Moderate-Vigorous Physical Activity, Screen Time and Sleep Time Profiles: A Cluster Analysis in Spanish Adolescents.

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; ß = 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.

Moderate-Vigorous Physical Activity, Family Support, Peer Support, and Screen Time: An Explanatory Model.

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.

The Relationships between Physical Activity, Screen Time and Sleep Time According to the Adolescents' Sex and the Day of the Week.

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.

Physical Activity, Energy Expenditure, Screen Time and Social Support in Spanish Adolescents-Towards an Explanatory Model about Health Risk Factors.

Youth obesity has been a pandemic for decades. One of its causes is a low level of physical activity. It is necessary to know the specific situation of adolescents and the factors that influence it in order to be able to act accordingly. The first aim of the current study is to create an explanatory model to establish the relationships between light physical activity time, light physical activity energy expenditure, screen time and social support. The second aim is to propose a theoretical model specifying the relationships between moderate-vigorous physical activity time, moderate-vigorous physical activity energy expenditure, screen time and social support. The study design was non-experimental (ex post facto), descriptive-correlational and cross-sectional. A total of 694 adolescents from the region of Soria (12-17 years) participated in the study. The instruments administered were the Four by One-Day Physical Activity Questionnaire, Parent Support Scale and Peer Support Scale. Two structural equation models were developed to analyse the relationships between the variables that comprised the explanatory models. The results show that social support had a negative influence on screen time in the proposed model in relation to light physical activity (r = -0.210; p ≤ 0.001) and in the proposed one regarding moderate-vigorous physical activity (r = -0.173; p ≤ 0.05). Social support was negatively related to light physical activity time (r = -0.167; p ≤ 0.05). Family support had a greater influence than did peer support. In conclusion, the models for light and moderate-vigorous physical activity are useful to describe the relationships between time, energy expenditure, screen time and social support.

An Explanatory Model of the Relationships between Physical Activity, Social Support and Screen Time among Adolescents.

Effective physical activity studies are necessary to understand how factors involved in physical activity mediate behaviour. Therefore, more reliable explanatory models can be generated in order to design effective actions to promote physical activity. The study had two aims: (1) to develop an explanatory model to identify and establish the relationships between physical activity, social support and screen time among adolescents; and (2) to contrast the explanatory structural model by means of a multi-group analysis according to sex. The study design was cross-sectional with descriptive and correlational analysis. The research was carried out with a representative sample of adolescents from the province of Soria (mean age 14.06 ± 1.27 years). The instruments used were: Four by One-Day Physical Activity Questionnaire, Parent Support Scale and Peer Support Scale. The results show that social support had a negative relationship with screen time (r = -0.178; p ≤ 0.001); males had a positive relationship between physical activity and screen time (r = 0.118; p ≤ 0.05); and peer support had more influence on social support than parental support. In conclusion, the proposed model was effective in triangulating the relationships between physical activity, social support and screen time in a novel way, while allowing us to discriminate these results according to participants' sex.

¿El buen entrenador nace o lo hace el deportista? El camino hacia el alto nivel en triatlón / Are great coaches born or made by their athletes? the path to high level triathlon coaching

Regarding the coach’s importance in the sports system and in their athletes’ outcomes, expert coaches’ keys for success have been studied from different approaches. One of these approaches is the retrospective research of the path to the high performance level. The aim of this study was to describe the triathlon coaches’ path, previous to the high performance stage, and the circumstances in which the step to the high level was achieved. 14 high level triathlon coaches were interviewed. Results show a usual way, in which the coach was previously an athlete and coach in any discipline related to triathlon (swimming, cycling, endurance athletics), starting the high performance stage at the approximate age of 30. Previous average experience to high level stage depends on the coaches’ background, but it never lasts more than 10 years. In order to choose expert coaches’ samples, it would be recommendable to set the years of previous experience taking into account the sport context (AU)

La figura del entrenador adquiere un peso importante en el sistema deportivo y por tanto en el éxito de sus deportistas. Las claves de su éxito han sido estudiadas desde diferentes perspectivas. El estudio en retrospectiva del recorrido por el cual se llega al alto nivel es una de ellas. El propósito de este estudio fue determinar el camino de los entrenadores de triatlón previo a su llegada al alto nivel, así como las circunstancias en las que se produjo el paso hacia el alto rendimiento. Para ello se entrevistó a una muestra de 14 entrenadores españoles de alto nivel en triatlón. Los resultados muestran un recorrido prevalente en el que el entrenador fue anteriormente deportista y entrenador en alguna/s de las disciplinas fundamentales (DF) de las que se compone el triatlón (natación, ciclismo, atletismo), llegando al alto nivel de triatlón con una edad aproximada de 30 años. Los años de experiencia previa varían en función del pasado del entrenador, no llegándose a alcanzar los 10 años de media en ningún caso, hasta el inicio en la etapa de alto nivel. Sería recomendable, por tanto, contextualizar los años de experiencia previos, para optimizar la selección de muestras de entrenadores expertos (AU)

Cuantificación podométrica de la influencia del puesto de trabajo y ámbito de estudio sobre los patrones de actividad física en un campus universitario / Pedometeric quantification of the influence of job and field of study on physical activity patterns on a college campus

La actividad física (AF) se ha convertido en eslabón primordial en las medidas de la Organización Mundial de la Salud para la prevención de las enfermedades no transmisibles. En este sentido, el lugar de trabajo está reconocido internacionalmente como un marco adecuado para el estudio y la promoción de la salud. El propósito del presente estudio es cuantificar mediante podómetros los niveles de AF en diferentes estratos profesionales de un campus universitario (estudiantes, profesores, personal de administración y limpieza), a partir de los cuales se determinan patrones basados en el número de pasos realizados, y cómo estos varían según se trate de días laborables o días festivos. Los resultados muestran un rasgo común de patrón para todos los estratos, determinado por la disminución de AF durante los fines de semana. Excepto el sector administración, el resto de grupos si cumplen con las recomendaciones diarias de AF en función de los pasos. En su globalidad el ambiente universitario puede considerarse como un entorno favorecedor de la AF y oportuno para la promoción de planes de mejora de la salud tanto dentro como fuera del mismo (AU)

The World Health Organization considers physical activity (PA) a fundamental link in preventing non-communicable diseases. In this sense, the workplace is internationally recognized as a framework for studying and promoting health. The aim of this study is to use pedometers to quantify levels of PA in different professional strata on a university campus (students, teachers, administrative officers and cleaning staff). The PA patterns were determined on the basis of the number of steps taken and how they varied according to working days or holidays. The results show a characteristic pattern common to all strata, determined by decreased PA at the weekends. Except for the administration sector, the other groups met the daily recommendations of PA according to steps. The university environment can be considered an enabling environment for PA and an appropriate one for promoting plans to improve health both inside and outside of it (AU)

Psycho-social factors determining success in high-performance triathlon: compared perception in the coach-athlete pair.

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".