Research questions: Some researchers propose that using a second language (L2) enhances empathy by broadening perspectives, while studies on the foreign-language effect suggest L2 may reduce empathy by dampening emotions and increasing cognitive control. This study examines the influence of L1 and L2 on empathy and ethnocentrism, employing virtual reality (VR), a tool fostering understanding of diverse perspectives.
Design: Polish university students, late bilinguals (N = 111), participated in a 2 (L1 vs. L2) × 3 (Pretest, Posttest 1, Posttest 2) mixed-design study, with all materials and subtitles in the assigned language. During a 9-minute VR experience, participants embodied Polish and Chinese students involved in a misunderstanding, heard their thoughts, and received cultural explanations.
Data and analysis: L2 exposure significantly enhanced cognitive empathy and reduced ethnocentrism immediately after the VR experience, with cognitive empathy remaining elevated 2 weeks later.
Conclusions: Results suggest that foreign language use in immersive VR environments may facilitate perspective-taking and cultural understanding through mechanisms consistent with the stunted intuitions model and cultural frame-switching.
Originality and implications: As the first to test the foreign-language effect in VR, we situated our findings within existing literature and outlined future research directions.
In two studies, people estimated the percent of vegans, vegetarians, those following a reduced meat diet and omnivores for specific populations. In a study of Polish adults (n = 1038), participants provided estimates of the diets of Poles and of residents of the US. In a US student sample (n = 2538), participants provided estimates of the diets of their fellow students and of the US population. With a few exceptions, participants overestimated the sizes of dietary minorities (vegans, vegetarians, and reducetarians) and underestimated size of the dietary majority (omnivores). Moreover, these under- and overestimates did not vary systematically as a function of participant diet or vegetarian threat. Although women's estimates of the size of dietary minorities were larger than men's and women's estimates of the size of the omnivorous majority were smaller than men's, both men and women overestimated the percent of dietary minorities and underestimated the percent of omnivores. These misestimates reflect the operation of a general cognitive bias called ‘Uncertainty-Based Rescaling’, that has been found to explain why people consistently underestimate the sizes of majorities and overestimate the sizes of minorities without the need to infer the operation of biases due to similarity, threat and so forth.
This study examined cognitive and temperamental predictors of susceptibility to orientation illusions, using adjustment tasks based on the Poggendorff and Zöllner figures. Cognitive predictors included field dependence–independence and the efficiency of Posner’s attentional networks (alerting, orienting, and executive control), while temperamental traits were assessed within Strelau’s Regulative Theory of Temperament. A total of 161 participants aged 20–33 years took part in the study. Susceptibility to the Poggendorff illusion was associated only with lower alerting network efficiency. In contrast, susceptibility to the Zöllner illusion was linked to both cognitive and temperamental factors: a field-dependent cognitive style combined with moderate or high Endurance, and an efficient orienting network combined with high Briskness. The findings support a multifactorial, illusion-specific account of susceptibility to orientation illusions, demonstrating that attentional, cognitive-style, and temperamental characteristics jointly contribute to individual differences in illusion strength.
Recent advances in machine learning (ML) have led to growing interest in the classification of psychiatric disorders using biomarkers such as electroencephalography (EEG), offering promising prospects for improving diagnostic accuracy. However, the methodological variability in existing studies makes it challenging to identify the best strategies for enhancing this crucial tool. This systematic review summarizes studies using resting-state EEG for psychiatric disorders classification to identify key strategies for optimizing classification performance. Our analysis reveals a significant interaction between the EEG features used for classification and the chosen ML algorithms. Notably, neural networks outperform traditional ML methods, especially when applied to raw data or to complex data without feature selection. Relying solely on linear features can undermine model performance, whereas combining diverse feature types leads to higher accuracies. Additionally, preprocessing data with a notch filter can enhance model performance. We underline the importance of obtaining sufficient sample sizes and using
subject-wise validation to mitigate potential overfitting. Moreover, we investigate the best-performing features, showing the importance of connectivity features, alpha and beta frequency bands, and frontal brain regions for depression detection; raw features and theta and alpha frequency bands for schizophrenia; and combined features and theta and alpha frequency bands for addiction. These insights synthesize the most effective approaches and provide valuable guidance for developing new tools in this field.
The article examines the role of protective factors in explaining temporal changes in violence risk among forensic psychiatric patients and prison inmates in Poland. A longitudinal study was conducted with 403 men (201 forensic patients and 202 inmates). Participants were assessed twice at a six-month-long interval using the HCR-20v3 and SAPROF. Forensic psychiatric patients showed a significant reduction in integrated risk for vioence, while prison inmates exhibited a slight increase in this field during the same period. In the patient group, the level of motivational protective factors from SAPROF was the sole notable predictor (albeit with low predictive power) explaining the variance in risk reduction. No protective factors significantly predicted risk changes in the inmate group. The findings indicate that risk dynamics may be context-dependent. The conducted analyses require further deepening and expansion. To facilitate this within the Polish psychiatric and penitentiary systems, systemic improvements are necessary, including the further implementation of Structured Professional Judgement (SPJ) risk assessment tools.
