International Journal of Psychology最新文献

Gender differences in grief expression have been widely studied, yet findings remain inconsistent. Some research reports higher grief intensity in women, while others find no difference. Two possible explanations are: (a) the neglect of third variables interacting with gender, and (b) men and women follow distinct grief trajectories. This study employed an observational longitudinal design to examine both hypotheses using data from Canada, Belgium and Spain. A total of 1328 bereaved adults were assessed between two and five times at different post-loss intervals. Sociodemographic, loss-related, grief and psychopathological variables were collected. Linear mixed models identified predictors of grief symptomatology and compared trajectories by gender. Results revealed significant gender differences in grief intensity, even after adjusting for other variables. However, no significant interaction between gender and time was found, indicating that men and women differ in intensity but follow similar grief trajectories. These findings may reflect gendered emotional socialisation: women may be more socially conditioned toward introspection and verbalization, which are more readily detected by standard assessment tools. Conversely, men's grief expression may be underestimated by existing instruments. Methodologically, the underrepresentation of men in grief research and the reliance on tools built on narrow conceptualisations of grief limit generalizability.

Teacher praise and criticism significantly influence students' learning and emotional development, yet the neural basis of how males and females process evaluative language remains unclear. This study used functional near-infrared spectroscopy (fNIRS) to examine gender differences in neural responses to emotional evaluation in educational contexts. A total of 35 female and 34 male students were recruited to listen to audio recordings of teacher evaluations with positive, negative, and neutral valences while their brain activity was monitored. Self-esteem and depression were incorporated as covariates in generalised linear model (GLM) and repeated-measures ANOVA analyses. The results showed that although there were no gender differences in behavioural responses, the brain activation (particularly in the right DLPFC) and functional connectivity (particularly inter-hemispheric connectivity) of men showed a preference for negative evaluations, while women showed a preference for positive evaluations. Male students also showed stronger local efficiency (i.e., more segregated processing and synchronised local neural circuitry) when responding to emotional stimuli, whereas females showed more global efficiency (i.e., more integrated, widespread and interconnected whole-brain processing). These findings reveal fundamental gender divergences in neural processing of social-evaluative stimuli, highlighting distinct neurocognitive strategies for emotional regulation and may help tailor teaching communication to support diverse student needs.

Attachment theory is one of the key frameworks for understanding close relationships, yet how marital attachment interacts within a dyadic context remains unclear. Using two-wave longitudinal data with a 6-month interval collected from 501 heterosexual spousal pairs, the present study examined interactive relationships in marital attachment within a dyadic context through cross-lagged panel network (CLPN) analysis. Firstly, the results found that wives' attachment components more strongly predicted husbands' attachment components within CLPN. Secondly, wives' attachment avoidance component, not show feel deep down, more strongly predicted other components and husbands' components within CLPN. Finally, bidirectional associations were observed between wives' and husbands' attachment avoidance components. These findings deepen our understanding of marital attachment interactions and offer practical insights for marital and family practices aimed at improving marital relationships.

Advancements in functional MRI have linked neurostructural and functional architecture to personality traits, but few studies focus on personality styles. This study examines 99 patients with moderate to severe depression and 97 matched controls, categorised into four personality styles using the Eysenck personality questionnaire. The study aims to identify behavioural and neurological differences between depressed and control groups. An SVM algorithm was used to differentiate between these groups within the same personality styles. Results indicated that the depression group exhibited lower grey matter volume in several brain regions, including the left superior parietal, left fusiform, left superior temporal gyrus, left inferior frontal gyrus, right precentral and left cingulate. These neuroanatomical changes facilitated successful discrimination between depressed and control groups. The study provides new insights into the neurobiological basis of personality styles and their role in the development of depression.

A widely accepted model of first impressions posits that trait judgements of faces have two orthogonal underlying dimensions: ‘valence’ (trustworthiness) and ‘dominance’. Studies have tested whether this model extends to body perception, but results were inconsistent. Given previous findings that stimulus viewpoints can significantly alter trait ratings of bodies, the present study aimed to determine whether this confound can explain the discrepancy between previous studies. Participants rated 100 bodies in either frontal or profile view on 14 personality traits. The resulting data were then analysed using principal components analysis (PCA) and exploratory factor analysis (EFA). The PCA and EFA produced two factors regardless of viewpoint, replicating the valence–dominance model for frontal and profile stimuli. As stimulus viewpoint did not strongly affect the underlying factors, the discrepancy between past papers is likely due to other stimulus differences. The present study confirmed that the valence–dominance model applies to body perception, raising the possibility that this model may apply to person perception more generally. Future research should determine whether these dimensions arise in other modalities, such as movement perception (e.g., walking gait) or touch perception (e.g., handshakes).

Borderline Personality Disorder (BPD) is marked by emotional instability and intense negative affect. The Predictive Coding Model posits that impaired prediction of bodily signals may underlie such deficits, though empirical validation remains lacking. In this study, we compared a high BPD-trait group (score ≥ 6 on the Chinese Version of the McLean Screening Instrument for BPD, without a BPD diagnosis) with a low BPD-trait group (score ≤ 2). Participants were examined using the Multidimensional Assessment of Interoceptive Awareness-2 (MAIA-2) for interoceptive sensitivity (IS), the Heartbeat Counting Task (HBCT) for interoceptive accuracy (IA) and heartbeat-evoked potentials (HEP) as the neural correlates of cardiac interoceptive processing. Results showed that the high BPD-trait group scored lower in the two subscales of the MAIA-2 (Not-Worrying and Trusting); however, no differences were observed for the HBCT. Furthermore, HEP amplitudes were significantly modulated by attention in the low BPD-trait group, with higher amplitudes during the heartbeat-focused condition, whereas the high BPD-trait group exhibited consistently high amplitudes across both conditions. Within the predictive coding framework, the observed pattern (intact IA, low interoceptive trust and altered HEP responses) may indicate a rigidity in precision weighting that impairs adaptive interoceptive modulation in individuals with BPD traits.

Teachers worldwide, including those in Taiwan, were compelled to transition from traditional classroom settings to online teaching because of the COVID-19 pandemic. This abrupt shift created numerous challenges. The ways in which individuals cope with such difficulties are closely related to their creative personality traits. Unlike conventional correlational analyses that examine relationships between specific dimensions, a typological approach emphasizes differences among distinct groups across particular variables. This study explored the perceived difficulties and coping strategies of middle school teachers in Taiwan with different creative personality types when adapting to online teaching. A typological approach was first employed to classify various creative personality traits. Subsequently, the problems that teachers encountered during the online teaching were examined across four dimensions, as well as the strategies they used to cope with these challenges in relation to their creative personality type. Through cluster analysis, nine creative personality traits were categorized into four types: extremely low, weakly low, weakly high, and extremely high. The findings indicated that teachers with extremely low and weakly low creative personality types were more likely to experience difficulties in classroom management and teacher–student interaction. These teachers tended to engage in peer communication or participate in professional development workshops to enhance their information technology skills. They also expressed a greater willingness to apply online teaching technologies in physical classrooms to foster students' motivation to learn. Conversely, teachers with weakly high and extremely high creative personality types were more proactive in implementing and refining their IT skills.

In the era of nature 2.0, new media rewires how we experience nature. To understand the psychological implications of this shift, three studies were conducted to explore the positive effects of techno-biophilia design in video games on various pro-social outcomes. In Study 1, online comments of certain popular video games were utilised to show a co-occurrence between the presence of nature elements and perceived natural beauty. Study 2, through the public goods game, then confirmed that individuals exposed to game scenes featuring natural landscapes reported statistically higher cooperative behaviour and helping intention, mediated by perceived natural beauty. Study 3 further recruited participants to participate in a virtual driving game, replicating the results by detecting higher climate change policy support and greater propensity for charitable donations among participants driving in the natural landscape. This research contributes to ‘technology for good’ through the exploration of nature element inclusion in video games, shedding light on techno-biophilia design and positive technology paradigm. It thus provides a foundational blueprint for how intelligent technologies of this era can be designed to foster inclusive pathways to the benefits of nature engagement, catering to diverse preferences and contexts.

The incorporation of AI-powered applications into music education is becoming increasingly important, as these tools can extend practice support beyond the session and provide rapid performance feedback. The current study investigated whether an app-assisted learning technique improves pianists' performance skills and self-efficacy compared to traditional instruction. Participants were separated into experimental and control groups and given pre- and post-test assessments. The psychometric instruments used included the Practical Piano Performance Assessment and the Music Performance Self-Efficacy Scale. Statistical analysis, involving paired and independent t-tests, revealed that the experimental group showed significant improvements in piano performance (F = 113.528, p < 0.001) and in all four dimensions of self-efficacy—mastery experience (t = 7.031, p < 0.001), vicarious experience (t = 7.126, p < 0.001), verbal/social persuasion (t = 7.929, p < 0.001) and physiological states (t = 12.812, p < 0.001)—compared to the control group, which followed a standard curriculum. These findings highlight the practical value of AI-based applications that provide not only personalised real-time feedback but also interactive learning. Future research should explore the long-term effects of using this software and its potential in blended learning environments to optimise the curriculum.