Search Results (90)

Background: Social anxiety in adolescence is a prevalent mental health concern characterized by intense fear of negative evaluation in social situations. The Social Anxiety Questionnaire for Adolescents (CASO-N24) is a Spanish-language instrument requiring validation in Peruvian populations. Objective: This study aimed to validate the CASO-N24 in Peruvian adolescents aged 12–17 years, extending its application beyond the original 9–15-year range, and examine its psychometric properties including factorial structure, measurement invariance, nomological validity, and internal consistency. Methods: A stratified probability sample of 710 adolescents (352 males, 358 females; M = 14.82 years, SD = 1.45) from four northern Peruvian educational centers completed the CASO-N24 and ASQ-14. Exploratory and confirmatory factor analyses, multigroup invariance testing by age and gender, nomological validity assessment, and reliability estimation (Cronbach’s α and McDonald’s ω) were conducted using polychoric correlations and robust estimation methods. Results: The six-factor structure was replicated, explaining 47.13% of variance with factor loadings ranging 0.48–0.78. Model fit indices were excellent (GFI = 0.981, AGFI = 0.976, NFI = 0.971, SRMR = 0.046). Complete measurement invariance was achieved across age groups (12–15 vs. 16–17 years). Partial invariance by gender was observed, with differential item functioning identified in item 17. Nomological validity was confirmed through moderate-to-high correlations with ASQ-14 (males: r = 0.622; females: r = 0.604). Internal consistency was adequate (total scale ω = 0.95; subscales ω = 0.69–0.82). Conclusions: The CASO-N24 demonstrated robust psychometric properties for assessing social anxiety in Peruvian adolescents aged 12–17 years, supporting its multidimensional structure and utility for early detection in school settings while highlighting gender-specific response patterns warranting clinical consideration. Full article

Background: Although the concepts of meteoropathy and meteosensitivity are not included in official classifications, such as the ICD-11 or DSM-5, they are increasingly being studied as potential symptom complexes linking weather variability to health status. The METEO-Q questionnaire, originally developed in Italy, has been adapted in Japan and Turkey, where it has demonstrated satisfactory reliability parameters, although the authors emphasized the need for further verification of the tool’s temporal stability. The present study aimed to adapt METEO-Q to the Polish language and conduct a critical assessment of its factor structure, measurement invariance, and validity in clinical groups. Methods: This cross-sectional study involved 1128 adults: healthy individuals (n = 711), cardiac outpatients (n = 194), and subclinical group with diagnosed mental disorders (n = 223). Data from healthy participants were divided into a training sample (n = 426) for exploratory factor analysis (EFA) and a test sample (n = 285) for confirmatory factor analysis (CFA). Measurement invariance was assessed in the clinical groups. Validity was verified through correlations with a list of 21 symptoms and measures of anxiety and worry about climate change. Results: A two-factor model (meteoropathy and meteosensitivity) was better fitted to the data than a one-factor model, which is consistent with findings from Italian, Japanese, and Turkish studies. However, absolute fit indices in the test sample indicated significant model misfit [CFA: χ² (43) = 210.192, p < 0.001, RMSEA = 0.120, CFI = 0.927], suggesting the presence of local errors in the tool’s structure. The reliability of the subscales was high (α from 0.86 to 0.93). Multi-group analyses suggested metric and scalar invariance. Patients with mental disorders obtained the highest scores, while cardiac outpatients reported a lower level of meteoropathy (M = 6.13) than healthy individuals (M = 7.24). Conclusions: METEO-Q demonstrates a stable two-factor structure and high internal consistency. The obtained RMSEA index (0.12), although indicative of some misfit, is similar to results obtained in other adaptations, such as the Japanese (RMSEA = 0.10) and the Turkish (RMSEA = 0.11), which suggests it is a consistent feature of this tool across different cultural contexts. Accordingly, the instrument is suitable for research purposes; however, its clinical application requires considerable caution and further work to optimize the model. Full article

This study develops and tests an Engagement–Experience–Co-creation–Loyalty (EECL) framework explaining how hospitality brand engagement (HBE) is translated into multidimensional hotel loyalty through two parallel mechanisms: Hospitality brand experience (HBX) and hospitality value co-creation (HVCC). A variance-based PLS-SEM model with seven reflective latent constructs and 57 indicators was estimated using data from 1407 members of four global hotel loyalty programs; generational cohort was used only as a grouping variable in multi-group analysis, not as an additional construct. MICOM established measurement invariance across Generation Z, Millennials, Generation X, and Baby Boomers. HBE is positively associated with both HBX and HVCC, and both mechanisms transmit its relationship to cognitive, affective, and conative loyalty. These three attitudinal facets jointly predict action loyalty, supporting a parallel rather than strictly staged loyalty-formation logic in hotel loyalty-program contexts. Younger cohorts translate engagement more strongly into experience and co-creation, whereas older cohorts rely more on experience when forming cognitive loyalty. The study contributes a hospitality-specific, predictive, and cohort-sensitive explanation of how engagement is converted into hotel loyalty. Full article

Hyperspectral imagery (HSI) offers rich spectral signatures and fine-grained spatial structures for remote sensing, but practical HSI classification is often constrained by scarce labels and complex geometric disturbances, including translation, rotation, scaling, and shear. Existing deep models are typically developed under Euclidean assumptions and rely on data-hungry training pipelines, which makes them brittle in the few-shot regime. To address this challenge, we propose EMNet, a Lie-group-based Equivariant Manifold Network for few-shot HSI classification that explicitly encodes geometric invariance and improves discriminative accuracy. EMNet couples an SE(2)-based Equivariance-Guided Module (EGM) to enforce equivariance to translations and rotations with an affine Lie-group-based Characteristic Filtering Convolution (CFC) that models scaling and shearing on the feature manifold while adaptively suppressing redundant responses. Extensive experiments on WHU-Hi-HongHu, Houston2013, and Indian Pines demonstrate state-of-the-art performance with competitive complexity, achieving OAs of 95.77% (50 samples/class), 97.37% (50 samples/class), and 96.09% (5% labeled samples), respectively, and yielding up to +3.34% OA, +6.01% AA, and +4.14% Kappa over the strong DGPF-RENet baseline. Under a stricter 25-samples-per-class protocol with 10 repeated random hold-out splits, EMNet consistently improves the mean accuracy while exhibiting lower variance, indicating better stability to sampling uncertainty. On the city-scale Xiongan New Area dataset with extreme long-tail imbalance (1580 × 3750 pixels, 256 bands, and 5.925 M labeled pixels), EMNet further boosts OA from 85.89% to 93.77% under the 1% labeled-sample protocol, highlighting robust generalization for large-area mapping. Beyond point estimates, we report mean ± SD/SE across repeated splits and provide rigorous statistical validation by computing Yule’s Q statistic for class-wise behavior similarity, performing the Friedman test with Nemenyi post hoc comparisons for multi-method ranking significance, and presenting 95% confidence intervals together with Cohen’s d effect sizes to quantify practical improvement. Full article

This paper presents an exploratory cross-cultural analysis of autonomous vehicle expectations through a 57-question survey distributed in the United States (n = 50), Germany (n = 66), and Panama (n = 41). Five scales are presented and validated: Driving Behavior Aggressiveness (DBA), Self-Driving Car Aggressiveness (SDCA), Artificial Intelligence (AI) Trust (AIT), AI Driving Mechanics Trust (AIDMT), and Driver Safety Score (DSS). Each scale is validated via confirmatory factor analysis and multi-group measurement invariance testing. Results show that drivers prefer a self-driving car driving style more conservative than their own; however, participants who are more trustful of AI show DBA–SDCA equivalence, consistent with acceptance of a driving style comparable to their own. Significant cross-cultural differences emerge, with Panama diverging from the United States and Germany on DBA, SDCA, AIDMT, and DSS; these country effects largely persist after controlling for demographics. These findings suggest that self-driving car behaviors should be tailored to regional expectations and passenger trust profiles to improve adoption. Full article

When measurement invariance (MI) is violated in multi-group structural equation models, group-specific measurement artifacts inflate the between-group variance of structural parameters beyond their true values. Existing remedies—partial invariance, group-specific estimation, or moderation analysis—address the consequences of inflation but not its mechanism. This article introduces the stabilizer variable, a covariate that absorbs measurement-induced parameter heterogeneity while maintaining structural independence from the focal relationship. Two theoretical results are established: a variance decomposition theorem showing that MI violations inflate dispersion through an identifiable artifactual component, and a purification theorem proving that a stabilizer reduces this dispersion via Frisch–Waugh–Lovell projection. Two stabilization mechanisms are identified: variance purification (Type A) and directional alignment (Type B). We then develop the stabilizer variable test, a dual-criterion procedure combining nonparametric bootstrap testing for stabilization magnitude with binomial testing for directional consistency, incorporating adaptive MI severity scoring with calibrated fit-index weights. Simulations comprising 949,100 replications across varying group counts, sample sizes, and MI severity levels demonstrate 80–99% power with false-positive rates below 2%. Practical guidelines recommend $K\ge 10$ groups and $n\ge 100$ per group for conservative applications. The framework generalizes to any multi-group regression context where systematic measurement error induces spurious parameter heterogeneity. Full article

Background: Anxiety symptoms among medical students often emerge at the intersection of sustained academic pressure, anticipatory uncertainty and early professional socialisation, complicating their distinction from transient stress responses. Instruments employed in this context are therefore expected to operate consistently across subgroups while preserving conceptual clarity under non-clinical conditions. The Generalized Anxiety Disorder scale (GAD-7), widely adopted as a brief screening measure, has shown variable factorial behaviour across populations, particularly when applied to student cohorts. Materials and methods: Using confirmatory factor analysis with robust weighted least squares estimation, the latent structure of a culturally adapted Spanish version of the GAD-7 was examined in a sample of medical students enrolled across all academic years at a public university. Model performance was evaluated through multiple fit indices suited for ordinal data, alongside estimates of convergent validity based on average variance extracted and reliability assessed via both Cronbach’s α and McDonald’s ω. Measurement invariance across sex was explored through a sequence of increasingly constrained multi-group models. Results: The unidimensional configuration originally proposed for the scale remained statistically coherent, despite minor tensions between absolute and incremental fit indicators commonly reported in comparable university-based samples. Convergent validity estimates suggested that the latent construct accounted for a substantial proportion of item variance, while reliability coefficients fell within the upper range observed internationally. Invariance testing supported comparability at the configurational and scalar levels, although full metric equivalence was less stable. Conclusions: Rather than resolving ongoing debates regarding the internal structure of the GAD-7, these findings situate its psychometric behaviour within the specific demands of medical education, where anxiety-related symptoms may fluctuate between normative adaptation and clinically relevant distress. This positioning invites further examination of how screening instruments perform when anxiety is shaped as much by institutional context as by individual psychopathology. Full article

The ambivalent sexism theory supports differences in the manifestations of sexism among individuals with diverse genders and sexual orientations. However, it still remained unclear whether individuals who share common strong cultural values endorse different levels of sexism according to their gender and sexual orientation. The current study aimed to examine differences in sexist attitudes based on gender and sexual orientation among Korean adults. We first tested measurement invariance in a Korean Multi-dimensional Sexism Inventory (K-MSI) between heterosexuals (n = 374) and sexual minorities (n = 445), and second, we compared the latent means across groups using the Multiple Indicators Multiple Causes (MIMIC) model. The results confirmed the first-order six-factor structure of the K-MSI with adequate internal consistency, and supported partial scalar invariance across heterosexual and sexual minority men and women. The MIMIC model approach revealed significant age, gender, and sexual orientation differences in most of hostile sexism (HS) and benevolent sexism (BS) components. Overall, heterosexuals reported higher levels of sexism than non-heterosexuals within each gender. Gender differences in BS have become nuanced when sexual orientation was considered. The current study also provides an overview of Korean culture that may uniquely influences individuals’ sexist attitudes, which would interest international researchers. Full article

Soft skills are increasingly viewed as essential personal resources for sustainable employability, yet their combined role with Psychological Capital (PsyCap) and proactive career behaviors among university students remains insufficiently understood. Grounded in the Job Demands–Resources model, this study examines whether soft skills predict PsyCap, employability, job crafting (seeking challenges) and active job search behavior, and whether these relationships differ between STEM and non-STEM students. A sample of 501 Italian university students (mean age = 22.7) completed validated measures of soft skills, PsyCap (resilience and optimism), employability (employability, networking, social networks), seeking challenges and active job search. Structural equation modeling revealed that soft skills significantly predicted PsyCap (β = 0.57), employability (β = 0.45), seeking challenges (β = 0.61) and active job search (β = 0.25). Multi-group analyses showed configural invariance across STEM and non-STEM groups and generally comparable relationships, with slightly stronger effects of soft skills on PsyCap and employability for non-STEM students. These findings extend prior work by testing an integrated JD–R-informed employability model that links soft skills to both psychological resources and proactive career behaviors within the same SEM and across academic domains. Overall, findings highlight soft skills as foundational resources that enhance students’ psychological functioning and proactive career behaviors, ultimately supporting readiness for work and the development of adaptive, sustainable career paths. Full article

This study analyzes the socio-cultural and behavioral determinants of FinTech adoption and access to credit among Ecuadorian SMEs. A probabilistic sample of 600 firms, operating in the services, commerce, information and communication technologies (ICT), and industry sectors, was surveyed to ensure representation of the country’s productive structure. The model integrates financial literacy, institutional trust, and perceived accessibility as key independent variables, with FinTech adoption as a digital behavioral factor and access to credit and credit conditions as the primary dependent outcomes. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), complemented by multi-group invariance tests and cluster analysis, the study evaluates seven hypotheses linking cognitive, perceptual, and digital mechanisms to financing behavior and firm performance. Results show that financial literacy and institutional trust significantly improve access to formal credit, with perceived accessibility acting as a partial mediator. FinTech adoption enhances credit conditions but remains limited among micro and small firms. Based on these findings, the study recommends strengthening financial education programs, simplifying credit procedures to reduce perceived barriers, and developing trust-building regulatory frameworks for digital finance. The results highlight the importance of socio-cultural and behavioral factors in shaping SME financing decisions and contribute to the understanding of financial inclusion dynamics in emerging economies. Full article

Background/Objective: This study aimed to adapt the Mental Fatigue Scale (MFs) to evaluate the psychometric properties in adult and adolescent athletes. Methods: A total of 491 adolescent and adult athletes (n = 491) consisting of 204 adults (men = 115; female = 90; age = 24.38 ± 3.18 year) and 287 adolescents (men = 178; female = 109; age = 14.97 ± 1.55 year) who actively participated in various sports branches voluntarily participated in this study. The MFs consists of fifteen (15) items and a single-factor structure and is a measurement tool used to measure the general mental fatigue level of athletes. Two experts used a four-point Likert scale to assess the content validity of each of the fifteen MFs items, which were aligned with the provided definition of mental fatigue in a sports context. Drawing on these findings, a confirmatory factor analysis was conducted on the survey data collected to assess the construct validity of this measure. Results: The outcomes of the confirmatory factor analysis provided acceptable support for factorial validity (χ²/sd = 1.52; p < 0.01, SRMR = 0.05, RMSEA = 0.08, GFI = 0.94, CFI = 0.89, NNFI = 0.87). Additionally, multi-group confirmatory factor analysis supported measurement invariance, indicating that the scale functions equivalently across adolescent and adult athletes. Furthermore, the analysis demonstrated favorable internal consistency (α = 0.88), confirming the reliability of the MFs. Test–retest after two weeks revealed an intra-class correlation of 0.90. Conclusions: Collectively, these results suggest that the MFs is a dependable and valid instrument that is particularly valuable for gauging overall mental fatigue in athletes. Coaches and sports scientists can use this assessment tool to evaluate athletes’ general mental fatigue effectively. Full article

Background: Rural healthcare providers encounter multifaceted barriers including geographic isolation, resource limitations, and provider shortages that impede optimal patient care delivery. The Barriers Experienced in Providing Healthcare Instrument (BTCPI) was designed to assess provider challenges; however, concerns regarding its psychometric properties necessitated comprehensive validation. The primary purpose of the study was to evaluate the structural validity of the instrument using confirmatory factor analysis with a sample of Idaho healthcare professionals. Because the model failed to meet criteria, the study identified a more parsimonious model that then underwent multi-group invariance testing. Methods: A survey consisting of a modified Barriers to Providing Optimal Healthcare instrument and a demographic questionnaire was distributed to Idaho healthcare providers across 22 clinical sites in the state. The structural validity of the modified 41-item, 9-factor instrument was assessed using confirmatory factor analysis (CFA), exploratory structural equation modeling (ESEM), and exploratory factor analysis (EFA). Multi-group invariance testing was also conducted to assess measurement equivalence across provider profession, practice setting (rural vs. urban), and years of experience. Results: A total of 373 healthcare providers completed the survey and were used for analysis. The proposed BTCPI model did not meet model fit criteria. An ESEM analysis was conducted and identified a 9-factor, 14-item model. However, due to fit concerns, an exploratory factor analysis was subsequently conducted and identified the 4-factor, 12-item (BPOC-12) that also met invariance criteria across groups. A group mean and variance differences were found between nurses and primary care providers as well as between rural and urban practitioners on several barrier factors. Conclusions: The BTCPI did not meet model fit criteria. Subsequent model refinement resulted in the BPOC-12, which had preliminary psychometric validity. Although the refined model offered a more condensed and preliminarily valid psychometric framework, future research should be done to assess this model. Future research should also collect responses from different healthcare professions to enhance its applicability. Full article

Background/Objectives: Emotional and behavioral difficulties are common during adolescence and have lasting implications for well-being. Although several psychological resources—such as self-efficacy, mindfulness, and reflective functioning—have been individually linked to better adjustment, less is known about how these strengths jointly relate to perceived stress, difficulties, and health-related quality of life (HRQoL). This study aimed to develop and test an integrative structural model capturing the interplay of these factors during early and mid-adolescence. Methods: A cross-sectional online survey was conducted among 395 adolescents (222 girls, 173 boys; aged 10–16 years) who completed self-report questionnaires assessing HRQoL (KIDSCREEN-10), emotional–behavioral difficulties (SDQ), perceived stress (PSS), self-efficacy (GSE), mindfulness (CAMM), and reflective functioning (RFQY-5). After descriptive analyses and correlation testing, the structural path model using observed variables examined how these variables were interrelated. Multi-group analyses assessed whether structural pathways were invariant across gender and age groups. Results: Mindfulness, self-efficacy, and reflective functioning were each indirectly associated with better HRQoL, mainly through lower perceived stress and fewer emotional–behavioral difficulties. Perceived stress showed a strong positive association with difficulties, and both constructs uniquely predicted lower HRQoL. The overall pattern of associations was fully consistent across age and broadly comparable across gender. Conclusions: The findings highlight the interconnected role of psychological resources, stress, and emotional–behavioral difficulties in adolescents’ well-being. However, the cross-sectional design, convenience sampling, reliance on self-report measures, and single-country sample limit the generalizability and causal interpretation of the results. The robustness of these pathways across age and their broad comparability across gender underscore their developmental relevance and suggest that programs aimed at strengthening socio-emotional competences may be meaningfully applied to support adolescents’ well-being already from early adolescence. Full article

Background. The Multidimensional Scale of Perceived Social Support (MSPSS) is widely used, although it has not been validated among early adolescents in Darjeeling, India. The aims of the study were to validate the psychometric properties of the MSPSS, and to test for measurement invariance by gender. Methods. Survey data was collected from 274 early adolescents ages 10–14 living in Darjeeling, India. Confirmatory factor analysis (CFA) evaluated 1-, 2-, and 3-factor models. Reliability (Cronbach’s α, McDonald’s ω), convergent (peer problems), and concurrent validity (prosocial behavior) were assessed. Measurement invariance by gender was tested using multi-group CFA. Results. The three-factor model of the MSPSS (Family, Friends, Significant Other) fit these data well (X²[49] = 69.3, p = 0.030; CFI = 0.98; RMSEA = 0.039; SRMR = 0.036). Measures of reliability, concurrent, and convergent validity were good with MSPSS scores correlated positively with prosocial behavior and negatively with peer problems (|r| = 0.30–0.45, p ≤ 0.001). Configural invariance by gender was not supported, indicating differences in item-level loadings. Limitations. The MSPSS is a self-report measure, and social desirability bias is a potential limitation. Conclusion. The MSPSS demonstrates good reliability and validity among early adolescents in Darjeeling, India. Given non-invariance by gender, subscale comparisons across boys and girls should be interpreted with caution. Full article

This study examined the psychometric properties of the Pre-Literacy Test, developed to measure the literacy readiness skills of children who have completed preschool education. Using a quantitative, multistage design, the study was conducted with a total of 5966 children aged 6–7 who were about to enter elementary school in the 2024–2025 academic year (N₁ = 1911; N₂ = 1644; N₃ = 2411). Exploratory Factor Analysis revealed a three-factor structure—Reading Skills, Writing Skills (Dictation), and Writing Skills (Copying)—which explained 82.38% of the total variance. Confirmatory Factor Analysis demonstrated that this structure showed an acceptable model fit (CFI = 0.997, TLI = 0.997, SRMR = 0.030, RMSEA = 0.111). The internal consistency coefficients (α = 0.891–0.962; ω = 0.912–0.983) and convergent validity values (AVE = 0.867–0.949) of the PLT were found to be high. Discriminant validity was confirmed according to the Fornell–Larcker criterion, and measurement invariance across gender was supported through Multigroup Confirmatory Factor Analysis. Item analyses indicated that most test items were of moderate difficulty (mean difficulty = 0.409) and high discrimination (mean discrimination = 0.516). In conclusion, the PLT was determined to be a psychometrically robust, valid, and reliable instrument for assessing basic literacy skills prior to elementary school entry. These findings suggest that the test can be confidently used in early literacy research and school readiness assessments. Full article