Sport Behavior Research Articles

Big data-driven intelligent governance of college students' physical health: System and strategy.

With the development of information technology, the application of a new generation of information technologies, such as big data, Internet Plus, and artificial intelligence, in the sports field is an emerging, novel trend. This paper examined the relevant research results and literature on physical education, computer science, pedagogy, management, and other disciplines, then used a self-made questionnaire to investigate the physical health status of Chinese college students. The big data were subsequently analyzed, which provided a scientific basis for the construction of an intelligent governance system for college students' physical health. Intelligent devices may be used to obtain big data resources, master the physical sports development and psychological status of college students, and push personalized sports prescriptions to solve the problems existing in college students' physical health. Research shows that there are four reasons for the continuous decline in Chinese college students' physical health levels. These are students' lack of positive exercise consciousness and healthy sports values (85.43%), a weak family sports concept and lack of physical exercise habits (62.76%), poor implementation of school sports policies (55.35%), and people's distorted sports value orientation (42.27%). Through the connecting effect of data, we can bring together the positive role of the government, school, society, family, and students so as to create an interlinked impact to promote students' physical health. The problems of insufficient platform utilization, lack of teaching resources, lagging research, and insufficient combination with big data in the intelligent governance of physical health of Chinese college students can be solved by building an intelligent governance system of physical health. Such a system would be composed of school infrastructure, data resources and technology processing, and intelligent service applications. Among these, school infrastructure refers to the material foundation and technical support. The material foundation includes perceptions, storage, computing, networks, and other equipment, and the technical support includes cloud computing, mobile Internet, the Internet of Things, artificial intelligence, and deep learning. Data resources refer to smart data, such as stadium data, physical health management data, and students' sports behavior data, which are mined from data resources such as students' physical development, physical health, and sports through big data technology and intelligent wearable devices. Intelligent managers provide efficient, intelligent, accurate, and personalized intelligent sports services for college students through data resource value mining, venue space-time optimization, health knowledge discovery, sports prescription pushes, etc. Finally, we put forward the development strategy for further deepening and improving the big data-driven intelligent governance system for college students' physical health. The intelligent governance system of physical health driven by big data and its development strategy can not only accurately guide and improve the physical health level of college students but also realize integrated teaching inside and outside physical education classes.

Youth Sports Special Skills’ Training and Evaluation System Based on Machine Learning

Nowadays, most sports training adopts such a mode, that is, the coach guides and observes the movements of the trainer on the side, or uses the camera to collect the data information in the training video. After the training, the trainer needs to experience and comprehend it according to the coach’s guidance and suggestions, which leads to a poor training effect to a certain extent, and the training movements are not so standardized. The most important thing is that the physical condition of the trainer will change at any time during the exercise. However, the traditional training mode cannot perceive and predict it at all, and it may even lead to the training volume being too large for the athletes to bear, which also causes irreversible effects on the body. Based on this, this paper aims to use the relevant theories and technologies of machine learning to build a system for the training and evaluation of sports-specific skills. This paper automatically determines and guides the movements of the trainer, which greatly improves the training efficiency. The movements are also more standardized, and the workload of the coaches is also reduced. In addition, the system includes explained functions. It uses holographic projection to play various videos of training and guidance, which brings convenience to trainers to observe and understand specific sports behaviors. Finally, the data results of the experimental subjects were analyzed to verify the effectiveness and feasibility of this training evaluation system, in which their special scores increased by 1.51% compared with the previous ones.

Transgressive Behavior in Dutch Youth Sport

The current article reports on the second large-scale prevalence study on transgressive behavior in sport in the Netherlands, and is a follow up of an earlier, comparable prevalence study in 2015. Using a dedicated and customized online questionnaire, approximately 4000 adults who met the inclusion criteria (18 to 50 years old and have played sports in an organized context during childhood in the Netherlands) were surveyed with respect to their experiences of childhood psychological, physical, and sexual transgressive behavior while playing sports. The survey showed that 71.7% experienced some form of transgressive behavior as a child, in which 48.6% of these events also made an impact (in other words, was significant at the time it took place). The degree of impact the event made is also related to the severity of the event. Severe emotional transgression events occurred in 22% of the youth athletes, severe physical assault events in 12.7%, and severe sexual assault events occurred in 6.9% of the youth athletes. Disabled athletes, and those competing at national and international levels, report more experiences of transgressive behavior in sport. The results are consistent with former research and indicate the need for structural attention to create a safe sports climate.

STUDY OF COMMITMENT TO RECREATIONAL SPORTS IN CHINESE URBAN RESIDENTS

ABSTRACT Introduction: Exercise commitment plays an explanatory and guiding role in an individual's adherence to exercise behavior. However, exercise commitment in recreational situations is poorly studied. Objective: Develop a sporting and recreational behavior questionnaire based on the commitment scale for Chinese urban residents. Methods: Two stages were conducted, the first with a sample of 453 individuals to explore and verify the determinants of behavioral commitment in recreational sport and the fit of the framework, and the second with a sample of 786 individuals to investigate the relationship between behavioral commitment in recreational sport and its determinants. Results: Behavioral commitment in-play sport included five determinants: ‘motivation to participate’, ‘personal involvement’, ‘choice to participate’, ‘opportunity to participate’, ‘social support’. The constructed model showed a good fit. The factors: ‘motivation to participate’, ‘personal engagement’ and ‘interest to participate’, showed a significant positive association with engagement and a significant negative association with a choice to participate. Conclusion: The resulting model shows characteristics of recreational sport behavior and can be used as a measure of commitment to recreational sport behavior among residents of a Chinese city. Level of evidence II; Diagnostic Studies- Investigating a Diagnostic Test.

Attention-Deficit Hyperactivity Disorder and Learning Disabilities Modify Recovery and Sport Behavior Following Sport-Related Concussion.

Limited evidence exists concerning how a diagnosis of attention-deficit hyperactivity disorder and/or learning disabilities (ADHD/LD) modifies recovery and behavior following sport-related concussion (SRC). To understand how ADHD/LD modifies the post-SRC experience, we conducted a retrospective cohort study of concussed young athletes through phone interviews with patients and guardians. Outcomes included time until symptom resolution (SR) and return-to-learn (RTL), plus subjective changes in post-SRC activity and sports behavior. Multivariate Cox and logistic regression was performed, adjusting for biopsychosocial characteristics. The ADHD/LD diagnosis was independently associated with worse outcomes, including lower likelihood to achieve SR (hazard ratio [HR] = 0.62, 95% confidence interval [CI] = [0.41-0.94]; P = .02) and RTL (HR = 0.55, 95% CI = [0.36-0.83]; P < .01) at any time following injury, and increased odds of changing sport behavior after concussion (odds ratio [OR] = 3.26, 95% CI = [1.26-8.42], P = .02), often to a safer style of play (62.5% vs 39.6%; P = .02) or retiring from the sport (37.5% vs 18.5%; P = .02). These results provide further evidence of the unique needs for athletes with ADHD/LD following SRC.

Deciphering the offensive process in women's elite football: A multivariate study

Over the last few years, there has been considerable increase in scientific knowledge about women's football. However, the tactical and tactical-strategic aspects have not yet been sufficiently covered in scientific literature. Therefore, this work proposed the following aims: To describe how the offensive phase is produced in women's football, to identify the significant statistical criteria that may be modulating success in attack, and finally to propose different predictive success models, with the ultimate aim of passing this knowledge on to the applied field. The observational methodology was used, one of the most appropriate methodologies for the analysis of motor behaviors in sport. The units of analysis collected and analyzed were 6063 attacks carried out during the FIFA Women's World Cup Canada 2015 and France 2019. The available results demonstrate that, on the one hand, offensive team actions are ineffective (almost 70% finish unsuccessfully), but criteria such as the start form of the attack, zone of ball possession, partial match result, or ball possession time are statistically significant criteria that modulate attack success (goal, shot or pass into the area). Lastly, the multivariate results allow us to propose a theoretical model, passing the probability of success from 31% in the absence of a model, to a theoretical auction probability of 52.6%, based on fast attacks with the intervention of few players, and with possession zone in the opposite field. These results could be directly transferred to the practical field where trainers and technical bodies can put this information into practice in training sessions or matches.

The Effect of Education Model in Physical Education on Student Learning Behavior.

This research explores the effect of the sports education model implemented in physical education on college students' learning motivation and outcomes. The sports education model was compared with traditional physical education teaching as a control group. Participants were 60 college students in two classes. The ARCS (Attention, Relevance, Confidence, Satisfaction) Learning Motivation Scale, the Physical Education Affection Scale and a learning sheet were used for pre- and post-test comparison. Quantitative analysis was carried out on the post-test data using a dependent sample t-test and an independent sample t-test. The study found that: (1) the students in the sports education model group showed clear progress in learning motivation, affection, cognition and behavior, whereas the students in the traditional physical education group showed clear progress in cognition but no significant improvement in learning motivation, affection or behavior; (2) the sports education model group is clearly superior to the traditional physical education group in terms of learning motivation, affection, cognition, and behavior. This research shows that students are highly receptive to the sports education model, with a positive attitude and a high degree of motivation to learn to actively change their sports behavior. The sports education model brings several benefits: (1) it is an effective teaching method; (2) students' sense of responsibility, leadership and participation can be improved; (3) the preliminary homework and course structure descriptions take more time to compose, but can better guide students' motivation for learning physical education and can enhance teachers' professional growth.

Leisure Sports Behavior Recognition Algorithm Based on Deep Residual Network

Aiming at the related problems existing in the field of leisure sports computing, in order to study the behavior recognition of leisure sports by deep residual network, based on the deep residual neural network theory, the behavior recognition algorithm and the corresponding robust model are used to analyze the leisure sports related samples, and the correlation model is used to predict and analyze the leisure sports related content. The results show that the change curves of Sig and Tanh functions can be divided into slow increasing stage, linear increasing stage, and stable stage. The y value corresponding to ReLU curve shows a linear change trend with the increase of x value. The Leaky function’s corresponding curve can be divided into two stages. The function coincides with the ReLU function in the first quadrant and remains linear in the third quadrant. The activation function curves corresponding to layers 56 and 20 have a relatively large variation range, and both of them show an overall trend of gradual decline. On the whole, the curve value corresponding to layer 56 is higher than that corresponding to layer 20, indicating that the method of layer 20 is relatively good and the corresponding training error is relatively low. It can be seen from the robustness recognition rate of various methods under different training samples that Fl has the highest overall data recognition rate while Sc has relatively poor stability. However, the recognition rate of IDCC and DCC shows a relatively flat trend, indicating that these two methods have certain advantages in describing the robust recognition rate. The research results can provide theoretical support for the application of deep residual neural networks in other fields.

Analysis of Factors Related to Adolescents' Physical Activity Behavior Based on Multichannel LSTM Model.

The health problems of teenagers are closely related to their sports behavior. In order to understand the relevant factors of teenagers' sports behavior, we use a variety of research methods to make a brief theoretical analysis of the relevant factors of teenagers' sports behavior and analyze the impact of the model on teenagers' sports behavior from different levels. The model analyzes the factors affecting youth sports behavior, reveals the relationship between these factors, puts forward corresponding intervention strategies, and uses effective means to develop youth sports practice. Therefore, based on the analysis of the relevant factors of teenagers' sports behavior, this paper puts forward the LSTM model from many aspects, which shows that our model can be very effective in analyzing the factors affecting teenagers' sports behavior.

A Model of Perfectionism, Moral Disengagement, Altruism, and Antisocial and Prosocial Behaviors in Wheelchair Athletes.

Two forms of perfectionism were examined in the present study to see whether they predicted prosocial and antisocial behaviors in sport through moral disengagement and altruism in a sample of 327 wheelchair basketball and rugby athletes (M = 33.57years, SD = 10.51; 83% male). Using structural equation modeling, the following significant direct and indirect effects were found. First, perfectionistic strivings positively predicted perceived prosocial behaviors and altruism. Second, perfectionistic concerns negatively predicted altruism and prosocial behaviors and positively predicted moral disengagement. Third, antisocial behaviors were positively predicted by moral disengagement and altruism. Furthermore, perfectionistic concerns indirectly predicted antisocial behaviors positively through moral disengagement and negatively through altruism. Finally, perfectionistic strivings positively predicted antisocial behaviors through altruism. Results provided partial support for the role of perfectionism in predicting prosocial and antisocial behaviors through moral disengagement among athletes with a disability.

Sports Analysis and Action Optimization in Physical Education Teaching Practice Based on Internet of Things Sensor Perception.

With the progress of the Internet of things technology in recent years, all aspects of people's lives have also been affected. More and more people are immersed in the virtual world and ignore the real activities. According to the survey, nearly 50% of people in China are in subhealth, mainly modern diseases caused by long-term inactivity. Therefore, to form a good habit of physical exercise, we must start from an early age. Starting from the physical education teaching in primary and secondary schools and from the perspective of modern scientific and technological facilities, this paper discusses the practical sports analysis and action optimization of physical education teaching based on the perception of the Internet of things. Starting from the practice of Internet of things sensor sensing in physical education teaching, we have successively determined the multisensor motion acquisition system algorithm, motion pattern recognition algorithm, and motion energy consumption algorithm, which provides modern equipment for motion analysis and motion optimization in physical education teaching practice, which breaks the current situation that traditional teachers spend a lot of time and energy for students. Combining sports mode with sports energy consumption can not only analyze sports data accurately and in real time but also optimize and predict students' sports behavior in time. We hope to supervise and urge primary and secondary school students to exercise through technical means to improve the quality of primary and secondary school students' exercise and improve people's health through physical exercise.

Design of College Physical Education Curriculum Based on Mobile App Development Platform

As a new term, mobile client app is common in the software market and has mature commercial cases, while for mobile client app of educational content, it is relatively new. The purpose of this paper is to design the sports curriculum app in line with the current university. This paper uses the research method of questionnaire to investigate and analyze the current situation of the organization and management of sports activities and public sports facilities of college students in Taian. Based on the analysis of the influence of sports app on college students’ sports behavior, it constructs the theoretical framework of school campus sports management system with app as the carrier. The experimental results show that about 41% of the students in the city use sports app, mainly including running app and fitness app. It can have a significant and positive impact on students’ physical activity and sports motivation, but it has no significant effect on students’ choice of sports. Through the realization of the physical education teaching function of the campus sports app, students can get rid of the restriction of venue, organization form, and time and make students exercise independently under the guidance of science and system. This design has very important practical significance.

The Effect of Multimedia Teaching Intervention on Physical Education Curriculum on University Students� Sports Attitudes and Sports Behaviors

The Effect of Multimedia Teaching Intervention on Physical Education Curriculum on University Students� Sports Attitudes and Sports Behaviors

Factors affecting bullying among Iranian professional football coaches

Introduction: As an integral part of society, sport faces problems similar to that of society. One problem is the bullying of football coaches. Aim: This study identifies the factors affecting bullying among Iranian professional football coaches. Method: The research method is descriptive survey based on structural equations modeling. The statistical population included all professional football coaches in Iran in 2021. 205 coaches are selected as a sample based on the simple random sampling method. A researcher-made questionnaire with 33 questions was used based on qualitative interviews and coding to collect the data. Once expert’s validation is obtained (n=8), the reliability of the questionnaire is evaluated and confirmed by Cronbach's alpha method and mixed reliability. SPSS-23 and PLS Smart-2 are used to analyze the data in the descriptive and inferential sections. Results: The confirmatory factor analysis results show 8 factors of anti-social behaviors in sports, athletes, interactions, bullying and harassment experience, occupational factor, behavioral factor, contextual and managerial factors, and individual and psychological factors as factors affecting bullying among Iranian professional football coaches. The results of confirmatory factor analysis indicate an acceptable fit. Content, divergent and convergent validity indicated good scale validity. Conclusion: The results showed that different factors affect the bullying of coaches. Therefore, it is necessary to study the identified factors and focus on football coaches. It is suggested that sports managers and officials be better informed about the factors identified in this study.

The Effect of Comprehensive Rehabilitation Nursing on the Rehabilitation of Sports-Induced Ankle Joint Injuries.

The purpose of participating in sports is to enhance physical fitness and promote physical and mental health. The occurrence of sports injuries will cause physical and mental injuries to athletes, especially the ankle joint injuries that often occur. Therefore, it is particularly important to understand the causes, symptoms, treatment, and prevention of athletes' ankle injuries. This article aims at studying the significance of comprehensive rehabilitation nursing for the rehabilitation of sports-induced ankle joint injuries and introduces the concepts of comprehensive rehabilitation nursing and ankle joint injuries. This article proposes how to use comprehensive rehabilitation nursing to recover ankle injuries caused by sports based on smart medical care. In the experiment of this article, it can be seen from Table 5 that the recovery speed of 5 athletes with ankle joint injuries before rehabilitation training was 8% (lowest) and 14% (highest). The recovery rate after rehabilitation care is up to 25%. It can be seen that comprehensive rehabilitation care is of great help to athletes with ankle injuries. As can be seen from Table 4, the number of ankle injuries in acute secondary injuries is 25, accounting for 33%, which is the highest; the number of contusions is 15, accounting for 21%, which is the lowest ratio, so it can be seen that the ankle joint injury in sports is the most serious. Therefore, the application of comprehensive rehabilitation care needs to be popularized, which is of great significance to ankle joint injuries. The ankle joint is one of the most easily sprained joints in the human body, not only because of the flexibility of the ankle joint, but also because of the anatomical characteristics of the ankle joint. The main cause of ankle injuries is inappropriate behavior in sports.

Computing Cluster and Intelligent Sensor Network in the Analysis and Application of College Students’ Physical Exercise Behavior

Based on computing cluster and intelligent sensor network technology, in view of network delay, this paper uses first-in-first-out buffers to be built at the node sending and receiving ports to convert the random delay of the physical exercise behavior network control system into a fixed delay. First, we analyze and model the controller design of the physical exercise behavior network control system. Through the analysis and synthesis of the current situation and methods of the physical exercise behavior network control system controller at home and abroad, the sensor is driven by time, and the controller and actuator are used. In the event-driven method, the sending and receiving buffers are set on the network ports of the nodes, the delay is changed from random to fixed at the same time, and the problem of data packet timing disorder is improved. Secondly, through the analysis of the internal control system node, the internal AD, DA conversion, data storage, CPU internal tasks, and task scheduling algorithm modules are implemented in the model. Experimental simulations show that, in view of the difficulty of unsatisfactory tracking effect caused by the aliasing of multiple target signals collected by sensor nodes, a combined tracking strategy is adopted; that is, multiple tracking dynamic clusters are combined into one for tracking when the sports behavior is close. In order to avoid the heavy communication and computing requirements in the centralized mode, mobile sensor networks usually adopt a distributed fusion architecture. The dynamic cluster maintenance and positioning strategy are given. In the stage of separation of multiple sports behaviors, a dynamic cluster decomposition algorithm based on boundary search is proposed, which can effectively determine the degree of separation of sports behaviors and provide a basis for establishing new dynamic clusters for follow-up tracking. The results show that the algorithm can effectively realize the merging and decomposition of dynamic clusters of multiple sports behaviors and effectively realize the dynamic tracking of multiple sports behaviors.

Health literacy and health-related behavior in sport among University students in East Java, Indonesia: A cross sectional study

Health literacy is an important determinant of health outcomes due to its close relation to an individual’s health status and well-being. The purpose of this study is to measure the level of health literacy in university students as well as analyze its relationship with socio-demographic factors and health-related behaviors. A total of 163 university students participated in this study via online-based questionnaires that assessed socio-demographic factors, health-related behavior, physical activity, and health literacy using well-validated instruments. An independent t-test and ANOVA were performed to explore any statistical significance and mean differences in health literacy score. The results discovered no significant differences in demographic characteristics on health literacy scores. However, female respondents, majoring in sport and living in urban areas with parents having higher education degrees, had a slightly higher score than their counterparts. A significant difference in scores was observed in the smoking variable (p = 0.007). Therefore, health literacy in university students is not influenced by demographic characteristics. However, this study showed that higher health literacy scores contribute to better practice of health-related behavior, especially smoking.

Moral Disengagement in Youth Athletes: A Narrative Review.

The sports environment can be considered as a context characterized by interactions typical of social groups, where children have the chance to learn good values. Positive and negative behaviours in sports, also called prosocial and antisocial behaviours, have been studied according to a moral perspective, as has doping behaviour, taking into consideration the concept of moral disengagement. Moral disengagement in children has been associated with maladaptive behaviours later in life, even though it should disappear with growth. Concerning the sports environment, previous reviews on the topic have extensively illustrated the role of moral variables in sport and their relation to antisocial behaviour and doping, positing some research questions that should be investigated in the future. Starting from these questions, the current narrative review aims to update literature about the effects of moral disengagement on youth athletes. Therefore, new studies about the predictors of moral disengagement are introduced, followed by contributions concerning the relationship between moral disengagement and doping and between moral disengagement and antisocial behaviour. Finally, the review summarizes which research questions have been solved in the last decade and which should be researched further on.

Construction Principles of Physical Fitness Training Objective System Based on Machine Learning and Data Mining

The objective is to address the issue of simplification of physical education classes offered by large colleges and universities. The evaluation standard of physical education curriculum is not unified. The physical education management system focuses on the functions of collecting information, sorting, and statistics and has low timeliness and guiding significance. This paper puts forward an analysis of the construction principle of physical fitness training target system based on machine learning and data mining. This paper uses informational analysis to statistically analyze the healthy behavior of college students, to guide the physical education of college students, and to propose a model for the analysis of healthy sports behavior of college students based on data mining technology. Create a decision tree template for students whose cardiovascular function does not meet the standard using the decision tree algorithm. The association rule algorithm is used to mine the association of five indexes of physical health, so as to judge the hidden law between students’ physical fitness and behavior habits and get the correlation information of various physical health indicators. The simulation results show that, through the prediction of college students’ healthy sports behavior data, when the sample point is 5, the original value data is 16, which is higher than the estimated value, the convergence of the overall data characteristic distribution is good, and the disturbance error is low. Therefore, using this method to analyze the application of college students’ healthy sports behavior has a high accuracy of sports-related data mining and can effectively guide college students’ sports management and training.

COVID-19 and sports fans: examining the pandemic’s impact on need fulfillment and psychosocial outcomes

ABSTRACT Rational/Purpose: In March 2020, the sports world came to a standstill as COVID-19 spread across the globe. Sport fans were among the industry stakeholders most affected. Fans turn to sports to satisfy a variety of needs [Trail, G.T. (2018). Sport consumer behavior (4th ed.). Printed by the author.] and experience psychosocial benefits by way of their fandom [Wann et al. (2000). The self-presentation of sport fans: Investigating the importance of team identification and self-esteem. Journal of Sport Behavior, 23(2), 198–206.; Wann et al. (2017). Testing the team identification–social psychological health model: Mediational relationships among team identification, sport fandom, sense of belonging, and meaning in life. Group Dynamics: Theory, Research, and Practice, 21(2), 94–107.] Without games, however, to what extent were fans able to fulfill these needs? Further, did fans experience detrimental impacts to their self-esteem and sense of belongingness in relation to their team/fan communities? Design/methodology/approach: Data were collected via an online survey using select online NBA and MLB team message boards in addition to Amazon MTurk. Fan needs were measured using adapted versions of prior sport fan motivation scales [Trail & James (2001). The motivation scale for sport consumption: Assessment of the scale’s psychometric properties. Journal of Sport Behavior, 24, 108–127; Wann (1995). Preliminary validation of the sport fan motivation scale. Journal of Sport & Social Issues, 19(4), 377–396.]. Self-esteem was measured using an adapted version of Harris et al.’s [Harris et al. (2018). The Lifespan Self-Esteem scale: Initial validation of a new measure of global self-esteem. Journal of Personality Assessment, 100(1), 84–95]. Lifespan Self-Esteem Scale. Belongingness was measured using four items from Malone et al.’s [Malone et al. (2012). The general Belongingness Scale (GBS): Assessing achieved belongingness. Personality and Individual Differences, 52(3), 311–316]. General Belongingness Scale. Findings: Survey results from 417 sports fans revealed many of the needs typically met through sport consumption (i.e. achievement, drama, escape, family togetherness, social connections, group affiliation, and entertainment) went largely unmet during the pandemic. Further, highly passionate fans maintained higher perceived levels of self-esteem and belongingness than less passionate respondents. Practical implications: Results of this study should aid sports organizations in understanding the experience of their fans during the pandemic and better prepare teams and leagues to engage their consumers in future situations where live sports are unavailable. Research contribution: This paper builds on our understanding of fan motivation and psychosocial outcomes of fandom in a time when the sport was suspended due to COVID-19.