Search Results (738)

Introduction: Medical care for transgender minors is understudied, largely because these forms of care are relatively recent. The primary objective of this work was to describe the cohort of transgender adolescents who initiated follow-up at the Strasbourg University Hospital before the age of 18, whether or not they began hormone therapy prior to reaching adulthood. Method: This was an observational, retrospective, single-center, descriptive study conducted among adolescents who had attended at least one consultation in our center before the age of 18 between January 2017 and March 2024. Results: Our population consisted of 115 patients predominantly made up of transmasculine (AFAB) adolescents (68%). Compared with the general population, we observed significantly higher rates of psychiatric co-occurrences, autism spectrum disorder (ASD), and attention-deficit/hyperactivity disorder (ADHD). Only 46.1% initiated gender-affirming hormone therapy (GAHT) in our cohort, and just 34.8% before age 18. A total of 6% of adolescents received puberty blockers as monotherapy. The mean age at GAHT initiation was 16.99 years. Transition pathways appear to differ according to the adolescent’s type of schooling. The rate of retransition/treatment interruption in our sample ranged from 0% to 6.1%, depending on the criteria applied. We did not identify any adolescent who retransitioned to their sex assigned at birth after starting GAHT by the end of the data collection. Discussion: The high prevalence of psychiatric co-occurrences raises important questions regarding how to improve care for these adolescents. The predominance of AFAB adolescents similarly prompts reflection on the barriers that transfeminine adolescents may face when seeking to transition before adulthood. In addition, the substantial number of adolescents presenting with ASD or ADHD underscores the need for particular vigilance regarding their specific needs and overall well-being. Finally, the variability in retransition rates depending on the criteria applied highlights the absence of a consensual definition, which limits the comparability and validity of existing studies. Conclusions: Long-term prospective studies are needed to objectively demonstrate the effectiveness of current transition pathways. Academic research in this field should be strengthened, along with the development of larger prospective datasets, to improve the overall health of this population. Full article

Accurate prediction of loan defaults is essential for financial institutions seeking to minimize credit losses and maintain portfolio stability. In the vehicle financing segment of emerging markets, real-world datasets frequently exhibit extreme class imbalance ratios that far exceed those encountered in standard benchmark corpora, posing severe challenges for conventional machine learning pipelines. This study introduces a gradient boosting framework integrating Weight of Evidence (WoE) transformation, Bayesian hyperparameter optimization, and three complementary classifiers—Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost)—to predict vehicle loan default risk. The methodology is evaluated on a large-scale, fully anonymized Turkish vehicle loan dataset ($N=207,572$) with an extreme imbalance ratio of 1:1133 (183 defaults versus 207,389 non-defaults). A strict three-way data partition (60% training, 20% validation, 20% test) is adopted to ensure leakage-free model selection and unbiased performance estimation. A multi-stage experimental pipeline is developed encompassing: (i) statistical feature selection via Mann–Whitney U and chi-square tests with adaptive thresholding, (ii) a comparative analysis of seven resampling strategies including Synthetic Minority Oversampling Technique (SMOTE) variants, Adaptive Synthetic Sampling (ADASYN), and focal loss weighting, (iii) a greedy forward selection ensemble procedure for heterogeneous model fusion, and (iv) a systematic training-set size sensitivity analysis across eight majority undersampling ratios. Under the leakage-free evaluation protocol, the highest-AUC individual model (LightGBM with SMOTE-ENN) achieves an Area Under the Curve (AUC) Receiver Operating Characteristic (ROC) of 0.710 (95% bootstrap CI: 0.614–0.798), while CatBoost with cost-sensitive weighting exhibits superior operational metrics (KS $=0.389$, PR-AUC $=0.011$). The greedy ensemble procedure exhibits high selection instability with only 37 validation-set positives, providing a methodological finding on the minimum sample requirements for reliable ensemble construction under extreme scarcity. Ablation results confirm that WoE encoding contributes 3.1 percentage points to the overall AUC gain. Tree SHAP-based interpretability analysis identifies the financing-to-age ratio, WoE-encoded occupation group, and log financing amount as the primary predictive drivers, with cross-model stability confirmed via Spearman rank correlation. A decision support analysis provides precision–recall curves, a Brier score of 0.0082, reliability diagrams, and threshold-dependent performance at operationally plausible review rates. Fairness evaluation across gender and marital status subgroups demonstrates that threshold-dependent metrics such as Disparate Impact Ratio and Equalized Odds Gap are inherently compromised under extreme minority scarcity, whereas rank-based subgroup AUC analysis with bootstrap 95% confidence intervals preserves meaningful discriminative assessment. These findings provide an empirically validated framework for credit default prediction in highly imbalanced and data-scarce financial environments. Full article

Background: Diversity in academia promotes research that can reduces health disparities and addresses equity issues for marginalized populations. This study aims to examine the effect of visible minority status on academic achievements in cancer physicians and scientists. Methods: Faculty at the tertiary cancer center in Calgary, Alberta, Canada, completed a survey in 2023 to evaluate demographics, academic rank, leadership positions, number of trainees mentored, number of publications, and amount of grant funding. Chi-square tests and regression analyses examined the impact of race and ethnicity on these academic achievements. Results: The survey was completed by 74 faculty members (47% male, 43% female, 9% gender fluid or providing no answer) with a response rate of 26%. Seven percent were Black or Latin American, 18% East Asian or Southeast Asian, 19% West or South Asian, 39% Caucasian, 6% mixed race, and 11% not providing an answer. Visible minorities were underrepresented in the full professor rank (19%) compared to non-visible minorities (38%) and were overrepresented in assistant/associate professors (28% and 53%, respectively), with 41% of non-visible minorities having the title of assistant professor and 21% as associate professor (p = 0.02). Visible minorities were less likely to have both parents college-educated (OR 0.30, 95% CI 0.09–0.92, p = 0.042) and also less likely to have been raised in a home with household income above $100,000 (OR 0.26, 95% CI 0.07–0.90, p = 0.040). Discussion: Visible minorities are underrepresented in the full professor academic rank. Larger studies are needed to evaluate whether race and ethnicity significantly impact achievements in oncology academics. Full article

Background/Objectives: Growing concern about narcissistic traits in younger generations and their effects on empathy, communication, and mental health underscores the need for focused research on medical students as future healthcare professionals. Medical training carries a substantial psychological burden that can compromise students’ well-being, professional development, and the future quality of patient care. Personality traits, including grandiose and vulnerable narcissistic dimensions, may shape susceptibility to such psychological distress. Therefore, this study aimed to examine narcissistic traits and their associations with psychological distress among Croatian medical students across study years and trait levels. Methods: In this cross-sectional study, 413 medical students from the University of Split completed self-administered questionnaires during mandatory classes. Narcissistic traits were assessed using the Pathological Narcissism Inventory (PNI) and psychological distress was measured with the Brief Symptom Inventory (BSI). High pathological narcissistic traits were operationally defined as scores within the highest quartile. Statistical analyses included correlation, comparative, and regression analyses. Results: Overall, pathological narcissistic traits were expressed at low to moderate levels and did not differ across academic years. High narcissistic traits were identified in 35% of students, with 15% exhibiting elevated levels of both grandiose and vulnerable dimensions, suggesting an overlap between the two dimensions. Gender differences emerged across both narcissistic dimensions, with women scoring higher on vulnerable and men scoring higher on grandiose narcissism. One-quarter of students met the criteria for clinically significant psychological distress, which was more prevalent in the earlier years of study. High levels of pathological narcissistic traits, particularly vulnerable traits, were significantly associated with clinically significant distress and elevated symptoms across nearly all BSI domains, most notably interpersonal sensitivity and paranoid ideation. Despite this burden, only a minority of distressed students reported seeking psychological help. Conclusions: Elevated pathological narcissistic traits are significantly associated with psychological distress in medical students. The high prevalence of distress, combined with low help-seeking rates, underscores the need for early identification strategies and structured mental health support within medical education. Addressing personality-related vulnerability factors may improve student well-being, enhance professional development, and, ultimately, elevate the quality of healthcare delivery. Full article

While the “model minority” stereotype has been extensively studied in relation to Asian Americans, there is limited research that distinguishes these experiences by specific national origins. This paper explores the stereotypes faced by India-born scientists and engineers in the United States. They represent a significant segment of the foreign-born workforce in the U.S., accounting for one-third of this population and comprising the largest group of H-1B visa holders. Through qualitative data gathered from 40 India-born scientists and engineers employed in U.S. high-tech firms, this study examines how these individuals perceive and navigate the cultural stereotypes that shape their professional and personal lives. The paper delves into the intersections of ethnicity, nationality, and gender in shaping their experiences, challenging the characterization of Indians as “model immigrants”. Full article

Transgender individuals face unique challenges in vascular health due to the complex interactions between gender identity, psychosocial determinants of health, and medical interventions such as gender-affirming hormone therapy (GAHT). Growing evidence indicates that transgender populations may exhibit distinct patterns of vascular disease risk compared with cisgender individuals; however, available data remain limited and heterogeneous. A narrative review of the literature was conducted using major biomedical databases to identify studies examining the vascular and cardiovascular effects of gender-affirming hormone therapy in transgender individuals. This review provides a comprehensive overview of vascular health in transgender people, with particular attention to both venous and arterial disease. We summarize current epidemiological evidence on vascular outcomes and explore biological mechanisms through which exogenous sex hormones, including estrogens, anti-androgens, and testosterone, may influence endothelial function, vascular remodeling, inflammation, and coagulation pathways. Specific emphasis is placed on venous disorders, such as thromboembolic disease and chronic venous disease (CVD), as well as arterial conditions, including chronic peripheral arterial disease (PAD). In addition, we discuss the contribution of traditional vascular risk factors, minority stress, disparities in healthcare access, and social determinants of health in shaping vascular risk profiles. Clinical implications for vascular risk assessment, prevention strategies, and long-term monitoring in transgender individuals receiving GAHT are addressed. Finally, key knowledge gaps and priorities for future research are identified, underscoring the need for robust, longitudinal studies to support personalized and evidence-based vascular care in transgender populations. Full article

Generative artificial intelligence (GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and social sciences (HSS), where learning outcomes are commonly expressed through written and interpretive forms that align closely with GenAI’s capabilities. Yet, systematic evidence on the educational impacts of GenAI on HSS students remains limited. Addressing this gap, this study draws on a large-scale survey of HSS students in China to examine its role in academic development. Guided by relevant learning theories, this study focuses on four dimensions: patterns of use, effects on learning processes and academic performance, challenges associated with GenAI use, and preferred approaches to curricular integration. We found that more than half perceived enhanced learning motivation, independent thinking and creativity, although a substantial minority reported little change or even decline. Comparatively, a notably larger majority reported academic performance gains, although these gains may partly reflect limitations in conventional assessment practices. The study identifies variations in perceived learning and performance improvements among students with differing durations of GenAI experience, along with observable disciplinary differences and modest gender differences. While an overwhelming majority valued the importance of ethical considerations, only slightly more than half were satisfied with privacy protection. Limited accuracy and overreliance emerged as the most pressing concerns reported by students. Students favored partial or optional curricular integration supported by practice-oriented training, and widely recognized GenAI’s significance for their future professional development. Grounded in student perspectives, this study offers evidence-based recommendations for the responsible and pedagogically meaningful integration of GenAI. Full article

This study examines how individual political predispositions and national mobilisation contexts jointly structure protest participation in contemporary Europe across the pre-pandemic, pandemic and post-pandemic periods. Using data from Rounds 9, 10 and 11 of the European Social Survey (2018–2023), the analytical sample includes 106,106 respondents from 33 countries. Descriptively, protest participation remains a minority behaviour, yet displays pronounced cross-national heterogeneity, with participation rates ranging from below 3% in several Central and Eastern European countries to nearly 20% in the most mobilised contexts and remains remarkably stable across rounds at approximately 8.5%. Building on resource mobilisation theory, political process approaches and New Social Movements perspectives, the analysis conceptualises protest participation not as an isolated behavioural act but as the outcome of interactions between individual resources, evaluative orientations toward democratic institutions and broader mobilisation environments. Logistic regression models, country fixed-effects specifications and multilevel models with random intercepts are used to assess these relationships. At the individual level, political engagement emerges as the strongest predictor of participation: higher political interest is associated with substantially higher protest propensity, while ideological self-placement indicates lower participation among respondents positioned further to the right. Younger age and higher education also increase participation. Lower satisfaction with democracy and stronger perceptions of inequality are consistently associated with protest behaviour, supporting grievance-based interpretations linked to democratic evaluations rather than material deprivation alone. Country fixed-effects and multilevel models confirm that these individual-level associations are robust within countries, while significant between-country variation persists (random-intercept SD = 0.554), indicating that national mobilisation environments shape baseline levels of protest participation. Multilevel results further reveal that protest participation was significantly lower during the pandemic period (Round 10) relative to the pre-pandemic baseline, with only partial recovery in the post-pandemic period. A cross-round comparison demonstrates that the core individual-level associations are stable across all three periods, indicating that these relationships reflect durable structural patterns rather than dynamics specific to any particular mobilisation cycle. Beyond this overall stability, the analysis identifies two theoretically informative exceptions: subjective financial difficulty is significant only in the pre-pandemic period and gender differences in protest participation attenuate over time—patterns consistent with broader shifts in protest repertoires during and after the pandemic. These findings make three contributions to the comparative literature on contentious politics. First, by extending the analysis across three ESS rounds, the study demonstrates the temporal robustness of individual-level determinants of protest—an empirical question rarely addressed in the existing literature. Second, the multilevel design with round fixed effects allows for direct estimation of pandemic-related suppression and post-pandemic recovery in protest activity at the aggregate level. Third, the cross-national scope and temporally structured comparison provide new evidence on how individual political predispositions interact with shifting mobilisation environments across a period of exceptional socio-political strain in Europe. Full article

Thermal comfort in operating rooms is critical for staff performance and safety, but conflicting requirements among professional groups create complex challenges. In a real operating room with a unidirectional airflow system, air velocity and temperature were measured, and predicted thermal sensation as well as the proportion of dissatisfied staff were calculated according to international standards. Analyses included surgeons, technical assistants, and anesthesiologists, considering clothing insulation, task-specific activity, gender, body mass index, and the use of lead aprons of different weights. Gender, body mass index, and temperature strongly influenced thermal comfort, whereas variation in air velocity had only minor effects. Thermal comfort targets diverged markedly between professional groups. Under identical conditions in our operating room, up to 75% of male surgeons wearing lead aprons experienced pronounced heat stress, whereas approximately 22% of female anesthesiologists experienced predominantly cold discomfort. Female surgeons would require temperatures as low as 16 °C to achieve thermal comfort, while nearly 50% of male surgeons perceived even this temperature as uncomfortably warm. Removing lead aprons reduced heat stress in surgeons but increased cold stress in anesthesiologists. Higher body-mass index improved heat dissipation in surgeons but aggravated cold stress in anesthesiologists. These findings demonstrate that uniform temperature settings cannot ensure thermal comfort for all professional groups. Practical implications include the need for role-specific strategies, such as targeted personal cooling or warming measures and differentiated clothing systems, to improve working conditions and maintain patient safety in operating rooms. Full article

This scoping review synthesises the current literature to explore the related concepts of victim blaming and bystander intervention in the context of image-based sexual abuse. Image-based sexual abuse refers to the creation, taking and distribution of non-consensual intimate images, including the threat to share or distribute. The databases Web of Science, ASSIA, ProQuest Dissertation & Theses and Scopus were searched in August 2024, with an updated search being conducted in December 2025. A supplementary search was conducted in Google Scholar, along with a hand search of four key journals within the topic area. The search focused on five geographical locations that share a common cultural background (UK, USA, Canada, New Zealand, and Australia). A total of 31 studies and reviews were included. The main findings were that: (a) there is limited research in relation to bystander intervention in the context of image-based sexual abuse; (b) there are no studies that examine the relationship between victim blaming and bystander intervention; (c) there appears to be a gendered dimension in relation to the phenomena (victim blaming and bystander intervention), which is reflected in the literature around image-based sexual abuse; (d) accountability and victim blaming are increased when a victim–survivor has created the images/videos themselves; (e) research within this area neglects the experiences of diverse communities, specifically sexual and gender minority people; and (f) there appears to be a disregard to capture the experiences of men who are victim–survivors, irrespective of sexual identity. Full article

Human papillomavirus (HPV) is one of the most widespread sexually transmitted infections globally, whose persistent infection plays a major role in causing cervical cancer. Vaccination is therefore a key prevention strategy. Using a gender-stratified dynamic transmission model tailored to a Tunisian case, we investigate the impact of bivalent HPV vaccination. The proposed model accounts for partial cross-immunity and captures both direct and indirect effects of female-only vaccination. We derive the basic reproduction number and the corresponding herd immunity threshold, and a global sensitivity analysis shows that vaccine coverage, efficacy, and cross-protection are strong drivers of transmission reduction. Their combined effects on disease spread are quantified by varying these parameters across biologically relevant ranges. An optimal control problem was formulated and analyzed using Pontryagin’s Maximum Principle to minimize persistent infections and cancer cases while limiting vaccination effort. Three vaccination scenarios are compared: an ideal case with full vaccine availability and two resource-constrained cases with respective maximum coverage rates of $100\%$ and $80\%$. The numerical simulations revealed that the optimal strategy under unconstrained conditions can achieve significant suppression of infection, persistence, and cancer. Under constrained effort, the optimal control still achieves substantial reductions in disease burden, with minor differences in dynamics and speed of immunity buildup. Our results highlight the effectiveness of female-only HPV vaccination in providing both direct and indirect protection. They also emphasize the importance of sustained coverage in constrained settings. Full article

Internet addiction and problem gambling represent significant public health issues among young people. A link between the two has been noted, but few studies have comprehensively examined their comorbidity, including lifestyle factors, among Japanese university students. This study clarified the prevalence of co-occurrence of Internet addiction and problem gambling among such students, identified associated factors, and examined the relationship between these conditions and lifestyle habits. A sample of 5083 Japanese university students completed the Internet Addiction Test (IAT) and South Oaks Gambling Screen (SOGS). Logistic regression was used to examine associations with demographic characteristics and lifestyle habits (sleep, physical activity, and dietary habits). Internet addiction was significantly associated with problem gambling, and the risk of problem gambling increased with IAT scores. Internet addiction was associated with being male, being in lower academic years, poor sleep quality, insufficient physical activity, and unhealthy eating. Problem gambling was associated with IAT scores, male gender, and family history of gambling. The association between lifestyle habits and problem gambling was minor. These results suggest that Internet addiction and problem gambling are not independent issues but may share a common psychological and neural basis. These findings suggest the need for a comprehensive approach in prevention and intervention. Full article

Background: Sleep apnea is identified and treated less frequently among racial and ethnic minorities. Objective: The purpose of this systematic review was to examine disparities among racial and ethnic minorities and to understand the reasons for poor sleep health. Methods: The authors conducted a literature search using PubMed and Cochrane Library databases, last accessed in September 2025, using regular and MeSH keywords. A total of 123 articles were identified. PRISMA guidelines were followed, the PICO framework was applied, and the inclusion criteria were based on studies conducted in the past 10 years. After quality assessment, 18 studies were included for in-depth analysis. Results: The 18 studies included meta-analyses and observational cohort studies. In total, 51,489 patients were represented. Studies revealed that sleep apnea is underdiagnosed and undertreated in ethnic minority populations. Resident location, gender, economic status, and marital status also play an important role. One study noted clinically insignificant differences in positive airway pressure requirements between black and white populations. Nocturnal hypertension and increased left ventricle size are also observed in untreated sleep apnea. Given the heterogenous nature of the studies, quality risk assessment was not possible, which is a limitation of this study. Conclusions: Sleep apnea is underdiagnosed and undertreated among ethnic minorities. Factors such as ancestry, comorbidities, social determinants, geography, and healthcare access drive global inequities. Further sleep apnea phenotyping may be of value in planning treatment strategies. Full article

This study examines the validity of the Spanish version of the Scientific Epistemic Beliefs (SEB) Questionnaire among university students in northeastern Mexico, considering multiple sources of evidence. The SEB measures four dimensions of epistemic beliefs: Source, Certainty, Development, and Justification. Data from pilot (n = 150) and main (n = 791) samples were analyzed using Exploratory and Confirmatory Factor Analyses (EFA, CFA), Item Response Theory (IRT), and Differential Item Functioning (DIF). The results provided evidence consistent with a four-factor model, with adequate internal consistency (α = 0.85) and acceptable-to-good fit indices (CFI = 0.944, TLI = 0.936, RMSEA = 0.067, SRMR = 0.071) for a 22-item scale. IRT analyses indicated strong item discrimination, with Source and Certainty covering a broad range of the latent trait, while Development and Justification were more informative at lower to moderate levels. DIF analyses indicated negligible differences in item functioning by gender and academic semester, with minor DIF detected across faculties. Non-parametric analyses identified statistically significant but small differences, with females scoring slightly higher across all dimensions and variations also observed across academic semesters and faculties. Descriptive comparisons with published international data provide contextual evidence within a broader cross-cultural framework. Full article

Obesity is ranked as one of the biggest health challenges facing humanity today. Globally, the number of obese people has almost tripled since 1975, and this lifestyle disease currently affects hundreds of millions of adults who suffer from major health problems due to it, such as heart disease, type 2 diabetes and some cancers, that weigh heavily on the global health systems, In order to keep high standards for methods, anthropometric variables, i.e., Height and Weight have been intentionally excluded from the features, because labels for obesity classes are based on these measurements; thus, including them would introduce target leakage. All models were individually tuned with Optuna (50 trials, TPE sampler), and the class imbalance was managed by the synthetic minority over-sampling technique (SMOTE), which was done only in training folds. The models were evaluated by stratified five-fold cross-validation, with the macro-averaged F1-score being used as the main metric for evaluation. The best model was the fine-tuned XGBoost, which gave a test macro F1-score value of 0.872 and a macro-AUC of 0.977. The model was higher performing than others such as Random Forest (F1 = 0.869), MLP (F1 = 0.777), and Logistic Regression (F1 = 0.605). This means that behavioral and lifestyle variables may have a very strong and sufficient signal to identify obesity status, even when there are no direct anthropometric measurements available. However, it is worth noting that results here represent only performance on a single public benchmark dataset, so they cannot be taken as proof that the model would do well in real-world clinical settings. With the advent of ML methods for obesity prediction, rigorous, leakage-free evaluation becomes indispensable. Apart from external validation of the clinical models on independent datasets, the use of interpretability tools such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) for understanding decision-making, as well as sex and gender subgroup analyses for evaluating fairness and equity, should also be pursued in the future. This study highlights the importance of rigorous, leakage-free evaluation in machine learning-based obesity research. Future work should focus on external validation using independent clinical cohorts, the integration of interpretability techniques such as SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME), and subgroup analyses by sex and gender to assess model fairness and clinical equity. Full article