Background/Objectives: Traditional models like ordinary least squares (OLS) struggle to capture non-linear relationships in children’s subjective well-being (SWB), which is associated with physical activity. This study evaluated machine learning (ML) for predicting SWB, focusing on sports participation, and explored theoretical prediction limits using a global dataset. It addresses a gap in understanding complex patterns across diverse cultural contexts. Methods: We analyzed 128,184 records from the ISCWeB survey (ages 6–14, 35 countries), with self-reported data on sports frequency, emotional states, and family support. To ensure cross-country generalizability, we used GroupKFold CV (grouped by country) and leave-one-country-out (LOCO) validation, yielding mean R² = 0.45 ± 0.05, confirming robustness beyond cultural patterns, SHAP for interpretability, and bootstrapping for error estimation. No pre-registration was required for this secondary analysis. Results: XGBoost and LightGBM outperformed OLS, achieving R² up to 0.504 in restricted datasets (sensitivity excluding affective leakage: R² = 0.35), with sports-related variables (e.g., exercise frequency) associated positively with SWB predictions (SHAP values: +0.15–0.25; incremental ΔR² = 0.06 over demographics/family/school base). Using test–retest reliability from literature (r = 0.74), the estimated irreducible RMSE reached 0.941; XGBoost achieved RMSE = 1.323, approaching the predictability bound with 68.1% of explainable variance captured (after noise adjustment). Partial dependence plots showed linear associations with exercise without satiation and slight age decline. Conclusions: ML improves SWB prediction in children, highlighting associations with sports participation, and approaches predictable variance bounds. These findings suggest potential for data-driven tools to identify patterns, such as through physical literacy pathways, informing physical activity interventions. However, longitudinal studies are needed to explore causality and address cultural biases in self-reports.

La salud se entiende como una compleja relación entre diversas variables, además de los estilos de vida, y calidad de vida (CV). Es así como la condición física (CF) y actividad física (AF), cobran real importancia en los estudiantes universitarios, población particular, que se encuentra vulnerable a adquirir estilos de vida poco saludables y disminuir su CV, afectando su salud. Objetivo: determinar la relación entre condición física, actividad física y la calidad de vida en estudiantes universitarios chilenos. Método: estudio cuantitativo observacional con 131 estudiantes universitarios. Se evaluaron variables como antropometría, CF, AF y CV mediante pruebas y cuestionarios estandarizados. Resultados: se encontraron correlaciones significativas entre el IMC y la fuerza, así como asociaciones negativas con la capacidad aeróbica. La capacidad aeróbica se correlacionó positivamente con la salud psicológica y la percepción de salud y CV. Además, niveles más altos de AF se relacionaron positivamente con una mejor percepción de la salud y CV. Discusión: los hallazgos sugieren la importancia de la CF y la AF en la salud, bienestar y CV de estudiantes universitarios chilenos. La promoción de estilos de vida saludables podría tener un impacto positivo en la calidad de vida. Conclusiones: en estudiantes universitarios se identificaron relaciones significativas entre IMC y diversos aspectos de la CF, así como correlaciones entre CF y CV, y AF y CV. Estos hallazgos respaldan la promoción de estilos de vida saludables y subrayan la importancia de intervenciones integrales para mejorar la CF y CV de los estudiantes universitarios en Chile. Palabras claves: Condición Física, Actividad Física, Ejercicio, Calidad de Vida, Estudiantes. Health is understood as a complex relationship between several variables, in addition to lifestyle and quality of life (QoL). Thus, physical condition (FC) and physical activity (PA) become important in university students, a particular population that is vulnerable to acquire unhealthy lifestyles and reduce their QoL, affecting their health. Aim: To determine the relationship between physical fitness, physical activity and quality of life in Chilean university students. Methods: Quantitative observational study of 131 university students. Variables such as anthropometry, FC, PA and QOL were assessed using standardized tests and questionnaires. Results: Significant correlations were found between BMI and strength and negative associations with aerobic capacity. Aerobic capacity was positively associated with psychological health, health perception and quality of life. In addition, higher levels of PA were positively associated with better perceived health and QoL. Discussion: The results suggest the importance of FC and PA in the health, well-being and QoL of Chilean university students. Promoting healthy lifestyles could have a positive impact on QoL. Conclusions: Significant relationships between BMI and different aspects of FC, as well as correlations between FC and QoL, and PA and QoL, were found in Chilean university students. These findings support the promotion of healthy lifestyles and highlight the importance of comprehensive interventions to improve FC and QoL among university students in Chile. Key words: Physical Fitness, Physical Activity, Exercise, Quality of Life, Students.

Introduction: The fitness industry continues adapting to customers' unique characteristics and needs across different regions. Studying fitness trends enables industry professionals to make informed decisions, seize new opportunities, and foster a culture of health and well-being. Objective: This observational and cross-sectional study aimed to determine the most relevant fitness trends in Ibero-America for the first time and examine any differences between global fitness trends for 2025. Methodology: A national online survey was conducted in two countries of the Iberian Peninsula (Spain and Portugal) and three countries in the Americas (Mexico, Brazil, and Chile), following the methodology used by the American College of Sports Medicine (ACSM) since 2006. An online questionnaire was sent to fitness professionals to assess the relevance of over 50 fitness trends. Discussion: A total of 5,262 responses were collected across the 5 national surveys, with an overall mean response rate of 13.44%. Some of the most relevant fitness trends in Ibero-America for 2025 include: exercise for weight loss, personal training, employing certified exercise professionals, fitness programs for older adults, and traditional strength training. Conclusions: The present findings highlight the similarities in the results of the Ibero-American surveys and their significant differences in global fitness trends. The results can help fitness professionals plan services and make strategic decisions based on the priorities of each Ibero-American region.

Physical inactivity remains a major modifiable risk factor for non-communicable diseases and continues to exhibit marked socioeconomic and gender disparities in Latin America. Identifying robust and interpretable predictors of inactivity in nationally representative datasets is essential for informing public health strategies. This study compared a survey-weighted logistic regression model and an explainable machine learning approach (XGBoost) to predict physical inactivity among Chilean adults using data from the 2024 National Physical Activity and Sports Survey (ENAFyD; n = 5248). Models were evaluated on a stratified held-out test set (n = 1050) using weighted and unweighted area under the ROC curve (AUC), Brier scores, and calibration curves. Survey-weighted logistic regression achieved a weighted AUC of 0.801, while XGBoost achieved 0.797, demonstrating comparable discrimination. XGBoost showed marginally lower Brier scores, indicating slightly improved probabilistic calibration. Low socioeconomic status, female sex, lower monthly physical activity expenditure, limited facility access, and lower engagement with digital resources were consistently associated with higher inactivity risk. SHAP-style contribution analysis provided additional insight into feature-level influence within the machine learning framework. Overall, both approaches demonstrated similar predictive capacity, supporting the complementary use of classical regression and explainable machine learning for population-level physical inactivity research.

Background/Objectives: University students exhibit high levels of sedentary behavior and low adherence to physical activity recommendations, and immersive virtual reality (IVR) represents an innovative strategy to increase physical activity participation. The aim of this study was to evaluate the effect of a physical activity intervention using IVR on anthropometric variables, physical fitness, and blood pressure in university students. Methods: A randomized controlled trial was conducted with 60 participants (30 control, 30 intervention) over 12 weeks. The intervention group performed three weekly exercise sessions using IVR, while the control group maintained their usual activity. BMI, waist and hip circumferences, handgrip strength, cardiorespiratory fitness, and blood pressure were assessed. Baseline characteristics between groups were compared using Student’s t-test. The effect of the intervention was analyzed using analysis of covariance adjusted for baseline values. Sensitivity analyses were performed to assess between-group changes, and subgroup analyses were conducted to determine the impact of sex. Results: The intervention produced significant improvements in cardiorespiratory fitness (VO₂ and the 20 m shuttle run test); no significant changes were observed in anthropometric variables, strength, or blood pressure. Conclusions: A 12-week intervention with immersive virtual reality-based physical training improves cardiorespiratory fitness in university students, representing a promising tool for health promotion in this population.

Introduction: Sports motivation plays a key role in long-term adherence and athletes' commitment. In the context of rugby, intrinsic and extrinsic motivation may vary depending on individual factors such as occupational status. Objective: To examine the relationship between motivation dimensions and sports adherence in Chilean rugby players, considering occupational status as a moderating factor. Methods: A cross-sectional study was conducted with 280 rugby players from 12 regions of Chile. The Sport Motivation Scale (SMS-28) was used to evaluate intrinsic motivation, extrinsic motivation, and amotivation. Data were analyzed using descriptive statistics, ANOVA, and Pearson correlations. Results: Intrinsic motivation for experiencing sensations had the highest average score, followed by intrinsic motivation for achieving things. Identified regulation was significantly higher among students and workers compared to unemployed participants (p = 0.050). Introjected regulation showed significant differences across occupational status (p = 0.001), with higher levels among workers. Amotivation was negatively associated with sports participation, although no significant differences were observed between occupational groups (p = 0.419). Conclusions: The findings highlight the importance of fostering intrinsic motivation to sustain sports participation in rugby players. Additionally, strengthening identified regulation may improve commitment, particularly among unemployed players. Reducing amotivation is crucial to prevent sports dropout.