Environmental degradation and climate change are of paramount concern and require urgent action. Physical education holds an important role in addressing environmental issues and contributing to environmental sustainability. The present study assesses the effectiveness of an intervention program to cultivate environmental awareness in fifth-grade children through physical activities and games in physical education. The participants were 74 children (39 girls and 35 boys) divided into two groups, the experimental and control group. Participants completed a scale assessing their knowledge of environmental issues, which had been shown by previous research to be valid and reliable for this population. The experimental procedure of the study included three stages: completing the questionnaire before the implementation of the intervention and at the end, as well as a retention measurement after four months. The results indicated that the students of the experimental group maintained a significantly higher level of knowledge of fundamental environmental concepts at the end of the program compared to their counterparts in the control group (p < 0.05). In addition, children of the experimental group seemed to retain their knowledge as a result of the intervention program (p > 0.05). The findings suggest that interventions using physical education can serve as a meaningful strategy for promoting environmental care and sustainability and turn young tourists into tomorrow’s responsible consumers and travelers who respect and protect nature. Finally, such a process could potentially aim to increase environmental awareness as a learning experience through the provision of physical activity and recreation.

Emotional intelligence is a key determinant of healthy aging, contributing to psychological resilience and quality of life. Physical activity has been recognized as a promising means to enhance emotional functioning, especially when it involves social interaction. This study examined the effect of an 18-week structured physical exercise program on emotional intelligence in older adults, as measured by the trait emotional intelligence subscale of the TEIQue-SF. A total of 86 participants were divided into three groups: individual exercise ( n = 31), collaborative exercise ( n = 32), and a control group ( n = 23). Pre- and post-intervention assessments were conducted using the TEIQue-SF questionnaire. Correlation analysis indicated strong relationships between well-being and other emotional intelligence dimensions such as self-control, emotionality, and sociability, both before and after the program. These relations were strengthened following the intervention. Repeated-measures analysis revealed a significant interaction between intervention type and time, in well-being scores. Notably, the collaborative exercise group showed the most pronounced improvement in well-being post-intervention. The findings suggest that social aspects of physical activity may amplify its emotional benefits, particularly in enhancing trait well-being. Such interventions may serve as a valuable tool in promoting emotional health and supporting successful aging.

Background: Well-being in the elderly is shaped by complex emotional and social factors. Early identification of individuals at risk for reduced well-being may support timely preventive or supportive interventions. This study examined whether emotional intelligence indicators collected at baseline can predict well-being status 5 months later using explainable machine learning models. Methods: A cohort of elderly participants aged 60 to 89 years completed emotional intelligence measures at baseline, and well-being was assessed 5 months later using the POMS questionnaire. Four machine learning algorithms, Logistic Regression (LR), Support Vector Machines (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost), were developed using 5-fold stratified cross-validation. Model performance was evaluated through accuracy, precision, recall, F1-score, ROC AUC, and normalized confusion matrices. SHapley Additive exPlanations (SHAP) were applied to interpret the contribution and directionality of each predictor. Results: XGBoost achieved the highest predictive performance (accuracy = 0.789; F1 = 0.778) and demonstrated balanced classification across well-being categories. SVM also performed robustly (accuracy = 0.760), while LR showed reduced sensitivity for detecting those with poorer well-being. SHAP analysis identified self-control, emotionality, sociability, self-motivation, and well-being components as the most influential predictors. Lower emotionality, higher sociability, and higher self-control scores were linked to a greater probability of favorable well-being outcomes. Conclusions: The findings demonstrate the feasibility of using explainable machine learning models to predict 5-month well-being status within this sample of older adults using emotional intelligence indicators. XGBoost provided the strongest and most balanced performance, while SHAP analysis clarified how specific emotional intelligence dimensions influenced predictions. These findings suggest that interpretable machine learning approaches may support future efforts toward early recognition of older adults who may be at risk for reduced well-being and guide personalized intervention strategies.

Background/Objectives: Quality of life is conceptualized as a multidimensional construct encompassing subjective well-being, health, and social functioning. Evidence suggests that engagement in physical activity contributes to higher quality of life scores among older adults, indicating that structured exercise programs can positively influence both physical and psychological domains in this population. The present study examined the impact of an 18-week structured physical exercise program on the quality of life of older adults, assessed through the World Health Organization Quality of Life-BREF (WHOQOL-BREF) instrument, which consists of four domains: physical health, psychological, social relationships and environment. A total of 86 participants were allocated to three groups: individual exercise (n = 31), collaborative exercise (n = 32), and a control group (n = 23). Quality of life was evaluated before and after the intervention using the WHOQOL-BREF. Results: Correlation analysis indicated strong relationships among the WHOQOL-BREF domains, both before and after the program. Repeated-measures analysis revealed no significant Group × Time interaction effects for any WHOQOL-BREF domain. A significant main effect of Time was observed for the Environment domain, indicating a small overall decrease across all groups during the study period. Conclusions: The structured exercise protocol did not lead to greater changes in quality of life compared to the control condition. Perceived environmental quality of life showed a small overall decrease over time across participants.

Background: Hatha yoga has gained increasing popularity worldwide and has been associated with benefits for mental health and short-term emotional functioning. Objective: The present study examined pre–post changes in mood states following a single Hatha yoga session in adult women participating in community-based exercise programs. Methods: A total of 253 adult women participated in the study. Participants completed the Profile of Mood States (POMS) questionnaire immediately before and after a single 60 min Hatha yoga session. The questionnaire assesses anxiety–tension, depression, anger, fatigue, confusion, and vigor. Repeated measures ANOVA was used to examine the changes in mood states and the potential differences between the age groups. Results: Significant improvements in mood states were observed following the session. Anxiety–tension, depression, anger, fatigue, and confusion decreased, while vigor increased. No significant time × age group interaction was observed for most mood variables. However, a significant interaction was found for vigor, indicating that women aged 41 and older showed a greater increase following the session. Conclusions: Participation in a single Hatha yoga session was associated with short-term changes in mood states among adult women, suggesting that yoga may represent a potentially beneficial community-based activity for supporting short-term mood regulation.

Assessing body image efficiently requires brief, psychometrically sound instruments. This study evaluated the 15-item short-form Appearance Scales of the Multidimensional Body-Self Relations Questionnaire (MBSRQ-AS15) to determine its structural validity, internal consistency, and cross-sex measurement invariance. A community sample of 1776 Greek adults (899 men, 877 women; mean age = 33.68 ± 9.89 years) completed the MBSRQ-AS15 alongside validation measures (Rosenberg Self-Esteem Scale [RSES], Eating Attitudes Test-26 [EAT-26]). Sex-specific Confirmatory Factor Analysis (CFA) and Multi-Group CFA evaluated factor structure and scalar invariance. The five-factor model showed excellent fit in women (CFI = 0.984, RMSEA = 0.070) but poorer fit in men (CFI = 0.946, RMSEA = 0.105). Multi-group analysis established full scalar invariance (ΔCFI = 0.000). Internal consistency was robust in women (ω = 0.681–0.843) and most male subscales, except Overweight Preoccupation (OWPREOC) (ω = 0.477). Convergent validity was supported, though OWPREOC correlated weaker with eating attitudes in men (r = 0.348) than women (r = 0.555; z = −5.52, p < 0.001). To facilitate preliminary empirical research, sample-based reference percentiles for community comparisons are provided. Overall, the MBSRQ-AS15 offers a practical brief option for body image research, though its psychometric performance remains distinctly stronger in women than in men. While scalar invariance enables mean comparisons, male weight preoccupation scores require cautious interpretation due to potential confounding with muscularity goals.