Background: Few studies have addressed mental health in finswimmers. Objective: This study examines the effect of NLP used as mental training on the finswimmers’ anxiety, self-confidence, self-esteem, and swimming records. Methods: The NLP intervention lasted two months. The study involved thirty young finswimmers (mean age M = 15.53, SD = 1.024), divided equally into two groups: the experimental and the control group. We carried out a pre- and post-test research design and conducted a follow-up test. We used two questionnaires, the French version of the CSAI-2R and the French version of the PSPP, along with semi-structured interviews for all three tests. Results: In the post-intervention test, the experimental group significantly decreased their cognitive anxiety (β = −3.47, p < .001) and somatic anxiety (β = −2.20, p = .001). Significantly increased their self-confidence (β = 2.07, p < .001), their global self-esteem (β = 1.93, p = .002), and their physical self-worth (β = 2.13, p = .004). The same parameters, except for the global self-esteem, also recorded significant change in the follow-up test, p < .005. Time effect did not show significance in the body attractiveness, physical strength, physical conditioning, and sport competence. Furthermore, outcomes showed notable between-subject variability in the mental skills, suggesting substantial variability in baseline parameter levels between individuals. Consequently, the finswimmers enhanced their swimming records. Conclusions: NLP showed a powerful impact in optimizing finswimmers’ mental health and, accordingly, their athletic performance. Besides, the technique showed relatively durable effectiveness. Coaches can reinforce the effect through ongoing NLP training.

Objective: Physical activity and adequate sleep are essential for health and wellbeing. University students face distinct challenges affecting their habits. This study investigates sociodemographic impacts on physical activity and sleep patterns, and examines the association between physical activity and sleep quality in Hungarian university students. Methods: An online cross-sectional survey was conducted among students (N = 1,340, mean age 20.00 ± 1.59 years; 60.7% female and 39.3% male) from the Budapest University of Economics and Business. The survey was based on sociodemographic data, the Hunarian version of the International Physical Activity Questionnaire-Short Form (IPAQ-SF), and the Pittsburgh Sleep Quality Index (PSQI) questionnaires. In IPAQ-SF, respondents indicated physical activities lasting at least 10 min during the last seven days. Responses were categorised by WHO and IPAQ guidelines. Metabolic Equivalent of Task (MET) was calculated. Statistical analyses were conducted using IBM SPSS Statistics 29.0.0.0, with significance set at p < 0.05. Results: Most participants (85.8%–86.9%) performed below the WHO recommendations for moderate-intensity physical activity. Significant sex differences were noted in physical activity levels (p < 0.001 for vigorous intensity; p < 0.043 for moderate intensity), with men being more active than women. Regarding sleep quality, 57.1% of participants reported good sleep quality (PSQI 0–5), 36.1% had moderate sleep disturbances (PSQI 6–10), and 6.8% experienced poor to severe sleep disturbances (PSQI 11–21). Women reported significantly poorer sleep quality than men did (p < 0.001). Multiple linear regression analysis revealed a significant interaction between energy expenditure on physical activity and sports participation frequency (β = −0.09, p = 0.012), indicating that regular sports participation may buffer against potential negative effects of high overall physical activity on sleep quality. The model explained 3.1% of the variance in sleep quality (R² = 0.031, p < 0.001). Conclusion: The relationship between physical activity (MET-minutes/week) and sleep quality was moderated by the frequency of sports participation. Given that poor sleep can negatively impact academic performance, health, and well-being, these findings support the promotion of organized sports within university settings. Interventions targeting both physical activity and sleep hygiene may yield synergistic benefits, particularly for students with sedentary lifestyles.

Introduction: Although the relationship between functionality, as reflected in physical performance (PHP), and mental health in older adults has been researched, its strength remains unclear. Methods: This field study aimed to determine the strength of this relationship in adults aged 60 and above using seven PHP indices and six psychological measures. We individually tested 114 older adults. Objective measures included six PHP indices consisting of the Senior Test and handgrip strength. Subjective measures included resilience, wellbeing, happiness, perceived stress, hopelessness, and life satisfaction. Results: Structural equation modeling (SEM) revealed two latent constructs: PHP and mental wellbeing (MWB): robust fit (MLR): X² (75) = 136.28, p < 0.001; CFI = 0.967; TLI = 0.960; RMSEA = 0.066 (90% CI [0.000, 0.128]); SRMR = 0.088. The latent partial correlation between PHP and MWB (adjusted for Age) was φ = 0.46, indicating ∼21% shared variance. The correlation between the two latent factors was moderate (r = 0.46), suggesting that other unassessed factors might account for the relationship. Discussion: Based on objective PHP and subjective MWB measures, these results suggest a modest connection, with the two latent constructs sharing ∼1/5 of their variances. Consequently, further research is needed to identify other factors affecting the studied relationship in older adults. These cross-sectional findings, suggesting a moderate association, should be interpreted with caution. Still, they support recommending physical activity as one component of broader, multi-domain strategies to support the wellbeing of older adults.

The widespread use of smartphones and tablets has greatly increased screen exposure among preschoolers. Since early childhood is crucial for cognitive, behavioural and social development, excessive screen time represents a major public health concern. Identifying factors influencing young children's screen use is vital for creating effective family guidance and health policies. Using convenience sampling, this study collected data from 633 parents across 31 countries to examine how family composition, parental and child characteristics affect the screen time of preschoolers (aged 1–5 years). The model, based on Ordinary Least Squares regression, explained 42% of the variance in children's screen time. Parental device-giving frequency emerged as the strongest predictor, with more frequent giving linked to greater exposure. Screen time also increased with child age and the number of children in the family. Children supervised by mothers had significantly less screen time than those supervised by fathers. Parental age, number of adults in the home, child's sex and temperament were not significant predictors. These findings highlight the significant impact of parental behaviour and household dynamics on preschoolers' screen habits. Interventions should directly target these factors, and family screen time guidelines must evolve to reflect the modern technology landscape, promoting balanced and healthy use.