Do handwritten words magnify lexical effects in visual word recognition?

An examination of how the word recognition system is able to process handwritten words is fundamental to formulate a comprehensive model of visual word recognition. Previous research has revealed that the magnitude of lexical effects (e.g., the word-frequency effect) is greater with handwritten words than with printed words. In the present lexical decision experiments, we examined whether the quality of handwritten words moderates the recruitment of top-down feedback, as reflected in word-frequency effects. Results showed a reading cost for difficult-to-read and easy-to-read handwritten words relative to printed words. But the critical finding was that difficult-to-read handwritten words, but not easy-to-read handwritten words, showed a greater word-frequency effect than printed words. Therefore, the inherent physical variability of handwritten words does not necessarily boost the magnitude of lexical effects.     

Belief in a zero-sum game and subjective well-being across 35 countries

Current Psychology - This article presents a short research report on the relationship between perceived antagonism in social relations measured using the Belief in a Zero-Sum Game (BZSG) scale,...     

Predicting Intense Levels of Child Anxiety During Anesthesia Induction at Hospital Arrival

In children, intense levels of anxiety during anesthetic induction are associated with a higher risk of pain, poor recovery, and emergence delirium. Therefore, it is important to identify these high-risk children at hospital arrival. The current study examined internalizing behavior (Child Behavior Checklist, CBCL) and state anxiety measures (modified Yale Preoperative Anxiety Scale, mYPAS, and State Trait Anxiety Inventory for Children, STAIC) at hospital arrival as predictors of anxiety during induction of anesthesia. One hundred children (aged 4 to 12 years) undergoing elective daycare surgery were included. The STAIC and mYPAS at hospital arrival were significant predictors of anxiety during induction, whereas CBCL was not. The STAIC state form at hospital arrival was the strongest predictor and could be used to identify children who will experience intense levels of anxiety during anesthetic induction, with sufficient to good diagnostic accuracy. Using the STAIC at hospital arrival allows targeted interventions to reduce anxiety in children.

     

The "Efficiency" Effect of Conceptual Referents on the Generation of Happiness: A Cross-National Analysis

Journal of Happiness Studies - This paper analyses how different definitions of happiness affect the individual assessment of subjective wellbeing. Bearing in mind the production theory, we study...     

Throwing spatial light: on topological explanations in Gestalt psychology

Phenomenology and the Cognitive Sciences - It is a well-known fact that mathematics plays a crucial role in physics; in fact, it is virtually impossible to imagine contemporary physics without it....     

Joking for Gender Equality: Subversive Humor Against Sexism Motivates Collective Action in Men and Women with Weaker Feminist Identity

Sex Roles - Subversive humor has historically been considered a way of protesting, raising awareness, and seeking change. However, to date, no known empirical research has explored the consequences...     

Emotional Valence Precedes Semantic Maturation of Words: A Longitudinal Computational Study of Early Verbal Emotional Anchoring

We present a longitudinal computational study on the connection between emotional and amodal word representations from a developmental perspective. In this study, children's and adult word representations were generated using the latent semantic analysis (LSA) vector space model and Word Maturity methodology. Some children's word representations were used to set a mapping function between amodal and emotional word representations with a neural network model using ratings from 9-year-old children. The neural network was trained and validated in the child semantic space. Then, the resulting neural network was tested with adult word representations using ratings from an adult data set. Samples of 1210 and 5315 words were used in the child and the adult semantic spaces, respectively. Results suggested that the emotional valence of words can be predicted from amodal vector representations even at the child stage, and accurate emotional propagation was found in the adult word vector representations. In this way, different propagative processes were observed in the adult semantic space. These findings highlight a potential mechanism for early verbal emotional anchoring. Moreover, different multiple linear regression and mixed-effect models revealed moderation effects for the performance of the longitudinal computational model. First, words with early maturation and subsequent semantic definition promoted emotional propagation. Second, an interaction effect between age of acquisition and abstractness was found to explain model performance. The theoretical and methodological implications are discussed.