The Relationship between Regular Sports Participation and Vigilance in Male and Female Adolescents

Abstract

The present study investigated the relationship between regular sport participation (soccer) and vigilance performance. Two groups of male and female adolescents differentiated in terms of their sport participation (athletes, n = 39, and non-athletes, n = 36) took part in the study. In one session, participants performed the Leger Multi-stage fitness test to estimate their aerobic fitness level. In the other session, participants completed the Psychomotor Vigilance Task (PVT) to evaluate their vigilance performance. Perceived arousal prior to the task and motivation toward the task were also measured in the PVT session. The results revealed that athletes had better cardiovascular fitness and showed better performance in the PVT. However, correlation analyses did not show any significant relationship between cardiovascular fitness and performance in the PVT. Athletes showed larger scores in motivation and perceived arousal measures with respect to non-athletes, although, once again, these variables were not correlated with PVT performance. Gender differences were observed only in the Leger test, with males showing greater fitness level than females. The major outcome of this research points to a positive relationship between regular sport participation and vigilance during adolescence. This relationship did not seem to be influenced by gender, perceived arousal, motivation toward the task or cardiovascular fitness. We discuss our results in terms of the different hypotheses put forward in the literature to explain the relationship between physical activity and cognitive functioning.

Physical Activity, Fitness, Cognitive Function, and Academic Achievement in Children

“…The sample size in these studies has ranged from 24 to 224 children among the ages of 6 and 13 years old (with a mean age of 9 or 10 in 75% of the studies). Fitness has most often been measured using a shuttle-run task (often the PACER) (7, 16, 82, 83, 91, 140, 141) or a graded exercise test (24-27, 29, 50, 60, 96, 129-131, 161, 167). In addition to the large number of studies assessing fitness, there is one study that assessed PA objectively using accelerometry (148) and one study that assessed sport participation in addition to their measure of fitness (7).…”

“…Fitness has most often been measured using a shuttle-run task (often the PACER) (7, 16, 82, 83, 91, 140, 141) or a graded exercise test (24-27, 29, 50, 60, 96, 129-131, 161, 167). In addition to the large number of studies assessing fitness, there is one study that assessed PA objectively using accelerometry (148) and one study that assessed sport participation in addition to their measure of fitness (7). With regard to the statistical analyses, fitness or activity has either been maintained as a continuous variable (7, 16, 50, 60, 91, 96, 118, 140, 141, 148), has been used to categorize participants as low- or high-fit, with this judgment typically based upon normative PACER data (82, 83) or normative VO 2max data (24-27, 29, 129-131, 161, 167), or participants have been identified as athletes or non-athletes (7).…”

“…In addition to the large number of studies assessing fitness, there is one study that assessed PA objectively using accelerometry (148) and one study that assessed sport participation in addition to their measure of fitness (7). With regard to the statistical analyses, fitness or activity has either been maintained as a continuous variable (7, 16, 50, 60, 91, 96, 118, 140, 141, 148), has been used to categorize participants as low- or high-fit, with this judgment typically based upon normative PACER data (82, 83) or normative VO 2max data (24-27, 29, 129-131, 161, 167), or participants have been identified as athletes or non-athletes (7). When researchers have categorized participants as low- or high-fit, the average difference in VO 2max among the groups is 14.75 ml/kg/min (SD=4.76, n=13) and the average difference in the number of laps in a shuttle run task is 18.40 laps (SD=0.28, n=2), indicating that there are substantial fitness differences among the groups.…”

“…These studies have included behavioral measures of cognitive performance in isolation (7, 16, 27, 29, 50, 60, 91, 96, 115, 130, 131, 140, 141, 148, 167) or in combination with measures of brain function (82, 83, 118, 129, 161, 168) or brain structure (24-26). In studies that include only behavioral measures of cognitive performance, a wide variety of cognitive outcomes have been assessed including processing speed (7, 115, 167), EF (16, 50, 130, 140, 141, 148, 167), memory (27, 60, 115, 131), learning (131), attention (16, 50, 96, 115, 148), crystallized and fluid intelligence , and a novel street crossing/virtual reality task (29).…”

“…In studies that include only behavioral measures of cognitive performance, a wide variety of cognitive outcomes have been assessed including processing speed (7, 115, 167), EF (16, 50, 130, 140, 141, 148, 167), memory (27, 60, 115, 131), learning (131), attention (16, 50, 96, 115, 148), crystallized and fluid intelligence , and a novel street crossing/virtual reality task (29). In studies that also incorporated measures of brain function, their use has been almost exclusively during tasks that measure EF with a particular focus on inhibition (25, 26, 82, 118, 129, 161), which is particularly well suited for the inclusion of assessments of event-related brain potentials (ERPs; electroencephalographic measures that reflect neural activity in response to, or in preparation for a stimulus or response).…”