Despite a growing number of studies suggesting that emotion words affect perceptual judgments of emotional stimuli, little is known about how emotion words affect perceptual memory for emotional faces. In Experiments 1 and 2 we tested how emotion words (compared with control words) affected participants' abilities to select a target emotional face from among distractor faces. Participants were generally more likely to false alarm to distractor emotional faces when primed with an emotion word congruent with the face (compared with a control word). Moreover, participants showed both decreased sensitivity (d') to discriminate between target and distractor faces, as well as altered response biases (c; more likely to answer "yes") when primed with an emotion word (compared with a control word). In Experiment 3 we showed that emotion words had more of an effect on perceptual memory judgments when the structural information in the target face was limited, as well as when participants were only able to categorize the face with a partially congruent emotion word. The overall results are consistent with the idea that emotion words affect the encoding of emotional faces in perceptual memory. (PsycINFO Database Record
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1037/emo0000330 | DOI Listing |
Diabetol Metab Syndr
January 2025
Department of Endocrinology, Bharti Hospital, Karnal, Haryana, India.
Background: Of the numerous complications encountered by people with diabetes (PWD), the effect on mental health is concerning. Within mental health, diabetes distress (DD) occurs when a patient has unfavourable emotional stress while managing their condition, which can be managed by coping strategies but are less studied together in Indian settings. So, the present study aimed to determine the proportion of DD and associated factors and coping skills among the PWD.
View Article and Find Full Text PDFBMC Psychiatry
January 2025
Division of Epidemiology and Social Sciences, Institute for Health and Equity, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI, 53226, USA.
Background: During adolescence, a critical developmental phase, cognitive, psychological, and social states interact with the environment to influence behaviors like decision-making and social interactions. Depressive symptoms are more prevalent in adolescents than in other age groups which may affect socio-emotional and behavioral development including academic achievement. Here, we determined the association between depression symptom severity and behavioral impairment among adolescents enrolled in secondary schools of Eastern and Central Uganda.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
January 2025
Editorial Board of Jiangsu Medical Journal, the First Affiliated Hospital With Nanjing Medical University, Nanjing, 210029, China.
Background: Gestational diabetes mellitus is hyperglycemia in special populations (pregnant women), however gestational diabetes mellitus (GDM) not only affects maternal health, but also has profound effects on offspring health. The prevalence of gestational diabetes in my country is gradually increasing.
Objective: To study the application effect of self-transcendence nursing model in GDM patients.
Sci Rep
January 2025
Laboratory of Pharmacology, Department of Pharmacy, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Chiba, Japan.
Recently, exposure to sounds with ultrasound (US) components has been shown to modulate brain activity. However, the effects of US on emotional states remain poorly understood. We previously demonstrated that the olfactory bulbectomized (OBX) rat depression model is suitable for examining the effects of audible sounds on emotionality.
View Article and Find Full Text PDFSci Rep
January 2025
College of Physical Education and Health Sciences, Zhejiang Normal University, Jinhua, 321004, China.
Athlete engagement is influenced by several factors, including cohesion, passion and mental toughness. Machine learning methods are frequently employed to construct predictive models as a result of their high efficiency. In order to comprehend the effects of cohesion, passion and mental toughness on athlete engagement, this study utilizes the relevant methods of machine learning to construct a prediction model, so as to find the intrinsic connection between them.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!