Those who participate in sport due to feelings of having to play are demonstrating

Dropout

Sport participation tends to increase steadily during late childhood and early adolescence (both in terms of the number of sports played and the time spent playing sports), peaking at approximately age 12 years for females and age 15 years for males, before declining sharply in later adolescence. Although girls' rates of involvement in sport have increased since the 1970s, girls are still less active than boys, especially during adolescence. One reason for the gender difference in sport participation may be the different societal expectations that have existed for males and females. Traditionally, sport was perceived as a male domain, providing young men with an opportunity to display their strength, skill, and physical attributes. Although females are increasingly receiving support for sport participation, research continues to indicate that males are more likely to receive financial and logistical support than females.

Estimates suggest that approximately 30% of youth drop out of a given sport program annually, and highest attrition occurs during adolescence. Reasons for dropout include injury, the attraction of other activities, lack of success, lack of playing time, lack of teamwork, not meeting new friends, needing to get a job, inconvenient game or practice schedules, and needing more time to study. Unfortunately, some studies have also indicated that negative aspects of youth sport programs can also lead to participants dropping out. For example, in some studies, adolescents have reported the competitive emphasis of sports programs and an overemphasis on winning as reasons for leaving the sport. The overemphasis on winning and competition may lead to adolescents experiencing increased feelings of pressure and anxiety. In turn, this may result in a lack of enjoyment and ultimately lead youth to burnout or dropout.

The continuity of sport participation is important. Continuous participation over an extended period of time may facilitate skill mastery and sporting knowledge. Further, research by Richard Lerner and colleagues has shown that adolescents who participate in sport for at least 2 years are likely to report more positive functioning and fewer risk behaviors than adolescents with less continuous participation. Intensity of sport participation (i.e., the total amount of time spent in sport) may also be important because adolescents who spend more time in an activity may benefit more than those who participate at lower levels of intensity. In fact, research has shown that adolescents who spend more time participating in sport report high levels of positive functioning and lower depression. Furthermore, inconsistent sport participation and dropout is associated with negative developmental outcomes. For example, one study showed that adolescents with decreasing or erratic participation in youth sport were nearly three times more likely than adolescents with high participation to be smokers. Sport dropout also contributes to declining rates of overall physical activity participation among youth.

As mentioned previously in this article, in a sense those who remain in sport during adolescence are a self-selected sample. Sport obviously works for the majority of these adolescents because they likely have sufficient competence and enjoy the competitive aspects of sport. By committing to sport, adolescents usually devote less time to other activities (such as arts, music, etc.). Thus, the decision to participate in sport is likely influenced by a strong commitment to the activity. If adolescents who enjoy sport tend to stay involved for longer, this may partially explain the numerous positive outcomes that have been associated with sport. In other words, those who did not enjoy sport and perhaps had negative experiences are unlikely to remain involved in sport during adolescence and therefore do not participate in certain studies.

College athletes

Sports participation in National Collegiate Athletic Association (NCAA) sports has never been higher for both male and female student-athletes (Tables 7.2 and 7.3). In the 2015–2016 academic year, there were approximately 487,000 student-athletes (275,000 male and 212,000 female) (Irick, 2016). This represents an increase of 23.7% from the 2005–2006 academic year, when there were approximately 394,000 student-athletes (Irick, 2016). The increase in participation by female student-athletes slightly outpaced their male counterparts (25.722.3%) (Irick, 2016). Overall, there are over 19,300 women's and men's sports teams across NCAA member institutions (Irick, 2016). Based on the number of participants in Tables 7.2 and 7.3, there are approximately 283,000 athletes in NCAA sports that will be highlighted later in the chapter. These are the sports whose concussion incidence is higher than other NCAA sports.

Table 7.2. Participation in men's collegiate athletics among select sports – United States, 2015–2016

Reproduced from Irick E (2016) Student-athlete participation 1981-1982–2015-16. NCAA sport sponsorship and participation rates report. Indianapolis, IN: The National Collegiate Athletic Association. Available online at: http://www.ncaapublications.com/productdownloads/PR1516.pdf (accessed June 8, 2017).

Table 7.3. Participation in women's collegiate athletics among select sports – United States – 2015–2016

Reproduced from Irick E (2016) Student-athlete participation 1981-1982–2015-16. NCAA sport sponsorship and participation rates report. Indianapolis, IN: The National Collegiate Athletic Association. Available online at: http://www.ncaapublications.com/productdownloads/PR1516.pdf (accessed June 8, 2017).

Abstract

Sport participation, fitness, and expertise have been associated with a range of cognitive benefits in a range of populations but both the factors that confer such benefits and the nature of the resulting changes are relatively unclear. Additionally, the interactions between time pressure and cognitive performance for these groups is little studied. Using a flanker task, which measures the ability to selectively process information, and with different time limits for responding, we investigated the differences in performance for participants in (1) an unpredictable, open-skill sport (volleyball), (2) an exercise group engaged in predictable, closed-skill sports (running, swimming), and (3) nonsporting controls. Analysis by means of a drift diffusion analysis of response times was used to characterize the nature of any differences. Volleyball players were more accurate than controls and the exercise group, particularly for shorter time limits for responding, as well as tending to respond more quickly. Drift diffusion model analysis suggested that better performance by the volleyball group was due to factors such as stimulus encoding or motor programming and execution rather than decision making. Trends in the pattern of data seen also suggest less noisy cognitive processing (rather than greater efficiency) and should be further investigated.

Abstract

Exposure to repetitive head impacts from contact sport participation (e.g., American football, boxing, soccer) is associated with the neurodegenerative disorder known as chronic traumatic encephalopathy (CTE). The neuropathology of CTE is becoming well defined, and diagnostic criteria have been developed and are being refined. The critical next step in this emerging field is the diagnosis of CTE during life. The objective of this chapter is to describe what is currently known about the clinical presentation and in vivo diagnosis of CTE. This chapter reviews studies in which clinical manifestation of CTE was examined through retrospective telephone interviews with informants of individuals whose brains were donated and were diagnosed with CTE through neuropathologic examination. In vivo research examining the long-term neurobehavioral consequences of repetitive head impacts is also reviewed, followed by a comparison of the existing provisional clinical diagnostic criteria for CTE, as well as preliminary research on possible fluid and neuroimaging biomarkers. An illustrative case study of CTE is presented, and the chapter concludes with a discussion of gaps in knowledge and future directions.

Benefits and Costs of Sport Participation for Girls and Boys

There are several positive outcomes associated with sport participation. For example, sport involvement has been linked to positive academic performance, school engagement, and future educational aspirations. Research has also found a positive longitudinal relationship between high school sport involvement and psychological adjustment. This pattern may be likely because sport participation is highly valued in US high schools, and athletes often hold high status positions in their peer groups.

Some benefits associated with athletic participation are especially likely among adolescent girls. Research shows that girls' involvement in sports and physical activities is related to increased self-esteem, self-efficacy, and feeling self-reliant. In addition, several studies show that adolescent girls and college women who play sports are more likely than nonathletes to report more satisfaction with their bodies. In addition, female high school athletes are less likely than nonathletes to report eating disorders. Adolescent girls who are involved in sports also show a number of positive behaviors related to sexuality. Female athletes engage in fewer risky sexual behaviors and do more to protect their sexual health than do their nonathletic peers.

Despite the various psychological, social, and physical benefits associated with involvement in sports, positive outcomes are not an automatic byproduct of participation. There are negative attitudes and behaviors that may increase with athletic involvement. For example, some research in the United States suggests that high school athletes are more likely than nonathletes to drink alcohol. However, this pattern may vary across ethnic groups or communities; for example, it appears more likely for European American than African American athletes. For girls, there is evidence that participation in lean sports (in which being slender is believed to be an advantage, such as distance running) is related to self-objectification, which involves focusing on how one's body appears rather than what it can do. Further, some female athletes are at risk for developing disordered eating problems. This includes dancers, girls and women who play aesthetic (in which bodies are judged as part of the competition, such as figure skating) and lean sports, and elite athletes (who play in professional leagues or compete at national or international events).

For boys, sport fields have historically been a place to learn about and prove one's masculinity, and boys achieve status among their peers based on their athletic ability. For many male athletes, there is a locker room culture that promotes misogyny and homophobia. Those who are less athletically skilled tend to be lower on the dominance hierarchy in US high schools, and can be targets for bullying and homophobic taunts. High status male athletes at the top of the social hierarchy in some communities are more likely to hold rape-tolerant attitudes and to commit sexual violence against females.

In an effort to cultivate positive sport environments, researchers and youth sport advocates have created models for optimal sport contexts as well as specific sport programs with a positive youth development focus. These programs focus on teaching sports skills along with life skills in a safe, fun, supportive, and challenging environment that involves caring relationships, well-trained adult leaders, facilitated and experiential learning, and moderate-to-vigorous physical activity.

Return to school

Although returning the injured athlete back to sport participation is an important goal, increasing attention has been paid to returning the student-athlete to school, across all levels from elementary grades to college (Gioia, 2016). Assessing and treating the postinjury cognitive, behavioral, and emotional effects, particularly as they relate to a successful school return, is a skillset that the sports neuropsychologist uniquely possesses.

Ransom et al. (2015, 2016) describe the range of academic problems experienced by students following an SRC, ranging from headaches and fatigue interfering with learning and performance, to poor concentration, difficulties holding information in working memory, emotional intolerance, and sensitivity to sensory stimulation in the school environment. Recent reviews (Centers for Disease Control and Prevention, 2017; Purcell et al., 2018) have highlighted planning for the student-athlete’s return to school as a significant aspect of concussion management, to which the sports neuropsychologist can contribute significantly. The process of school return following concussion has been articulated in recent publications, including the CDC's Heads Up to Schools: Know Your Concussion ABC’s (Centers for Disease Control and Prevention, 2010), evidence-based recommendations by the CDC (Centers for Disease Control and Prevention, 2017), Berlin conference (Davis et al., 2017b), and the American Academy of Pediatrics clinical report (Halstead et al., 2013).

When considering the clinical needs of the student with a concussion, the sports neuropsychologist should consider two primary targets for management: (1) the effect of the concussion on school learning and performance; and (2) the effect of school learning/performance demands on concussion recovery (Gioia, 2016). Both issues must be supported in the student's recovery. The neuropsychological effects of concussion – impaired cognition (attention/concentration, working memory, new learning and memory, speed of information processing, executive function) and social-emotional functioning (increased irritability, moodiness, emotional overresponse) – must be defined in terms of their effects on academic learning and performance. To support recovery in the student-athlete’s return to school, specific accommodations can be used, such as the Symptom Targeted Academic Management Plan (STAMP; Gioia, 2017). Sports neuropsychologist can play a central role in the return-to-school process, given their expertise in the manifestations of postconcussion cognitive, behavioral, and emotional factors on academic learning.

Developmental considerations

Given that social processes feature prominently in sport participation motives for children and youth (e.g., Ewing & Seefeldt, 1996), it is possible that grouping tendencies and experiences differ from those in more performance oriented environments such as adult sport and from industrial/organizational psychology literature where much of the preliminary sport research has been informed (e.g., Carton & Cummings, 2012; Cronin et al., 2011). As such, two important avenues for researchers interested in subgroups and cliques in youth sport will be to (a) carefully explore developmental/age considerations and (b) recognize the novelty of the sport context in comparison to traditional settings involved in peer group research (e.g., classrooms).

The transition from childhood to adolescence is a time where individuals begin to voluntarily and purposefully select their peer groups (e.g., Gottman, 1983) and there is evidence to support the impact of these decisions on eventual behaviors and psychological adjustment (e.g., Bagwell & Schmidt, 2013). Peer interactions are critical in facilitating social skills (e.g., cooperation, empathy, respect) that can be utilized across social situations (Bukowski, Newcomb, & Hartup, 1996), with a chapter in this text being dedicated to such development (Chapter 13). However, whereas friendship involves reciprocity, similarity, and fun (Bukowski et al., 1996), peer group dynamics appear to be influenced by social structure and norms (Brown & Dietz, 2009). Accordingly, the reasons for why children may decide to interact with particular groupings over others could be more complex within sport teams based on social status determinants (e.g., athletic competence; Chase & Dummer, 1992) and an innate desire for acceptance or belonging (e.g., Allen, 2003); and these desires or experiences are also likely to change as athletes transition from younger childhood to older adolescence (Bukowski et al., 1996).

Recognizing the contextual novelty of sport is also important, especially considering that much of the literature from developmental psychology has investigated peer groups in the educational domain (e.g., classrooms). Based on the Lickel et al. (2000) classification for group types, classrooms would be considered loose affiliations, whereas sport teams align more closely with task groups. Boundary permeability and identity issues pertaining to the superordinate groups differ (i.e., classroom vs. sport team), and scholars have noted the lack of meaningfulness and different perceptions of source of “status” within classroom groups for youth (Brown & Dietz, 2009; Rodkin, Farmer, Pearl, & Van Acker, 2006). Within a sport team, athletes share common objectives, so any visible divisions within that team are likely accentuated. In addition, social identity beliefs are likely stronger in sport, as many teams at the youth level include selection processes, matching attire, and team names (see Chapters 1 and 616) that are not present in other contexts. Clearly, social acceptance and feelings of belonging are important to youth, especially given the significance of peer groups for establishing identity (Brown & Lohr, 1987). Building from the preliminary research on subgroups and cliques described above with a particular emphasis on youth sport populations will be an exciting avenue for future research.

4 Discussion

We found that frequency of weekly team ball sport participation was related to performance on two sustained spatiotemporal attentional tasks: a position monitoring variant of the MOT task and the RSVP task. In the RSVP task, our results contrast with those of Overney et al. (2008) who found no such relationship between RSVP performance and participation in either tennis or triathlon. As neither tennis nor triathlon requires attending to multiple moving targets at the same time, it is possible that the effect we report here applies only to team ball sports and other sports which do require multiple successive events to be monitored. Participants performed more poorly when T2 was presented at the shortest lags, although there was no statistically significant evidence that an attentional blink had occurred, as traditionally defined (in terms of a decrement in performance between single task and dual task performance at short lags; e.g., Chun and Potter, 2001). Perhaps using a white letter as T1 embedded in a stream of black letters caused attention capture for T1 due to its luminance contrast with the distractor items, a feature known to have attention capture properties (Christ and Abrams, 2008). This may also have overridden differences between participants in terms of their attentional abilities for responding to T1, resulting in a non-significant relationship with frequency of sport participation. Traditionally, T1 performance is not the variable of interest—rather, the task of responding to T1 is added to increase the overall difficulty of responding accurately to T2. Indeed, the relationship with amount of weekly participation in team ball sports was evident in performance for the more attentionally demanding T2 task and also approaching significance for T1 reporting.

For the position monitoring variant of the MOT task, our findings are consistent with those of Zhang et al. (2009) who reported that athletes showed faster RTs than non-athletes in their change detection version of the MOT task. However, our findings contrast with those of Memmert et al. (2009) who found that team sports players performed no better than non-team sports players or non-athletes in MOT. It is possible that the position monitoring task used here was more sensitive to the group differences, since it probes the precision of representations of positions more directly, without recourse to capacity estimates based on performance in identifying targets or speed threshold estimation. Another somewhat counterintuitive possibility is that sporting individuals are superior at the spatial precision requirements of our task here, but not at the task of keeping track of targets as they move along intermingled trajectories among distractors, as is the case in traditional 2D MOT tasks. For some time it was thought that there may be architectural constraints on tracking objects, leading to a performance limit at around four objects (Pylyshyn and Storm, 1988). Although a flexible resource account has now been shown to be better able to explain tracking performance, tracking has repeatedly been shown to be markedly worse once set sizes reach around four targets (Alvarez and Franconeri, 2007; Howard and Holcombe, 2008). Hence, it is striking that in addition to the overall performance benefit we see associated with greater time spent playing team ball sports, those playing more sport performed at a similar level when tracking four targets to those who played very little sport when they were tracking a single target. It is clearly the case here that playing team ball sports was associated with being able to monitor the positions of several more target objects without such a heavy attentional penalty being paid for spreading attention over greater numbers of targets.

Comparing with training studies, the relationship we show here between position tracking performance and team ball sport participation is also consistent with the findings of Faubert (2013) who showed that professional team athletes were able to achieve faster speed thresholds in 3D MOT than non-professional athletes, who in turn, performed better than non-athletes during a training study. Further, Romeas et al. (2016) argued that 3D MOT training improved soccer decision making, indicating a possible role for object tracking as part of the cognitive demands of engaging in team ball sports. Faubert and Sidebottom (2012) were able to train sportspeople at 3D MOT, although they did not compare sportspeople with non-sportspeople, nor did they assess transfer to sporting success. In contrast, Schwab and Memmert (2012) attempted to train young hockey players on MOT and found no improvement in their MOT performance. It is possible that these sportspeople were already quite accomplished at the task hence perhaps why little improvement was observed. Another possibility is again that their MOT task was not sensitive enough to detect any differences, especially as in the same study, a functional field of view task performance did show improvements with training.

Hüttermann et al. (2014) reported differences in the distribution of attention, with athletes displaying greater attentional breadth across the visual field than non-athletes. Additionally they found some relationship between the type of sport and shape of attentional focus, with football players showing with horizontal spread of attention than volleyball players. Perhaps this wider focus of attention and greater ability to flexibly distribute attention according to the task demands contributed to position monitoring ability here in those who participate in sport more frequently.

Executive function may be a candidate mechanism by which engaging in sport may facilitate performance on these sustained spatiotemporal tasks, either to sustain attention to the task or to deploy attention strategically to the aspects of the task that would yield greatest benefit. Evidence for improved executive function in sportspeople (Colcombe et al., 2004; Dupuy et al., 2015; Jacobson and Matthaeus, 2014) makes this a feasible suggestion. Further, since sport participation has been associated with the control of inhibitory attentional effects (e.g., Lum et al., 2002; Sanabria et al., 2011; Tsai et al., 2016), it is possible that part of the benefit seen for team sports players in the MOT task here was due to more effective inhibition of distractor items. Superior control of inhibition could also aid in the detection of targets in the RSVP stream with executive control being used additionally to switch between attentional sets for T1 and T2. Further, in MOT there remains an ongoing debate about whether or not attention is spread between targets serially or in parallel (e.g., Howe et al., 2010) and the extent to which distractors are suppressed in MOT (e.g., Meyerhoff et al., 2017) although it is clear that control of attention directed toward targets and inhibition of distractors would require executive function.

Although we report a statistical relationship here between time spent playing ball sports and performance on these two tasks, it is not possible to make conclusions about the direction of causality in this relationship. It may be the case that sports training was the whole or partial cause of these performance differences. Of course there are a number of alternate possibilities including causality in the opposite direction if people who are skilled in these ways are drawn toward sporting pursuits. Another note of caution is that the data we present here do not allow conclusions to be drawn around the relative importance of cardiovascular exercise versus the benefits of the cognitive training afforded by sports, such as training in attention to multiple players and tracking the trajectory of the ball, as well as dual task requirements from simultaneous execution of multiple complex motor commands and any social interactions during team ball sports. Certainly, it would be worthwhile for these questions to be examined further.

Sport participation appears to be part of a larger group of individual differences factors associated with performance on these dynamic visual attention tasks. Other individual differences factors associated with MOT performance have been identified including fast-paced action video gaming (Green and Bavelier, 2006), age (Sekuler et al., 2008; Trick et al., 2005a,b), neurophysiological factors such as the speed of resting alpha oscillations (Howard et al., 2017b), training and expertise (Allen et al., 2004). The extent to which these factors are in fact either causally related or subserved by one or more underlying cognitive or neurological differences certainly deserves further investigation.

For RSVP tasks, individual differences have previously been reported for the attentional blink, i.e., how much T2 performance is negatively affected by the demands of responding to T1 (Martens et al., 2006). Lutz et al. (2008) have reported that participants who received 3 months of intensive meditation training showed less attentional blink than control participants. Further, individuals who engage in fast-paced action video gaming perform better on the RSVP task (Howard et al., 2017a; Mishra et al., 2011). It is therefore interesting that individuals reporting playing more team ball sports also appear to show superior performance on the RSVP task. Compared to the position monitoring task, which arguably has greater ecological validity as a measure of some aspects of spatial attention during sports, the RSVP task is a more traditional laboratory based measure of sustained attention to rapidly changing stimuli. It is interesting to note therefore that playing team ball sports was associated with superior performance in both of these tasks, supporting the view that both general attentional processes and those which are engaged in more sports-like tasks may share a common mechanism.

Introduction

Physical injury is a common by-product of sport participation. Literally millions of athletes around the world sustain one or more injuries each year, incurring billions, of dollars of medical costs in the process. Although most of the injuries are minor and require minimal medical treatment, many of the injuries require extensive and costly diagnostic testing, surgery, and rehabilitation. In the short term, sport injuries can impair performance both on and off the athletic field. Athletes can be prevented from training or competing as a result of injury, and their daily activities can be disrupted by injury-related pain or disability. In the long term, certain sport injuries may place athletes at increased risk for developing arthritis and other chronic medical conditions. Some of the more severe injuries may bring about the end of athletes' sport careers and result in permanent disabilities.

Historically, injury has been considered primarily as a physical phenomenon within the sport community, with an emphasis on identifying the physical factors that cause injuries to occur and on helping athletes to recover from injuries. Unfortunately, even with all of the medical and technical advances that have been made over the past several decades in equipment, playing surfaces, and other safety features, the number of sport-related injuries has continued to increase. This unexplained rise in injury rates has been accompanied by a growing recognition of the possible role of psychological factors in the sport injury process. Psychological factors are now thought to contribute to not only the occurrence but also the rehabilitation of sport injuries. Indeed, psychological interventions have been implemented to assist in the prevention and treatment of sport injury.

10.5.2 Overuse injuries

Sports injuries comprise various types of musculoskeletal damage caused by sports participation, and severity is determined by the impact of the injury on daily function and exercise habits (Healy, 2015). An overuse injury develops from overloading the body without appropriate time for restitution. Up to 40% of long-distance runners report knee injuries (Glasser, 1976), while about 12 million US athletes aged 5–22 years incur a sports-related injury each year (Carmack & Martens, 1979). Sports injuries can lead to periods of exercise withdrawal and reduced physical performance. Veale (1987) argued that exercise addiction is most likely found in athletes with persistent physiological injuries. Veale referred to several studies documenting the physical complications of exercise addiction in long-distance runners (Colt & Spyropoulos, 1979; Liberman & Palek, 1984; Stanish, 1984).

These studies examine physical injuries, such as pressure sores and stress fractures. Given that many people develop these problems, a question arises as to why people might continue to exercise despite the discomfort? It is hypothesized that addicted athletes, who are prevented from training due to injury, often experience withdrawal symptoms in the form of restlessness and irritability and that this encourages them to continue exercising despite their injury. In support of this view, Hausenblas and Downs (2002a) found that persons at risk of exercise addiction were more likely to report that they would exercise in spite of bad weather, pain, or discomfort, than nonaddicted responders. This shows that exercising in spite of injuries and pain seems characteristic for people suffering from exercise addiction.

Other studies have investigated the psychological risk factors associated with ignoring physical pain and injury (Byrne, 1996; Carver, Coleman, & Glass, 1976; Hassmen, Stahl, & Borg, 1993). These studies illustrate that “type-A behavior” impacts the risk of suffering from stress fractures and repeated injuries due to running, because pain and injuries are ignored. Type-A behavior is characterized by over-the-average energy, aggressiveness, impatience, competitiveness, and hostility (Byrne, 1996; Carver et al., 1976; Hassmen et al., 1993; Rosenman, 1990). Based on these findings, it is suggested that runners with type-A behavior suffer from more injuries and are more likely to get stress fractures related to running than others (Ekenman, Hassmen, Koivula, Rolf, & Fellander-Tsai, 2001). Other case study evidence supports this work. Griffiths (1997), for example, examined compulsive exercise in a case study of a 25-year-old woman (Griffiths, 1997). For 5 years, she had exercised increasingly and that pain in her arm worried her, because it did not get enough time to heal between competitions. She was advised by her doctor to give up sports, due to the risk of permanently damaging her arm, but she felt it was impossible to reduce her exercise despite this risk. Given these findings, it seems likely that addicted exercisers can be characterized as persons with a competitive personality profile which is prone to exercise in spite of pain and injury, even if it threatens physical health permanently.