Search Results (1,055)

Growing geopolitical instability has led to increasing concerns about the psychological impact of war beyond directly affected populations, highlighting the need for culturally appropriate instruments to assess fear of war. In this study, we evaluate the psychometric properties of the Turkish version of the Fear of War Scale (FOWARS) and examine its associations with sociodemographic characteristics and personality traits. A total of 643 adults across two independent samples (sample 1 = 360; sample 2 = 283) completed the FOWARS, the Tolerance of Uncontrollability Questionnaire, the Next Big Five Inventory (BFI-2), the Depression Anxiety Stress Scale-21 (DASS-21), and a sociodemographic information form. Confirmatory factor analysis supported the original two-factor structure of the FOWARS, with the Turkish version demonstrating satisfactory structural validity, convergent validity, discriminant validity, criterion-related validity, strong internal consistency, and measurement invariance across gender. Fear of war was negatively associated with tolerance of uncontrollability and positively associated with depression, anxiety, and stress. In addition, fear of war was significantly associated with gender, socioeconomic status, agreeableness, neuroticism, and conscientiousness. These findings expand the understanding of the individual determinants of fear of war, underscoring the importance of developing targeted interventions for vulnerable populations. Full article

In the current study, we examined the associations between four time perspective constructs (time attitudes, time frequency, time relation, and time orientation) and two academic outcomes (self-reported academic achievement and educational expectations), controlling for the Big Five personality traits and demographics (age, gender, and maternal education). Participants included 758 adolescents (M_age = 15.81, SD_age = 1.22) from the Western United States. Several subscales had associations with academic achievement and educational expectations above and beyond personality. Specifically, negative attitudes toward the future were negatively associated with academic achievement, and positive attitudes toward the future were positively associated with educational expectations. Present negative attitudes were also significantly associated with academic achievement, though this association was not practically meaningful. The remaining time attitude subscales, time frequency, time relation, and time orientation did not survive Bonferroni correction. Overall, the effect sizes were limited for most of the identified statistically significant associations, suggesting minimal practical significance. These findings identify specific time perspective dimensions that may warrant further longitudinal and intervention research to evaluate their potential role in promoting academic outcomes among adolescents. Full article

Many organizations increasingly adopt personalization techniques to enhance user satisfaction. However, current systems generally cannot automatically infer and interpret individual personality traits (PTs), although these traits are key drivers of user behavior. While Large Language Models (LLMs) are widely used, they remain poorly suited to reliable and explainable Personality Assessment (PA). To address this gap, we propose ExPAM, a novel Explainable Personality Assessment Method that combines hybrid feature fusion with in-context learning in off-the-shelf LLMs to predict Big Five PTs from text. ExPAM explicitly grounds its predictions in interpretable linguistic patterns without requiring LLM fine-tuning. Its hybrid fusion is designed to improve both predictive performance and interpretability in PA. Transformer-based embeddings encode local contextual information, whereas features extracted using the Linguistic Inquiry and Word Count (LIWC) dictionary provide complementary global and local linguistic indicators of PTs. These interpretable feature patterns are included in prompts that guide the LLM to produce both PT predictions and human-understandable explanations. ExPAM shows competitive performance compared with multi-task models on the ChaLearn First Impressions v2 (FIv2) corpus and single-task models on the PANDORA corpus that rely on a single feature set. On FIv2, it achieves a mean accuracy (mAC) of 0.891 and a Concordance Correlation Coefficient (CCC) of 0.333. On PANDORA, it achieves a mean Pearson Correlation Coefficient (PCC) of 0.240 and a CCC of 0.101. Prompting the LLM with hybrid global–local patterns further improves CCC by 9.9% on FIv2 and 15.8% on PANDORA, while changes in mAC and mean PCC remain marginal. Qualitative interpretability analysis reveals trait-specific linguistic patterns, highlighting the potential of ExPAM for psychological research, computational linguistics, and paralinguistic studies. Full article

Background/Objectives: Clinically overt Alzheimer’s disease (AD) is associated with significant changes in personality factors. Earlier studies indicated that personality factors do not remain stable in elderly controls. Whether the early presence of AD neuroimaging markers may predict subsequent changes in personality factors is still debatable. Methods: To address this issue, we examined the association between Big Five factor scores and baseline AD and vascular imaging markers in a previously established cohort of 58 elderly controls with a 4.5-year follow-up. Personality was assessed with the Neuroticism–Extraversion–Openness Personality Inventory—Revised scale at inclusion and 55-month follow-up. Regression models were used to identify predictors of personality factor changes including time, age, sex, APOE epsilon 4 allele, baseline MMSE scores, amyloid PET positivity, abnormal FDG-PET patterns, mesial temporal lobe atrophy and Fazekas scores, and number of microbleeds. Results: In both univariate and multivariable models, the decrease in openness was related to abnormal FDG PET patterns. This single variable explained 15% of the variance of this personality factor. In univariate models, lower MMSE scores and amyloid positivity at baseline were associated with a subsequent decrease in agreeableness scores. In multivariable models, these two parameters explained 11% and 8% of variance respectively. The other personality factors were not associated with AD and cerebrovascular imaging markers. Conclusions: Personality patterns at baseline may impact the emergence of AD pathology but they may also change rapidly as a function of the presence of early AD-related PET abnormalities. Full article

Research on the informal economy has traditionally emphasized its measurement and macroeconomic effects, focusing on structural and institutional determinants. Individual psychological factors that may help explain social tolerance toward informal practices have received far less attention. This exploratory study addresses this gap by examining how Big Five personality traits and dimensions of competitiveness are associated with two components of tolerance: the acceptance of informal behaviors, and justificatory beliefs. To this end, an ad hoc questionnaire was developed, and a cross-sectional design was implemented using a stratified sample of 339 students enrolled in Business Administration programs at a Spanish university. Multivariable models estimated these associations while adjusting for gender. The results indicate that conscientiousness and extraversion are negatively associated with both acceptance and justificatory beliefs, whereas competitive affectivity exhibits a positive and consistent association with both dimensions. Within the study sample, tolerance scores were higher among male respondents. These findings raise a hypothesis for future research: awareness campaigns may achieve greater precision when they account for psychological heterogeneity. This implication should be tested in broader and more diverse populations. Drawing on this exploratory evidence, we propose a preliminary analytical model that articulates the relationships between dispositional traits and competitiveness dimensions in relation to the two components of tolerance, providing a basis for future research. From a theoretical perspective, the proposed model offers a structured basis for longitudinal testing and future experimental designs aimed at deepening the understanding of the microfoundational mechanisms underlying the informal economy. Full article

Depressive symptoms are prevalent among college students. This study examined cross-domain associations among depressive symptom dimensions, physical activity, Big Five personality traits, and goal orientation using network analysis, latent profile analysis (LPA), multi-group network analysis, and multiple linear regression. LPA was conducted using behavioral, personality, and motivational variables only, with depressive symptom indicators excluded from class extraction. Data from 911 Chinese undergraduates were analyzed. The results showed that psychological equivalents, a cognitive-related depressive subdimension, had the highest strength centrality in the overall network, while neuroticism showed prominent positive bridge expected influence between personality traits and depression-related indicators. In the regression models, task orientation, agreeableness, conscientiousness, and openness were negatively associated with depressive symptoms to varying degrees. MVPA and sedentary time were not significantly associated with depressive symptoms in the total-sample model, whereas walking showed a subgroup-specific negative association only in the maladaptive, low-motivation, inactive profile. Three behavioral–personality–motivation profiles were identified, and the maladaptive profile showed relatively higher depressive symptom levels and stronger neuroticism-related associations. These findings provide associative, network- and profile-based evidence for understanding depressive symptoms among college students and may inform future longitudinal and intervention studies targeting behavioral–personality–motivation heterogeneity. Full article

Real-world IoT network security generates traffic at big-data scale with extreme class imbalance, temporal non-stationarity, and continuously evolving attack strategies that overwhelm static supervised classifiers. This paper presents a cognitive computing framework for network intrusion detection: a CNN–LSTM–DQN architecture with Prioritized Experience Replay (PER) evaluated on a 5,000,000-flow naturalistic sample of the TON_IoT Processed_Network dataset (4,000,000 training/1,000,000 temporally held-out test flows; 94.5% attack ratio) under a strict temporal split. The cognitive agent optimizes detection decisions using an Alerts per Million Flows (ARMF)-aware reward function that encodes both alert-fatigue cost and missed-attack penalty. We conduct a cross-attack-family generalization study: the methodology—architecture template, reward design, and hyperparameter calibration—is inherited from a framework previously validated on CSE-CIC-IDS2018, re-instantiated and retrained on the structurally different TON_IoT environment, and compared against the previously published benchmark. Initialization sensitivity is characterized across five independent random seeds using paired Wilcoxon signed-rank and t-tests. Across the five seeds, the proposed X2 model attains recall 0.833 ± 0.306 and F1 0.874 ± 0.241 (mean ± sample SD), versus the supervised X1 baseline at 0.858 ± 0.178 and 0.912 ± 0.116; the best-performing seed (42) achieves 97.52% accuracy, 98.02% attack recall, 99.46% precision, and 98.73% F1-score on 1,000,000 held-out XSS flows—an attack family entirely absent from training—with temporal stability variances of 4.63 × 10⁻⁷ (recall) and 1.38 × 10⁻⁷ (F1). The X2 advantage observed among the four stable seeds is not statistically demonstrated at n = 5 (statistical power ≈ 5.1%); the initialization-sensitivity finding itself, including one degenerate alert-suppression seed, is reported as a primary contribution. A formal, exactly additive ARMF decomposition distinguishes the detected-attack (structural) component (99.46%) from the model-induced false-positive component (0.54%), and we report a multi-seed, ARMF-aware cognitive IDS evaluation on naturalistic TON_IoT traffic under an unseen-attack-family test condition that, to the best of our knowledge, has not been reported in the surveyed RL-based NIDS literature. Full article

Background/Objectives: In recent decades, health care for those living with chronic and disabling conditions has expanded beyond symptom and disease management to include efforts to promote health and quality of life. This narrative review synthesizes insights from a 26-year longitudinal study examining health promotion and quality of life among persons living with the chronic and disabling condition of multiple sclerosis (MS). Methods: The longitudinal study, launched in 1999, included a sample of 621 community-residing persons with MS. Our longitudinal research design allowed us to investigate unique issues related to the speed, sequence, direction, and duration of changes in a wide range of MS outcomes. Guided by Braun and Clarke’s thematic analysis framework, we have critically reviewed the more than 100 peer-reviewed publications and presentations generated by the study, in which we have identified overarching “Big Picture” themes, and we have contextualized them in relation to other MS research. Results: Five major themes were supported by the findings in this narrative review: (1) Strong interest in health promotion behaviors; (2) Positive view of overall health; (3) Mediation of the impact of functional limitations on quality of life; (4) Physical activity impacts the trajectory of functional limitations over time; and (5) Association of health behaviors with quality of life and health outcomes. Conclusions: Interventions that recognize and incorporate the positive health behaviors and perceptions of persons living with a long-term chronic condition can assist persons aging with chronic conditions to adjust to changes in their environment and the demands of self-management. Full article

Background: Medical training is characterized by high academic demands, repeated performance evaluation, and sustained exposure to emotionally demanding situations. Although medical student distress has been widely investigated, fewer studies have examined how broad personality traits relate to multidimensional, eudaimonic psychological well-being (PWB), particularly in Central and Eastern European medical student populations. This study examined associations between Big Five personality traits and Ryff’s PWB dimensions among Polish medical students. Methods: A cross-sectional, anonymous paper-and-pencil survey was conducted among 169 Polish medical students. Personality was assessed using the Polish adaptation of the NEO Five-Factor Inventory (NEO-FFI), and PWB was measured using the 84-item Ryff Psychological Well-Being Scales. Descriptive statistics, reliability analyses, normality checks, and bivariate Spearman correlations were used. Results: The global PWB total score was 352.69 (SD = 45.55; observed range 235–450). Among PWB domains, the highest mean score was observed for personal growth (M = 62.86, SD = 8.04), followed by purpose in life (M = 61.76, SD = 10.31), positive relations with others (M = 61.25, SD = 10.94), self-acceptance (M = 57.00, SD = 11.67), autonomy (M = 55.85, SD = 10.58), and environmental mastery (M = 53.97, SD = 10.03). Internal consistency was acceptable to excellent for all PWBS domains (Cronbach’s alpha = 0.796–0.906). Neuroticism was negatively associated with all PWB domains, most strongly with environmental mastery (rho = −0.620) and self-acceptance (rho = −0.618). Conscientiousness was strongly positively associated with environmental mastery (rho = 0.627) and purpose in life (rho = 0.570). Extraversion showed positive associations with self-acceptance, positive relations, environmental mastery, purpose in life, and personal growth. Openness was positively associated with personal growth and negatively associated with environmental mastery, whereas Agreeableness was positively associated with self-acceptance, positive relations, and personal growth, but negatively associated with autonomy. Conclusions: Big Five traits showed domain-specific associations with PWB among Polish medical students. The findings support a differentiated, trait-informed perspective on student well-being, but the cross-sectional design precludes causal inference. Future longitudinal and multi-center studies should clarify temporal relationships and evaluate whether universal or optional well-being supports are differentially useful for students with distinct personality profiles. Full article

Background and Objectives: HPV vaccination is critical for cervical cancer prevention, but HPV vaccination coverage stays low among young women in China. While various factors shaping vaccination willingness have been explored, the role of personality traits remains insufficiently understood. This study investigated the relationships between Big Five personality traits and three facets of HPV vaccination willingness (consideration, determination, recommendation) among female healthcare undergraduates. We also specifically examined whether academic major moderated the association between extraversion and vaccination willingness. Methods: A cross-sectional survey was conducted among 703 female undergraduates enrolled in healthcare majors at a medical college in Chengdu using a stratified cluster sampling method. Data were collected via online questionnaires, including the 10-item Big Five Inventory (BFI-10) and a scale measuring three motivational facets of HPV vaccination willingness: consideration, determination and recommendation. Descriptive statistics, correlation analysis and hierarchical regression analysis were performed to examine the research questions. Results: A total of 672 valid questionnaires were analyzed. Distinct associations were found between personality dimensions and each facet of vaccination willingness. Agreeableness (β = 0.193, p < 0.01) and openness (β = 0.079, p < 0.05) correlated with vaccination consideration (ΔR² = 0.061). Extraversion (β = 0.103, p < 0.05), agreeableness (β = 0.113, p < 0.01) and conscientiousness (β = 0.096, p < 0.05) correlated with determination (ΔR² = 0.049). Extraversion (β = 0.125, p < 0.01), agreeableness (β = 0.129, p < 0.01), conscientiousness (β = 0.102, p < 0.01) and neuroticism (β = 0.081, p < 0.05) were positively related to recommendation willingness (ΔR² = 0.061). Academic major did not exert a significant moderating effect. Conclusions: The findings highlight the complexity of the relationships between personality traits and vaccination attitudes and behaviors. While the observed associations were modest in magnitude, this study provides preliminary empirical evidence that may inform personality-sensitive HPV vaccination promotion strategies. Tailored, multi-dimensional interventions that consider diverse population characteristics could be considered to optimize HPV vaccination outreach, though their effectiveness awaits further validation. Full article

Personality research has traditionally focused on stable trait differences, but increasing attention has been devoted to the internal organization of personality traits within individuals. The present study examined whether intraindividual variability in the Big Five traits, operationalized as the within-person standard deviation across trait scores (iSD_BFI), is associated with problematic digital engagement in young adults. A sample of 316 participants completed the Big Five Inventory and selected subscales of the Behavioral Addiction Questionnaire assessing smartphone use, internet use and video gaming. Pearson correlations, hierarchical regression and independent samples t-tests were conducted to evaluate associations between personality trait-profile dispersion and digital behaviors. Results showed that higher iSD_BFI was weakly but significantly associated with greater problematic smartphone use (r = 0.115, p = 0.044) and internet use (r = 0.141, p = 0.012), whereas no significant association emerged with video gaming (r = 0.029, p = 0.764). Hierarchical regression analyses further indicated that iSD_BFI explained a small but statistically significant additional proportion of variance in smartphone use (ΔR² = 0.014, p = 0.023) and internet use (ΔR² = 0.019, p = 0.008) beyond age, sex, and the five Big Five traits, but not in video gaming. Participants in the problematic smartphone use group exhibited significantly higher iSD_BFI than those in the moderate risk group. Rather than representing a direct measure of self-coherence or identity fragmentation, iSD_BFI was considered an exploratory structural indicator of personality profile dispersion. Accordingly, a more heterogeneous personality profile may be associated with a greater approach to digitally mediated environments, possibly because these environments provide predictability, feedback, and reinforcement. Overall, the study highlights the importance of exploring intraindividual personality configuration as a complementary dimension to traditional trait-based approaches. Full article

The research investigates the sequential routes through which customer-centric culture (CCC) leads to sustainable performance (SP) in the hospitality sector, by analyzing the mediating impacts of sales force automation (SFA) and big data analytics capabilities (BDACs), and the moderating impact of employee digital competence (EDC). A serial mediation model (CCC → SFA → BDACs → SP) was proposed and empirically tested using partial least squares structural equation modeling (PLS-SEM) on survey data from 315 managerial and operational employees in five-star hotels in Riyadh, Saudi Arabia, grounded in the resource-based view, dynamic capabilities theory, and service-dominant logic. The results support all eleven hypotheses and show that SFA has a positive effect on BDACs (β = 0.391) and SP (β = 0.319), and BDACs have a significant effect on SP (β = 0.143). The CCC has a significant direct impact on SFA (β = 0.746) and SP (β = 0.421). Importantly, the serial mediation pathway (CCC → SFA → BDACs → SP) is significant (β = 0.042) and EDC significantly moderates the SFA–BDAC (β = 0.447) and BDACs–SP (β = 0.112) relationships. The model accounted for 72.1% of the variance in SP. The findings emphasize that sustainable performance is not driven by mere technology adoption but a synergistic integration of customer-oriented culture, automation, analytics, and digital workforce competencies. Full article

Emotional and behavioral problems (EBPs) experienced by children have become an important global health issue requiring immediate attention. Previous studies have shown that parental neuroticism is associated with EBPs in children. However, the mechanisms underlying this association have yet to be fully elucidated. This study examined the relationship between parental neuroticism and preschoolers’ EBPs, focusing on the mediating role of parental emotional distress (e.g., anxiety, depression, and somatization). In addition, to gain a deeper understanding of children’s emotional and behavioral difficulties, this study constructed a comprehensive network of preschoolers’ EBPs to investigate the interconnections among individual symptoms. A total of 1216 Chinese families (M_{children age} = 4.46 years; 47.6% girls) participated in this study, completing the Chinese Big Five Personality Inventory, Brief Symptom Inventory, and Strengths and Difficulties Questionnaire. Data analysis was conducted using structural equation modeling (SEM) and network analysis. The results showed that parental neuroticism was positively associated with children’s EBPs, and this relationship was partially mediated by parental emotional distress. “Constantly fidgeting or squirming”, “stealing from home, kindergarten, or other places”, “often unhappy‚ depressed or tearful”, and “many fears‚ easily scared” emerged as the most central symptoms in the network of EBPs. These findings hold significant implications for enhancing well-being among parents and their preschool children, suggesting that parents should prevent the spread of negative emotions such as anxiety and depression. Timely, targeted interventions focusing on central symptoms of EBPs are essential for promoting children’s mental well-being. Full article

Emotional intelligence and personality traits are key dimensions of individual differences contributing to developmental adjustment. This cross-sectional study investigated how trait emotional intelligence (trait EI), conceptualized as self-perceived dispositions closely embedded within personality hierarchies rather than a cognitive ability, is configured alongside the Big Five traits to influence socio-emotional functioning among preadolescents. Using a convenience sampling strategy, data were collected from 194 Greek preadolescents (aged 10–12) who completed self-report measures of trait EI, personality, and psychosocial adjustment via the Strengths and Difficulties Questionnaire (SDQ). Latent Profile Analysis (LPA) identified three distinct individual configurations: Emotionally Resourceful (54.6%), Emotionally Vulnerable (14.9%), and Emotionally Resilient (30.4%). Distal outcome testing via the Bolck-Croon-Hagenaars (BCH) three-step approach revealed that the Emotionally Resilient profile exhibited the most favorable adjustment (higher prosocial behavior, lower emotional/behavioral difficulties), whereas the Emotionally Vulnerable group displayed the highest psychosocial risks. While the reliance on cross-sectional self-reports requires cautious interpretation regarding causality, the findings underscore that preadolescent adjustment is better understood through integrated dispositional configurations rather than isolated traits, clarifying the role of trait EI within the broader personality space. Full article

This paper addresses the call for greater integration of science, technology, engineering, and mathematics (STEM) in the context of creating a foundational focus for STEM, beginning in early childhood. The work draws on a birth-to-five developmental framework that models and connects seamlessly with the U.S. Framework for K-12 Science Education). These 3D frameworks integrate STEM across a small set of big ideas in four disciplinary areas (including engineering and technology), acquired through active engagement in science, engineering, and mathematical practices, and connected through meaningful crosscutting concepts. In addition, this project addresses the challenges and obstacles that teachers face in effective implementation by leveraging teachers’ comfort and young students’ enjoyment of storybooks as an additional level of integration, as recommended by the U.S. National Academies of Sciences, Engineering, and Medicine 2022 consensus volume on science and engineering from preschool through elementary grades. Finally, given the increase in young children in the U.S. who are learning more than one language as well as in other countries, the current study examined the instructional practices of preschool teachers during shared book reading sessions using a Spanish-English bilingual STEM storybook in an intentionally Spanish-English preschool setting. Findings support an increase in teacher use of three-dimensional (3D) STEM talk to provide information upon re-reading the storybook, regardless of the language(s) used to read. Interviews with the teachers revealed approval for the translational-equivalent structure of the bilingual storybook, and an appreciation of the STEM-embedded content format for introducing the content to these young students. This study extends findings on teacher practices and language use with a bilingual STEM-focused storybook in a bilingual preschool setting to support bilingual learners. Full article