Background: The basic discrete emotions, namely, happiness, disgust, anger, fear, surprise, and sadness, are present across different cultures and societies. Facial emotion recognition is crucial in social interactions, but normal and pathological aging seem to affect this ability. The present research aims to identify the differences in the capacity for recognition of the six basic discrete emotions between young and older healthy controls (HOC) and mildly cognitively impaired patients (MCI).
Method: The sample ( = 107) consisted of 47 young adults, 27 healthy older adults, and 33 MCI patients. Several neuropsychological scales were administered to assess the cognitive state of the participants, followed by the emotional labeling task on the Ekman 60 Faces test.
Results: The MANOVA analysis was significant and revealed the presence of differences in the emotion recognition abilities of the groups. Compared to HOC, the MCI group obtained a significantly lower number of hits on fear, anger, disgust, sadness, and surprise. The happiness emotion recognition rate did not differ significantly among the three groups. Surprisingly, young people and HOC did not show significant differences.
Conclusions: Our results demonstrated that MCI was associated with facial emotion recognition impairment, whereas normal aging did not seem to affect this ability.
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http://dx.doi.org/10.3390/ijerph191912757 | DOI Listing |
Atten Percept Psychophys
January 2025
Department of Psychology, Rutgers University - New Brunswick, 152 Frelinghuysen Rd, Piscataway, NJ, 08854, USA.
Human observers can often judge emotional or affective states from bodily motion, even in the absence of facial information, but the mechanisms underlying this inference are not completely understood. Important clues come from the literature on "biological motion" using point-light displays (PLDs), which convey human action, and possibly emotion, apparently on the basis of body movements alone. However, most studies have used simplified and often exaggerated displays chosen to convey emotions as clearly as possible.
View Article and Find Full Text PDFBMJ Ment Health
January 2025
National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australian Capital Territory, Australia
Climate change poses enormous, rapidly increasing risks to human well-being that remain poorly appreciated. The growing understanding of this threat has generated a phenomenon often called 'eco-anxiety'. Eco-anxiety (and its synonyms) is best documented in the Global North, mostly among people who are better educated and whose reasons for concern are both altruistic and self-interested.
View Article and Find Full Text PDFBMC Psychol
January 2025
Department of Basic and Clinical Psychology, and Psychobiology, Universitat Jaume I, Castellon, Spain.
Background: Improving mental health within correctional facilities, specifically to address self-harm behaviors, is a crucial endeavor. However, significant challenges arise when implementing evidence-based programs within this complex setting. Despite these hurdles, the Systems Training for Emotional Predictability and Problem Solving (STEPPS) program has garnered recognition, notably in the United States, for its efficacy in tackling such issues.
View Article and Find Full Text PDFNephrol Nurs J
January 2025
Director, the Marian K. Shaughnessy Nurse Leadership Academy.
Nephrology nurses working in hemodialysis units face unique challenges managing multiple patients - an experience often contributing to higher levels of burnout and stress, and potentially lower job satisfaction and retention rates, exacerbating the existing nursing shortage in dialysis settings. Targeted strategies are essential to improve job satisfaction. In this study, we explored the relationship between emotional intelligence and job satisfaction among nephrology nurses working in acute and chronic hemodialysis settings.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore, Tamil Nadu 641032 India.
Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people.
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