This study had two aims: (1) to identify the levels of physical activity, screen time and sleep time of adolescents according to the sex of the participant and the day of the week; (2) to find out the relationships between physical activity, screen time and sleep time according to the sex of the participant and the day of the week. The study design was non-experimental, descriptive-correlational and cross-sectional. The sample consisted of 694 adolescents in Compulsory Secondary Education from Soria (Spain). Four by One-Day Physical Activity Questionnaires were used to measure levels of physical activity, screen time and sleep time. Levene’s test and Student’s t-test were used to calculate the difference between the means of the variables. Pearson’s test was used to calculate bivariate correlations between variables. Results showed higher levels of screen time in males (136.93 min/day ± 81.548). Screen time, sleep time and moderate–vigorous physical activity are higher during the weekend. Positive relationships were found between screen time and light physical activity (rmales = 0.274; p ≤ 0.01; rfemales = 0.065; p > 0.05). The correlations between moderate–vigorous physical activity and screen time were negative (rmales = −0.282; p ≤ 0.01; rfemales = −0.187; p ≤ 0.05). The relationship between screen time and sleep time was negative in males (r = −0.135; p ≤ 0.05). In conclusion, the levels of physical activity, screen time and sleep time vary according to the sex of the participants and the day of the week.
The study had two aims: (1) To classify the adolescents according to their levels of moderate–vigorous physical activity, screen time and sleep time, and (2) to analyze, in a descriptive and correlational manner, the profiles of moderate–vigorous physical activity, screen time and sleep time of each cluster according to the sex and grade of the adolescents. The study design was cross-sectional, with descriptive and correlational analysis. The sample consisted of 663 adolescents in Compulsory Secondary Education from Soria (Spain). The Four by One-Day Physical Activity Questionnaire was used to measure levels of physical activity, screen time and sleep time. The results showed that the young people had an average of 67.99 ± min/day of moderate–vigorous physical activity, 112.56 min/day of screen time and 548.63 min/day of sleep time. Adolescents were classified into three clusters according to their levels of physical activity, screen time and sleep time (FMANOVA (6,1318) = 314.439; p ≤ 0.001; β = 1; f = 1.177). In conclusion, only 28.21% of the young people accomplished the recommendations for physical activity practice, screen time and sleep time. Moreover, these results vary according to the sex and grade of the adolescents.
It is important to investigate how the different factors of physical activity and screen time influence each population group in order to design effective proposals for health promotion. This study aims to: (1) create an explanatory model to establish the relationships between moderate-vigorous physical activity time, screen time, family support, and peer support of adolescents in the region of Soria (Spain); (2) contrast the explanatory structural model according to the intensity of physical activity. A representative sample of 694 adolescents, aged 12–17 years, from the region of Soria was selected. The Four by One-Day Physical Activity Questionnaire, the Parent Support Scale, and the Peer Support Scale were administered. The data were treated according to a structural equation model to demonstrate the relationships between the study variables. The Chi-square p-values and standardised fit indices (CFI, NFI, IFI, TLI, and RMSEA) were appropriate. Moreover, acceptable parameters were obtained in the general equations. The theoretical model is useful to explain the relationships between moderate-vigorous physical activity, family support, peer support, and screen time. In addition, models that differentiate between moderate and vigorous physical activity independently are also useful. Peer support plays a particular role relative to physical activity time, and family support plays a specific role regarding screen time.
Introduction: Although practicing physical activity according to recommendations has health benefits, many studies have reported that the level of participation is lower than recommended. Methods: In this behavioural epidemiological study, we used a correlational design to determine the contribution made by physical education (PE) classes to daily physical activity in a sample of 694 Spanish adolescents. Physical activity levels were determined using the Four by One-Day Physical Activity Questionnaire. Results: 65.1% of adolescents comply with the recommendations on PE school days, compared to 36.6% who do so on the days with no PE class. Moreover, on PE school days, they obtain significantly higher physical activity level scores compared to days with no PE class. Conclusion: The study, therefore, shows the fundamental role of PE in increasing daily physical activity levels. Proposals to improve physical activity levels in these adolescents should be put forward, with educational centres being one of the best settings to achieve this goal.
High-level sport can be analyzed using the complex system model, in which performance is constrained by many factors. Coaches' and athletes' perceptions of important positive and negative factors affecting performance were compared. Participants were 48 high-level international triathletes ( n = 34) and their coaches ( n = 14). They were personally interviewed via a questionnaire designed by four accredited experts, who selected groups of both positive and negative factors affecting performance. A list of factors was developed, in order of greater to lesser importance in the opinion of athletes and coaches, for subsequent analysis. Two ranked lists (positive and negative factors) indicated that athletes appear to rate personal environment factors (family, teammates, lack of support from relatives) higher, while the coaches tended to give more importance to technical and institutional aspects (institutional support, coach, medical support). There was complete agreement between coaches and triathletes about the top five positive factors. Negative factor agreement was somewhat lower (agreement on 3/5 factors). The most important positive factor for coaches and athletes was “dedication/engagement,” while the most important factor adversely affecting performance was “injuries.”