suggests, but the role of therapists’ cognitive biases is unclear. In particular, susceptibility to thought-action fusion (TAF) may be related to the underutilization of ERP in OCD.Therapists (N = 353) were divided into those recommending (ERP+, n = 228) and not recommending ERP (ERP−, n = 125) as treatment for an OCD case example. TAF in therapists was assessed using behavioral and self-report measures (TAFS).TAF was higher in the ERP− than the ERP+ group, with a small to moderate effect size (0.2 ≤ d ≤ 0.4). ERP− therapists showed more avoidance and neutralizing behavior and a stronger emotional response than the ERP+ therapists during the experimental task. Moreover, higher TAF as measured by the TAFS was associated at a small magnitude with lower likelihood of using ERP in the therapists’ actual clinical practices.Therapists’ cognitive biases should be addressed in their training in order to increase the dissemination of evidence-based treatment (i.e., ERP) and thus improve the treatment of OCD.     

A data–information–knowledge cycle for modeling driving behavior

When talking about automation, “autonomous vehicles”, often abbreviated as AVs, come to mind. In transitioning from the “driver” mode to the different automation levels, there is an inevitable need for modeling driving behavior. This often happens through data collection from experiments and studies, but also information extraction, a key step in behavioral modeling. Particularly, naturalistic driving studies and field operational trials are used to collect meaningful data on drivers’ interactions in real–world conditions. On the other hand, information extraction methods allow to predict or mimic driving behavior, by using a set of statistical learning methods. In simple words, the way to understand drivers’ needs and wants in the era of automation can be represented in a data–information cycle, starting from data collection, and ending with information extraction. To develop this cycle, this research reviews studies with keywords “data collection”, “information extraction”, “AVs”, while keeping the focus on driving behavior. The resulting review led to a screening of about 161 papers, out of which about 30 were selected for a detailed analysis. The analysis included an investigation of the methods and equipment used for data collection, the features collected, the size and frequency of the data along with the main problems associated with the different sensory equipment; the studies also looked at the models used to extract information, including various statistical techniques used in AV studies. This paved the way to the development of a framework for data analytics and fusion, allowing the use of highly heterogeneous data to reach the defined objectives; for this paper, the example of impacts of AVs on a network level and AV acceptance is given. The authors suggest that such a framework could be extended and transferred across the various transportation sectors.     

Cross-cultural comparison of ADHD symptoms among Japanese and US university students

Problems related to attention, hyperactivity, and impulsiveness are known to impact social, academic, and vocational success. When the problems begin in childhood and lead to impaired functioning, the syndrome is identified as attention-deficit/hyperactivity disorder (ADHD). Symptoms of the syndrome persist into adolescence and adulthood for many individuals, but less is known about characteristics of adults compared to children, especially adults attending university. Furthermore, there is little cross-national and cross-cultural research. This study compared DSM-IV-TR ADHD symptoms of US university students (N=271) to Japanese peers (N=712). Comparison of group means on a DSM-IV-TR-based checklist indicated that Japanese students reported more problems with inattention (and overall ADHD symptoms) but not hyperactive-impulsive symptoms. Although differences were statistically significant, effect sizes were small, indicating that for practical purposes, the students reported similar levels of symptoms. Japanese students reported higher rates of meeting or exceeding symptom counts that comprise diagnostic criteria for ADHD, but differences were quite small. Using DSM-IV-TR thresholds, 5.70% of US students and 6.27% of Japanese students reported enough symptoms to meet the cut-off for inattentive, hyperactive/impulsive, or combined type during childhood. With regard to recent problems, 2.66% of US students and 4.52% of Japanese students reported enough symptoms to meet the cut-off for one of the three subtypes. Comparisons using other methods of calculating rates are also provided. This research adds to the limited knowledge of ADHD symptoms in university students across countries and it supports the view that ADHD is not merely a cultural construct. This study is among the first to identify potential attention problems in Japanese university students.     

Prediction during statistical learning, and implications for the implicit/explicit divide

Accounts of statistical learning, both implicit and explicit, often invoke predictive processes as central to learning, yet practically all experiments employ non-predictive measures during training. We argue that the common theoretical assumption of anticipation and prediction needs clearer, more direct evidence for it during learning. We offer a novel experimental context to explore prediction, and report results from a simple sequential learning task designed to promote predictive behaviors in participants as they responded to a short sequence of simple stimulus events. Predictive tendencies in participants were measured using their computer mouse, the trajectories of which served as a means of tapping into predictive behavior while participants were exposed to very short and simple sequences of events. A total of 143 participants were randomly assigned to stimulus sequences along a continuum of regularity. Analysis of computer-mouse trajectories revealed that (a) participants almost always anticipate events in some manner, (b) participants exhibit two stable patterns of behavior, either reacting to vs. predicting future events, (c) the extent to which participants predict relates to performance on a recall test, and (d) explicit reports of perceiving patterns in the brief sequence correlates with extent of prediction. We end with a discussion of implicit and explicit statistical learning and of the role prediction may play in both kinds of learning.