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Research Article
Different Perceptual Mechanism of Categorizing Emotional Faces in Depression and Schizophrenia
Yang Chen*,
Jiayu Wu,
Lu Che,
Yuping Du,
Xi Gao*
Issue:
Volume 14, Issue 3, June 2025
Pages:
70-75
Received:
9 May 2025
Accepted:
22 May 2025
Published:
23 June 2025
DOI:
10.11648/j.ajap.20251403.11
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Abstract: Background: Emotional stimuli affect basic and cognitive operations, such as perception, attention and memory and changes in emotional perception are associated with various mental disorders. Changes in emotional perception are associated with various mental disorders, such as major depressive disorder (MDD) and schizophrenia (SCZ). However, the differences in emotional cognition and their mechanisms among different mental disorders are still unclear. Objective: Different from negative expression processing preferences (attention, memory, etc.), categorizing positive facial expressions are much faster than emotion neutral and negative facial expressions, i.e., positive face classification advantage (PFCA). The present experiment directly investigated the difference in categorizing emotional faces between patients with MDD and SCZ. Main ideas: In healthy controls, happy faces were classified faster than sad faces (i.e., positive face classification advantage, PFCA). Although the ability of expression classification in both MDD and SCZ patients was reduced, the processing patterns of the two groups were different. The PFCA in patients with MDD was similar to that in normal controls. On the contrary, the PFCA was absent in patients with SCZ due to the need to invest more attention resources in classifying a face as happy emotion, suggesting that patients with SCZ have greater obstacles in processing positive facial expressions. Conclusion: The patterns of categorizing emotional faces was different between SCZ and MDD patients, which has important clinical significance for the differential diagnosis of the two diseases and the cognitive evaluation during treatment.
Abstract: Background: Emotional stimuli affect basic and cognitive operations, such as perception, attention and memory and changes in emotional perception are associated with various mental disorders. Changes in emotional perception are associated with various mental disorders, such as major depressive disorder (MDD) and schizophrenia (SCZ). However, the di...
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Research Article
The Influence of Personality Traits and Self-efficacy on Academic Performance Among Young Adults
Priyadharshini Sivanandham*,
Sindhu Sivasailam
Issue:
Volume 14, Issue 3, June 2025
Pages:
76-88
Received:
19 April 2025
Accepted:
8 May 2025
Published:
23 June 2025
DOI:
10.11648/j.ajap.20251403.12
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Abstract: This study seeks to explore how the personality traits and self-efficacy influence academic performance among young adults of 18 to 25 years. This topic falls within the scope of positive psychology studies, which contribute to the mental health of all ages and backgrounds. Utilizing a correlational research design and quantitative approach the research will involve approximately 300 participants elected through purposive sampling based on a defined inclusion and exclusion criteria. Validated questionnaire will be employed to assess the personality traits, self-efficacy and academic performance. Statistical analysis such as, Descriptive statistics, Spearman Rank Correlation and Linear Regression method was conducted to evaluate the relationship between the variables such as personality traits, self-efficacy and academic performance. This study revealed that there is relationship between personality traits, self-efficacy and academic performance. The variables such as personality traits and self-efficacy is a predictor of academic performance among young adults.
Abstract: This study seeks to explore how the personality traits and self-efficacy influence academic performance among young adults of 18 to 25 years. This topic falls within the scope of positive psychology studies, which contribute to the mental health of all ages and backgrounds. Utilizing a correlational research design and quantitative approach the res...
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A Cross-cultural Comparison of Chinese and Western Listeners’ Expectation of Musical Emotions in Different Daily Scenes: Happiness, Sadness, and Anger
Issue:
Volume 14, Issue 3, June 2025
Pages:
89-100
Received:
15 May 2025
Accepted:
23 June 2025
Published:
26 June 2025
DOI:
10.11648/j.ajap.20251403.13
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Abstract: This study investigated the cultural background effect on the expected emotional intensity of listeners in music for 3 basic emotions (happiness, sadness, anger) and 10 daily listening scenes. 127 subjects received a fully factorial questionnaire (2 [Culture: Chinese vs. Western] × 3 [Emotion] × 10 [Scene]). A significant Culture × Emotion × Scene interaction indicated that cultural difference manifests in specific emotion-scene pairs. The subsequent analyses indicated that Western listeners rated happiness more than Chinese listeners in move, social activity, housework, and party scenes, and rated anger more than Chinese listeners in exercise and coping with emotion scenes. Secondary two-way analyses also once more confirmed Western participants consistently anticipating more anger and happiness intensity than Chinese participants, with no group differences in sadness—highlighting cross-cultural universality in sad music experience. Culture × Scene analysis also identified stronger emotional expectations in Western listeners in move, study/work, exercise, coping with emotion, and pure music listening scenes. Overall, Westerners are more likely to anticipate high-arousal or functional states, i.e., strong emotions, while sadness elicits comparable expectations across both cultures. These findings demonstrate cross-cultural music-emotion theory by revealing conditional modulation of emotional expectations by culture. Follow-up research could employ actual musical pieces in conjunction with physiological or psychological measures to deconstruct the mechanisms of the culture-emotion-scene interactions.
Abstract: This study investigated the cultural background effect on the expected emotional intensity of listeners in music for 3 basic emotions (happiness, sadness, anger) and 10 daily listening scenes. 127 subjects received a fully factorial questionnaire (2 [Culture: Chinese vs. Western] × 3 [Emotion] × 10 [Scene]). A significant Culture × Emotion × Scene ...
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The Impact of Artificial Intelligence Usage on Employee Career Commitment: The Moderating Role of Artificial Intelligence Awareness
Xuan Liu
,
Yuci Chen*
Issue:
Volume 14, Issue 3, June 2025
Pages:
101-112
Received:
3 June 2025
Accepted:
23 June 2025
Published:
26 June 2025
DOI:
10.11648/j.ajap.20251403.14
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Abstract: Amid the wave of digital transformation, the widespread adoption of artificial intelligence (AI) has become an unstoppable trend. An increasing number of organizations are embracing AI to boost efficiency, streamline processes, and enhance decision-making quality. However, while AI helps improve organizational performance, it also exerts a profound influence on employees’ professional attitudes and behaviors. Exploring the impact of artificial intelligence applications on employees' career commitment is crucial. Grounded in the person-environment fit theory, this study aims to investigate how AI usage influences employees' career commitment through the mediating role of job crafting and the moderating role of AI awareness. Based on an empirical analysis of two hundred and two survey responses, the study reveals that AI usage positively correlates with employees' career commitment. Job crafting mediates this relationship, enhancing the positive effect of AI usage on career commitment. Additionally, AI awareness functions as a moderator, negatively adjusting both the impact of AI usage on job crafting and the indirect effect of AI usage on career commitment through job crafting. The research findings not only deepen our understanding of the relationship between AI usage and employee career commitment, but also offer theoretical grounding and practical guidance for organizations seeking to manage employee uncertainty and negative expectations while advancing intelligent transformation.
Abstract: Amid the wave of digital transformation, the widespread adoption of artificial intelligence (AI) has become an unstoppable trend. An increasing number of organizations are embracing AI to boost efficiency, streamline processes, and enhance decision-making quality. However, while AI helps improve organizational performance, it also exerts a profound...
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